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We recently reported that DNA content of breast adenocarcinomas, cytometrically assessed by diploid (D), tetraploid (T), and aneuploid (A) categories, can be further divided into genomically stable and unstable subtypes by means of the stemline scatter index (SSI). The aim of the present study was to survey the clinical correlates and the prognosti...
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Context 1
... Putative Prognostic Factors. The Agu breast tumors were, on the average, 2.9 mm larger than Ags tumors (P < 0.03; Table 3), a difference also seen for D (2.9 mm) and T (4.5 mm) tumors but not reaching statistical significance in the latter two subgroups. Remarkably, genomic instability did not seem to be associated with local lymph node metastases ( Table 4), suggesting that they can function as independent prognostic factors. ...
Citations
... P < 0.05 was considered statistically significant. Subcellular localization of lncRNAs was predicted using lncLocator tool [45] (http:// www. csbio. ...
... instability is a key diagnostic and prognostic marker in cancer [45,46]. Advances in immunotherapy in cancer medicine have increased interest in understanding the mechanisms by which patients respond or are resistant to immunotherapy. ...
Background
Pancreatic adenocarcinoma (PAAD) is a leading cause of malignancy-related deaths worldwide, and the efficacy of immunotherapy on PAAD is limited. Studies report that long non-coding RNAs (lncRNAs) play an important role in modulating genomic instability and immunotherapy. However, the identification of genome instability-related lncRNAs and their clinical significance has not been investigated in PAAD.
Methods
The current study developed a computational framework for mutation hypothesis based on lncRNA expression profile and somatic mutation spectrum in pancreatic adenocarcinoma genome. We explored the potential of GInLncRNAs(genome instability-related lncRNAs) through co-expression analysis and function enrichment analysis. We further analyzed GInLncRNAs by Cox regression and used the results to construct a prognostic lncRNA signature. Finally, we analyzed the relationship between GILncSig (genomic instability derived 3-lncRNA signature) and immunotherapy.
Results
A GILncSig was developed using bioinformatics analyses. It could divide patients into high-risk and low-risk groups, and there was a significant difference in OS between the two groups. In addition, GILncSig was associated with genome mutation rate in pancreatic adenocarcinoma, indicating its potential value as a marker for genomic instability. The GILncSig accurately grouped wild type patients of KRAS into two risk groups. The prognosis of the low-risk group was significantly improved. GILncSig was significantly correlated with the level of immune cell infiltration and immune checkpoint.
Conclusions
In summary, the current study provides a basis for further studies on the role of lncRNA in genomic instability and immunotherapy. The study provides a novel method for identification of cancer biomarkers related to genomic instability and immunotherapy.
... 85 Given the above, telomere crisis has been considered one of the mechanisms underlying genomic instability and an important source of CIN in cancer 86 ( Figure 5), also associated with aggressiveness and poor prognosis. 87,88 For instance, breast tumor cells generally have shorter telomeres than corresponding cells in normal tissue, 89,90 and such telomere shortening has been considered a negative prognostic indicator in BC patients. 91,92 In addition, specific associations between telomere shortening and BC tumor subtypes have been established. ...
Chromosomal instability (CIN) has become a topic of great interest in recent years, not only for its implications in cancer diagnosis and prognosis but also for its role as an enabling feature and central hallmark of cancer. CIN describes cell-to-cell variation in the number or structure of chromosomes in a tumor population. Although extensive research in recent decades has identified some associations between CIN with response to therapy, specific associations with other hallmarks of cancer have not been fully evidenced. Such associations place CIN as an enabling feature of the other hallmarks of cancer and highlight the importance of deepening its knowledge to improve the outcome in cancer. In addition, studies conducted to date have shown paradoxical findings about the implications of CIN for therapeutic response, with some studies showing associations between high CIN and better therapeutic response, and others showing the opposite: associations between high CIN and therapeutic resistance. This evidences the complex relationships between CIN with the prognosis and response to treatment in cancer. Considering the above, this review focuses on recent studies on the role of CIN in cancer, the cellular mechanisms leading to CIN, its relationship with other hallmarks of cancer, and the emerging therapeutic approaches that are being developed to target such instability, with a primary focus on breast cancer. Further understanding of the complexity of CIN and its association with other hallmarks of cancer could provide a better understanding of the cellular and molecular mechanisms involved in prognosis and response to treatment in cancer and potentially lead to new drug targets.
... The classification helps in prognosis, treatment. The lack of estrogen repeptors, progesterone receptors and human epidermal growth receptors2 leads to higher staged nuclear grade cancer with intense mitotic action and poor prognosis the Triple Negative Breast cancer are tolerant of endocrine therapy due to no hormonal expression [5][6][7][8][9]. ...
Cancer cell are undisciplined normal cells that grows disorganized way leads to life threaten and serious complication. Cancer cell can invade any organ and cause disruption in the functioning of the tissues. Breast are the mammary glands aids in production of milk in postnatal mothers, apart from the vital function breast are glands develop after puberty, the parenchyma cells of breast are risk of developing abnormal growth leads to condition called Breast cancer. According to research 23% female and 0.5 to 1% of males are facing the problem of breast cancer. Breast cancer is second leading cause of death in men and women, globally 66% of deaths are due to breast cancer. Death due to breast cancer can be delayed by proper diagnostic techniques, these techniques not only delay the death and also increases the survival rate of the population. Early detection of the breast cancer gives better care, prevent complication and effective management. A number of research study identified the diagnostic tools and therapy for breast cancer; however, these tool and treatment are identified in late stage, and significant detection of breast cancer is still lagging. Hence, the present review article is an effort to comprehensively describe the early and advanced diagnostic tools for detection of breast cancer and advanced therapeutic management for breast cancer.
... Additionally, these cancer cell lines vary in the level of malignancy [40]. Tumors that are negative for hormone receptors are more aggressive, causing limited treatment options [41] than positive ones [40]. ...
Selenoureas are widespread as useful elements for constructing important species and biologically active molecules. Finding an efficient and straightforward method to prepare this motif and biologically screen derivatives thereof is crucial. Herein, we demonstrate the effectiveness of using ethanol as a solvent in the preparation of various substituted aryl-, benzyl-, and piperazine-selenoureas from isoselenocyanates and amines. The synthetic method includes mild reaction conditions, large substrate scope, and good isolated yields. Biological evaluation of the prepared products on MDA-MB-231 and MCF-7 cancer cell lines revealed several remarkably active compounds (IC50 < 10 μΜ) with the best one exhibiting IC50 values of 1.8 μΜ and 1.2 μΜ observed against the challenging former triple-negative breast cancer cell line and the latter one, respectively. The chemical structures of all new compounds were fully characterized by multinuclear nuclear magnetic resonance (NMR) spectroscopy and high accuracy mass measurements.
... Importantly, the value of genomic instability in cancer prognosis is also prominent [6][7][8]. Some studies showed that compared with genome instability, genome stability had a significantly higher survival rate [9,10]. Studies have found that long noncoding RNA (lncRNA), one type of endogenous RNA longer than 200nt, is associated with recurrent mutations in AML, thereby predicting treatment response and survival rates [11,12]. ...
Objectives: Genomic instability has several implications for acute myeloid leukemia (AML) prognosis. This article aims to construct a somatic mutation-associated risk index (SMRI) of genomic instability for AML to predict prognosis and explore the potential determinants of AML prognosis.
Methods: We obtained differentially expressed lncRNAs from genomic instability subtypes and selected six lncRNAs to construct the SMRI through multivariate Cox regression analysis. The median SMRI classified patients into high and low SMRI groups. Kaplan–Meier survival analysis was used to clarify the prognostic differences of SMRI subtypes. Receiver operating characteristic curve analysis was performed to elucidate the value of SMRI as a prognostic indicator. Gene set variation analysis, tumor mutation burden (TMB) analysis, immune infiltration, and immune checkpoint expression analysis were performed to investigate possible causes for the differences in prognosis of SMRI subtypes.
Results: The high SMRI group exhibited a poor prognosis, which was characterized by elevated levels of TMB, mutation counts (TP53, NPM1, DNMT3A, and FLT3-TKD), CD8⁺ T cell infiltration, and immune checkpoint (PD-1, PD-L2, CTLA4, LAG3) expression. The SMRI was still associated with prognosis, even after adjustment for age, sex, cytogenetic risk, DNMT3A status, FLT3 status, and NPM1 status. Gene set variation analysis showed that AML with FLT3-ITD mutation, CEBPA mutation, and LSCs (leukemia stem cells) were enriched in the high SMRI group.
Conclusion: Our research suggests that the SMRI derived from genomic instability subtypes is a useful biomarker for predicting prognosis and may be beneficial for improving the clinical outcome of patients with AML.
... Some other computational methods have also been proposed in the same context, including Bayesian network analysis and support vector machine methodologies. Bayesian network analysis of signaling pathways facilitates the evaluation of a probabilistic relationship among candidate genes within the network [122] Moreover, transcriptomic microarray and sequence data analysis provide multigene signatures [123], which not only contribute to prognosis, but also can predict tumor sub types and their specific resistance to chemo or radiation [124]. Such multigene models generally classify patients by indicating the particular outcome of the disease or treatment response according to the disease pathology; e.g., the DNA content of patients with breast cancer classifies them in either stable or unstable (conferring a good or poor prognosis) states [125]. ...
Breast cancer is a diverse disease caused by mutations in multiple genes accompanying
epigenetic aberrations of hazardous genes and protein pathways, which distress tumor-suppressor
genes and the expression of oncogenes. Alteration in any of the several physiological mechanisms
such as cell cycle checkpoints, DNA repair machinery, mitotic checkpoints, and telomere maintenance
results in genomic instability. Theranostic has the potential to foretell and estimate therapy response,
contributing a valuable opportunity to modify the ongoing treatments and has developed new
treatment strategies in a personalized manner. “Omics” technologies play a key role while studying
genomic instability in breast cancer, and broadly include various aspects of proteomics, genomics,
metabolomics, and tumor grading. Certain computational techniques have been designed to facilitate the early diagnosis of cancer and predict disease-specific therapies, which can produce many
effective results. Several diverse tools are used to investigate genomic instability and underlying
mechanisms. The current review aimed to explore the genomic landscape, tumor heterogeneity, and
possible mechanisms of genomic instability involved in initiating breast cancer. We also discuss the
implications of computational biology regarding mutational and pathway analyses, identification
of prognostic markers, and the development of strategies for precision medicine. We also review
different technologies required for the investigation of genomic instability in breast cancer cells,
including recent therapeutic and preventive advances in breast cancer.
... The Mann-Whitney U test was conducted to compare that between two different risk groups F I G U R E 6 Time-dependent ROC curves study of 3-year OS for the GILncSig, YulncSig and ZenglncSig performance of patients with LUAD remains somewhat heterogeneous owing to the shortcomings of typical histopathologic characteristics. 49 Genomic instability has been reported in recent years as the pervasive hallmark of most cancers, [50][51][52] and is also considered one of the prognostic factors of LUAD. 53,54 During the development and recurrence of cancers, the diagnostic and prognostic implications of the genomic instability is non-ignorable. ...
Evidence has been emerging of the importance of long non-coding RNAs (lncRNAs) in genome instability. However, no study has established how to classify such lncRNAs linked to genomic instability, and whether that connection poses a therapeutic significance. Here, we established a computational frame derived from mutator hypothesis by combining profiles of lncRNA expression and those of somatic mutations in a tumor genome, and identified 185 candidate lncRNAs associated with genomic instability in lung adenocarcinoma (LUAD). Through further studies, we established a six lncRNA-based signature, which assigned patients to the high- and low-risk groups with different prognosis. Further validation of this signature was performed in a number of separate cohorts of LUAD patients. In addition, the signature was found closely linked to genomic mutation rates in patients, indicating it could be a useful way to quantify genomic instability. In summary, this research offered a novel method by through which more studies may explore the function of lncRNAs and presented a possible new way for detecting biomarkers associated with genomic instability in cancers.
... Genomic instability plays an important role in the development, progression, and recurrence of various cancers (Bartkova et al., 2005;Gorgoulis et al., 2005;Kronenwett et al., 2006;Mettu et al., 2010;Negrini et al., 2010). Therefore, genomic instability could be a promising biomarker to predict the oncological outcome of patients with cancers. ...
Hepatocellular carcinoma (HCC) is one of the major cancer-related deaths worldwide. Genomic instability is correlated with the prognosis of cancers. A biomarker associated with genomic instability might be effective to predict the prognosis of HCC. In the present study, data of HCC patients from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases were used. A total of 370 HCC patients from the TCGA database were randomly classified into a training set and a test set. A prognostic signature of the training set based on nine overall survival (OS)–related genomic instability–derived genes (SLCO2A1, RPS6KA2, EPHB6, SLC2A5, PDZD4, CST2, MARVELD1, MAGEA6, and SEMA6A) was constructed, which was validated in the test and TCGA and ICGC sets. This prognostic signature showed more accurate prediction for prognosis of HCC compared with tumor grade, pathological stage, and four published signatures. Cox multivariate analysis revealed that the risk score could be an independent prognostic factor of HCC. A nomogram that combines pathological stage and risk score performed well compared with an ideal model. Ultimately, paired differential expression profiles of genes in the prognostic signature were validated at mRNA and protein level using HCC and paratumor tissues obtained from our institute. Taken together, we constructed and validated a genomic instability–derived gene prognostic signature, which can help to predict the OS of HCC and help us to explore the potential therapeutic targets of HCC.
... GIN plays an important role in the occurrence, progression and recurrence of cancer. The pattern and degree of GIN are of great significance to the diagnosis and prognosis of tumors [39,40]. However, the quantitative measurement of the degree of GIN has always been a challenge. ...
Background
Muscle-invasive bladder cancer (MIBC) is one of the most important type of bladder cancer, with a high morbidity and mortality rate. Studies have found that long non-coding RNA (lncRNA) plays a key role in maintaining genomic instability. However, Identification of lncRNAs related to genomic instability (GIlncRNAs) and their clinical significance in cancers have not been extensively studied yet.
Methods
Here, we downloaded the lncRNA expression profiles, somatic mutation profiles and clinical related data in MIBC patients from The Cancer Genome Atlas (TCGA) database. A lncRNA computational framework was used to find differentially expressed GIlncRNAs. Multivariate Cox regression analysis was used to construct a genomic instability-related lncRNA signature (GIlncSig). Univariate and multivariate Cox analyses were used to assess the independent prognostic for the GIlncSig and other key clinical factors.
Results
We found 43 differentially expressed GIlncRNAs and constructed the GIlncSig with 6 GIlncRNAs in the training cohort. The patients were divided into two risk groups. The overall survival of patients in the high-risk group was lower than that in the low-risk group (P < 0.001), which were further verified in the testing cohort and the entire TCGA cohort. Univariate and multivariate Cox regression showed that the GIlncSig was an independent prognostic factor. In addition, the GIlncSig correlated with the genomic mutation rate of MIBC, indicating its potential as a measure of the degree of genomic instability. The GIlncSig was able to divide FGFR3 wild- and mutant-type patients into two risk groups, and effectively enhanced the prediction effect.
Conclusion
Our study introduced an important reference for further research on the role of GIlncRNAs, and provided prognostic indicators and potential biological therapy targets for MIBC.
... In general, diploid tumors prove to be less malignant than their aneuploid counterparts. Furthermore, not only the status quo of nuclear DNA content, i.e., diploid or aneuploid, but also the degree of genomic instability reflected as the variability of the DNA content within the breast cancer cell population is associated with prognosis [20]. It could be shown that patients with genomically stable tumors have a significantly better prognosis than patients with genomically instable tumors [20]. ...
... Furthermore, not only the status quo of nuclear DNA content, i.e., diploid or aneuploid, but also the degree of genomic instability reflected as the variability of the DNA content within the breast cancer cell population is associated with prognosis [20]. It could be shown that patients with genomically stable tumors have a significantly better prognosis than patients with genomically instable tumors [20]. However, the exact interplay between chromosomal aneuploidy, genomic instability, intra-tumor heterogeneity and disease outcome needs further elucidation. ...
... Examples for this observation are visualized in Figures 3 and 4 presenting the cases 7L and 8S with a low, and the cases 5L and 4S with a high degree of instability, occurring both in the group of short and long survival, indicating that the degree of ITH in breast cancer patients aged 50 years and older does not necessarily correlate with aggressive disease. At first view, this seems to be contrary to previous studies mainly based on image cytometry that showed (for breast carcinomas of patients not selected by age) that both aneuploidy and the degree of genomic instability result in general in a poorer prognosis [18,20,56,57]. However, we should at first emphasize the fact that we exclusively studied patients with an age range of 50-85 years, hence, the higher likelihood of comorbidities could also explain these discrepancies to the results of age unbiased breast cancer patients. ...
Purpose:
Older breast cancer patients are underrepresented in cancer research even though the majority (81.4%) of women dying of breast cancer are 55 years and older. Here we study a common phenomenon observed in breast cancer which is a large inter- and intratumor heterogeneity; this poses a tremendous clinical challenge, for example with respect to treatment stratification. To further elucidate genomic instability and tumor heterogeneity in older patients, we analyzed the genetic aberration profiles of 39 breast cancer patients aged 50 years and older (median 67 years) with either short (median 2.4 years) or long survival (median 19 years). The analysis was based on copy number enumeration of eight breast cancer-associated genes using multiplex interphase fluorescence in situ hybridization (miFISH) of single cells, and by targeted next-generation sequencing of 563 cancer-related genes.
Results:
We detected enormous inter- and intratumor heterogeneity, yet maintenance of common cancer gene mutations and breast cancer specific chromosomal gains and losses. The gain of COX2 was most common (72%), followed by MYC (69%); losses were most prevalent for CDH1 (74%) and TP53 (69%). The degree of intratumor heterogeneity did not correlate with disease outcome. Comparing the miFISH results of diploid with aneuploid tumor samples significant differences were found: aneuploid tumors showed significantly higher average signal numbers, copy number alterations (CNAs) and instability indices. Mutations in PIKC3A were mostly restricted to luminal A tumors. Furthermore, a significant co-occurrence of CNAs of DBC2/MYC, HER2/DBC2 and HER2/TP53 and mutual exclusivity of CNAs of HER2 and PIK3CA mutations and CNAs of CCND1 and PIK3CA mutations were revealed.
Conclusion:
Our results provide a comprehensive picture of genome instability profiles with a large variety of inter- and intratumor heterogeneity in breast cancer patients aged 50 years and older. In most cases, the distribution of chromosomal aneuploidies was consistent with previous results; however, striking exceptions, such as tumors driven by exclusive loss of chromosomes, were identified.
