Update of gene expression/methylation and MiRNA profiling in colorectal cancer; application in diagnosis, prognosis, and targeted therapy

Data-Driven Identification of Early Cancer-Associated Genes via Penalized Trans-Dimensional Hidden Markov Models

Colorectal cancer (CRC) is a significant worldwide health problem due to its high prevalence, mortality rates, and frequent diagnosis at advanced stages. While diagnostic and therapeutic approaches have evolved, the underlying mechanisms driving CRC initiation and progression are not yet fully understood. Early detection is critical for improving patient survival, as initial cancer stages often exhibit epigenetic changes-such as DNA methylation-that regulate gene expression and tumor progression. Identifying DNA methylation patterns and key survival-related genes in CRC could thus enhance diagnostic accuracy and extend patient lifespans. In this study, we apply two of our recently developed methods for identifying differential methylation and analyzing survival using a sparse, finite mixture of accelerated failure time regression models, focusing on key genes and pathways in CRC datasets. Our approach outperforms two other leading methods, yielding robust findings and identifying novel differentially methylated cytosines. We found that CRC patient survival time follows a two-component mixture regression model, where genes CDH11, EPB41L3, and DOCK2 are active in the more aggressive form of CRC, whereas TMEM215, PPP1R14A, GPR158, and NAPSB are active in the less aggressive form.

miR-4486 inhibits colorectal cancer proliferation via targeting MAP2K4 to inhibit the activation of the p38MAPK/JNK signaling

Objective

Since MAP2K4 was reportedly involved in colorectal cancer development and the p38MAPK/JNK signaling transcription, this study aimed to investigate the mechanism by which the microRNA (miR)-4486 acts on colorectal cell proliferation.

Methods

RT-PCR was conducted to measure the expression levels of the MAP2K4 and miR-4486 in NCM460, SW1116, and HCT116 cells. TargetScanHuman site anticipated that MAP2K4 may be a target of miR-4486. The dual-luciferase reporter assay confirmed their relationship. After plasmids of miR-4486 mimic and si-MAP2K4 transfection, MAP2K4 was quantified again, The CCK-8 assay was carried out to assess cell proliferation, while Scratch and Transwell assays were used to evaluate cell migration and invasion. Finally, miR-4486 mimic and SB203580 were applied in HCT116 and SW1116 cells separately or in combination. CCK-8, Scratch and Transwell assay were performed again. In addition, the proteins including c-capase3, Bax, Bcl2, MAP2K4, and the p38MAPK/JNK signaling-related proteins expression levels were quantified by Western blot (WB).

Results

Compared with the NCM460 cells, the expression level of MAP2K4 was elevated, while the expression level of miR-4486 was reduced in SW1116 and HCT116 cells. The results showed that elevated levels of miR-4486 suppressed cell proliferation, migration, and invasion in colorectal cells by downregulating MAP2K4 expression. miR-4486 mimic showed similar effects to SB203580, which promoted colorectal cell apoptosis and inhibited the p38 MAPK/JNK signaling transcription.

Conclusion

miR-4486 may target MAP2K4 to inhibit colorectal cell proliferation by inhibiting the activation of the p38/JNK signaling pathway.

Prognostic analysis of hepatocellular carcinoma based on cuproptosis -associated lncRNAs

OBJECTIVES

Cuproptosis represents an innovative type of cell death, distinct from apoptosis, driven by copper dependency, yet the involvement of copper apoptosis-associated long non-coding RNAs (CRLncRNAs) in hepatocellular carcinoma (HCC) remains unclear. This study is dedicated to unveiling the role and significance of these copper apoptosis-related lncRNAs within the context of HCC, focusing on their impact on both the development of the disease and its prognosis.

METHODS

We conducted an analysis of gene transcriptomic and clinical data for HCC cases by sourcing information from The Cancer Genome Atlas database. By incorporating cuproptosis-related genes, we established prognostic features associated with cuproptosis-related lncRNAs. Furthermore, we elucidated the mechanism of cuproptosis-related lncRNAs in the prognosis and treatment of HCC through comprehensive approaches, including Lasso and Cox regression analyses, survival analyses of samples, as well as examinations of tumor mutation burden and immune function.

RESULTS

We developed a prognostic model featuring six cuproptosis-related lncRNAs: AC026412.3, AC125437.1, AL353572.4, MKLN1-AS, TMCC1-AS1, and SLC6A1-AS1. This model demonstrated exceptional prognostic accuracy in both training and validation cohorts for patients with tumors, showing significantly longer survival times for those categorized in the low-risk group compared to the high-risk group. Additionally, our analyses, including tumor mutation burden, immune function, Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment, and drug sensitivity, further elucidated the potential mechanisms through which cuproptosis-associated lncRNAs may influence disease outcome.

CONCLUSIONS

The model developed using cuproptosis-related long non-coding RNAs (lncRNAs) demonstrates promising predictive capabilities for both the prognosis and immunotherapy outcomes of tumor patients. This could play a crucial role in patient management and the optimization of immunotherapeutic strategies, offering valuable insights for future research.

Bioinformatics Analysis of RNA-seq Data Reveals Genes Related to Cancer Stem Cells in Colorectal Cancerogenesis

Cancer stem cells (CSC) play one of the crucial roles in the pathogenesis of various cancers, including colorectal cancer (CRC). Although great efforts have been made regarding our understanding of the cancerogenesis of CRC, CSC involvement in CRC development is still poorly understood. Using bioinformatics and RNA-seq data of normal mucosa, colorectal adenoma, and carcinoma (n = 106) from GEO and TCGA, we identified candidate CSC genes and analyzed pathway enrichment analysis (PEI) and protein–protein interaction analysis (PPI). Identified CSC-related genes were validated using qPCR and tissue samples from 47 patients with adenoma, adenoma with early carcinoma, and carcinoma without and with lymph node metastasis and were compared to normal mucosa. Six CSC-related genes were identified: ANLN, CDK1, ECT2, PDGFD, TNC, and TNXB. ANLN, CDK1, ECT2, and TNC were differentially expressed between adenoma and adenoma with early carcinoma. TNC was differentially expressed in CRC without lymph node metastases whereas ANLN, CDK1, and PDGFD were differentially expressed in CRC with lymph node metastases compared to normal mucosa. ANLN and PDGFD were differentially expressed between carcinoma without and with lymph node metastasis. Our study identified and validated CSC-related genes that might be involved in early stages of CRC development (ANLN, CDK1, ECT2, TNC) and in development of metastasis (ANLN, PDGFD).