Colon Cancer-Related Genes Identification and Function Study Based on Single-Cell Multi-Omics Integration

Single cell analyses of cancer cells identified two regulatorily and functionally distinct categories in differentially expressed genes among tumor subclones

To explore the feature of cancer cells and tumor subclones, we analyzed 101,065 single-cell transcriptomes from 12 colorectal cancer (CRC) patients and 92 single cell genomes from one of these patients. We found cancer cells, endothelial cells and stromal cells in tumor tissue expressed much more genes and had stronger cell-cell interactions than their counterparts in normal tissue. We identified copy number variations (CNVs) in each cancer cell and found correlation between gene copy number and expression level in cancer cells at single cell resolution. Analysis of tumor subclones inferred by CNVs showed accumulation of mutations in each tumor subclone along lineage trajectories. We found differentially expressed genes (DEGs) between tumor subclones had two populations: DEGCNV and DEGreg. DEGCNV, showing high CNV-expression correlation and whose expression differences depend on the differences of CNV level, enriched in housekeeping genes and cell adhesion associated genes. DEGreg, showing low CNV-expression correlation and mainly in low CNV variation regions and regions without CNVs, enriched in cytokine signaling genes. Furthermore, cell-cell communication analyses showed that DEGCNV tends to involve in cell-cell contact while DEGreg tends to involve in secreted signaling, which further support that DEGCNV and DEGreg are two regulatorily and functionally distinct categories.

Technologies and applications of single-cell DNA methylation sequencing

DNA methylation is the most stable epigenetic modification. In mammals, it usually occurs at the cytosine of CpG dinucleotides. DNA methylation is essential for many physiological and pathological processes. Aberrant DNA methylation has been observed in human diseases, particularly cancer. Notably, conventional DNA methylation profiling technologies require a large amount of DNA, often from a heterogeneous cell population, and provide an average methylation level of many cells. It is often not realistic to collect sufficient numbers of cells, such as rare cells and circulating tumor cells in peripheral blood, for bulk sequencing assays. It is therefore essential to develop sequencing technologies that can accurately profile DNA methylation using small numbers of cells or even single cells. Excitingly, many single-cell DNA methylation sequencing and single-cell omics sequencing technologies have been developed, and applications of these methods have greatly expanded our understanding of the molecular mechanism of DNA methylation. Here, we summaries single-cell DNA methylation and multi-omics sequencing methods, delineate their applications in biomedical sciences, discuss technical challenges, and present our perspective on future research directions.

Comprehensive analysis of the differential expression and prognostic value of COL1A2 in colon adenocarcinoma

Background: Colon adenocarcinoma (COAD) is a highly heterogeneous disease, which is the second most common cancer in females and third in males. Collagen type I alpha 2 (COL1A2) has been documented to be involved in the carcinogenesis of multiple tumors; however, the expression and prognostic significance of COL1A2 and its underlying mechanism in COAD remains unclarified.

Materials and Methods: The general profile of COL1A2, its expression pattern, and prognostic value were systematically assessed through various bioinformatics tools. The protein level of COL1A2 was verified in COAD patients using immunohistochemistry analysis. In addition, enrichment analyses were performed to explore the possible regulatory pathways of COL1A2 in COAD.

Results: The mRNA and protein levels of COL1A2 were significantly increased in COAD than that in normal tissues (P < 0.05). The COL1A2 expression tended to increase along with cancer stages and nodal metastasis status in COAD, while the promoter methylation levels of COL1A2 might negatively related to its mRNA expression. Survival analysis showed that COL1A2 was a reliable predictor for distinguishing the status of disease-specific survival (DSS), overall survival (OS), and progression-free survival (PFS), and might serve as a robust independent prognostic biomarker for DSS and OS in COAD patients (P < 0.05). The enrichment analysis showed focal adhesion as the most possible regulatory pathway by COL1A2.

Conclusion: Collectively, COL1A2 functioned as an independent prognostic biomarker and might be a potential therapeutic target in COAD.