Dataset Information

Patterns of Somatic Variants in Colorectal Adenoma and Carcinoma Tissue and Matched Plasma Samples from the Hungarian Oncogenome Program.

ABSTRACT: Analysis of circulating cell-free DNA (cfDNA) of colorectal adenoma (AD) and cancer (CRC) patients provides a minimally invasive approach that is able to explore genetic alterations. It is unknown whether there are specific genetic variants that could explain the high prevalence of CRC in Hungary. Whole-exome sequencing (WES) was performed on colon tissues (27 AD, 51 CRC) and matched cfDNAs (17 AD, 33 CRC); furthermore, targeted panel sequencing was performed on a subset of cfDNA samples. The most frequently mutated genes were APC, KRAS, and FBN3 in AD, while APC, TP53, TTN, and KRAS were the most frequently mutated in CRC tissue. Variants in KRAS codons 12 (AD: 8/27, CRC: 11/51 (0.216)) and 13 (CRC: 3/51 (0.06)) were the most frequent in our sample set, with G12V (5/27) dominance in ADs and G12D (5/51 (0.098)) in CRCs. In terms of the cfDNA WES results, tumor somatic variants were found in 6/33 of CRC cases. Panel sequencing revealed somatic variants in 8 out of the 12 enrolled patients, identifying 12/20 tumor somatic variants falling on its targeted regions, while WES recovered only 20% in the respective regions in cfDNA of the same patients. In liquid biopsy analyses, WES is less efficient compared to the targeted panel sequencing with a higher coverage depth that can hold a relevant clinical potential to be applied in everyday practice in the future.

SUBMITTER: Kalmar A

PROVIDER: S-EPMC9913259 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Patterns of Somatic Variants in Colorectal Adenoma and Carcinoma Tissue and Matched Plasma Samples from the Hungarian Oncogenome Program.

Kalmár Alexandra A Galamb Orsolya O Szabó Gitta G Pipek Orsolya O Medgyes-Horváth Anna A Barták Barbara K BK Nagy Zsófia B ZB Szigeti Krisztina A KA Zsigrai Sára S Csabai István I Igaz Péter P Molnár Béla B Takács István I

Cancers 20230131 3

Analysis of circulating cell-free DNA (cfDNA) of colorectal adenoma (AD) and cancer (CRC) patients provides a minimally invasive approach that is able to explore genetic alterations. It is unknown whether there are specific genetic variants that could explain the high prevalence of CRC in Hungary. Whole-exome sequencing (WES) was performed on colon tissues (27 AD, 51 CRC) and matched cfDNAs (17 AD, 33 CRC); furthermore, targeted panel sequencing was performed on a subset of cfDNA samples. The mo ...[more]

PMID: 36765865

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Project description:Genetic testing to detect somatic alterations is usually performed on formalin-fixed paraffin-embedded tumor samples. However, tumor molecular profiling through ctDNA analysis may be particularly interesting with the emergence of targeted therapies for ovarian cancer (OC), mainly when tumor is not available and biopsy is not viable, also allowing representation of multiple neoplastic subclones. Using a custom panel of 27 genes, next-generation sequencing (NGS) was performed on tumor and matched plasma samples from 96 OC patients, which were combined in two groups (treatment naive and post-treatment). Overall, at least one somatic variant present in the tumor sample was also detected in the matched plasma sample in 35.6% of the patients, a percentage that increased to 69.6% of the treatment naive patients and 83.3% of those with stage IV disease, showing the potential of ctDNA analysis as an alternative to identify somatic variants in these patients, namely those that have predictive value for targeted therapy. In fact, of the two treatment-naive patients with somatic BRCA1 variants identified in tumor samples, in one of them we detected in ctDNA a BRCA1 somatic variant that was present in the tumor with a VAF of 53%, but not in the one that had a VAF of 5.4%. We also showed that ctDNA analysis has a complementary role to molecular unraveling of inter- and intra-tumor heterogeneity, as exemplified by one patient diagnosed with bilateral OC in which different somatic variants from both tumors were detected in ctDNA. Interestingly, as these bilateral tumors shared a rare combination of two of the three variants identified in ctDNA, we could conclude that these morphologically different tumors were clonally related and not synchronous independent neoplasias. Moreover, in the post-treatment group of patients with plasma samples collected after surgery, those with detectable somatic variants had poor prognosis when compared with patients with no detectable somatic variants, highlighting the potential of ctDNA analysis to identify patients at higher risk of recurrence. Concluding, this study demonstrated that somatic variants can be detected in plasma samples of a significant proportion of OC patients, supporting the use of NGS-based ctDNA testing for noninvasive tumor molecular profiling and to stratify patients according to prognosis.

Project description:Somatic variants play a crucial role in the occurrence and progression of cancer. However, in the absence of matched normal controls, distinguishing between germline and somatic variants becomes challenging in tumor samples. The existing tumor-only genomic analysis methods either suffer from limited performance or insufficient interpretability due to an excess of features. Therefore, there is an urgent need for an alternative approach that can address these issues and have practical implications. Here, we presented OncoTOP, a computational method for genomic analysis without matched normal samples, which can accurately distinguish somatic mutations from germline variants. Reference sample analysis revealed a 0% false positive rate and 99.7% reproducibility for variant calling. Assessing 2864 tumor samples across 18 cancer types yielded a 99.8% overall positive percent agreement and a 99.9% positive predictive value. OncoTOP can also accurately detect clinically actionable variants and subclonal mutations associated with drug resistance. For the prediction of mutation origins, the positive percent agreement stood at 97.4% for predicting somatic mutations and 95.7% for germline mutations. High consistency of tumor mutational burden (TMB) was observed between the results generated by OncoTOP and tumor-normal paired analysis. In a cohort of 97 lung cancer patients treated with immunotherapy, TMB-high patients had prolonged PFS (P = .02), proving the reliability of our approach in estimating TMB to predict therapy response. Furthermore, microsatellite instability status showed a strong concordance (97%) with polymerase chain reaction results, and leukocyte antigens class I subtypes and homozygosity achieved an impressive concordance rate of 99.3% and 99.9% respectively, compared to its tumor-normal paired analysis. Thus, OncoTOP exhibited high reliability in variant calling, mutation origin prediction, and biomarker estimation. Its application will promise substantial advantages for clinical genomic testing.

Project description:BackgroundObservations of recurrent somatic mutations in tumors have led to identification and definition of signaling and other pathways that are important for cancer progression and therapeutic targeting. As tumor cells contain both an individual's inherited genetic variants and somatic mutations, challenges arise in distinguishing these events in massively parallel sequencing datasets. Typically, both a tumor sample and a "normal" sample from the same individual are sequenced and compared; variants observed only in the tumor are considered to be somatic mutations. However, this approach requires two samples for each individual.ResultsWe evaluate a method of detecting somatic mutations in tumor samples for which only a subset of normal samples are available. We describe tuning of the method for detection of mutations in tumors, filtering to remove inherited variants, and comparison of detected mutations to several matched tumor/normal analysis methods. Filtering steps include the use of population variation datasets to remove inherited variants as well a subset of normal samples to remove technical artifacts. We then directly compare mutation detection with tumor-only and tumor-normal approaches using the same sets of samples. Comparisons are performed using an internal targeted gene sequencing dataset (n = 3380) as well as whole exome sequencing data from The Cancer Genome Atlas project (n = 250). Tumor-only mutation detection shows similar recall (43-60%) but lesser precision (20-21%) to current matched tumor/normal approaches (recall 43-73%, precision 30-82%) when compared to a "gold-standard" tumor/normal approach. The inclusion of a small pool of normal samples improves precision, although many variants are still uniquely detected in the tumor-only analysis.ConclusionsA detailed method for somatic mutation detection without matched normal samples enables study of larger numbers of tumor samples, as well as tumor samples for which a matched normal is not available. As sensitivity/recall is similar to tumor/normal mutation detection but precision is lower, tumor-only detection is more appropriate for classification of samples based on known mutations. Although matched tumor-normal analysis is preferred due to higher precision, we demonstrate that mutation detection without matched normal samples is possible for certain applications.

Dataset Information

Patterns of Somatic Variants in Colorectal Adenoma and Carcinoma Tissue and Matched Plasma Samples from the Hungarian Oncogenome Program.

Publications

Patterns of Somatic Variants in Colorectal Adenoma and Carcinoma Tissue and Matched Plasma Samples from the Hungarian Oncogenome Program.

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