Exploring the mystery of colon cancer from the perspective of molecular subtypes and treatment.
Scientific reports
The molecular categorization of colon cancer patients remains elusive. Gene set enrichment analysis (GSEA), which investigates the dysregulated genes among tumor and normal samples, has revealed the pivotal role of epithelial-to-mesenchymal transition (EMT) in colon cancer pathogenesis. In this study, we employed multi-clustering method for grouping data, resulting in the identification of two clusters characterized by varying prognostic outcomes. These two subgroups not only displayed disparities in overall survival (OS) but also manifested variations in clinical variables, genetic mutation, and gene expression profiles. Using the nearest template prediction (NTP) method, we were able to replicate the molecular classification effectively within the original dataset and validated it across multiple independent datasets, underscoring its robust repeatability. Furthermore, we constructed two prognostic signatures tailored to each of these subgroups. Our molecular classification, centered on EMT, hold promise in offering fresh insights into the therapy strategies and prognosis assessment for colon cancer.
10.1038/s41598-024-60495-8
Identification and validation of the prognostic signature of a novel demethylation-related gene associated with the clinical features of colon cancer.
International immunopharmacology
BACKGROUND:The aim of this study was to construct a prognostic model of colon cancer based on demethylation-related genes. An in-depth understanding of the relationship between the set of demethylated genes and colon cancer not only assists in revealing the pathogenesis of colon cancer but also provides strong support for future therapeutic strategies and individualized medicine. METHODS:Data were obtained from the TCGA database and the GEO-GSE39582 cohort. A risk score model for demethylation-related genes was developed using univariate Cox regression analysis and LASSO regression analysis. The accuracy and reliability of the model were confirmed using K-M survival analysis and ROC curve analysis. Additionally, a nomogram was created by integrating the risk score and clinicopathological variables. Finally, the biological function of the RCOR2 gene was verified by performing qPCR, MTT, colony formation, Transwell, and subcutaneous tumor formation assays in nude mice. RESULTS:We constructed a risk score model containing 30 demethylation-related genes for predicting the survival risk of patients with colon cancer. COAD patients were categorized into high-risk and low-risk groups, and Kaplan-Meier (KM) curve analysis revealed that the high-risk group was associated with a worse prognosis. Univariate and multivariate Cox regression analyses validated the risk score as an independent prognostic factor for COAD. We also analyzed the differences in the sensitivity to nine chemotherapeutic agents and small molecule targeted drugs between the high-risk and low-risk groups. Moreover, we performed experiments in COAD cell lines and nude mice to verify that RCOR2 was differentially expressed between tumor tissues and normal tissues and that high RCOR2 expression promoted a malignant phenotype of colon cancer. CONCLUSION:This study demonstrated the potential roles of demethylation-related genes in colon cancer by conducting a comprehensive analysis and constructing a risk score. These findings also highlight the ability of these genes to indicate patient prognosis and tumor immune microenvironment. Furthermore, this study provides a reliable predictive tool that can assist in guiding the treatment and management of colon cancer patients.
10.1016/j.intimp.2024.112798
Construction and validation of a colon cancer prognostic model based on tumor mutation burden-related genes.
Scientific reports
Currently, immunotherapy has entered the clinical diagnosis and treatment guidelines for colon cancer, but existing immunotherapy markers cannot predict the effectiveness of immunotherapy well. This study utilized the TCGA-COAD queue to perform differential gene analysis on high and low-mutation burden samples, and screen differentially expressed genes (DEGs). To explore new molecular markers or predictive models of immunotherapy by using DEGs for NMF classification and prognostic model construction. Through systematic bioinformatics analysis, the TCGA-COAD cohort was successfully divided into high mutation burden subtypes and low mutation burden subtypes by NMF typing using DEGs. The proportion of MSI-H between high mutation burden subtypes was significantly higher than that of low mutation burden subtypes, but there was no significant difference in immunotherapy efficacy between the two subtypes. Drug sensitivity analysis showed significant differences in drug sensitivity between the two subtypes. Subsequently, we constructed a prognostic model using DEGs, which can effectively predict patient survival and immunotherapy outcomes. The prognosis and immunotherapy outcomes of the low-risk group were significantly better than those of the high-risk group. The external dataset validation of the constructed prognostic model using the GSE39582 dataset from the GEO database yielded consistent results. At the same time, we also analyzed the TMB and MSI situation between the high and low-risk groups, and the results showed that there was no significant difference in TMB between the high and low-risk groups, but the proportion of MSI-H in the high-risk group was significantly higher than that in the low-risk group. Finally, we conclude that TMB is not a suitable molecular marker for predicting the efficacy of immunotherapy in colon cancer. The newly constructed prognostic model can effectively differentiate the prognosis of colon cancer patients and predict their immunotherapy efficacy.
10.1038/s41598-024-53257-z
Recent Advancements, Limitations, and Future Perspectives of the use of Personalized Medicine in Treatment of Colon Cancer.
Technology in cancer research & treatment
Due to the heterogeneity of colon cancer, surgery, chemotherapy, and radiation are ineffective in all cases. The genomic profile and biomarkers associated with the process are considered in personalized medicine, along with the patient's personal history. It is based on the response of the targeted therapies to specific genetic variations. The patient's genetic transcriptomic and epigenetic features are evaluated, and the best therapeutic approach and diagnostic testing are identified through personalized medicine. This review aims to summarize all the necessary, updated information on colon cancer related to personalized medicine. Personalized medicine is gaining prominence as generalized treatments are finding it challenging to contain colon cancer cases which currently rank fourth among global cancer incidence while being the fifth largest in total death cases worldwide. In personalized therapy, patients are grouped into specific categories, and the best therapeutic approach is chosen based on evaluating their molecular features. Various personalized strategies are currently being explored in the treatment of colon cancer involving immunotherapy, phytochemicals, and other biomarker-specific targeted therapies. However, significant challenges must be overcome to integrate personalized medicine into healthcare systems completely. We look at the various signaling pathways and genetic and epigenetic alterations associated with colon cancer to understand and identify biomarkers useful in targeted therapy. The current personalized therapies available in colon cancer treatment and the strategies being explored to improve the existing methods are discussed. This review highlights the advantages and limitations of personalized medicine in colon cancer therapy. The current scenario of personalized medicine in developed countries and the challenges faced in middle- and low-income countries are also summarized. Finally, we discuss the future perspectives of personalized medicine in colon cancer and how it could be integrated into the healthcare systems.
10.1177/15330338231178403
Biological and Clinical Characteristics of Proximal Colon Cancer: Far from Its Anatomical Subsite.
International journal of medical sciences
Colorectal cancer is a heterogeneous disease which can be divided into proximal colon cancer, distal colon cancer and rectal cancer according to the anatomical location of the tumor. Each anatomical location of colorectal cancer exhibits distinct characteristics in terms of incidence, clinical manifestations, molecular phenotypes, treatment, and prognosis. Notably, proximal colon cancer differs significantly from cancers of other anatomical subsites. An increasing number of studies have highlighted the presence of unique tumor biological characteristics in proximal colon cancer. Gaining a deeper understanding of these characteristics will facilitate accurate diagnosis and treatment approaches.
10.7150/ijms.97574
Use of Circulating Tumor DNA to Guide Decision-making in Adjuvant Colon Cancer.
Current oncology reports
PURPOSE OF REVIEW:The use of circulating tumor DNA (ctDNA) assays to guide clinical decision-making in early-stage colon cancer is an area of rapidly advancing active research. With assays clinically available, clinicians must be informed how to best use this novel tool to treat patients. RECENT FINDINGS:Recent observational and prospective studies have suggested that ctDNA has potential to guide clinical decision-making in early-stage colon cancer by detecting minimal residual disease (MRD) and predicting recurrence risks. MRD-negative patients may be able to de-escalate or forgo adjuvant chemotherapy (ACT) without compromising disease-free survival or overall survival, while MRD-positive patients may benefit significantly from ACT. Recent and ongoing studies have given reason for optimism about the future of ctDNA as a useful biomarker for clinicians treating early-stage colon cancer. Data thus far are mostly limited to observational studies; inconsistent results highlight the need for caution. As more evidence emerges, ctDNA may become standard of care for colon cancer patients.
10.1007/s11912-024-01565-y
Imaging in the era of risk-adapted treatment in colon cancer.
The British journal of radiology
The treatment landscape for patients with colon cancer is continuously evolving. Risk-adapted treatment strategies, including neoadjuvant chemotherapy and immunotherapy, are slowly finding their way into clinical practice and guidelines. Radiologists are pivotal in guiding clinicians toward the most optimal treatment for each colon cancer patient. This review provides an overview of recent and upcoming advances in the diagnostic management of colon cancer and the radiologist's role in the multidisciplinary approach to treating colon cancer.
10.1093/bjr/tqae061