Qifan Hu's research while affiliated with Tsinghua University and other places
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Publications (8)
Cancer models play critical roles in basic cancer research and precision medicine. However, current in vitro cancer models are limited by their inability to mimic the three-dimensional architecture and heterogeneous tumor microenvironments (TME) of in vivo tumors. Here, we develop an innovative patient-specific lung cancer assembloid (LCA) model by...
Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different appr...
Understanding the heterogeneity and dynamic plasticity of tumor cells is crucial for overcoming drug resistance. Single-cell technologies enable the analysis of cell states at a given condition or time point, but it is still challenging to catenate static tumor cell snapshots to characterize their dynamic responses after drug treatment. Here, we pr...
Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different appr...
Cancer Stem Cells In article number 2200364, Zhuo Xiong and co‐workers report that 3D bioprinted GelMA‐nanoclay hybrid hydrogels can induce and enrich colorectal cancer stem cells (CSCs) by promoting the formation of spheroids by activating Wnt/β‐catenin signaling. These spheroids can be isolated easily and are promising CSC enrichment models with...
Cancer stem cells (CSCs) are a rare cell population in tumors that are responsible for tumor recurrence and metastasis. They are a priority as therapeutic targets, however, assays targeting CSCs have been limited by expanding and maintaining CSCs in vitro. Here, the authors find that gelatin methacryloyl (GelMA)‐nanoclay hybrid hydrogels can induce...
Gene selection is an indispensable step for analyzing noisy and high-dimensional single cell RNA-seq (scRNA-seq) data. Compared with the commonly used variance-based methods, by mimicking the human maker selection in the 2D visualization of cells, a new feature selection method called HRG (Highly Regional Genes) is proposed to find the informative...
Citations
... However, conventional cancer organoid models based on matrigel mainly represent tumor epithelium, endogenous stromal and immune cells are gradually lost over time in culture 7,[9][10][11] . Although some studies reconstituted a part of the TME in organoid culture systems by the air-liquid interface (ALI) method 12 or coculturing organoids with TME cells such as CAFs 13,14 and immune cells 15,16 , some other studies developed non-Matrigel-based hydrogel 3D cancer models comprised of heterogeneous patient-derived tumor cells and stromal cells 17,18 , the models lacked precise controllability and uniformity in addition to labor costs. Some other cancer organoids derived from minced tumor fragments could maintain the native tissue architecture and TME cell components. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/1014646005829639-1618921867365_Q64/Zhuo-Xiong-3.jpg)
... Gene Selection Approaches derived from the concept of feature selection [23,24], tailored specifically for genomics research, including scRNAseq studies. Those approaches, whether highly depend on well-trained embedded machine learning models [25] to identify the importance of each gene, or they utilize heuristic metrics to determine key genes [26,27], are always unstable and not optimization-directed. ...
![[object Object]](https://i1.rgstatic.net/ii/profile.image/277193872691200-1443099577075_Q64/Jin-Gu-3.jpg)
