Abstract 119P
Background
Approximately 30% of colorectal cancer patients experience liver metastasis allowing surgical resection and systemic chemotherapy as treatment options. The existence of a reliable biomarker enables the prediction of optimal treatment after liver metastasis resection. This project aims to study the prognostic and therapeutic biomarkers by analyzing the differentially expressed (DE) genes in the tumor and non-tumor adjacent liver tissue and in patients stratified by early relapse (ER) of metachronous colorectal liver metastasis (mCLM) using RNA sequencing technology.
Methods
The total RNA (43 pairs; tumor and liver) of fresh frozen mCLM samples collected at University Hospital Pilsen, Czech Republic, was isolated using TRIzol reagent. The library was prepared using Lexogen QuantSeq 3’mRNA-seq library prep kit and sequenced with NextSeq 500 platform. The DE analysis of tumor vs. non-tumor (T vs. NT) and ER with cut-off 6 months was performed using the DESeq2 package in R and the clusterProfiler package was employed to perform Geneset enrichment analysis (GSEA).
Results
DE analysis of T vs. NT shows around 3,000 significantly dysregulated genes. HOXA1, MUC2, MISP, and AGR2 were 7-fold significantly upregulated whereas CFB, LGI1, MT1B, SULT1E1 were 3-fold significantly downregulated. LINC02141, CELA2B,and QRSL1P3 were significantly upregulated in patients with ER. The GSEA showed significance in various processes like extracellular matrix organization, skeletal development, glycosaminoglycan binding, and cellular components.
Conclusions
The DE indicates the complex alterations in various biological processes like cell proliferation, invasion, immune responses, and metabolism. Novel in mCLM etiology genes, CELA2B andQRSL1P3, and the non-coding RNA LINC02141 will be further investigated. The overall GSEA indicates that the extracellular matrix organization, structure, and cellular components are important for the interplay between the tumor and its microenvironment. Further validation on a larger cohort and functional analysis may be required to understand the molecular mechanism for developing novel therapeutic targets to improve the clinical management strategies for mCLM patients.
Legal entity responsible for the study
Laboratory of Pharmacogenomics, Biomedical Center, Faculty of Medicine in Pilsen, Charles University.
Funding
This work was funded by the European Union’s Horizon 2020 Research and Innovation Programme, under grant agreement No 856620; the Grant Agency of Charles University program Cooperatio – Surgical Disciplines, no. 207043; the Czech Health Research Council grant no. NU21-07-00247; and the Charles University Grant Agency (GAUK) Project No: 183424.
Disclosure
All authors have declared no conflicts of interest.