Multi-Institutional Evaluation of Interrater Agreement of Variant Classification Based on the 2017 Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer

Evolutionary history of adenomas to colorectal cancer in FAP families

Objective

Familial adenomatous polyposis (FAP) is a genetic syndrome characterized by multiple polyps at various evolutionary stages, which, if left untreated, inevitably progress to colorectal cancer (CRC). In this study, we present a comprehensive analysis of the evolutionary history of FAP-CRC from precancerous adenoma to carcinoma.

Design

Tissues were collected from gastrointestinal endoscopy or surgical resection. Exome sequencing was performed on multiple regions of adenocarcinoma (n = 8), villous adenoma (n = 10), tubular adenoma (n = 9) and blood samples were obtained from 9 patients belonging to 7 Chinese FAP families. Phylogenetic trees were reconstructed, and evolutionary analysis was conducted to reveal the temporal sequence of events leading to CRC.

Results

Inherited germline mutation sites in APC gene were identified in FAP01 (p.S1281*, COSM19212), FAP03 (p.S384Tfs*19), FAP04 (p.E1538*, COSM6041693), FAP05 (p.Q1062*, COSM3696862), and FAP07-FAP09 (p.V677Sfs*3). Notably, p.V677Sfs*3 mutation was recognized as a novel germline mutation in APC, supported by evidence of genotype-phenotype correlation in pedigree analysis. Adenomas exhibited lower mutational rates than FAP-CRC and displayed recurrent alterations in well-known chromosomal instability (CIN) genes (APC, RAS, SMAD4 and TP53) and DNA damage repair genes (SUZ12, KMT2C, BCLAF1, RUNX1, and ARID1B), suggesting the presence of genomic instability. Furthermore, a progressive increase in the HRD score (a measure of "genomic scars") was observed from tubular adenomas to villous adenomas and ultimately to carcinomas. TP53 emerged as the primary driver gene for adenoma-carcinoma transition, with driver mutations consistently appearing simultaneously rather than sequentially acquired from adenomas to carcinomas. Clonal evolution demonstrated that liver metastases can originate from the same cancer-primed cell present in a primary cancerous lesion.

Conclusion

We identified a novel pathogenic variant in APC, namely, p.V677Sfs*3. The process of carcinogenesis in FAP-CRC supports the classical cancerization model, where an initial APC mutation leads to the activation of the WNT signaling pathway and CIN. Subsequently, additional mutations occur in other putative CIN genes (e.g., DNA repair, chromatin remodeling), ultimately leading to the development of microsatellite stable (MSS) tumors. Our study provides a comprehensive understanding of the genomic landscapes that underlie the transition from adenoma to carcinoma.

Clinicopathological and molecular characterization of resected lung adenocarcinoma: Correlations with histopathological grading systems in Chinese patients

PURPOSE

Driver mutations inform lung adenocarcinoma (LUAD) targeted therapy. Association of histopathological attributes and molecular profiles facilitates clinically viable testing platforms. We assessed correlations between LUAD clinicopathological features, mutational landscapes, and two grading systems among Chinese cases.

METHODS

79 Chinese LUAD patients undergoing resection were subjected to targeted sequencing. 68 were invasive nonmucinous adenocarcinoma (INMA), graded via: predominant histologic pattern-based grading system (P-GS) or novel IASLC grading system (I-GS). Driver mutation distributions were appraised and correlated with clinical and pathological data.

RESULTS

Compared to INMA, non-INMA exhibited smaller, well-differentiated tumors with higher mucin content. INMA grade correlated with size, lymph invasion (P-GS), and driver/EGFR mutations. Mutational spectra varied markedly between grades, with EGFR p.L858R and exon 19 deletion mutations predominating in lower grades; while high-grade P-GS tumors often harbored EGFR copy number variants and complex alterations alongside wild-type cases. I-GS upgrade of P-GS grade 2 to grade 3 was underpinned by ≥20 % high-grade regions bearing p.L858R or ALK fusions. Both systems defined tumors of distinctive phenotypic attributes and molecular genotypes.

CONCLUSIONS

INMA represent larger, mucin-poor, molecularly heterogeneous LUAD with divergent grade-specific mutation profiles. Stronger predictor of clinicopathological attributes and driver mutations, P-GS stratification offers greater accuracy for molecular testing. A small panel encompassing EGFR and ALK captures the majority of P-GS grade 1/2 mutations whereas expanded panels are optimal for grade 3.

Current and Emerging Diagnostic, Prognostic, and Predictive Biomarkers in Head and Neck Cancer

Head and neck cancers (HNC) are a biologically diverse set of cancers that are responsible for over 660,000 new diagnoses each year. Current therapies for HNC require a comprehensive, multimodal approach encompassing resection, radiation therapy, and systemic therapy. With an increased understanding of the mechanisms behind HNC, there has been growing interest in more accurate prognostic indicators of disease, effective post-treatment surveillance, and individualized treatments. This chapter will highlight the commonly used and studied biomarkers in head and neck squamous cell carcinoma.

Assessments of Somatic Variant Classification Using the Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists Guidelines: A Report from the Association for Molecular Pathology

To assess the clinical implementation of the 2017 Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists, identify content that may result in classification inconsistencies, and evaluate implementation barriers, an Association for Molecular Pathology Working Group conducted variant interpretation challenges and a guideline implementation survey. A total of 134 participants participated in the variant interpretation challenges, consisting of 11 variants in four cancer cases. Results demonstrate 86% (range, 54% to 94%) of the respondents correctly classified clinically significant variants, variants of uncertain significance, and benign/likely benign variants; however, only 59% (range, 39% to 84%) of responses agreed with the working group's consensus intended responses regarding both tiers and categories of clinical significance. In the implementation survey, 71% (157/220) of respondents have implemented the 2017 guidelines for variant classification and reporting either with or without modifications. Collectively, this study demonstrates that, although they may not yet be optimized, the 2017 guideline recommendations are being adopted for standardized somatic variant classification. The working group identified significant areas for future guideline improvement, including the need for a more granular and comprehensive classification system and education resources to meet the growing needs of both laboratory professionals and medical oncologists.

Deriving tumor purity from cancer next generation sequencing data: applications for quantitative ERBB2 (HER2) copy number analysis and germline inference of BRCA1 and BRCA2 mutations

Tumor purity, or the relative contribution of tumor cells out of all cells in a pathological specimen, influences mutation identification and clinical interpretation of cancer panel next generation sequencing results. Here, we describe a method of calculating tumor purity using pathologist-guided copy number analysis from sequencing data. Molecular calculation of tumor purity showed strong linear correlation with purity derived from driver KRAS or BRAF variant allele fractions in colorectal cancers (R² = 0.79) compared to histological estimation in the same set of colorectal cancers (R² = 0.01) and in a broader dataset of cancers with various diagnoses (R² = 0.35). We used calculated tumor purity to quantitate ERBB2 copy number in breast carcinomas with equivocal immunohistochemical staining and demonstrated strong correlation with fluorescence in situ hybridization (R² = 0.88). Finally, we used calculated tumor purity to infer the germline status of variants in breast and ovarian carcinomas with concurrent germline testing. Tumor-only next generation sequencing correctly predicted the somatic versus germline nature of 26 of 26 (100%) pathogenic TP53, BRCA1 and BRCA2 variants. In this article, we describe a framework for calculating tumor purity from cancer next generation sequencing data. Accurate tumor purity assessment can be assimilated into interpretation pipelines to derive clinically useful information from cancer genomic panels.

An Independent Assessment of a Commercial Clinical Interpretation Software Indicates That Software Can Mitigate Variation in Human Assessment

Comprehensive next-generation sequencing (NGS) panels for cancer diagnostics create a bottleneck for interpretation. QIAGEN Clinical Insights Interpret One (QCI) is a clinical decision support software that supports molecular pathologists in the classification of oncology-related variants. This study compares variant assessments by QCI to assessments utilizing current laboratory methods. Eight laboratories were recruited by the external quality assessment organization GenQA. The laboratories submitted VCFs from sequencing studies performed on both hematological disorders and solid tumors for analysis by QCI and an independent laboratory. Results were compared and conflicts were resolved using a panel of experts. In total, 14/149 variants (9%) reported as Tier 1 or Tier 2 by either QCI or the submitting laboratory were found to be discordant after expert panel review. In contrast, 41/149 variants (28%) reflected discrepancy among human reviewers. The expert panel was unable to reach resolution on eight variants. QCI demonstrates high concordance in the classification of actionable mutations with independent laboratory methods and expert assessment. The rate of disagreement among laboratories and the expert panel was greater than the disagreement between QCI and expert assessment. Disagreement among experts highlights the subjectivity of classifying variants. The study demonstrates that QCI interpretation supports streamlining and standardization of NGS variant interpretation.

CancerVar: An artificial intelligence-empowered platform for clinical interpretation of somatic mutations in cancer

Several knowledgebases are manually curated to support clinical interpretations of thousands of hotspot somatic mutations in cancer. However, discrepancies or even conflicting interpretations are observed among these databases. Furthermore, many previously undocumented mutations may have clinical or functional impacts on cancer but are not systematically interpreted by existing knowledgebases. To address these challenges, we developed CancerVar to facilitate automated and standardized interpretations for 13 million somatic mutations based on the AMP/ASCO/CAP 2017 guidelines. We further introduced a deep learning framework to predict oncogenicity for these variants using both functional and clinical features. CancerVar achieved satisfactory performance when compared to several independent knowledgebases and, using clinically curated datasets, demonstrated practical utility in classifying somatic variants. In summary, by integrating clinical guidelines with a deep learning framework, CancerVar facilitates clinical interpretation of somatic variants, reduces manual work, improves consistency in variant classification, and promotes implementation of the guidelines.

Guiding the global evolution of cytogenetic testing for hematologic malignancies

Cytogenetics has long represented a critical component in the clinical evaluation of hematologic malignancies. Chromosome banding studies provide a simultaneous snapshot of genome-wide copy number and structural variation, which have been shown to drive tumorigenesis, define diseases, and guide treatment. Technological innovations in sequencing have ushered in our present-day clinical genomics era. With recent publications highlighting novel sequencing technologies as alternatives to conventional cytogenetic approaches, we, an international consortium of laboratory geneticists, pathologists, and oncologists, describe herein the advantages and limitations of both conventional chromosome banding and novel sequencing technologies and share our considerations on crucial next steps to implement these novel technologies in the global clinical setting for a more accurate cytogenetic evaluation, which may provide improved diagnosis and treatment management. Considering the clinical, logistic, technical, and financial implications, we provide points to consider for the global evolution of cytogenetic testing.

Tiered Somatic Variant Classification Adoption Has Increased Worldwide With Some Practice Differences Based on Location and Institutional Setting

CONTEXT.—

The 2017 Association for Molecular Pathology/American Society of Clinical Oncology/College of American Pathologists (CAP) tier classification guideline provides a framework to standardize interpretation and reporting of somatic variants.

OBJECTIVE.—

To evaluate the adoption and performance of the 2017 guideline among laboratories performing somatic next-generation sequencing (NGS).

DESIGN.—

A survey was distributed to laboratories participating in NGS CAP proficiency testing for solid tumors (NGSST) and hematologic malignancies (NGSHM).

RESULTS.—

Worldwide, 64.4% (152 of 236) of NGSST and 66.4% (87 of 131) of NGSHM participants used tier classification systems, of which the 2017 guideline was used by 84.9% (129 of 152) of NGSST and 73.6% (64 of 87) of NGSHM participants. The 2017 guideline was modified by 24.4% (30 of 123) of NGSST and 21.7% (13 of 60) of NGSHM laboratories. Laboratories implementing the 2017 guideline were satisfied or very satisfied (74.2% [89 of 120] NGSST and 69.5% [41 of 59] NGSHM), and the impression of tier classification reproducibility was high (mean of 3.9 [NGSST] and 3.6 [NGSHM] on a 5-point scale). Of nonusers, 35.2% (38 of 108) of NGSST and 39.4% (26 of 66) of NGSHM laboratories were planning implementation. For future guideline revisions, respondents favored including variants to monitor disease (63.9% [78 of 122] NGSST, 80.0% [48 of 60] NGSHM) and germline variants (55.3% [63 of 114] NGSST, 75.0% [45 of 60] NGSHM). Additional subtiers were not favored by academic laboratories compared to nonacademic laboratories (P < .001 NGSST and P = .02 NGSHM).

CONCLUSIONS.—

The 2017 guideline has been implemented by more than 50.0% of CAP laboratories. While most laboratories using the 2017 guideline report satisfaction, thoughtful guideline modifications may further enhance the quality, reproducibility, and clinical utility of the 2017 guideline for tiered somatic variant classification.

From Information Overload to Actionable Insights: Digital Solutions for Interpreting Cancer Variants from Genomic Testing

Given the increase in genomic testing in routine clinical use, there is a growing need for digital technology solutions to assist pathologists, oncologists, and researchers in translating variant calls into actionable knowledge to personalize patient management plans. In this article, we discuss the challenges facing molecular geneticists and medical oncologists in working with test results from next-generation sequencing for somatic oncology, and propose key considerations for implementing a decision support software to aid the interpretation of clinically important variants. In addition, we review results from an example decision support software, NAVIFY Mutation Profiler. NAVIFY Mutation Profiler is a cloud-based software that provides curation, annotation, interpretation, and reporting of somatic variants identified by next-generation sequencing. The software reports a tiered classification based on consensus recommendations from AMP, ASCO, CAP, and ACMG. Studies with NAVIFY Mutation Profiler demonstrated that the software provided timely updates and accurate curation, as well as interpretation of variant combinations, demonstrating that decision support tools can help advance implementation of precision oncology.