Unknown

Dataset Information

0

Long-Read Nanopore Sequencing Identifies Mismatch Repair-Deficient Related Genes with Alternative Splicing in Colorectal Cancer


ABSTRACT:

Background

Alternative splicing (AS) plays a crucial role in regulating the progression of colorectal cancer (CRC), but its distribution remains to be explored. Here, we aim to investigate the genes edited by AS which show differential expression in patients with mismatch repair deficiency (dMMR)/microsatellite instability (MSI).

Materials and Methods

We applied long-read nanopore sequencing to determine the mRNA profiles and screen AS genes using Oxford Nanopore Technologies (ONT) method in ten paired CRC tissues. CRC tissue and plasma samples were used to validate the differential genes with AS using real-time fluorescent quantitative PCR, immunohistochemistry, and enzyme-linked immunosorbent assay.

Results

ONT sequencing identified 404 genes were downregulated, and 348 genes were upregulated in MSI cancer tissues compared with microsatellite stability (MSS) cancer tissues. In total, 6,200 AS events were identified in 2,728 mRNA transcripts. WGCNA revealed dMMR/MSI-correlated gene modules, including INHBA and RPL22L1, which were upregulated; conversely, HMGCS2 was downregulated in MSI cancer. Overexpression of RPL22L1, INHBA, and CAPZA1 was further confirmed in CRC tissues. INHBA was found to be associated with tumor lymphatic metastasis. Importantly, the levels of INHBA in CRC plasma were significantly increased compared with those in noncancer plasma. INHBA showed a higher level in dMMR/MSI CRC than in MSS CRC, indicating that INHBA is a useful biomarker.

Conclusion

Our results showed that ONT-identified genes provide a pool to explore AS-associated markers for dMMR/MSI CRC. We demonstrated INHBA as a promising signature for clinical application in predicting tumor lymphatic metastasis and screening dMMR/MSI candidates.

SUBMITTER: Qu H 

PROVIDER: S-EPMC9334049 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

| S-EPMC10618188 | biostudies-literature
| S-EPMC9390830 | biostudies-literature
| S-EPMC10512518 | biostudies-literature
| S-EPMC10484994 | biostudies-literature
2022-03-31 | GSE178383 | GEO
| S-EPMC2634718 | biostudies-literature
| S-EPMC1891934 | biostudies-literature
| S-EPMC11250277 | biostudies-literature
2022-03-31 | GSE178377 | GEO
| S-EPMC2671341 | biostudies-literature