Exploring biomarkers for prognosis and neoadjuvant chemosensitivity in rectal cancer: Multi-omics and ctDNA sequencing collaboration - Jiang, Xiu-Feng; Zhang, Bo-Miao; Du, Fen-Qi; Guo, Jun-Nan; Wang, Dan; Li, Yi-En; Deng, Shen-Hui; Cui, Bin-Bin; Liu, Yan-Long (Frontiers in Immunology, 2022)
Background: This study aimed to identified the key genes and sequencing metrics for predicting prognosis and efficacy of neoadjuvant chemotherapy in rectal cancer (RC) based on genomic DNA sequencing in samples with different origin and multi-omics association database. Methods: We collected 16 RC patients and obtained DNA sequencing data from cancer tissues and plasma cell-free DNA before and after neoadjuvant chemotherapy. Various gene variations were analyzed, including single nucleotide variants (SNV), copy number variation (CNV), tumor mutation burden (TMB), copy number instability (CNI) and mutant-allele tumor heterogeneity (MATH). We also identified genes by which CNV level can differentiate the response to neoadjuvant chemotherapy. The Cancer Genome Atlas database and the Clinical Proteomic Tumor Analysis Consortium database were used to further screen out the key genes in multi-omics levels. After the intersection of the screened genes from differential expression analysis, survival analysis and principal components analysis dimensionality reduction cluster analysis, the key genes were finally identified. Results: The genes CNV level of principal component genes in baseline blood and cancer tissues could significantly distinguish the two groups of patients. The CNV of HSP90AA1, EGFR, SRC, MTOR, etc. were relatively gained in the better group compared with the poor group in baseline blood. The CNI and TMB was significantly different between the two groups. The increased expression of HSP90AA1, EGFR, and SRC was associated with increased sensitivity to multiple chemotherapeutic drugs. After a series of analysis in multi-omics association database, EGFR and HSP90AA1 with significant differences in multiple aspects were identified as the key predictive genes related to prognosis and the sensitivity of neoadjuvant chemotherapy. Conclusion: This work revealed that effective combined application and analysis in multi-omics data are critical to search for predictive biomarkers. The key genes EGFR and HSP90AA1 could serve as an effective biomarker to predict prognose and neoadjuvant chemosensitivity.