Panomics reveals patient-individuality as the major driver for colorectal cancer progression

Abstract

AbstractColorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases. The prognosis of CRC considerably depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aims to integrate genomic, transcriptomic, and proteomic analyses to identify significant expression differences during colorectal progression using a unique set of paired patient samples concerning tumor heterogeneity.We analyzed fresh-frozen tissue samples of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from same patients prepared under strict cryogenic conditions. While somatic mutations of known cancer-related genes were analyzed using Illumina’s TruSeq Amplicon Cancer Panel, the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC-MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated using differential expression results.While panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumor and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with a patient-individual transcriptome and proteome.In conclusion, the results highlight the importance of inter- and intra-tumor heterogeneity alongside the individual, patient-paired evaluation for clinical studies. Next to changes among groups reflecting colorectal cancer progression, we identified significant expression differences between patient-individual normal colon mucosa, primary tumor, and liver metastasis, which could speed up the implementation of precision oncology in the future.