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Next-generation sequencing (NGS) technology detects specific mutations that can provide treatment opportunities for colorectal cancer (CRC) patients. Patients and Methods: We analyzed the mutation frequencies of common actionable genes and their association with clinicopathological characteristics and oncologic outcomes using targeted NGS in 107 Saudi Arabian patients without a family history of CRC. Results: Approximately 98% of patients had genetic alterations. Frequent mutations were observed in BRCA2 (79%), CHEK1 (78%), ATM (76%), PMS2 (76%), ATR (74%), and MYCL (73%). The APC gene was not included in the panel. Statistical analysis using the Cox proportional hazards model revealed an unusual positive association between poorly differentiated tumors and survival rates (p = 0.025). Although no significant univariate associations between specific mutations or overall mutation rate and overall survival were found, our preliminary analysis of the molecular markers for CRC in a predominantly Arab population can provide insights into the molecular pathways that play a significant role in the underlying disease progression. Conclusions: These results may help optimize personalized therapy when drugs specific to a patient’s mutation profile have already been developed. 

The ability to identify and track T-cell receptor (TCR) sequences from patient samples is becoming central to the field of cancer research and immunotherapy. Tracking genetically engineered T cells expressing TCRs that target specific tumor antigens is important to determine the persistence of these cells and quantify tumor responses. The available high-throughput method to profile TCR repertoires is generally referred to as TCR sequencing (TCR-Seq). However, the available TCR-Seq data are limited compared with RNA sequencing (RNA-Seq). In this paper, we have benchmarked the ability of RNA-Seq-based methods to profile TCR repertoires by examining 19 bulk RNA-Seq samples across 4 cancer cohorts including both T-cell-rich and T-cell-poor tissue types. We have performed a comprehensive evaluation of the existing RNA-Seq-based repertoire profiling methods using targeted TCR-Seq as the gold standard. We also highlighted scenarios under which the RNA-Seq approach is suitable and can provide comparable accuracy to the TCR-Seq approach. Our results show that RNA-Seq-based methods are able to effectively capture the clonotypes and estimate the diversity of TCR repertoires, as well as provide relative frequencies of clonotypes in T-cell-rich tissues and low-diversity repertoires. However, RNA-Seq-based TCR profiling methods have limited power in T-cell-poor tissues, especially in highly diverse repertoires of T-cell-poor tissues. The results of our benchmarking provide an additional appealing argument to incorporate RNA-Seq into the immune repertoire screening of cancer patients as it offers broader knowledge into the transcriptomic changes that exceed the limited information provided by TCR-Seq.