Recent Trends and Opportunities for the Targeted Immuno-Nanomaterials for Cancer Theranostics Applications

Abstract

The targeted delivery of cancer immunotherapies has increased noticeably in recent years. Recent advancements in immunotherapy, particularly in blocking the immune checkpoints (ICs) axis, have shown favorable treatment outcomes for multiple types of cancer including melanoma and non-small-cell lung cancer (NSLC). Engineered micromachines, including microparticles, and nanoplatforms (organic and inorganic), functionalized with immune agonists can effectively deliver immune-targeting molecules to solid tumors. This review focuses on the nanomaterial-based strategies that have shown promise in identifying and targeting various immunological markers in the tumor microenvironment (TME) for cancer diagnosis and therapy. Nanomaterials-based cancer immunotherapy has improved treatment outcomes by triggering an immune response in the TME. Evaluating the expression levels of ICs in the TME also could potentially aid in diagnosing patients who would respond to IC blockade therapy. Detecting immunological checkpoints in the TME using noninvasive imaging systems via tailored nanosensors improves the identification of patient outcomes in immuno-oncology (IO). To enhance patient-specific analysis, lab-on-chip (LOC) technology is a rapid, cost-effective, and accurate way of recapitulating the TME. Such novel nanomaterial-based technologies have been of great interest for testing immunotherapies and assessing biomarkers. Finally, we provide a perspective on the developments in artificial intelligence tools to facilitate ICs-based nano theranostics toward cancer immunotherapy.

Full text

Citation: John, C.; Jain, K.; Masanam,
H.B.; Narasimhan, A.K.; Natarajan, A.
Recent Trends and Opportunities for
the Targeted Immuno-Nanomaterials
for Cancer Theranostics Applications.
Micromachines 2022,13, 2217.
https://doi.org/10.3390/
mi13122217
Academic Editors: Cristina Chircov
and Ionela Andreea Neacsu
Received: 17 November 2022
Accepted: 10 December 2022
Published: 14 December 2022
Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in
published maps and institutional affil-
iations.
Copyright: © 2022 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
micromachines
Review
Recent Trends and Opportunities for the Targeted
Immuno-Nanomaterials for Cancer Theranostics Applications
Clyde John 1, Kaahini Jain 2, Hema Brindha Masanam 3, Ashwin Kumar Narasimhan 3
and Arutselvan Natarajan 4, *
1Department of Molecular and Cellular Biology, University of Illinois Urbana-Champaign,
Urbana, IL 61801, USA
2Department of Neuroscience, Boston University, Boston, MA 02215, USA
3Advanced Nano-Theranostics (ANTs), Biomaterials Lab, Department of Biomedical Engineering, SRM
Institute of Science and Technology, Kattankulathur, Chennai 603203, Tamil Nadu, India
4Molecular Imaging Program at Stanford (MIPS), Department of Radiology and Bio-X Program, Stanford
University, Stanford, CA 94305, USA
*Correspondence: anatarajan@stanford.edu; Tel.: +1-650-736-9822
Abstract:
The targeted delivery of cancer immunotherapies has increased noticeably in recent years.
Recent advancements in immunotherapy, particularly in blocking the immune checkpoints (ICs)
axis, have shown favorable treatment outcomes for multiple types of cancer including melanoma
and non-small-cell lung cancer (NSLC). Engineered micromachines, including microparticles, and
nanoplatforms (organic and inorganic), functionalized with immune agonists can effectively de-
liver immune-targeting molecules to solid tumors. This review focuses on the nanomaterial-based
strategies that have shown promise in identifying and targeting various immunological markers in
the tumor microenvironment (TME) for cancer diagnosis and therapy. Nanomaterials-based cancer
immunotherapy has improved treatment outcomes by triggering an immune response in the TME.
Evaluating the expression levels of ICs in the TME also could potentially aid in diagnosing patients
who would respond to IC blockade therapy. Detecting immunological checkpoints in the TME using
noninvasive imaging systems via tailored nanosensors improves the identification of patient out-
comes in immuno-oncology (IO). To enhance patient-specific analysis, lab-on-chip (LOC) technology
is a rapid, cost-effective, and accurate way of recapitulating the TME. Such novel nanomaterial-based
technologies have been of great interest for testing immunotherapies and assessing biomarkers.
Finally, we provide a perspective on the developments in artificial intelligence tools to facilitate
ICs-based nano theranostics toward cancer immunotherapy.
Keywords:
immunotherapy; immune checkpoint inhibitors; immuno-nanomaterials; immunodiagnostics
1. Introduction
The immune system defends the body against pathogens, which suggests extensive
implications for its use in therapeutic interventions. For one, many characteristics of cancer
cells are similar to those of healthy cells, thus making it difficult for the immune system to
identify them as foreign elements. It also enables the biomolecules expressed by tumors at
the tumor microenvironment (TME) to evade detection by immune cells. Cytokines may
even form a tumor-supportive immune microenvironment that inhibits antitumor activity
and transmits signals that directly promote tumor growth [
1
–
3
]. Therefore, new treatment
strategies are required to overcome these challenges in detecting cancer cells and thereby
preventing tumor development.
Cancer immunotherapy is a treatment method in which the immune system is stimu-
lated to communicate with the tumor at the TME to detect, target, and destroy the growth of
the cancer cells or malignancy [
4
]. Currently, several clinical studies are using immunother-
apy as a first line of treatment for cancer, which has enormous potential in comparison to
Micromachines 2022,13, 2217. https://doi.org/10.3390/mi13122217 https://www.mdpi.com/journal/micromachines

Micromachines 2022,13, 2217 2 of 21
conventional treatments such as surgery, chemotherapy, and radiotherapy [
5
]. Additionally,
immunotherapies are showing significant advancements in the treatment of solid tumors.
A recent report on immune drugs, in which monoclonal antibodies (mAbs) were used
for solid tumors in poor-prognosis patients, showed a 20% increased survival when compared
to chemo- and radiotherapy. Patients lived longer when monoclonal antibodies, molecular
inhibitors, or chemotherapy were given directly to the tumour site [
6
]. However, immunother-
apy is not widely accessible to patients due to the high cost—up to USD 250,000 per patient [
7
].
Consequently, tailored immune drug administration is an essential treatment method for solid
cancer therapy and should be integrated into ongoing clinical trials.
In this review, we have outlined multiple diagnostic imaging platforms with targeted
nanomaterials that allow for the selection of patients shows positive results from the use of
noninvasive immunotherapy. In this treatment, target-specific activation of immunogenic
antigens initiates a defensive effector immune response that kills specific cancer cells.
Various diagnostic imaging systems can be used to measure immune activation in the TME,
which provides a better prognosis for cancer [8].
1.1. Challenges in Immunotherapy
Cancer immunotherapy based on immune checkpoint inhibition (ICI) for patient
screening remains complex in terms of clinical decision-making. ICI therapy is only
effective for patients with mismatch repair deficit (dMMR) or high-microsatellite instability
(MSI-H) in their metastatic colorectal cancer (mCRC) [
9
]. In addition, neurological immune-
related adverse events (irAEs) are increasingly common in oncologic treatment approaches,
especially in patients treated with ICIs and combination therapy [
10
]. The immune-related
response criteria (irRC) clearly define an important concept necessary for the assessment of
immune-related responses; however, several pitfalls and issues related to irRC remain to
be solved [11].
Cancer treatments using ICI have short-term and long-term side effects, and many
long-term, or chronic, side effects are currently unfolding. A new study reported that ICI
can cause a range of long-term side effects, but most of them are mild, with more than
40% of the patients affected [
12
]. These chronic effects were skin rashes, hypothyroidism,
and joint pain. Monitoring immune checkpoint blockade (ICB) therapy can provide more
information to address these issues. Measuring IC expressions in the TME over time
could provide clinicians with useful information for evaluating potential outcomes. In
addition, biomarkers that can predict therapy response to ICB can be utilized for further
advanced-precision immunotherapy.
1.2. Need for Targeted Cancer Immunotherapy
Treatment response by immunotherapeutic drugs is characterized by immune cell
activation, which can have adverse effects on normal cells. Hence, a controlled mechanistic
pathway is required to understand the genomic sequence and mutations in the tumor to
prescribe treatments. Effective transport of cancer-immune drugs at the molecular level can
be delivered through engineering nano- and microcarriers functionalized using targeted
moieties. However, the regulated release kinetics of immune drugs at the intra-tumoral
region would follow burst release than controlled fashion. To improve drug release patterns,
externally triggered sources across electromagnetic regions, such as photothermal, sound,
and radiation (X-rays and radiofrequency), are utilized for personalized medicine.
The ability of solid tumors to bypass the body’s antitumor immune response is becom-
ing a hallmark characteristic of cancers (Figure 1). Galluzzi et al. defined the hallmarks of
anticancer immunotherapy as immunogenicity, immunosuppression, susceptibility, compo-
sition, localization, and functionality [
13
]. These hallmarks of anticancer immunotherapy
can lead to a successful treatment modality for personalized care. Systemic activation
reduces the sensitivity of immunotherapies and potentially hinders the anticancer-immune-
drug response [
14
]. The beneficial effects of anticancer immunotherapy are dependent on
(i) their innate capacity to elicit a tumor-targeting immune response, (ii) their capacity to

Micromachines 2022,13, 2217 3 of 21
establish an immunosuppressive TME, and (iii) their sensitivity to immune-effector mecha-
nisms [
15
]. These hallmarks aid in developing personalized immunotherapeutic regimes,
requiring improved effectiveness and multiparametric evaluations. However, there is a
need to search for the hallmark identifications that improve immune-based therapeutic
outcomes, beginning with the identification and usage of ICIs, which provide prognostic
insights into cancer immunotherapy.
Micromachines 2022, 13, x 3 of 22
The ability of solid tumors to bypass the body’s antitumor immune response is be-
coming a hallmark characteristic of cancers (Figure 1). Galluzzi et al. defined the hall-
marks of anticancer immunotherapy as immunogenicity, immunosuppression, suscepti-
bility, composition, localization, and functionality [13]. These hallmarks of anticancer im-
munotherapy can lead to a successful treatment modality for personalized care. Systemic
activation reduces the sensitivity of immunotherapies and potentially hinders the anti-
cancer-immune-drug response [14]. The beneficial effects of anticancer immunotherapy
are dependent on (i) their innate capacity to elicit a tumor-targeting immune response, (ii)
their capacity to establish an immunosuppressive TME, and (iii) their sensitivity to im-
mune-effector mechanisms [15]. These hallmarks aid in developing personalized immu-
notherapeutic regimes, requiring improved effectiveness and multiparametric evalua-
tions. However, there is a need to search for the hallmark identifications that improve
immune-based therapeutic outcomes, beginning with the identification and usage of ICIs,
which provide prognostic insights into cancer immunotherapy.
Figure 1. Schematic representation of cancer hallmarks for the immunological component of a tu-
mor. Modified from Ref. [13].
1.3. Nanotechnology in Cancer Immunotherapy
Nanomaterials ranging from 1 to 100 nm were used for immunotherapy with combi-
national drugs for effective cancer treatment [16]. Typically, these targeted nanoparticles
(NPs) were composed of a drug-concentrated core and a functionalized outside layer, or
shell. These engineered nanoparticles were further optimized based on size, shape, and
surface properties to increase their efficacy and reduce side effects. Nanomaterials with
different compositions were used to generate an effective cancer immunotherapy based
on ICIs.
Anticancer drugs currently used in clinical settings are hydrophobic, thereby making
it hard for them to travel in aqueous-body environments [17]. Encapsulation is one strat-
egy used for loading hydrophobic drugs in a nanoparticle carrier. This increases the con-
centration of hydrophobic drugs in the human system by a factor of over 5 × 10
4
[18]. Hy-
drophilic drugs come in the form of both macromolecules and small molecules, with some
limitations. For instance, cellular uptake is poor because they struggle to cross hydropho-
bic membranes, have low bioavailability, and have a short half-life. However, this has
Figure 1.
Schematic representation of cancer hallmarks for the immunological component of a tumor.
Modified from Ref. [13].
1.3. Nanotechnology in Cancer Immunotherapy
Nanomaterials ranging from 1 to 100 nm were used for immunotherapy with combina-
tional drugs for effective cancer treatment [
16
]. Typically, these targeted nanoparticles (NPs)
were composed of a drug-concentrated core and a functionalized outside layer, or shell. These
engineered nanoparticles were further optimized based on size, shape, and surface properties
to increase their efficacy and reduce side effects. Nanomaterials with different compositions
were used to generate an effective cancer immunotherapy based on ICIs.
Anticancer drugs currently used in clinical settings are hydrophobic, thereby making
it hard for them to travel in aqueous-body environments [
17
]. Encapsulation is one strategy
used for loading hydrophobic drugs in a nanoparticle carrier. This increases the concentration
of hydrophobic drugs in the human system by a factor of over 5
×
10
4
[
18
]. Hydrophilic drugs
come in the form of both macromolecules and small molecules, with some limitations. For
instance, cellular uptake is poor because they struggle to cross hydrophobic membranes, have
low bioavailability, and have a short half-life. However, this has been combated through the
use of nanoparticles, which protect and deliver hydrophilic drugs.
“Naturally targeted” immune cells, such as macrophages, monocytes, neutrophils,
and dendritic cells (DCs), phagocytose the free NP drugs to transport them to the cancer
site. Targeting cancerous cells using selective binding to specific receptors is possible due
to ligands such as small organic molecules, peptides, antibodies, and nucleic acids. This
design allows for the transport and simultaneous delivery of multiple drugs to a target,
which is useful for multimodal therapy techniques. Through the enhanced permeability
and retention (EPR) effect, NPs can easily drive into the TME. NPs are a flexible platform to
use in cancer immunotherapy, displaying potential in a variety of fields such as imaging and
drug delivery without harming another internal system [
19
]. Thus cancer immunotherapy

Micromachines 2022,13, 2217 4 of 21
is a cutting-edge treatment that dynamically changes the immune system’s ability to fight
cancer [20].
2. Immune-Targeting Nanomaterials
Immunotherapy can be classified as either active or passive immunotherapy. Active
immunotherapy directly stimulates the immune system to target cancer cells, whereas
passive immunotherapy activates immune cells through external agents like monoclonal
antibodies, drugs, and cytokines. Cancer immunotherapy remains challenging, however,
as it can have life-threatening side effects due to the severity of the disease [
21
]. The lack of
targeting is the fundamental cause of immunotherapy failure against cancer. Nontargeted
ICIs elicit a critical immunological response in the host that affects even normal cells.
Immunotherapy must be delivered in a precise way to get the optimal therapeutic effect
in cancer patients [
22
]. Clinical trials of cancer immunotherapies have shown promising
outcomes for immunological checkpoint inhibition, adoptive T cell therapy, therapeutic
cancer vaccines, and ablation-enhanced immunogenic cell death (Figure 2). Coloading of
drugs into a nanocarrier platform can efficiently deliver the drug to the subcellular levels
of cancer residing in the TME [23].
Micromachines 2022, 13, x 4 of 22
been combated through the use of nanoparticles, which protect and deliver hydrophilic
drugs.
“Naturally targeted” immune cells, such as macrophages, monocytes, neutrophils,
and dendritic cells (DCs), phagocytose the free NP drugs to transport them to the cancer
site. Targeting cancerous cells using selective binding to specific receptors is possible due
to ligands such as small organic molecules, peptides, antibodies, and nucleic acids. This
design allows for the transport and simultaneous delivery of multiple drugs to a target,
which is useful for multimodal therapy techniques. Through the enhanced permeability
and retention (EPR) effect, NPs can easily drive into the TME. NPs are a flexible platform
to use in cancer immunotherapy, displaying potential in a variety of fields such as imag-
ing and drug delivery without harming another internal system [19]. Thus cancer immu-
notherapy is a cutting-edge treatment that dynamically changes the immune system’s
ability to fight cancer [20].
2. Immune-Targeting Nanomaterials
Immunotherapy can be classified as either active or passive immunotherapy. Active
immunotherapy directly stimulates the immune system to target cancer cells, whereas
passive immunotherapy activates immune cells through external agents like monoclonal
antibodies, drugs, and cytokines. Cancer immunotherapy remains challenging, however,
as it can have life-threatening side effects due to the severity of the disease [21]. The lack
of targeting is the fundamental cause of immunotherapy failure against cancer. Nontar-
geted ICIs elicit a critical immunological response in the host that affects even normal
cells. Immunotherapy must be delivered in a precise way to get the optimal therapeutic
effect in cancer patients [22]. Clinical trials of cancer immunotherapies have shown prom-
ising outcomes for immunological checkpoint inhibition, adoptive T cell therapy, thera-
peutic cancer vaccines, and ablation-enhanced immunogenic cell death (Figure 2). Co-
loading of drugs into a nanocarrier platform can efficiently deliver the drug to the subcel-
lular levels of cancer residing in the TME [23].
Figure 2. Schematic depiction of the role of nanomaterials platforms in various immunotherapies
for cancer.
2.1. Nanocarriers for Immune Checkpoint Inhibitor (ICI) or Blockade (ICB)
Recently, cancer immunotherapies using ICIs or ICBs have shown remarkable ad-
vancements in the treatment of advanced-stage cancers, displayed by improved patient
outcomes. When these ICIs bind to the surface of partner proteins such as T cells, they
Figure 2.
Schematic depiction of the role of nanomaterials platforms in various immunotherapies
for cancer.
2.1. Nanocarriers for Immune Checkpoint Inhibitor (ICI) or Blockade (ICB)
Recently, cancer immunotherapies using ICIs or ICBs have shown remarkable advance-
ments in the treatment of advanced-stage cancers, displayed by improved patient outcomes.
When these ICIs bind to the surface of partner proteins such as T cells, they turn “off” T
cell signals and render them inactive. In other words, the ICIs inhibit cytokine expression,
which prohibits a proper immune response from the T cell. ICIs block the checkpoint
proteins of the tumor cells from binding to the ligand, resulting in a deeply improved
prognosis. The ability of ICIs to regulate both innate and adaptive immune cells allows
them to effectively renew the immune response and restore tumor-cell infiltration [
24
].
Research shows that sixteen FDA-approved immunomodulators, nine ICIs, and multiple
cytokines and adjuvants are available as cancer immunotherapies [25].
Throughout the decade, many mAb-based ICI drugs have shown remarkable results
towards several IC targets, e.g., cytotoxic T lymphocyte-associated protein 4 (CTLA-4),
and programmed cell death 1 or ligand 1 and 2 (PD-1 or PD-L1 or PD-L2) show successful
results in the clinic [
26
]. These induce remarkable tumor regression and long-lasting
recovery in certain cancer patients. For example, acute lymphoblastic leukemia (ALL)
is highly cancer-resistant, but T cells expressing chimeric antigen receptors (CAR) have

Micromachines 2022,13, 2217 5 of 21
shown improved prognosis [
27
]. In clinical trials, a variety of immunostimulatory mAbs,
small molecules that reverse cancer-associated immunosuppression, and tumor-targeting
therapeutic vaccines are used for treatments. Several immunotherapeutic cancer treatments
are becoming more widely used and some ICIs have even reached late-stage clinical testing.
When utilizing nontargeted drug delivery, patients may be at risk for developing au-
toimmune reactions and related adverse effects [
28
]. Critical challenges in ICI-based cancer
immunotherapies include targeted localization, protein infusion stability, and regulated ICI
release. ICI blockage of the receptor on T cells results in more peripheral T cell recruitment,
leading to an autoimmune reaction [
29
]. Nanotechnology-assisted administration of ICIs
has benefits, including enhanced drug accumulation in tumors, simultaneous delivery
of multiple ICIs, real-time delivery monitoring, and even facilitating advanced delivery
techniques. The engineered nanoparticles with ICIs are better able to reach the tumor
via enhanced permeability and retention (EPR) effects. The nanomedicine-based ICIs can
penetrate complicated tumor environments by overcoming physiological barriers such as
the blood–brain barrier and the host immune response (Figure 3).
Micromachines 2022, 13, x 5 of 22
turn “off” T cell signals and render them inactive. In other words, the ICIs inhibit cytokine
expression, which prohibits a proper immune response from the T cell. ICIs block the
checkpoint proteins of the tumor cells from binding to the ligand, resulting in a deeply
improved prognosis. The ability of ICIs to regulate both innate and adaptive immune cells
allows them to effectively renew the immune response and restore tumor-cell infiltration
[24]. Research shows that sixteen FDA-approved immunomodulators, nine ICIs, and mul-
tiple cytokines and adjuvants are available as cancer immunotherapies [25].
Throughout the decade, many mAb-based ICI drugs have shown remarkable results
towards several IC targets, e.g., cytotoxic T lymphocyte-associated protein 4 (CTLA-4),
and programmed cell death 1 or ligand 1 and 2 (PD-1 or PD-L1 or PD-L2) show successful
results in the clinic [26]. These induce remarkable tumor regression and long-lasting re-
covery in certain cancer patients. For example, acute lymphoblastic leukemia (ALL) is
highly cancer-resistant, but T cells expressing chimeric antigen receptors (CAR) have
shown improved prognosis [27]. In clinical trials, a variety of immunostimulatory mAbs,
small molecules that reverse cancer-associated immunosuppression, and tumor-targeting
therapeutic vaccines are used for treatments. Several immunotherapeutic cancer treat-
ments are becoming more widely used and some ICIs have even reached late-stage clinical
testing.
When utilizing nontargeted drug delivery, patients may be at risk for developing
autoimmune reactions and related adverse effects [28]. Critical challenges in ICI-based
cancer immunotherapies include targeted localization, protein infusion stability, and reg-
ulated ICI release. ICI blockage of the receptor on T cells results in more peripheral T cell
recruitment, leading to an autoimmune reaction [29]. Nanotechnology-assisted admin-
istration of ICIs has benefits, including enhanced drug accumulation in tumors, simulta-
neous delivery of multiple ICIs, real-time delivery monitoring, and even facilitating ad-
vanced delivery techniques. The engineered nanoparticles with ICIs are better able to
reach the tumor via enhanced permeability and retention (EPR) effects. The nanomedi-
cine-based ICIs can penetrate complicated tumor environments by overcoming physio-
logical barriers such as the blood–brain barrier and the host immune response (Figure 3).
Figure 3. A diagrammatic representation of the immune checkpoint’s blockage using nanocarriers
loaded with checkpoint inhibitors and antibodies for targeted cancer immunotherapy. Antitumor
immune responses are regulated by proteins called checkpoints, such as PD-L1 on tumor cells and
PD-1 on T cells. When PD-L1 binds to PD-1, it inhibits the activity of T cells and prevents them from
killing tumor cells. Targeted nanocarriers functionalized with an immune checkpoint inhibitor (anti-
PD-L1 or anti-PD-1) allow T cells to destroy tumor cells by preventing PD-L1 from attaching to PD-
1.
Figure 3.
A diagrammatic representation of the immune checkpoint’s blockage using nanocarriers
loaded with checkpoint inhibitors and antibodies for targeted cancer immunotherapy. Antitumor
immune responses are regulated by proteins called checkpoints, such as PD-L1 on tumor cells and PD-1
on T cells. When PD-L1 binds to PD-1, it inhibits the activity of T cells and prevents them from killing
tumor cells. Targeted nanocarriers functionalized with an immune checkpoint inhibitor (anti-PD-L1 or
anti-PD-1) allow T cells to destroy tumor cells by preventing PD-L1 from attaching to PD-1.
Polo-like kinase 1 (PLK1) enzymes are key mitotic kinases that are overexpressed in
a variety of cancers and exhibit oncogenic properties. PLK1 inhibition kills cancer cells
and upregulates PD-L1 expression in the TME through the mitogen-activated protein
kinase (MAPK) pathway. Yantesee et al. developed a nanoplatform strategy to express the
relationship between PD-L1 antibody and PLK-1 inhibitor to target ICIs to improve the
survival of NSCLC. The nanoplatform consists of mesoporous silica nanoparticles (MSNs)
loaded with the immunotherapy drug Volasertib (PLK-1 inhibitor) and functionalized with
PD-L1 on the surface of nanostructures to target cancer cells. This combination of strategies
is defined as the ARAC platform (antigen-release agents and a checkpoint). The increase in
the uptake of MSNs in NSCLC via PD-L1, thereby delivering PLK-1 in the cytosol, leads to
cellular apoptosis.
In vivo
evaluation of ARAC has shown an improved survival rate (up to
30 days) and a threefold reduction in the tumor volume compared to Volasertib. Inhibiting
PLK1 results in an increase in PD-L1 expression in the remaining surviving cancer cells.
The PD-L1 antibody-targeted ARAC significantly enhances adaptive antitumor immunity
and T cell activity by elevating the CD8
+
ratio and tumor infiltration. The subsequent
dosage of ARAC results in immunosuppression in the TME [30].

Micromachines 2022,13, 2217 6 of 21
A decline In the efficacy of ICBs in cancer immunotherapy is often attributed to
tumor suppressors, which act as the driving force behind tumorigenesis. Despite the cell-
autonomous tumor-suppressive effects, evidence indicates that the p53 protein modulates
the TME by altering the contact of tumor cells with immune cells. When p53 is restored
genetically, myeloid cell activation is upregulated, and tumor antigen-specific adaptive
immunity is enhanced. Shi et al. developed specific hybrid nanoparticles with a lipid-based
poly (lactic-co-glycolic acid) (PLGA) polymer core to transport p53 mRNA transfection
complexes [
31
]. Targeted p53 mRNA nanoparticles suppressed the pro-tumorigenic M2-
type tumor-associated macrophage (TAM) and enhanced the MHC-1 expression with
antitumor immunity. Glycogen synthase kinase 3 (GSK-3) works as an unanticipated tumor
suppressor in certain cancers [
32
], as it is responsible for phosphorylating the oncoprotein
known as mouse double minute 2 homologs (MDM2). The MDM2 protein is the most
important regulator of the p53 protein [
33
]. Thus, instead of restoring the p53, direct
inhibition of GSK3 effectively reduces PD-1 expression and promotes the proliferation of
cytotoxic T cells, resulting in long-term T cell memory. However, delivery of the GSK-3
small molecule is challenging due to its relatively short half-life and high availability in
off-targeted organs. Thierry et al. reported a nano formulation containing a GSK-3 inhibitor
loaded with PEG-PLGA nanoparticles to block the PD-L1 ICP [
34
]. Results indicate that the
nanoplatform enhances the efficacy of the ICB therapy, thereby improving cancer treatment.
2.2. Nanocarrier for Adoptive Cell Transfer (ACT)
Adoptive cell therapy (ACT) involving T cells derived from tumor-infiltrating lympho-
cytes (TIL) has the potential for both immunostimulatory and immunosuppressive cancer
therapies [
35
]. However, ACT is still a barrier to a robust activation of the host immune
system, the regulation of signaling pathways, and the maintenance of a progression-free
state. The use of the nanoplatform can improve the production, application, and efficacy of
T cell immunotherapy for a variety of cancer conditions [36].
Cisplatin, also known as cis-diamminedichloroplatinum (II) (CDDP), is an effective
cancer drug in clinical trials [
37
]. The effectiveness of cisplatin in inhibiting tumor growth
has been established; however, its organ toxicity presents a significant challenge. Yao and
his colleague utilized the CDDP drug-loaded polyethylene glycol (PEG)–polyglutamate
block copolymer micelle nanoparticles (CDDP-NPs) for antitumor immune response [
38
].
The longer retention time of the CDDP-NPs in the TME upregulates the major histocompat-
ibility complex class I (MHC-I), leading to the activation of the amyloid precursor protein
(APP) pathway. The DCs are attributed to the interaction between the T cell receptor
(TCR) and the peptide it recognizes by the APP (Figure 4). Thus, the CDDP-NPs indirectly
activate the tumor antigen-presenting CD8
+
T cell through the TCR signaling pathways.
The OX40 is a tumor necrosis factor receptor superfamily (TNFRSF) domain that acts as
a costimulatory antigen molecule expressed in the CD8
+
T cells [
39
]. Therefore, the use
of CDDP-NPs along with the OX40 agonists (aOX40) had a remarkable therapeutic effect
in inducing T cell infiltration in the tumor environment. The promotion of aOX40 would
activate the proinflammatory cytokines and secrete TNF-
α
, IFN-
γ
, and IL-2 for killing the
tumor. Immunotherapies utilizing CDDP-NPs remain in the preclinical phase of develop-
ment. It is crucial to analyze the efficacy of nanomedicine in the clinic to determine the
possible role of T cell infiltration in the tumor.
The development of resistance to tumors can also be through the stimulation of the
innate immune system. The development of active nanocarriers facilitates binding with
the innate immune system to regulate “danger signals”. The activation of danger sig-
nals at the tumor site by Toll-like receptors such as retinoic-acid-inducible gene I (RIG-I),
nucleotide-binding oligomerization domain (NOD), and stimulator of interferon genes
(STING) improves T cell response [
40
]. Current clinical research indicates that natural lig-
ands for STING and cyclic dinucleotides (CDNs) are effective agonists for inducing potent
antitumor immunity. CDNs are susceptible to nucleases and impermeable to cell mem-
branes, which hinders their systemic delivery. Irvine et al. formulated PEGylated lipids

Micromachines 2022,13, 2217 7 of 21
conjugated with CDNs that self-assemble in lipid nanodiscs (LNDs) [
41
]. Discoid-shaped
nanoparticles (LNDs-CDNs) are optimal for intravenous delivery and show effective pene-
tration within the tumor model that leads to tumor necrosis.
Micromachines 2022, 13, x 7 of 22
The OX40 is a tumor necrosis factor receptor superfamily (TNFRSF) domain that acts as a
costimulatory antigen molecule expressed in the CD8
+
T cells [39]. Therefore, the use of
CDDP-NPs along with the OX40 agonists (aOX40) had a remarkable therapeutic effect in
inducing T cell infiltration in the tumor environment. The promotion of aOX40 would
activate the proinflammatory cytokines and secrete TNF-α, IFN-γ, and IL-2 for killing the
tumor. Immunotherapies utilizing CDDP-NPs remain in the preclinical phase of develop-
ment. It is crucial to analyze the efficacy of nanomedicine in the clinic to determine the
possible role of T cell infiltration in the tumor.
The development of resistance to tumors can also be through the stimulation of the
innate immune system. The development of active nanocarriers facilitates binding with
the innate immune system to regulate “danger signals”. The activation of danger signals
at the tumor site by Toll-like receptors such as retinoic-acid-inducible gene I (RIG-I), nu-
cleotide-binding oligomerization domain (NOD), and stimulator of interferon genes
(STING) improves T cell response [40]. Current clinical research indicates that natural lig-
ands for STING and cyclic dinucleotides (CDNs) are effective agonists for inducing potent
antitumor immunity. CDNs are susceptible to nucleases and impermeable to cell mem-
branes, which hinders their systemic delivery. Irvine et al. formulated PEGylated lipids
conjugated with CDNs that self-assemble in lipid nanodiscs (LNDs) [41]. Discoid-shaped
nanoparticles (LNDs-CDNs) are optimal for intravenous delivery and show effective pen-
etration within the tumor model that leads to tumor necrosis.
Effective cancer cytosol penetration of CDN-loaded lipid nanomaterials triggers an-
titumor immunity through CD8
+
T cell and natural killer (NK) cell activation [42]. STING
activation pathways trigger NK cells to produce interferon γ (IFN-γ), promoting PD-1
expression in tumor cells [43]. However, the data from studies imply that a single dose is
insufficient to activate NK cells [44]. Therefore, a combination of PD-1 antibody with the
CDN agonists loaded in lipid nanoparticles has an antitumor impact in lung metastasis
under multiple-dose cycles. Ferroptosis is an iron-dependent form of apoptosis for tumor
suppression. Cancer cells undergoing ferroptosis also trigger IFN-γ, which promotes the
CD8
+
T lymphocytes in the TME. The expression profile analysis identified miR-21-3p as
the highly upregulated microRNAs that regulate ferroptosis. Chunying Li’s group exam-
ined the anti-PD-1 immunotherapy impact of miR-21-3p-loaded gold nanoparticles in a
preclinical tumor model [45]. T-cell-adoptive cancer immunotherapies can be improved
by integrating the nanosystem loaded with the immune drugs.
Figure 4. Schematic illustration which depicts the mechanism of ACT using various nanocarriers.
The nanocarriers, such as lipid-based nanoparticles, nanodiscs, or core–shell nanoparticles are co-
Figure 4.
Schematic illustration which depicts the mechanism of ACT using various nanocarriers. The
nanocarriers, such as lipid-based nanoparticles, nanodiscs, or core–shell nanoparticles are coloaded
with immune drugs, antibodies, and adjuvants for active cancer immunotherapy. The immune
activation of the dendritic cells contributes to immunological responses to the TME by secreting
IFN-γ, which is promoted by the effector activities of CD8+T cells to cause tumor death.
Effective cancer cytosol penetration of CDN-loaded lipid nanomaterials triggers anti-
tumor immunity through CD8
+
T cell and natural killer (NK) cell activation [
42
]. STING
activation pathways trigger NK cells to produce interferon
γ
(IFN-
γ
), promoting PD-1
expression in tumor cells [
43
]. However, the data from studies imply that a single dose is
insufficient to activate NK cells [
44
]. Therefore, a combination of PD-1 antibody with the
CDN agonists loaded in lipid nanoparticles has an antitumor impact in lung metastasis
under multiple-dose cycles. Ferroptosis is an iron-dependent form of apoptosis for tumor
suppression. Cancer cells undergoing ferroptosis also trigger IFN-
γ
, which promotes the
CD8
+
T lymphocytes in the TME. The expression profile analysis identified miR-21-3p
as the highly upregulated microRNAs that regulate ferroptosis. Chunying Li’s group
examined the anti-PD-1 immunotherapy impact of miR-21-3p-loaded gold nanoparticles in
a preclinical tumor model [
45
]. T-cell-adoptive cancer immunotherapies can be improved
by integrating the nanosystem loaded with the immune drugs.
2.3. Nanocarriers for Cancer Vaccine
Cancer vaccines generally use tumor-associated antigens (TAAs) and tumor-specific
antigens (TSAs) to boost the patient’s immune system. Therapies involving TSAs or neoanti-
gens selectively expressed in the tumor have been at the forefront of cancer immunotherapy.
Vaccines based on neoantigens have the potential to circumvent central immune tolerance
and activate tumor-specific T cells [
46
]. Sipuleucel-T (Provenge
®
) and talimogene laher-
parepvec (IMLYGIC
®
) are some of the DCs-based cancer vaccines currently in phase I
clinical trials [
47
,
48
]. However, poor targeting of the neoantigen-based cancer vaccines
results in a low affinity to the TCR, making it incapable of mediating an effective antitumor
response. Combining the NPs platform with the neoantigen-targeted vaccine delivery has
therapeutic potential in cancer immunotherapy.
Jadidi and colleagues were the first to report that the combined suppression of
lymphocyte-associated gene 3 (LAG3) and PD-1 by DC vaccines improves anticancer
efficacy in the TME. LAG3 is an inhibitory receptor generated by immune cells to trigger T

Micromachines 2022,13, 2217 8 of 21
cell dysfunction [
49
]. Initiating immunosuppressive responses and promoting the prolif-
eration of cancer cells, LAG3 promotes the development of cancer [
50
]. Specific siRNAs
and LAG3/PD-1 antibodies were loaded onto chitosan–dextran sulfate–lactate (TMC-DS-L)
nanoparticles, which led to increased IFN-γproduction at the tumor site [51].
The primary obstacles in cancer immunotherapy are multiple drug resistance (MDR)
and the inadequate accumulation of cancer vaccines in the TME [
52
]. Yao et al. developed
a zwitterionic polymer employing poly (carboxy betaine methacrylate) (PBCMA) as a
polymer shell over mesoporous organo silica nanoparticles (MONs) to overcome MDR
in the TME [
53
]. PCBMA is loaded with redox-responsive sulfur dioxide (SO
2
), prodrug
molecules (DN 2,4 dinitrobenzene-sulfonyl chloride), and chemotherapeutic drugs (DOX,
doxorubicin) to treat MDR cancer effectively. The downregulation of P-glycoprotein in the
presence of SO
2
makes cancer cells more susceptible to chemotherapy-induced apoptosis.
PCBMA increases the nanomedicine’s intratumor accumulation, resulting in a 94.8% re-
duction in tumor growth. The redox-responsive SO
2
sensitizes cells, which aids DOX in
prolonging the apoptosis in the TME.
Preclinical immuno compatibility development requires the controlled activation of
innate immunity [
54
]. Biopolymers (proteins, nucleic acids, collagen, chitosan, etc.), syn-
thetic polymers (polystyrene, poly (lactic-co-glycolic acid) (PLGA), and poly (amino ester)
(PBAEs)), and stimuli-responsive polymers loaded with immunoadjuvants have MDR
capabilities that promote immunological activity. These polymers enable multi adjuvant
synergy in cancer immunotherapy by stabilizing drug–cargo transport and activating proin-
flammatory cytokines. Thus, the camouflage of polymeric nanoparticles for the delivery of
cancer vaccines provides an efficient platform for cancer immunotherapy (Figure 5).
Micromachines 2022, 13, x 9 of 22
Figure 5. The cancer vaccination nanoparticles were camouflaged for specific functions in the TME.
Nanovesicles containing a cancer vaccine comprised of a variety of antigens and biomolecules are
being developed for use in cancer immunotherapy.
2.4. Nanocarriers for Immunogenic Cell Death (ICD)
Immunotherapy is a treatment method to eradicate cancer cells with a high degree of
specificity and minimal side effects while preventing their recurrence. Chemotherapy,
photothermal therapy (PTT), radiotherapy, and reactive-oxygen-species (ROS)-mediated
therapies can induce immunogenic cell death (ICD), which is used to improve cytotoxic-
based antitumor immunity. Cancer immunotherapies have had limited success in ablation
treatment due to the development of local and systemic immunosuppression and immune
evasion. Local radiation therapy in the TME destroys cancer cells by activating the im-
mune system [55]. When radiation and immunotherapy are combined on a nanoplatform,
they have the potential to enhance the overall therapeutic efficacy [56]. These methods
have the potential to improve patient outcomes, but they encounter challenges in optimiz-
ing the radiation dose, toxicity, and timing of combined therapies [57].
Chemotherapeutics can induce ICD and release tumor-specific antigens that are ef-
fective against numerous types of cancer [58]. Combining chemotherapeutics and im-
mune adjuvants is a viable method for achieving synergistic therapeutic benefits. Deng et
al. reported a nanocarrier composed of liposomal spherical nucleic acids (SNAs) and FDA-
approved 1,2-dioleoyl-sn-glycerol-3-phosphoethanolamine (DOPE) for enhanced cellular
absorption and stability against nucleases [59]. Conjugating chemotherapeutics such as
doxorubicin (DOX) with DOPE triggered the ICD (DOPE-DOX) to secrete tumor-specific
antigens. CpG oligodeoxynucleotides (CpGs) and matrix metalloproteinases-9 (MMP-9)
are immunostimulatory reagents (DOPE-MMP-CpG) that amplify the immune response
and promote immune cell penetration into the TME, respectively. Tumor cell MMP-9 and
glutathione stimulated lipid-encapsulated SNAs to release DOX and CpGs into the TME.
However, immunosuppression and cytotoxic side effects continue to restrict the use of
these nanocarriers.
Figure 5.
The cancer vaccination nanoparticles were camouflaged for specific functions in the TME.
Nanovesicles containing a cancer vaccine comprised of a variety of antigens and biomolecules are
being developed for use in cancer immunotherapy.
2.4. Nanocarriers for Immunogenic Cell Death (ICD)
Immunotherapy is a treatment method to eradicate cancer cells with a high degree
of specificity and minimal side effects while preventing their recurrence. Chemotherapy,
photothermal therapy (PTT), radiotherapy, and reactive-oxygen-species (ROS)-mediated

Micromachines 2022,13, 2217 9 of 21
therapies can induce immunogenic cell death (ICD), which is used to improve cytotoxic-
based antitumor immunity. Cancer immunotherapies have had limited success in ablation
treatment due to the development of local and systemic immunosuppression and immune
evasion. Local radiation therapy in the TME destroys cancer cells by activating the immune
system [
55
]. When radiation and immunotherapy are combined on a nanoplatform, they
have the potential to enhance the overall therapeutic efficacy [
56
]. These methods have the
potential to improve patient outcomes, but they encounter challenges in optimizing the
radiation dose, toxicity, and timing of combined therapies [57].
Chemotherapeutics can induce ICD and release tumor-specific antigens that are effec-
tive against numerous types of cancer [
58
]. Combining chemotherapeutics and immune
adjuvants is a viable method for achieving synergistic therapeutic benefits. Deng et al.
reported a nanocarrier composed of liposomal spherical nucleic acids (SNAs) and FDA-
approved 1,2-dioleoyl-sn-glycerol-3-phosphoethanolamine (DOPE) for enhanced cellular
absorption and stability against nucleases [
59
]. Conjugating chemotherapeutics such as
doxorubicin (DOX) with DOPE triggered the ICD (DOPE-DOX) to secrete tumor-specific
antigens. CpG oligodeoxynucleotides (CpGs) and matrix metalloproteinases-9 (MMP-9)
are immunostimulatory reagents (DOPE-MMP-CpG) that amplify the immune response
and promote immune cell penetration into the TME, respectively. Tumor cell MMP-9 and
glutathione stimulated lipid-encapsulated SNAs to release DOX and CpGs into the TME.
However, immunosuppression and cytotoxic side effects continue to restrict the use of
these nanocarriers.
Yibru et al. developed a pH-responsive polyamidoamine (PAMAM) dendritic nanoparti-
cles into the copolymer hydrogel (PCLA-PEG-PCLA) for the codelivery of DOX (PAMAM-
DOX). PCLA-PEG-PCLA (poly(caprolactone-co-lactide)-poly (ethylene glycol)-b-poly(caprolac
tone-co-lactide) is a thermo reversible polymer ability to integrate with PAMAM-DOX nanocar-
riers for targeted drug delivery. At body temperature, PAMAM-DOX dendritic nanocarriers
form a gel and facilitate a sustained DOX release in the TME. The combination of the immune
activation with various cancer ablation techniques enhances the death of tumors. IND cou-
pled with PAMAM-DOX also promotes the activate NK cells to attack tumor cells. However,
immunological adjuvants in combination with chemotherapy remain resistant in treating
some forms of cancer, especially triple-negative breast cancer (TNBC).
The photothermal immunotherapy (PTT) technique has also been demonstrated to
reduce tumor development and enhance immune response. However, PTT efficiency in
clinical applications is hindered by its poor stability, low therapeutic potency, and loss of
affinity in the multistep delivery carrier synthesis [
60
]. A research team led by Zou devel-
oped a mesoporous carbon nanocomposite (MCN) loaded with IR792 a near-infrared (NIR)
laser dye (IR792-MCN) [
61
]. Photothermal immunotherapy using NIR laser irradiation
is improved by combining the PD-L1 antibody with the nanocarrier (IR792-MCN@ICB).
The delivered IR792-MCN@ICB irradiated at 808 nm efficiently kills tumor cells by in-
ducing DC maturation and secreting cytokines. PD-L1 gene silencing in conjunction with
photothermal immunotherapy promotes tumor-infiltrating CD8
+
and CD4
+
T cells, which
reduces tumor growth and prevents cancer metastasis. Cancer immunotherapy based on
ICDs in combination with inhibitors as adjuvants plays a significant role in determining
the effectiveness of personalized therapy (Figure 6).

Micromachines 2022,13, 2217 10 of 21
Micromachines 2022, 13, x 10 of 22
Yibru et al. developed a pH-responsive polyamidoamine (PAMAM) dendritic nano-
particles into the copolymer hydrogel (PCLA-PEG-PCLA) for the codelivery of DOX (PA-
MAM-DOX). PCLA-PEG-PCLA (poly(caprolactone-co-lactide)-poly (ethylene glycol)-b-
poly(caprolactone-co-lactide) is a thermo reversible polymer ability to integrate with PA-
MAM-DOX nanocarriers for targeted drug delivery. At body temperature, PAMAM-DOX
dendritic nanocarriers form a gel and facilitate a sustained DOX release in the TME. The
combination of the immune activation with various cancer ablation techniques enhances
the death of tumors. IND coupled with PAMAM-DOX also promotes the activate NK cells
to attack tumor cells. However, immunological adjuvants in combination with chemo-
therapy remain resistant in treating some forms of cancer, especially triple-negative breast
cancer (TNBC).
The photothermal immunotherapy (PTT) technique has also been demonstrated to
reduce tumor development and enhance immune response. However, PTT efficiency in
clinical applications is hindered by its poor stability, low therapeutic potency, and loss of
affinity in the multistep delivery carrier synthesis [60]. A research team led by Zou devel-
oped a mesoporous carbon nanocomposite (MCN) loaded with IR792 a near-infrared
(NIR) laser dye (IR792-MCN) [61]. Photothermal immunotherapy using NIR laser irradi-
ation is improved by combining the PD-L1 antibody with the nanocarrier (IR792-
MCN@ICB). The delivered IR792-MCN@ICB irradiated at 808 nm efficiently kills tumor
cells by inducing DC maturation and secreting cytokines. PD-L1 gene silencing in con-
junction with photothermal immunotherapy promotes tumor-infiltrating CD8
+
and CD4
+
T cells, which reduces tumor growth and prevents cancer metastasis. Cancer immuno-
therapy based on ICDs in combination with inhibitors as adjuvants plays a significant role
in determining the effectiveness of personalized therapy (Figure 6).
Figure 6. Schematic illustration of immunogenic cell death mediated by targeted nanocarriers con-
jugated with stimulating molecules such as immunological adjuvants and agonistic antibodies. The
combination of immune activation with various cancer-ablation techniques enhances the death of
tumors.
3. Diagnostic Imaging for Cancer Immunotherapy
To improve patient outcomes in the immuno-oncology (IO), existing diagnostic
methods, including CT, PET scans, and serum protein biomarkers, are unreliable. In this
regard, several point-of-care diagnostic approaches have been developed, but none of
Figure 6.
Schematic illustration of immunogenic cell death mediated by targeted nanocarriers
conjugated with stimulating molecules such as immunological adjuvants and agonistic antibodies.
The combination of immune activation with various cancer-ablation techniques enhances the death
of tumors.
3. Diagnostic Imaging for Cancer Immunotherapy
To improve patient outcomes in the immuno-oncology (IO), existing diagnostic meth-
ods, including CT, PET scans, and serum protein biomarkers, are unreliable. In this regard,
several point-of-care diagnostic approaches have been developed, but none of these tech-
niques are approved by the FDA to be in clinical practice. IHC is the only standard
diagnostic in practice, however, it does not provide complete information for the tumor
or metastatic cancers. IC markers from blood can be diagnosed easily, noninvasively, and
can be tested multiple times. Imaging technologies play a pivotal role in visualizing cancer
regions and revealing treatment responses (Figure 7).
Micromachines 2022, 13, x 11 of 22
these techniques are approved by the FDA to be in clinical practice. IHC is the only stand-
ard diagnostic in practice, however, it does not provide complete information for the tu-
mor or metastatic cancers. IC markers from blood can be diagnosed easily, noninvasively,
and can be tested multiple times. Imaging technologies play a pivotal role in visualizing
cancer regions and revealing treatment responses (Figure 7).
Figure 7. A schematic representation illustrating the nanoparticles’ role in different imaging modal-
ities for cancer immune checkpoint detections.
Imaging systems can be classified into structural and molecular modalities. In pre-
clinical and clinical practice, imaging techniques used to detect tumors include computed
tomography (CT), ultrasound (US), magnetic resonance imaging (MRI), positron emission
tomography (PET), and optical imaging (OI) [62]. PET and OI (visible and NIR-based)
show the molecular dynamics of cancer cells. All these imaging modalities have their pros
and cons when used for cancer immune checkpoint imaging.
3.1. PET Imaging
PET/CT combines the benefits of two imaging techniques to accurately determine the
state of the cancer. This hybrid imaging technique provides the complementary structural
and molecular information, the localization zone, and 3D volume information with an
improved signal-to-noise ratio. Extensive works based on imaging in cancer immunother-
apy enable whole-body visualization of the tumor and immune cell characteristics with-
out invasive procedures, which may help in the assessments for ICI therapies. Recently, a
large amount of interest was focused on targeting ICIs such as PD-L1, PD-L2, PD-1, and
CTLA-4. For instance, conjugating the contrast agents with small molecules, full antibod-
ies, and antibody fragments enables targeted imaging.
PET imaging is often used due to its high sensitivity; however, it is restricted in its
spatial resolution. The rise of immune PET imaging is well-regarded for its speed in diag-
nostic and tumor-progression evaluations [62]. PD-1 is an immune checkpoint that pre-
vents the immune system from attacking healthy cells. However, cancerous cells often
express their ligand, PD-L1, as a way of deceiving the body’s natural defense system. PD-
1 is expressed in T cells and cancer cells, or antigen-presenting cells will often express PD-
L1 as a way of blocking antitumor responses.
Recently, the
64
Cu-FN3hPD-L1 binder was engineered for imaging under PET/CT
scans. Natarajan and colleagues developed this binder to target the PD-L1 immune check-
point, using a 12kD human type 3 fibronectin (FN3) scaffold with a copper-64 radiotracer.
The binder was tested in vitro using cancerous human xenografts as well as in vivo using
mice models. It was found that the
64
Cu-FN3hPD-L1 binder could travel to the tumor site
and provide visualization of the cancer, as well as reveal treatment progress and cancer
metastasis [63]. The first immune checkpoint study using in vivo conditions tested two
different tracers using PET/CT imaging on the whole body. Before being treated with
Figure 7.
A schematic representation illustrating the nanoparticles’ role in different imaging modali-
ties for cancer immune checkpoint detections.
Imaging systems can be classified into structural and molecular modalities. In pre-
clinical and clinical practice, imaging techniques used to detect tumors include computed
tomography (CT), ultrasound (US), magnetic resonance imaging (MRI), positron emission
tomography (PET), and optical imaging (OI) [
62
]. PET and OI (visible and NIR-based)

Micromachines 2022,13, 2217 11 of 21
show the molecular dynamics of cancer cells. All these imaging modalities have their pros
and cons when used for cancer immune checkpoint imaging.
3.1. PET Imaging
PET/CT combines the benefits of two imaging techniques to accurately determine the
state of the cancer. This hybrid imaging technique provides the complementary structural
and molecular information, the localization zone, and 3D volume information with an im-
proved signal-to-noise ratio. Extensive works based on imaging in cancer immunotherapy
enable whole-body visualization of the tumor and immune cell characteristics without
invasive procedures, which may help in the assessments for ICI therapies. Recently, a large
amount of interest was focused on targeting ICIs such as PD-L1, PD-L2, PD-1, and CTLA-4.
For instance, conjugating the contrast agents with small molecules, full antibodies, and
antibody fragments enables targeted imaging.
PET imaging is often used due to its high sensitivity; however, it is restricted in its
spatial resolution. The rise of immune PET imaging is well-regarded for its speed in
diagnostic and tumor-progression evaluations [
62
]. PD-1 is an immune checkpoint that
prevents the immune system from attacking healthy cells. However, cancerous cells often
express their ligand, PD-L1, as a way of deceiving the body’s natural defense system. PD-1
is expressed in T cells and cancer cells, or antigen-presenting cells will often express PD-L1
as a way of blocking antitumor responses.
Recently, the
64
Cu-FN3hPD-L1 binder was engineered for imaging under PET/CT
scans. Natarajan and colleagues developed this binder to target the PD-L1 immune check-
point, using a 12kD human type 3 fibronectin (FN3) scaffold with a copper-64 radiotracer.
The binder was tested
in vitro
using cancerous human xenografts as well as
in vivo
using
mice models. It was found that the
64
Cu-FN3hPD-L1 binder could travel to the tumor site
and provide visualization of the cancer, as well as reveal treatment progress and cancer
metastasis [
63
]. The first immune checkpoint study using
in vivo
conditions tested two
different tracers using PET/CT imaging on the whole body. Before being treated with
nivolumab,
18
fluorine-labeled anti-PD-L1 Adnectin (
18
F-BMS-986192) and
89
zirconium-
labeled nivolumab (
89
Zr-nivolumab) were tested in patients with non-small-cell lung cancer
(NSCLC). The
89
Zr-nivolumab tracer has a large molecular size and therefore was found to
be effective when imaged 5–7 days after injection. On the other hand, the
18
F-BMA-986192
tracer was enhanced when imaged on the same day as injected. Both tracers were found to
have significant binding and high-contrast visualization under the PET/CT scans, with no
adverse reactions to the tracers (Figure 8). Two of the patients tested had metastasis to the
brain, which was not all visible under the scans due to low penetration of the tracers or the
low PD-1/PD-L1 expression in the cancer regime [64].
Engineering the antibody with the
89
Zr tracer facilitates metastasis tracing using an
immune-PET/CT scan. The cluster of differentiation 3 (CD3) is an immune checkpoint that
acts as a T cell coreceptor and is necessary for T cell activation. CD3 will bind to antigens
which are presented on antigen-presenting cells. CD3 will then send a signal back to the
nucleus of the T cell for immune activation. Anti-CD3 is an antibody that will bind to
CD3 on the surface of T cells and tracking anti-CD3 allows for the visualization of the
antigen. Deferoxamine (DFO) was used as a bifunctional chelating agent because of its
high chemical and biological stability with
89
Zr.
89
Zr-DFO-anti-CD3 was tested in
in vitro
and
in vivo
conditions and was found to have a high uptake in the TME. The engineered
antibody also demonstrated a rapid clearance time, resulting in clear visualization under
the PET/CT scan. The study also found that the administration of
89
Zr-DFO-anti-CD3 led
to a decrease in the CD4
+
T cell population and an increase in the number of CD8
+
T cells,
although there was no significant change in the total number of T cells. This observation
benefits cancer patients, as a high CD8
+
-to-CD4
+
T cell ratio is associated with better patient
prognosis [65].

Micromachines 2022,13, 2217 12 of 21
Micromachines 2022, 13, x 12 of 22
nivolumab,
18
fluorine-labeled anti-PD-L1 Adnectin (
18
F-BMS-986192) and
89
zirconium-la-
beled nivolumab (
89
Zr-nivolumab) were tested in patients with non-small-cell lung cancer
(NSCLC). The
89
Zr-nivolumab tracer has a large molecular size and therefore was found
to be effective when imaged 5–7 days after injection. On the other hand, the
18
F-BMA-
986192 tracer was enhanced when imaged on the same day as injected. Both tracers were
found to have significant binding and high-contrast visualization under the PET/CT scans,
with no adverse reactions to the tracers (Figure 8). Two of the patients tested had metas-
tasis to the brain, which was not all visible under the scans due to low penetration of the
tracers or the low PD-1/PD-L1 expression in the cancer regime [64].
Figure 8.
PET/CT images of panel (A) and (B) are corresponding from two patients, respectively.
These images are
18
F-FDG PET (left),
18
F-BMS-986192 PET (center) and
89
Zr-Nivolumab (right).
18
F-
FDG PET scan results show malignancies with significant glucose metabolism in both the lungs and
the mediastinal lymph nodes. PET with
18
F-BMS-986192 reveals uneven tracer uptake within and
between tumors.
18
F-FDG PET scans show that the tumor on the left side has a high glucose metab-
olism. PET with
18
F-BMS-986192 indicates little tumor tracer uptake. Nivolumab PET with
89
Zr in-
dicates diverse tracer uptake in the tumor. Adapted from reference [64], licensed under a CC BY 4.0.
Engineering the antibody with the
89
Zr tracer facilitates metastasis tracing using an
immune-PET/CT scan. The cluster of differentiation 3 (CD3) is an immune checkpoint that
acts as a T cell coreceptor and is necessary for T cell activation. CD3 will bind to antigens
which are presented on antigen-presenting cells. CD3 will then send a signal back to the
nucleus of the T cell for immune activation. Anti-CD3 is an antibody that will bind to CD3
on the surface of T cells and tracking anti-CD3 allows for the visualization of the antigen.
Deferoxamine (DFO) was used as a bifunctional chelating agent because of its high chem-
ical and biological stability with
89
Zr.
89
Zr-DFO-anti-CD3 was tested in in vitro and in vivo
conditions and was found to have a high uptake in the TME. The engineered antibody
also demonstrated a rapid clearance time, resulting in clear visualization under the
PET/CT scan. The study also found that the administration of
89
Zr-DFO-anti-CD3 led to a
decrease in the CD4
+
T cell population and an increase in the number of CD8
+
T cells,
Figure 8.
PET/CT images of panel (
A
,
B
) are corresponding from two patients, respectively. These
images are
18
F-FDG PET (left),
18
F-BMS-986192 PET (center) and
89
Zr-Nivolumab (right).
18
F-FDG
PET scan results show malignancies with significant glucose metabolism in both the lungs and
the mediastinal lymph nodes. PET with
18
F-BMS-986192 reveals uneven tracer uptake within and
between tumors.
18
F-FDG PET scans show that the tumor on the left side has a high glucose
metabolism. PET with
18
F-BMS-986192 indicates little tumor tracer uptake. Nivolumab PET with
89
Zr indicates diverse tracer uptake in the tumor. Adapted from reference [
64
], licensed under a CC
BY 4.0.
3.2. Near-Infrared Imaging
Near-infrared fluorescence imaging (NIFR) has high sensitivity and specificity, al-
though the penetration depth of the laser holds it back. On the other hand, magnetic
resonance imaging (MRI) is known for its high resolution as well as strong contrast in
soft tissue images but has also been found to have high false-positive rates. However, it
has been discovered that combining the NIFR and MRI techniques can be a strong tool
for tumor detection. A study focusing on triple-negative breast cancer (TNBC) used this
dual-imaging method to target PD-L1 using a nanoparticle probe. Second-near-infrared
(NIR-II) imaging refers to light within the 1000–1700 nm wavelength range, as opposed to
near-infrared imaging, which begins around 800 nm [
66
]. NIR-II provides higher resolution
and a deeper penetration depth, allowing for more accurate imaging that provides more
functional anatomical information.
Lui and coworkers developed a nanoparticle combining the photosensitizer BODIPY
(BDP) and PD-L1 (BDP-I-N-anti-PD-L1) for molecular imaging, photodynamic treatment
(PDT), and immunological combination therapy. PDT’s known benefits include the microin-
vasive eradication of cancers, low adverse effects, and minimum tissue damage. However,
this study also emphasized the anticancer effects of PDT on fluorescent nanoparticles.
These engineered nanoparticles were tested
in vitro
and
in vivo
using mouse models and
were demonstrated to be a strong tool for the molecular imaging of MC38 tumors. They
also induced the formation of O
2
to kill the cancerous cells while preventing damage to
healthy cells [67].

Micromachines 2022,13, 2217 13 of 21
3.3. Magnetic Resonance Imaging
Magnetic resonance imaging (MRI) is a strong imaging technique for nanoparticles
using SPIONs. Nanoparticles imaged under MRIs have both magnetic and biodegradable
advantageous properties. A bioengineered nanoparticle using SPIONs and siRNA-targeting
PD-L1 for theranostics in gastric agents found improved MRI contrast, among other bene-
fits. The MR images showed increased T2-weighted contrast, making it easier to visualize
and therefore monitor cancer noninvasively [
68
]. Superparamagnetic iron oxide nanopar-
ticles (SPIONs) possess improved magnetization properties, as well as biocompatibility
and stability in aqueous solutions. SPIONS were used as a contrast agent for MRI and
conjugated with Cy5.5 dye for the NIRF. The SPIONs-L1-Cy5.5 probe was tested
in vitro
and
in vivo
conditions. Since PD-L1 is upregulated in TNBC and associated with poor
patient prognosis, its imaging can prevent oncologists from stopping immunotherapy when
it could be helpful. The synthesized dual-mode imaging probe was able to detect PD-L1
cancer and exhibited slight cytotoxicity [69].
3.4. Challenges and Perspectives of Cancer Immunotherapy Imaging
Medical imaging modalities are useful for imaging immune checkpoints. Multimodal
approaches are typically the most successful. For example, PET/CT scans allow for the
visualization of metabolic activity with the added benefit of seeing the structural anatomy
using CT. These imaging techniques visualize the cancer’s solid condition and metastatic
regime to identify affected organs. Combining NIFR imaging with MRIs improves molec-
ular sensitivity and specificity. The MRI offers more in-depth complementary structural
details during
in vivo
conditions. Combining imaging modalities with nanoparticles as
a contrast agent improves cancer immunotherapy detection and patient prognosis. Ul-
trasounds are gaining recognition in the field because of their low cost with no radiation
hazards. Microbubbles as contrast agents can target immune checkpoints and are cap-
tured using ultrasound imaging, which has better economic benefits over other techniques.
Currently, the cancer immunotherapy treatment success rate is ~20% [
70
], while the re-
maining patients were treated with traditional and painful invasive treatments, which
carries negative side effects and discomfort to patients. Therefore, there is an urgent need
to study these immune-modulated drugs before their clinical applications. In this regard,
additional diagnostic tools are required to monitor and measure the level of cancer markers
for drug interaction and treatment outcomes. For example, peptides, protein binders, and
antibodies-based tracers were developed and tested for immune checkpoint imaging to
measure the expression level in the TME. Systemically small protein binders are cleared
much faster than high-molecular-weight antibodies.
4. Lab-on-Chip-Based Theragnosis for Cancer Immunotherapy
Polydimethylsiloxane (PDMS) lab-on-chips (LOCs) are widely utilized in laboratories
for fabricating microchannels and microfluidic devices due to their low cost and ease of
production. Glass is another commonly utilized material due to its transparency, suitability
with micrometer-scale machining, and chemical inertness, which permits diverse electrode
integration. Silicon on the other hand is rarely utilized over glass polymers because
of its high electroconductivity, which is not ideal for high-voltage tests, and its high
expense [
71
]. Paper-based LOCs (P-LOCs) are mostly used for the detection of chemicals
and compounds, along with a few other applications. P-LOCs provide the most ecofriendly
and inexpensive device, which may have strong outcomes for applications requiring ultra-
low costs. Toxin and pathogen detection, as well as glucose, immunological molecule,
and protein concentration, are just some of the uses of P-LOCs [
72
]. When taking the
cost, the applicability in point-of-care diagnostics, and the reproducibility, PDMS is the
desired material for most labs to test nanomaterials for immunotherapy. PDMS improves
visualization of nanoparticles, quantum dots, and nanowires while being tested on the
TME, offers better biocompatibility, allowing enhanced sensitivity and biolabeling, and

Micromachines 2022,13, 2217 14 of 21
allows for proper gas permeability, which all contribute to the ability of LOCs to improve
cell culture and TME analysis.
Imaging, quantification, and recurrent testing are critical in the field of immunotherapy
to establish a treatment’s efficacy. Successfully validating a drug’s effectiveness takes
into account the interactions between the drug and disease and measures the specificity
in a realistic model. During the past few decades, the space of immunotherapy drug
development, testing, and translation have made tremendous strides. However, with each
drug costing an average of USD 1–2 billion and taking 10–15 years to be approved for
clinical applications, most of which are not as widely effective in the patient setting, the
ability for patients to receive a potentially life-saving treatment is not optimistic. There is a
lack of confidence in translating preclinical findings of immune-based therapies for any
given patient.
For testing, traditional animal and
in vitro
methods of cancer modeling cannot reca-
pitulate the human TME. Currently, some factors that contribute to the challenge of drug
development include (i) animal models often cannot recapitulate an entire disorder or
disease; (ii) the heterogeneity of the patient population cannot be considered. Even within
a single patient, the TME differs greatly.
Studying the TME using microfluidics platforms for both solid and hematological
cancers is possible through LOC microfluidic devices [
73
]. LOCs can be characterized
as an organization of electrodes, microchannels, and sensors. It presents the possibility
to study different cell types without the use of fluorescent or magnetic labeling. Instead,
it incorporates microfluidic technology such as pressure, capillary flow, or electrokinetic
effects with detectors for optical analysis. This enables LOCs to recapitulate the complex
and dynamic cancer–immune system interaction, providing a new way to conduct a host-
like preclinical evaluation of immunotherapeutic strategies, such as immune checkpoint
blockade therapy, to allow a more patient-specific understanding of a tumor’s biology [
74
].
The LOC’s small size (cm) and user-friendly interface provide a way of integrating
thousands of biochemical operations using as little as a drop of blood [
75
]. This can be
attributed to the spatial constraint in LOCs, as it translates to considerably reduced convec-
tive mixing in no-flow systems, hence losing less sample volume. Most of the movement
of molecules is instead powered by diffusion. The practicality of the LOC, because of its
small size, includes its ability to analyze data comparable to analyses conducted in a fully
equipped analytical laboratory. As of recently, the LOC places a focused look at human
data that might lead to improved target identification and validation.
The standard mechanism of LOCs includes the sample being passed through a network
of micrometer-sized channels fabricated on a surface compatible with the sample. With
these channels, handling and preparing the sample, along with the analysis of that sample,
can all be done without having to change the chip. In addition, the rate of flow of the
sample of interest passed through the device is closely controlled. The LOC allows a more
cost-effective and user-friendly alternative for single-cell analysis (SCA). For example, with
single-cell analysis, conventional flow cytometry, which requires the use of high volumes
of samples and reagents, is inferior to the LOC microfluidics device.
4.1. Multilayered Blood Vessel/Tumor Tissue Chip
Immunotherapy recipients are carefully chosen based on a number of criteria, includ-
ing microsatellite instability (MSI) status, PD-L1 expression, and the number of somatic
mutations present in the patient’s tumor. Because these biomarkers are associated with
positive immunotherapy results, investigating the TME for indicators such as levels of
PD-L1 expression has become the cornerstone of predicting immunotherapy success for a
particular patient. Selection for these patients leaves only a fraction of eligible candidates.
However, a faster, less invasive, and repeatable method of assessment would increase the
effectiveness and even expand the patient population who get to receive immunotherapy.
Additionally, T cells must extravasate from the blood vessels to reach the site of the tumor
and then interstitially migrate into tumors. Being able to observe the mechanism in real-

Micromachines 2022,13, 2217 15 of 21
time and understand how a therapy interacts with patient-specific cellular environments
would expand and expedite the patient selection process, thereby providing more people
with life-saving treatments.
The multilayered blood vessel/tumor tissue chip (MBTC) demonstrated the full series
of T cell/tumor infiltration, including extravasation and interstitial migration. The MBTC
is derived from a parallel plate flow chamber, which is an
in vitro
model that recapitulates
the fluid shear stress on cells that are naturally exposed to dynamic fluid flow. A porous
membrane covered with an endothelial cell monolayer mimics a host-like environment and
is referred to as the top fluidic chamber. Additionally, a collagen gel block encapsulates
the tumor cell and is referred to as the matrix. Systematic investigation of T cell/tumor
infiltration and T cell dynamics in TMEs are recapitulated in the MBTC. Preclinical evalua-
tion of immunotherapies was demonstrated by testing anti-vascular endothelial growth
factor (anti-VEGF) treatment on an MBTC. VEGF is produced by T cells and suppresses the
endothelial cell activation by cytokines or by inducing endothelial cell anergy, which refuses
T cell extravasation. Anti-VEGF is a treatment used to reverse the effects of VEGF, thereby
promoting T cell infiltration. Using the MBTC, Lee demonstrated that the endothelial cell
energy could be reversed by blocking VEGF secretion. The MBTC was concluded to show
how tumor cells can increase extravasation by induced endothelial cell anergy and can
promote the interstitial migration of T cells into tumors by producing chemokines to recruit
T cells [76].
4.2. Chimeric Antigen Receptor (CAR)-T LOC
Deficient TCR affinity and variable target toxicity are some of the limitations of im-
munotherapy, as low levels of expression of tumor antigens coupled with poor specific
TCRs make it so that target sites are less likely to be bound. Chimeric antigen receptor
cell therapy (CAR)-T is a way of genetically altering a host’s T cells
in vitro
to target many
hematological malignancies. However, it is not as efficacious when targeting solid tumors.
With CAR-T cell therapy having an overwhelming cost average of USD 1,000,000, and the
2D
in vitro
models failing to recapitulate the TME, a miniaturized method of CAR-T cell
therapy assessment using 3D solid tumor models would be a more effective strategy [77].
The multichannel microfluidic immunoassay was developed on a single chip and
used for the evaluation of CAR-T cell cytotoxicity and targeting specificity on 3D cancer
spheroids [
78
]. Using the lab-on-chip, the monitoring of the interaction between CAR-T
cells and spheroid cocultures demonstrated that CAR-T cells migrate to target-expressing
cancer cells to elicit a cytotoxic effect. A combination of CAR-T cells with other drug
therapies determined that CAR-T cell cytotoxicity is enhanced with therapeutic drugs of
anti-PD-L1 and carboplatin. LOC-based experiments propose a material-saving and better
preclinical screening tool for assessing immunotherapy.
4.3. D/3D Cell Culture Model for Better Cancer Immunotherapy
The standard 2D culture has been the gold standard in cancer biology for many years;
however, it is not representative of the real TME because cells are grown in a petri dish.
Two-dimensional systems are unable to integrate the structural and mechanical properties
that make up the TME, which provides an inaccurate understanding of a drug’s function.
However, 3D microfluidic culture systems are being incorporated into the laboratory. In
particular,
in vitro
microfluidic 3D models are more precise and realistic representations
of the host environment, creating a more human-like environment for the cells to grow in
(Figure 9).
A novel method of profiling the response to the PD-1 blockade therapy was studied
using organotypic tumor spheroids cultured in collagen hydrogels placed in a commercially
available 3D microfluidic device, the DAX-1 3D cell culture chip [
79
]. In addition to PD-1
inhibition, there is a need to assess the sensitivity of murine/patient-derived organotypic
tumor spheroids (MDOTS/PDOTS) to combination treatments. MDOTS/PDOTS was
added into a neutral pH collagen solution with a volume that was adjusted to retain

Micromachines 2022,13, 2217 16 of 21
10–20 thousand cells
per microfluidic chamber. Using the murine tumor model, the authors
show the sensitivity to ICB ex vivo with light/phase contrast microscopy, time-lapse (live)
imaging, immunofluorescence microscopy, live/dead imaging, and secreted cytokine
profiling. A disadvantage shared by 3D culture systems is the need to separate single cells
from spheroid structures by the proteolytic degradation of single layers, prolonging the
time needed to run the analysis. Addressing this problem in future LOCs would increase
its scope in point-of-care testing (Figure 10).
Micromachines 2022, 13, x 16 of 22
therapy (CAR)-T is a way of genetically altering a host’s T cells in vitro to target many
hematological malignancies. However, it is not as efficacious when targeting solid tumors.
With CAR-T cell therapy having an overwhelming cost average of USD 1,000,000, and the
2D in vitro models failing to recapitulate the TME, a miniaturized method of CAR-T cell
therapy assessment using 3D solid tumor models would be a more effective strategy [77].
The multichannel microfluidic immunoassay was developed on a single chip and
used for the evaluation of CAR-T cell cytotoxicity and targeting specificity on 3D cancer
spheroids [78]. Using the lab-on-chip, the monitoring of the interaction between CAR-T
cells and spheroid cocultures demonstrated that CAR-T cells migrate to target-expressing
cancer cells to elicit a cytotoxic effect. A combination of CAR-T cells with other drug ther-
apies determined that CAR-T cell cytotoxicity is enhanced with therapeutic drugs of anti-
PD-L1 and carboplatin. LOC-based experiments propose a material-saving and better pre-
clinical screening tool for assessing immunotherapy.
4.3. D/3D Cell Culture Model for Better Cancer Immunotherapy
The standard 2D culture has been the gold standard in cancer biology for many years;
however, it is not representative of the real TME because cells are grown in a petri dish.
Two-dimensional systems are unable to integrate the structural and mechanical proper-
ties that make up the TME, which provides an inaccurate understanding of a drug’s func-
tion. However, 3D microfluidic culture systems are being incorporated into the labora-
tory. In particular, in vitro microfluidic 3D models are more precise and realistic repre-
sentations of the host environment, creating a more human-like environment for the cells
to grow in (Figure 9).
Figure 9. The 3D cell culture model for immunotherapy compared to standard 2D cell tissue culture.
(A) The typical 2D culture grown as a monolayer in a flat petri dish, attached to a plastic surface.
(B) In vivo mouse model to test and validate immunotherapeutic response in real TME. (C) Full
recapitulation of the TME using human tissue layers to line 3D lab on chip microfluidic device with
proper vasculogenesis. PD-1/PD-L1 interaction with tumor-infiltrating lymphocyte. (D) Standard
imaging for analysis of TME interactions with immunotherapeutics for in vivo models, 2D cultures
and 3D microfluidics. Modified from Ref. [78].
A novel method of profiling the response to the PD-1 blockade therapy was studied
using organotypic tumor spheroids cultured in collagen hydrogels placed in a commer-
cially available 3D microfluidic device, the DAX-1 3D cell culture chip [79]. In addition to
Figure 9.
The 3D cell culture model for immunotherapy compared to standard 2D cell tissue culture.
(
A
) The typical 2D culture grown as a monolayer in a flat petri dish, attached to a plastic surface.
(
B
)
In vivo
mouse model to test and validate immunotherapeutic response in real TME. (
C
) Full
recapitulation of the TME using human tissue layers to line 3D lab on chip microfluidic device with
proper vasculogenesis. PD-1/PD-L1 interaction with tumor-infiltrating lymphocyte. (
D
) Standard
imaging for analysis of TME interactions with immunotherapeutics for
in vivo
models, 2D cultures
and 3D microfluidics. Modified from Ref. [78].
Micromachines 2022, 13, x 17 of 22
PD-1 inhibition, there is a need to assess the sensitivity of murine/patient-derived organ-
otypic tumor spheroids (MDOTS/PDOTS) to combination treatments. MDOTS/PDOTS
was added into a neutral pH collagen solution with a volume that was adjusted to retain
10–20 thousand cells per microfluidic chamber. Using the murine tumor model, the au-
thors show the sensitivity to ICB ex vivo with light/phase contrast microscopy, time-lapse
(live) imaging, immunofluorescence microscopy, live/dead imaging, and secreted cyto-
kine profiling. A disadvantage shared by 3D culture systems is the need to separate single
cells from spheroid structures by the proteolytic degradation of single layers, prolonging
the time needed to run the analysis. Addressing this problem in future LOCs would in-
crease its scope in point-of-care testing (Figure 10).
Figure 10. Programmed death-1 (PD-1) and programmed death-1 ligand (PD-L1)-blocker antibodies
binding to their respective sites on tumor-infiltrating lymphocytes and tumor cells are shown in a
lab-on-chip microfluidic device.
4.4. Challenges and Perspectives of LOC
Currently, the space of the LOC has revolutionized the realm of point-of-care testing
and carrying this expansion in LOC technology is promising. However, there are chal-
lenges with the mass production of chips of the same quality. Cost for production is a
limiting factor (still overall less expensive) because most LOCs are of one time-usage. To
combat these challenges, recycled materials such as CDs to make at-home LOCs with the
same accuracy as commercially bought LOCs are being developed. With many more de-
velopments to come, the multianalyte detection capabilities of LOCs are evidence of a
gateway to more accessible, precise, and cost-effective methods for immunotherapy test-
ing.
The current methods of imaging, analyzing, and encapsulating the TME with anti-
body-based immunotherapy ramp-up costs and diminish reproducibility. Animal-based
models are utilized for observing the effects of PD-1/PD-L1, CTLA-4, or VEGF antibody
treatments on solid tumors and hematological cancers, which, when paired with radio-
labeling for PET/CT or MRI, take longer and can cloud experiments with many confound-
ing variables. The LOC greatly expedites the time-to-image and analysis results for anti-
body treatment and other nanoparticle-type treatments. One challenge with LOCs is the
ability to analyze the large compilation of bioimages taken from the recapitulated TME.
Recently, a strategy for analyzing the infection and killing of cancer cells using the onco-
lytic vaccinia virus (OVV) was proposed. Using advanced algorithms along with appro-
priate analysis, the synergistic cooperation of the OVV and immune cells to kill cancer
cells was uncovered.
Figure 10.
Programmed death-1 (PD-1) and programmed death-1 ligand (PD-L1)-blocker antibodies
binding to their respective sites on tumor-infiltrating lymphocytes and tumor cells are shown in a
lab-on-chip microfluidic device.
4.4. Challenges and Perspectives of LOC
Currently, the space of the LOC has revolutionized the realm of point-of-care testing
and carrying this expansion in LOC technology is promising. However, there are challenges
with the mass production of chips of the same quality. Cost for production is a limiting factor

Micromachines 2022,13, 2217 17 of 21
(still overall less expensive) because most LOCs are of one time-usage. To combat these
challenges, recycled materials such as CDs to make at-home LOCs with the same accuracy
as commercially bought LOCs are being developed. With many more developments to
come, the multianalyte detection capabilities of LOCs are evidence of a gateway to more
accessible, precise, and cost-effective methods for immunotherapy testing.
The current methods of imaging, analyzing, and encapsulating the TME with antibody-
based immunotherapy ramp-up costs and diminish reproducibility. Animal-based models
are utilized for observing the effects of PD-1/PD-L1, CTLA-4, or VEGF antibody treatments
on solid tumors and hematological cancers, which, when paired with radiolabeling for
PET/CT or MRI, take longer and can cloud experiments with many confounding variables.
The LOC greatly expedites the time-to-image and analysis results for antibody treatment
and other nanoparticle-type treatments. One challenge with LOCs is the ability to analyze
the large compilation of bioimages taken from the recapitulated TME. Recently, a strategy
for analyzing the infection and killing of cancer cells using the oncolytic vaccinia virus
(OVV) was proposed. Using advanced algorithms along with appropriate analysis, the
synergistic cooperation of the OVV and immune cells to kill cancer cells was uncovered.
5. AI and ML in Immune-Targeted Drug Delivery
Artificial intelligence is a software tool to obtain sensitive information better than can
be achieved by human intelligence. In the medical community, AI can be effectively used
for generating disease and treatment models with the existing data, which can produce
high-throughput information to predict cancer cures. For instance, AI tools in medicine
provide suggestions on critical decision-making and interpreting the given data, thereby
generating visual representations to enhance clinicians’ knowledge [
80
]. The advancement
of cancer treatment and the prediction of personalized medicine was the primary focus of
AI researchers [
81
]. Radionics is an AI tool developed for the oncology-related analysis of
medical images to recognize tumor regions precisely. This technology helps physicians to
know how to perform a biopsy to obtain overall tumor regions before surgery. Currently,
AI is used in medical imaging modalities to delineate and segment tumors from normal
regions via imaging agents. Moreover, machine learning and deep learning algorithms
and methodologies are applied in medical images for automated labeling and annotation
to assist the routine workflow of physicians. In the future, medical imaging technolo-
gies enabled with AI/ML tools will be a revolutionizing strategy to monitor ICI-based
therapy and treatment response. Though methodologies and techniques used for cancer
immunotherapy are efficient, the variations in the treatment efficacy are still undetermined.
Post-cancer immunotherapy treatment affects the patient’s incidence of immune-related
problems such as autoimmune disorders that lead to organ dysfunction. In the future,
AI can be helpful for the clinician to predict personalized treatment options for effective
immunotherapy to cure cancer without any side effects.
6. Conclusions and Future Directions
The most important advantage of immunotherapy is the that immune system can
remember the disease, allowing it to detect and destroy tumor variants as they emerge.
This attribute will always be an inherent advantage over other cancer therapies. Currently,
the focus of cancer immunotherapy treatment has moved to treat the specific tumor char-
acteristics and their interaction with the intrinsic immune system instead of treating the
diseased organ. The good news is that several immunotherapy drugs are now rapidly
being approved to treat multiple cancers. This may be used either as first-line treatment or
when standard first-line treatment has failed. For instance, the usage of the FDA-approved
anti-PD-1, and pembrolizumab drugs for the treatment of unresectable tumor conditions
like high MSI or mismatch-repair–deficient has increased patients’ therapeutic options.
Patients with solid tumor recurrence who have exhausted all other therapy options are
satisfied with this treatment choice. In addition, this is the first time the FDA has approved
a cancer treatment based on a common biomarker rather than the location of the tumor.

Micromachines 2022,13, 2217 18 of 21
However, active research is needed to understand why some cancers and patients
respond so well to immunotherapy while others do not. This may be due to tumors
becoming resistant after the initial response. A cancer immunotherapy approach must
find ways to manipulate the immune system in patients who do not exhibit an immune
response to their tumors. TILs need to infiltrate into the TME for immunotherapy to be
effective [
82
]. Furthermore, by understanding the immunology of the host and tumor, we
will hopefully be able to identify more specific diagnostic biomarkers.
In the future, personalized medicine, with novel combinations of therapy and new
treatment sequences, could provide better cures for cancer. In addition, a better understanding
of resistance and recurrence will help effectively control the disease and promote the long-term
survival of the patient. For example, a combination of ICB and CAR-T cell therapy is surging
for noninvasive effective cancer treatment [
83
]. Overall, these novel approaches, including
immuno nano platforms, may provide better treatment options and opportunities to prolong
survival and improve the quality of the patient’s well-being from cancer.
Author Contributions:
Conceptualization, A.N.; writing—original draft preparation, C.J., K.J.,
H.B.M., A.K.N. and A.N.; writing—review and editing, C.J., K.J., H.B.M., A.K.N. and A.N.; su-
pervision, A.N.; project administration, A.N. All authors have read and agreed to the published
version of the manuscript.
Funding: This research received no external funding.
Data Availability Statement: Data available on request due to restrictions, e.g., privacy or ethical.
Acknowledgments:
The author acknowledges the Molecular Imaging Program at Stanford and the
Canary Center at Stanford for providing support. The author would also like to acknowledge that
all of the aforementioned figures were created using Servier Medical Art (supplied by Servier and
licensed by Creative Commons Attribution 3.0).
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Burkholder, B.; Huang, R.Y.; Burgess, R.; Luo, S.; Jones, V.S.; Zhang, W.; Lv, Z.Q.; Gao, C.Y.; Wang, B.L.; Zhang, Y.M.; et al.
Tumor-induced perturbations of cytokines and immune cell networks. Biochim. Biophys. Acta
2014
,1845, 182–201. [CrossRef]
[PubMed]
2.
Gonzalez, H.; Hagerling, C.; Werb, Z. Roles of the immune system in cancer: From tumor initiation to metastatic progression.
Genes Dev. 2018,32, 1267–1284. [CrossRef] [PubMed]
3.
Kartikasari, A.E.R.; Huertas, C.S.; Mitchell, A.; Plebanski, M. Tumor-Induced Inflammatory Cytokines and the Emerging
Diagnostic Devices for Cancer Detection and Prognosis. Front. Oncol. 2021,11, 692142. [CrossRef] [PubMed]
4.
Vesely, M.D.; Schreiber, R.D. Cancer immunoediting: Antigens, mechanisms, and implications to cancer immunotherapy. Ann. N.
Y. Acad. Sci. 2013,1284, 1–5. [CrossRef] [PubMed]
5.
Pucci, C.; Martinelli, C.; Ciofani, G. Innovative approaches for cancer treatment: Current perspectives and new challenges.
Ecancermedicalscience 2019,13, 961. [CrossRef] [PubMed]
6. Zahavi, D.; Weiner, L. Monoclonal Antibodies in Cancer Therapy. Antibodies 2020,9, 34. [CrossRef]
7.
Nixon, N.A.; Blais, N.; Ernst, S.; Kollmannsberger, C.; Bebb, G.; Butler, M.; Smylie, M.; Verma, S. Current landscape of
immunotherapy in the treatment of solid tumors, with future opportunities and challenges. Curr. Oncol.
2018
,25, e373–e384.
[CrossRef]
8.
Kirilovsky, A.; Marliot, F.; El Sissy, C.; Haicheur, N.; Galon, J.; Pages, F. Rational bases for the use of the Immunoscore in routine
clinical settings as a prognostic and predictive biomarker in cancer patients. Int. Immunol. 2016,28, 373–382. [CrossRef]
9.
Li, K.; Luo, H.; Huang, L.; Luo, H.; Zhu, X. Microsatellite instability: A review of what the oncologist should know. Cancer Cell
Int. 2020,20, 16. [CrossRef]
10.
Fan, S.; Ren, H.; Zhao, L.; Yin, J.; Feng, G.; Wang, J.; Guan, H. Neurological immune-related adverse events associated with
immune checkpoint inhibitors: A review of the literature. Asia Pac. J. Clin. Oncol. 2020,16, 291–298. [CrossRef]
11.
Nishino, M.; Ramaiya, N.H.; Hatabu, H.; Hodi, F.S. Monitoring immune-checkpoint blockade: Response evaluation and biomarker
development. Nat. Rev. Clin. Oncol. 2017,14, 655–668. [CrossRef] [PubMed]
12.
Patrinely, J.R., Jr.; Johnson, R.; Lawless, A.R.; Bhave, P.; Sawyers, A.; Dimitrova, M.; Yeoh, H.L.; Palmeri, M.; Ye, F.; Fan, R.; et al.
Chronic Immune-Related Adverse Events Following Adjuvant Anti-PD-1 Therapy for High-risk Resected Melanoma. JAMA
Oncol. 2021,7, 744–748. [CrossRef] [PubMed]
13.
Galluzzi, L.; Chan, T.A.; Kroemer, G.; Wolchok, J.D.; Lopez-Soto, A. The hallmarks of successful anticancer immunotherapy. Sci.
Transl. Med. 2018,10, eaat7807. [CrossRef] [PubMed]

Micromachines 2022,13, 2217 19 of 21
14.
Bai, R.; Chen, N.; Li, L.; Du, N.; Bai, L.; Lv, Z.; Tian, H.; Cui, J. Mechanisms of Cancer Resistance to Immunotherapy. Front. Oncol.
2020,10, 1290. [CrossRef]
15.
Rameshbabu, S.; Labadie, B.W.; Argulian, A.; Patnaik, A. Targeting Innate Immunity in Cancer Therapy. Vaccines
2021
,9, 138.
[CrossRef] [PubMed]
16.
Gavas, S.; Quazi, S.; Karpinski, T.M. Nanoparticles for Cancer Therapy: Current Progress and Challenges. Nanoscale Res. Lett.
2021,16, 173. [CrossRef]
17.
Anselmi, M.; Borbely, A.; Figueras, E.; Michalek, C.; Kemker, I.; Gentilucci, L.; Sewald, N. Linker Hydrophilicity Modulates the
Anticancer Activity of RGD-Cryptophycin Conjugates. Chemistry 2021,27, 1015–1022. [CrossRef]
18.
Li, Q.; Li, X.; Zhao, C. Strategies to Obtain Encapsulation and Controlled Release of Small Hydrophilic Molecules. Front. Bioeng.
Biotechnol. 2020,8, 437. [CrossRef]
19.
Subhan, M.A.; Yalamarty, S.S.K.; Filipczak, N.; Parveen, F.; Torchilin, V.P. Recent Advances in Tumor Targeting via EPR Effect for
Cancer Treatment. J. Pers. Med. 2021,11, 571. [CrossRef]
20. Tan, S.; Li, D.; Zhu, X. Cancer immunotherapy: Pros, cons and beyond. Biomed. Pharmacother. 2020,124, 109821. [CrossRef]
21.
Teixidor, E.; Bosch-Barrera, J. the dark side of immunotherapy: Challenges facing the new hope in cancer treatment. Ann. Transl.
Med. 2019,7, S183. [CrossRef] [PubMed]
22.
Chevolet, I.; Speeckaert, R.; Schreuer, M.; Neyns, B.; Krysko, O.; Bachert, C.; Hennart, B.; Allorge, D.; van Geel, N.; van Gele,
M.; et al. Characterization of the
in vivo
immune network of IDO, tryptophan metabolism, PD-L1, and CTLA-4 in circulating
immune cells in melanoma. Oncoimmunology 2015,4, e982382. [CrossRef] [PubMed]
23.
Peer, D.; Karp, J.M.; Hong, S.; Farokhzad, O.C.; Margalit, R.; Langer, R. Nanocarriers as an emerging platform for cancer therapy.
Nat. Nanotechnol. 2007,2, 751–760. [CrossRef] [PubMed]
24. He, X.; Xu, C. Immune checkpoint signaling and cancer immunotherapy. Cell Res. 2020,30, 660–669. [CrossRef] [PubMed]
25.
Mokhtari, R.B.; Sambi, M.; Qorri, B.; Baluch, N.; Ashayeri, N.; Kumar, S.; Cheng, H.M.; Yeger, H.; Das, B.; Szewczuk, M.R. The
Next-Generation of Combination Cancer Immunotherapy: Epigenetic Immunomodulators Transmogrify Immune Training to
Enhance Immunotherapy. Cancers 2021,13, 3596. [CrossRef]
26.
Qin, S.; Xu, L.; Yi, M.; Yu, S.; Wu, K.; Luo, S. Novel immune checkpoint targets: Moving beyond PD-1 and CTLA-4. Mol. Cancer
2019,18, 155. [CrossRef]
27.
Greenbaum, U.; Mahadeo, K.M.; Kebriaei, P.; Shpall, E.J.; Saini, N.Y. Chimeric Antigen Receptor T-Cells in B-Acute Lymphoblastic
Leukemia: State of the Art and Future Directions. Front. Oncol. 2020,10, 1594. [CrossRef]
28.
Yetisgin, A.A.; Cetinel, S.; Zuvin, M.; Kosar, A.; Kutlu, O. Therapeutic Nanoparticles and Their Targeted Delivery Applications.
Molecules 2020,25, 2193. [CrossRef]
29.
Yu, X.; Fang, C.; Zhang, K.; Su, C. Recent Advances in Nanoparticles-Based Platforms Targeting the PD-1/PD-L1 Pathway for
Cancer Treatment. Pharmaceutics 2022,14, 1581. [CrossRef]
30.
Reda, M.; Ngamcherdtrakul, W.; Nelson, M.A.; Siriwon, N.; Wang, R.; Zaidan, H.Y.; Bejan, D.S.; Reda, S.; Hoang, N.H.; Crumrine,
N.A.; et al. Development of nanoparticle-based immunotherapy targeting PD-L1 and PLK1 for lung cancer treatment. Nat.
Commun. 2022,13, 4261. [CrossRef]
31. Xiao, Y.; Chen, J.; Zhou, H.; Zeng, X.; Ruan, Z.; Pu, Z.; Jiang, X.; Matsui, A.; Zhu, L.; Amoozgar, Z.; et al. Combining p53 mRNA
nanotherapy with immune checkpoint blockade reprograms the immune microenvironment for effective cancer therapy. Nat.
Commun. 2022,13, 758. [CrossRef] [PubMed]
32.
Mills, C.N.; Nowsheen, S.; Bonner, J.A.; Yang, E.S. Emerging roles of glycogen synthase kinase 3 in the treatment of brain tumors.
Front. Mol. Neurosci. 2011,4, 47. [CrossRef] [PubMed]
33.
Kulikov, R.; Boehme, K.A.; Blattner, C. Glycogen synthase kinase 3-dependent phosphorylation of Mdm2 regulates p53 abundance.
Mol. Cell Biol. 2005,25, 7170–7180. [CrossRef] [PubMed]
34.
Badiee, P.; Maritz, M.F.; Thierry, B. Glycogen kinase 3 inhibitor nanoformulation as an alternative strategy to inhibit PD-1 immune
checkpoint. Int. J. Pharm. 2022,622, 121845. [CrossRef]
35.
Waldman, A.D.; Fritz, J.M.; Lenardo, M.J. A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nat.
Rev. Immunol. 2020,20, 651–668. [CrossRef]
36.
Yang, L.; Shi, P.; Zhao, G.; Xu, J.; Peng, W.; Zhang, J.; Zhang, G.; Wang, X.; Dong, Z.; Chen, F.; et al. Targeting cancer stem cell
pathways for cancer therapy. Signal Transduct. Target Ther. 2020,5, 8. [CrossRef]
37.
Dasari, S.; Tchounwou, P.B. Cisplatin in cancer therapy: Molecular mechanisms of action. Eur. J. Pharmacol.
2014
,740, 364–378.
[CrossRef]
38.
Yao, H.; Shen, N.; Ji, G.; Huang, J.; Sun, J.; Wang, G.; Tang, Z.; Chen, X. Cisplatin Nanoparticles Promote Intratumoral CD8(+) T
Cell Priming via Antigen Presentation and T Cell Receptor Crosstalk. Nano Lett. 2022,22, 3328–3339. [CrossRef]
39.
Bansal-Pakala, P.; Halteman, B.S.; Cheng, M.H.; Croft, M. Costimulation of CD8 T cell responses by OX40. J. Immunol.
2004
,
172, 4821–4825. [CrossRef]
40.
Liu, Z.; Han, C.; Fu, Y.X. Targeting innate sensing in the tumor microenvironment to improve immunotherapy. Cell Mol. Immunol.
2020,17, 13–26. [CrossRef]
41.
Dane, E.L.; Belessiotis-Richards, A.; Backlund, C.; Wang, J.; Hidaka, K.; Milling, L.E.; Bhagchandani, S.; Melo, M.B.; Wu, S.; Li,
N.; et al. STING agonist delivery by tumor-penetrating PEG-lipid nanodiscs primes robust anticancer immunity. Nat. Mater.
2022
,
21, 710–720. [CrossRef] [PubMed]

Micromachines 2022,13, 2217 20 of 21
42.
Nakamura, T.; Yamada, K.; Sato, Y.; Harashima, H. Lipid nanoparticles fuse with cell membranes of immune cells at low
temperatures leading to the loss of transfection activity. Int. J. Pharm. 2020,587, 119652. [CrossRef] [PubMed]
43.
Khalifa, A.M.; Nakamura, T.; Sato, Y.; Sato, T.; Hyodo, M.; Hayakawa, Y.; Harashima, H. Interval- and cycle-dependent combined
effect of STING agonist loaded lipid nanoparticles and a PD-1 antibody. Int. J. Pharm. 2022,624, 122034. [CrossRef] [PubMed]
44.
Messenheimer, D.J.; Jensen, S.M.; Afentoulis, M.E.; Wegmann, K.W.; Feng, Z.; Friedman, D.J.; Gough, M.J.; Urba, W.J.; Fox,
B.A. Timing of PD-1 Blockade Is Critical to Effective Combination Immunotherapy with Anti-OX40. Clin. Cancer Res.
2017
,
23, 6165–6177. [CrossRef]
45.
Guo, W.; Wu, Z.; Chen, J.; Guo, S.; You, W.; Wang, S.; Ma, J.; Wang, H.; Wang, X.; Wang, H.; et al. Nanoparticle delivery of
miR-21-3p sensitizes melanoma to anti-PD-1 immunotherapy by promoting ferroptosis. J. Immunother. Cancer 2022,10, e004381.
[CrossRef]
46.
Liu, J.; Fu, M.; Wang, M.; Wan, D.; Wei, Y.; Wei, X. Cancer vaccines as promising immuno-therapeutics: Platforms and current
progress. J. Hematol. Oncol. 2022,15, 28. [CrossRef]
47.
Pallerla, S.; Abdul, A.; Comeau, J.; Jois, S. Cancer Vaccines, Treatment of the Future: With Emphasis on HER2-Positive Breast
Cancer. Int. J. Mol. Sci. 2021,22, 779. [CrossRef]
48.
Chen, B.Q.; Zhao, Y.; Zhang, Y.; Pan, Y.J.; Xia, H.Y.; Kankala, R.K.; Wang, S.B.; Liu, G.; Chen, A.Z. Immune-regulating camouflaged
nanoplatforms: A promising strategy to improve cancer nano-immunotherapy. Bioact. Mater. 2023,21, 1–19. [CrossRef]
49.
Hassannia, H.; Chaleshtari, M.G.; Atyabi, F.; Nosouhian, M.; Masjedi, A.; Hojjat-Farsangi, M.; Namdar, A.; Azizi, G.; Mohammadi,
H.; Ghalamfarsa, G.; et al. Blockage of immune checkpoint molecules increases T-cell priming potential of dendritic cell vaccine.
Immunology 2020,159, 75–87. [CrossRef]
50.
Barshidi, A.; Karpisheh, V.; Noukabadi, F.K.; Kiani, F.K.; Mohammadi, M.; Afsharimanesh, N.; Ebrahimi, F.; Kiaie, S.H.;
Navashenaq, J.G.; Hojjat-Farsangi, M.; et al. Dual Blockade of PD-1 and LAG3 Immune Checkpoints Increases Dendritic Cell
Vaccine Mediated T Cell Responses in Breast Cancer Model. Pharm. Res. 2022,39, 1851–1866. [CrossRef]
51.
Jorgovanovic, D.; Song, M.; Wang, L.; Zhang, Y. Roles of IFN-gamma in tumor progression and regression: A review. Biomark Res.
2020,8, 49. [CrossRef] [PubMed]
52.
Shofolawe-Bakare, O.T.; Stokes, L.D.; Hossain, M.; Smith, A.E.; Werfel, T.A. Immunostimulatory biomaterials to boost tumor
immunogenicity. Biomater. Sci. 2020,8, 5516–5537. [CrossRef] [PubMed]
53.
Yao, X.; Ma, S.; Peng, S.; Zhou, G.; Xie, R.; Jiang, Q.; Guo, S.; He, Q.; Yang, W. Zwitterionic Polymer Coating of Sulfur Dioxide-
Releasing Nanosystem Augments Tumor Accumulation and Treatment Efficacy. Adv. Healthc. Mater.
2020
,9, e1901582. [CrossRef]
[PubMed]
54.
Weiss, A.M.; Hossainy, S.; Rowan, S.J.; Hubbell, J.A.; Esser-Kahn, A.P. Immunostimulatory Polymers as Adjuvants, Immunothera-
pies, and Delivery Systems. Macromolecules 2022,55, 6913–6937. [CrossRef]
55. Formenti, S.C.; Demaria, S. Systemic effects of local radiotherapy. Lancet Oncol. 2009,10, 718–726. [CrossRef]
56.
Wang, Y.; Deng, W.; Li, N.; Neri, S.; Sharma, A.; Jiang, W.; Lin, S.H. Combining Immunotherapy and Radiotherapy for Cancer
Treatment: Current Challenges and Future Directions. Front. Pharmacol. 2018,9, 185. [CrossRef]
57.
Hagan, C.T.t.; Mi, Y.; Knape, N.M.; Wang, A.Z. Enhancing Combined Immunotherapy and Radiotherapy through Nanomedicine.
Bioconjug. Chem. 2020,31, 2668–2678. [CrossRef]
58.
Lerner, E.C.; Edwards, R.M.; Wilkinson, D.S.; Fecci, P.E. Laser ablation: Heating up the anti-tumor response in the intracranial
compartment. Adv. Drug Deliv. Rev. 2022,185, 114311. [CrossRef]
59.
Deng, B.; Ma, B.; Ma, Y.; Cao, P.; Leng, X.; Huang, P.; Zhao, Y.; Ji, T.; Lu, X.; Liu, L. Doxorubicin and CpG loaded liposomal
spherical nucleic acid for enhanced Cancer treatment. J. Nanobiotechnol. 2022,20, 140. [CrossRef]
60.
Zhou, B.; Wu, Q.; Wang, M.; Hoover, A.; Wang, X.; Zhou, F.; Towner, R.A.; Smith, N.; Saunders, D.; Song, J.; et al. Immunologically
modified MnFe2O4 nanoparticles to synergize photothermal therapy and immunotherapy for cancer treatment. Chem. Eng. J.
2020,396, 125239. [CrossRef]
61.
Wang, Y.; Wang, H.; Song, Y.; Lv, M.; Mao, Y.; Song, H.; Wang, Y.; Nie, G.; Liu, X.; Cui, J.; et al. IR792-MCN@ZIF-8-PD-L1
siRNA drug delivery system enhances photothermal immunotherapy for triple-negative breast cancer under near-infrared laser
irradiation. J. Nanobiotechnol. 2022,20, 96. [CrossRef] [PubMed]
62.
Pan, X.; Gao, A.; Lin, Z. Fluorescence imaging of tumor immune contexture in immune checkpoint blockade therapy. Int.
Immunopharmacol. 2022,106, 108617. [CrossRef] [PubMed]
63.
Natarajan, A.; Patel, C.B.; Ramakrishnan, S.; Panesar, P.S.; Long, S.R.; Gambhir, S.S. A Novel Engineered Small Protein for
Positron Emission Tomography Imaging of Human Programmed Death Ligand-1: Validation in Mouse Models and Human
Cancer Tissues. Clin. Cancer Res. 2019,25, 1774–1785. [CrossRef] [PubMed]
64.
Niemeijer, A.N.; Leung, D.; Huisman, M.C.; Bahce, I.; Hoekstra, O.S.; van Dongen, G.; Boellaard, R.; Du, S.; Hayes, W.; Smith,
R.; et al. Whole body PD-1 and PD-L1 positron emission tomography in patients with non-small-cell lung cancer. Nat. Commun.
2018,9, 4664. [CrossRef] [PubMed]
65.
Vera, D.R.B.; Smith, C.C.; Bixby, L.M.; Glatt, D.M.; Dunn, S.S.; Saito, R.; Kim, W.Y.; Serody, J.S.; Vincent, B.G.; Parrott, M.C.
Immuno-PET imaging of tumor-infiltrating lymphocytes using the zirconium-89 radiolabeled anti-CD3 antibody in immune-
competent mice bearing syngeneic tumors. PLoS ONE 2018,13, e0193832.
66.
Xie, N.; Hou, Y.; Wang, S.; Ai, X.; Bai, J.; Lai, X.; Zhang, Y.; Meng, X.; Wang, X. Second near-infrared (NIR-II) imaging: A novel
diagnostic technique for brain diseases. Rev. Neurosci. 2022,33, 467–490. [CrossRef]

Micromachines 2022,13, 2217 21 of 21
67.
Liu, Q.; Tian, J.; Tian, Y.; Sun, Q.; Sun, D.; Wang, F.; Xu, H.; Ying, G.; Wang, J.; Yetisen, A.K.; et al. Near-Infrared-II Nanoparticles
for Cancer Imaging of Immune Checkpoint Programmed Death-Ligand 1 and Photodynamic/Immune Therapy. ACS Nano
2021
,
15, 515–525. [CrossRef]
68.
Luo, X.; Peng, X.; Hou, J.; Wu, S.; Shen, J.; Wang, L. Folic acid-functionalized polyethyleneimine superparamagnetic iron oxide
nanoparticles as theranostic agents for magnetic resonance imaging and PD-L1 siRNA delivery for gastric cancer. Int. J. Nanomed.
2017,12, 5331–5343. [CrossRef]
69.
Li, X.; Ji, Y.; Chen, M.; Zhang, S.; Wang, Z.; Su, D.; Luo, N. A Dual-Mode Imaging Nanoparticle Probe Targeting PD-L1 for
Triple-Negative Breast Cancer. Contrast Media Mol. Imaging 2022,2022, 2431026. [CrossRef]
70. Mellman, I.; Coukos, G.; Dranoff, G. Cancer immunotherapy comes of age. Nature 2011,480, 480–489. [CrossRef]
71.
Nguyen, N.T.; Shaegh, S.A.; Kashaninejad, N.; Phan, D.T. Design, fabrication, and characterization of drug delivery systems
based on lab-on-a-chip technology. Adv. Drug Deliv. Rev. 2013,65, 1403–1419. [CrossRef] [PubMed]
72.
Qamar, A.Z.; Shamsi, M.H. Desktop Fabrication of Lab-On-Chip Devices on Flexible Substrates: A Brief Review. Micromachines
2020,11, 126. [CrossRef] [PubMed]
73.
Parlato, S.; Grisanti, G.; Sinibaldi, G.; Peruzzi, G.; Casciola, C.M.; Gabriele, L. Tumor-on-a-chip platforms to study cancer-immune
system crosstalk in the era of immunotherapy. Lab Chip 2021,21, 234–253. [CrossRef] [PubMed]
74.
Zheng, F.; Xiao, Y.; Liu, H.; Fan, Y.; Dao, M. Patient-Specific Organoid and Organ-on-a-Chip: 3D Cell-Culture Meets 3D Printing
and Numerical Simulation. Adv. Biol. 2021,5, e2000024. [CrossRef]
75.
Arshavsky-Graham, S.; Segal, E. Lab-on-a-Chip Devices for Point-of-Care Medical Diagnostics. Adv. Biochem. Eng. Biotechnol.
2022,179, 247–265.
76.
Lee, J.; Kim, S.E.; Moon, D.; Doh, J. A multilayered blood vessel/tumor tissue chip to investigate T cell infiltration into solid
tumor tissues. Lab Chip 2021,21, 2142–2152. [CrossRef]
77.
Paterson, K.; Paterson, S.; Mulholland, T.; Coffelt, S.B.; Zagnoni, M. Assessment of CAR-T Cell-Mediated Cytotoxicity in 3D
Microfluidic Cancer Co-Culture Models for Combination Therapy. IEEE Open J. Eng. Med. Biol. 2022,3, 86–95. [CrossRef]
78.
Adriani, G.; Pavesi, A.; Tan, A.T.; Bertoletti, A.; Thiery, J.P.; Kamm, R.D. Microfluidic models for adoptive cell-mediated cancer
immunotherapies. Drug Discov. Today 2016,21, 1472–1478. [CrossRef]
79.
Aref, A.R.; Campisi, M.; Ivanova, E.; Portell, A.; Larios, D.; Piel, B.P.; Mathur, N.; Zhou, C.; Coakley, R.V.; Bartels, A.; et al. 3D
microfluidic ex vivo culture of organotypic tumor spheroids to model immune checkpoint blockade. Lab Chip
2018
,18, 3129–3143.
[CrossRef]
80.
Xu, Z.; Wang, X.; Zeng, S.; Ren, X.; Yan, Y.; Gong, Z. Applying artificial intelligence for cancer immunotherapy. Acta Pharm. Sin. B
2021,11, 3393–3405. [CrossRef]
81. Shimizu, H.; Nakayama, K.I. Artificial intelligence in oncology. Cancer Sci. 2020,111, 1452–1460. [CrossRef] [PubMed]
82.
Gajewski, T.F. The Next Hurdle in Cancer Immunotherapy: Overcoming the Non-T-Cell-Inflamed Tumor Microenvironment.
Semin. Oncol. 2015,42, 663–671. [CrossRef] [PubMed]
83.
Hegde, P.S.; Karanikas, V.; Evers, S. The Where, the When, and the How of Immune Monitoring for Cancer Immunotherapies in
the Era of Checkpoint Inhibition. Clin. Cancer Res. 2016,22, 1865–1874. [CrossRef] [PubMed]