Identification and evaluation of metabolic mRNAs and key miRNAs in colorectal cancer liver metastasis.

Abstract

Background: Colorectal cancer (CRC) represents a major global health challenge due to its high lethality, largely attributable to liver metastasis. Despite the established correlation between metabolic reprogramming of cancer cells and their proliferation, invasion, and metastasis, the specific role of metabolism-associated mRNAs in the liver metastasis of CRC remains unelucidated.

Methods: In our research, we procured and analyzed CRC liver metastasis-associated datasets from the GEO database. Subsequently, we employed Weighted Gene Co-expression Network Analysis (WGCNA) to construct an integrated co-expression network of mRNAs and miRNAs, facilitating the identification of pivotal mRNAs and miRNAs. We screened the featured genes using a machine-learning technique, followed by an evaluation of their diagnostic potential for CRC liver metastasis. Additionally, we conducted a functional enrichment analysis and constructed a network of miRNA-targeted mRNAs. Lastly, leveraging the UCSC Xena database, we assessed the correlation between core mRNAs and the clinical attributes and prognosis of CRC patients. Clinical samples from CRC patients and healthy volunteers were collected for validation using qRT-PCR.

Results: Our study identified 12 mRNAs and 4 miRNAs significantly associated with CRC liver metastasis. Functional enrichment analysis indicated that these key genes were intricately linked with biological processes like lipid transport, homeostasis, and metabolism. By implementing LASSO and SVM algorithms, we pinpointed six core mRNAs from the key mRNAs. Their expression patterns and diagnostic performance were validated across multiple datasets. Particularly, CAV1 showed significant diagnostic performance to discern between CRC and CRC liver metastasis samples. Additionally, we discerned two key miRNAs (hsa-miR-1246 and hsa-miR-1290) exhibiting diagnostic performance. Lastly, our findings indicate a significant association between AGT, FABP4, and GPD1L and the prognosis of CRC patients with liver metastasis. PCR validation in 40 paired tissue samples showed downregulation of CAV1 and upregulation of miRNA-1290 in CRC tissues of patients with liver metastasis.

Conclusions: This investigation identified modular genes and miRNAs linked to CRC liver metastasis, along with metabolism-associated differentially expressed mRNAs. These pivotal mRNAs and miRNAs could be instrumental in elucidating the biological mechanisms underpinning CRC liver metastasis and suggesting candidate biomarkers.