Identification of Genomic Signatures for Colorectal Cancer Survival Using Exploratory Data Mining.

Clinicopathological presentations are critical for establishing a postoperative treatment regimen in Colorectal Cancer (CRC), although the prognostic value is low in Stage 2 CRC. We implemented a novel exploratory algorithm based on artificial intelligence (explainable artificial intelligence, XAI) that integrates mutational and clinical features to identify genomic signatures by repurposing the FoundationOne Companion Diagnostic (F1CDx) assay. The training data set (n = 378) consisted of subjects with recurrent and non-recurrent Stage 2 or 3 CRC retrieved from TCGA. Genomic signatures were built for identifying subgroups in Stage 2 and 3 CRC patients according to recurrence using genomic parameters and further associations with the clinical presentation. The summarization of the top-performing genomic signatures resulted in a 32-gene genomic signature that could predict tumor recurrence in CRC Stage 2 patients with high precision. The genomic signature was further validated using an independent dataset (n = 149), resulting in high-precision prognosis (AUC: 0.952; PPV = 0.974; NPV = 0.923). We anticipate that our genomic signatures and NCCN guidelines will improve recurrence predictions in CRC molecular stratification.

TBX21 Methylation as a Potential Regulator of Immune Suppression in CMS1 Subtype Colorectal Cancer.

Cytotoxic T lymphocyte (CTL) infiltration is associated with survival, recurrence, and therapeutic response in colorectal cancer (CRC). Immune checkpoint inhibitor (ICI) therapy, which requires CTLs for response, does not work for most CRC patients. Therefore, it is critical to improve our understanding of immune resistance in this disease. We utilized 2391 CRC patients and 7 omics datasets, integrating clinical and genomic data to determine how DNA methylation may impact survival and CTL function in CRC. Using comprehensive molecular subtype (CMS) 1 patients as reference, we found TBX21 to be the only gene with altered expression and methylation that was associated with CTL infiltration. We found that CMS1 patients with high TBX21 expression and low methylation had a significant survival advantage. To confirm the role of Tbx21 in CTL function, we utilized scRNAseq data, demonstrating the association of TBX21 with markers of enhanced CTL function. Further analysis using pathway enrichment found that the genes TBX21, MX1, and SP140 had altered expression and methylation, suggesting that the TP53/P53 pathway may modify TBX21 methylation to upregulate TBX21 expression. Together, this suggests that targeting epigenetic modification more specifically for therapy and patient stratification may provide improved outcomes in CRC.

Immunogenomic pathways associated with cytotoxic lymphocyte infiltration and survival in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the second leading cancer killer in the US today and patients with metastatic disease have only a 14% 5-year survival. One of the most impactful recent advances in cancer therapy, immune checkpoint inhibition, has not been shown to be effective for the majority of these patients. In this study, we use The Cancer Genome Atlas (TCGA) and recently developed informatic-based tools to identify targets for immune based therapy in colorectal cancer patients. METHODS: Open access, pre-processed (level 3) mRNA data and clinical data from colorectal patients from the TCGA was downloaded from FireCloud. Using the Microenvironment Cell Populations-Counter method (MCP-Counter), cytotoxic lymphocyte scores were calculated for all patients. Patients were then grouped by cytotoxic lymphocyte score (High vs Low), pathologic stage, and location to identify differentially expressed genes. Pathway enrichment analysis was performed using Reactome to determine differentially expressed genes associated with immune pathways. Survival analysis was performed with identified differentially expressed genes. RESULTS: In the TCGA dataset, there are 461 colon and 172 rectal cancer patients. After stratifying patients by cytotoxic lymphocyte score, anatomical location, and stage, we found a significant number of differentially expressed genes. We identified one pathway, "immunoregulatory interactions between a lymphoid and non-lymphoid cell", that was highly enriched and included in all tumor locations and stages. Survival analysis performed with differentially expressed genes in this pathway identified 21 different genes associated with survival and cytotoxic lymphocyte infiltration, with ~ 70% of these genes occurring in the metastatic right-sided CRC group. Specifically, all genes associated with survival in the metastatic right-sided colorectal cancer group with low cytotoxic lymphocyte scores positively impacted survival. CONCLUSIONS: Utilizing the TCGA, a publicly available dataset, and informatics-based analyses, we identified potential targets to improve immune based therapy in colorectal cancer. Additionally, we note the most targets in metastatic right-sided CRC patients, the patient group with the worst predicted survival. The results from this study demonstrate the ability of informatics-based analytic techniques to identify new therapeutic targets as well as improve patient selection for intervention, helping us to achieve the goals of precision-based oncology.