Ultra-Deep Sequencing of Plasma-Circulating DNA for the Detection of Tumor- Derived Mutations in Patients with Nonmetastatic Colorectal Cancer.

Identification of tumor-derived mutation (TDM) in liquid biopsies (LB), especially in early-stage patients, faces several challenges, including low variant-allele frequencies, interference by white blood cell (WBC)-derived mutations (WDM), benign somatic mutations and tumor heterogeneity. Here, we addressed the above-mentioned challenges in a cohort of 50 nonmetastatic colorectal cancer patients, via a workflow involving parallel sequencing of paired WBC- and tumor-gDNA. After excluding potential false positive mutations, we detected at least one TDM in LB of 56% (28/50) of patients, with the majority showing low-patient coverage, except for one TDM mapped to KMT2D that recurred in 30% (15/30) of patients.

Multimodal analysis of ctDNA methylation and fragmentomic profiles enhances detection of nonmetastatic colorectal cancer.

Aims: Early detection of colorectal cancer (CRC) provides substantially better survival rates. This study aimed to develop a blood-based screening assay named SPOT-MAS ('screen for the presence of tumor by DNA methylation and size') for early CRC detection with high accuracy. Methods: Plasma cell-free DNA samples from 159 patients with nonmetastatic CRC and 158 healthy controls were simultaneously analyzed for fragment length and methylation profiles. We then employed a deep neural network with fragment length and methylation signatures to build a classification model. Results: The model achieved an area under the curve of 0.989 and a sensitivity of 96.8% at 97% specificity in detecting CRC. External validation of our model showed comparable performance, with an area under the curve of 0.96. Conclusion: SPOT-MAS based on integration of cancer-specific methylation and fragmentomic signatures could provide high accuracy for early-stage CRC detection.

A novel blood test for early detection of colorectal cancer. Colorectal cancer is a cancer of the colon or rectum, located at the lower end of the digestive tract. The early detection of colorectal cancer can help people with the disease have a higher chance of survival and a better quality of life. Current screening methods can be invasive, cause discomfort or have low accuracy; therefore newer screening methods are needed. In this study we developed a new screening method, called SPOT-MAS, which works by measuring the signals of cancer DNA in the blood. By combining different characteristics of cancer DNA, SPOT-MAS could distinguish blood samples of people with colorectal cancer from those of healthy individuals with high accuracy.

Evaluation of a Liquid Biopsy Protocol using Ultra-Deep Massive Parallel Sequencing for Detecting and Quantifying Circulation Tumor DNA in Colorectal Cancer Patients.

The identification and quantification of actionable mutations are critical for guiding targeted therapy and monitoring drug response in colorectal cancer. Liquid biopsy (LB) based on plasma cell-free DNA analysis has emerged as a noninvasive approach with many clinical advantages over conventional tissue sampling. Here, we developed a LB protocol using ultra-deep massive parallel sequencing and validated its clinical performance for detection and quantification of actionable mutations in three major driver genes (KRAS, NRAS and BRAF). The assay showed a 92% concordance for mutation detection between plasma and paired tissues and great reliability in quantification of variant allele frequency.

The T cell receptor ß chain repertoire of tumor infiltrating lymphocytes improves neoantigen prediction and prioritization.

In the realm of cancer immunotherapy, the meticulous selection of neoantigens plays a fundamental role in enhancing personalized treatments. Traditionally, this selection process has heavily relied on predicting the binding of peptides to human leukocyte antigens (pHLA). Nevertheless, this approach often overlooks the dynamic interaction between tumor cells and the immune system. In response to this limitation, we have developed an innovative prediction algorithm rooted in machine learning, integrating T cell receptor ß chain (TCRß) profiling data from colorectal cancer (CRC) patients for a more precise neoantigen prioritization. TCRß sequencing was conducted to profile the TCR repertoire of tumor-infiltrating lymphocytes (TILs) from 28 CRC patients. The data unveiled both intra-tumor and inter-patient heterogeneity in the TCRß repertoires of CRC patients, likely resulting from the stochastic utilization of V and J segments in response to neoantigens. Our novel combined model integrates pHLA binding information with pHLA-TCR binding to prioritize neoantigens, resulting in heightened specificity and sensitivity compared to models using individual features alone. The efficacy of our proposed model was corroborated through ELISpot assays on long peptides, performed on four CRC patients. These assays demonstrated that neoantigen candidates prioritized by our combined model outperformed predictions made by the established tool NetMHCpan. This comprehensive assessment underscores the significance of integrating pHLA binding with pHLA-TCR binding analysis for more effective immunotherapeutic strategies.

Prevalence and genetic spectrum associated with hereditary colorectal cancer syndromes, the need to improve cancer risk awareness, and family cascade testing in Vietnam.

In Vietnam, colorectal cancer is one of the top diagnosed cancers, with 5-10% originating from inherited mutations. This study aims to define the mutation spectrum associated with hereditary colorectal cancer syndromes (HCCS) in Vietnam, evaluate the influence of genetic testing on carriers' awareness, and also investigate the barriers in familial testing. Genetic test reports were collected to identify HCCS cases, then cases underwent a survey investigating self-risk and familial-risk awareness, proactive cancer screening, and familial testing barriers. Participant characteristics, mutation prevalence, and results from the survey were descriptively analyzed and reported. Of all genetic test results, 3% (49/1632) were identified with mutations related to HCCS. Over 77% of them belonged to Lynch syndrome. PMS2 appeared to be the gene with the highest mutation frequency, while MLH1 was the lowest. 44% of cases further undertook cancer screening tests, and 48% of cases' families had uptake genetic testing. The biggest barrier of familial members for not taking genetic test was psychological reasons (fear, not being interested, or not feeling necessary). This study provided new evidence for HCCS mutation spectrum in Vietnamese population and the success in promoting cascade test in high-risk family members through financial and technical support. Also, study has suggested the needs of an innovative genetic testing process focusing on the quality of pre-and post-test consultancy, an increase in follow-ups, and the change in policy for permission of contacting relatives directly to improve the rate of cascade testing and proactive cancer screening.

Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling.

Introduction: Neoantigen-based immunotherapy has emerged as a promising strategy for improving the life expectancy of cancer patients. This therapeutic approach heavily relies on accurate identification of cancer mutations using DNA sequencing (DNAseq) data. However, current workflows tend to provide a large number of neoantigen candidates, of which only a limited number elicit efficient and immunogenic T-cell responses suitable for downstream clinical evaluation. To overcome this limitation and increase the number of high-quality immunogenic neoantigens, we propose integrating RNA sequencing (RNAseq) data into the mutation identification step in the neoantigen prediction workflow. Methods: In this study, we characterize the mutation profiles identified from DNAseq and/or RNAseq data in tumor tissues of 25 patients with colorectal cancer (CRC). Immunogenicity was then validated by ELISpot assay using long synthesis peptides (sLP). Results: We detected only 22.4% of variants shared between the two methods. In contrast, RNAseq-derived variants displayed unique features of affinity and immunogenicity. We further established that neoantigen candidates identified by RNAseq data significantly increased the number of highly immunogenic neoantigens (confirmed by ELISpot) that would otherwise be overlooked if relying solely on DNAseq data. Discussion: This integrative approach holds great potential for improving the selection of neoantigens for personalized cancer immunotherapy, ultimately leading to enhanced treatment outcomes and improved survival rates for cancer patients.

Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.