Benchmarking of Whole Exome Sequencing and Ad Hoc Designed Panels for Genetic Testing of Hereditary Cancer

Spatial Mapping of Gene Signatures in Hematoxylin and Eosin-Stained Images: A Proof of Concept for Interpretable Predictions Using Additive Multiple Instance Learning

The relative abundance of cancer-associated fibroblast (CAF) subtypes influences a tumor's response to treatment, especially immunotherapy. However, the gene expression signatures associated with these CAF subtypes have yet to realize their potential as clinical biomarkers. Here, we describe an interpretable machine learning approach, additive multiple instance learning (aMIL), to predict bulk gene expression signatures from hematoxylin and eosin-stained whole-slide images, focusing on an immunosuppressive LRRC15+ CAF-enriched TGFβ-CAF signature. aMIL models accurately predicted TGFβ-CAF across various cancer types. Tissue regions contributing most highly to slide-level predictions of TGFβ-CAF were evaluated by machine learning models characterizing spatial distributions of diverse cell and tissue types, stromal subtypes, and nuclear morphology. In breast cancer, regions contributing most to TGFβ-CAF-high predictions ("excitatory") were localized to cancer stroma with high fibroblast density and mature collagen fibers. Regions contributing most to TGFβ-CAF-low predictions ("inhibitory") were localized to cancer epithelium and densely inflamed stroma. Fibroblast and lymphocyte nuclear morphology also differed between excitatory and inhibitory regions. Thus, aMIL enables a data-driven link between histologic features and transcription, offering biological interpretability beyond typical black-box models.

Novel MSH6 exon 5-6 skipping variant in a Taiwanese family with Lynch syndrome: implications for genetic testing and cancer management

Lynch syndrome is an autosomal dominant disorder predisposing individuals to colorectal and other cancers, primarily caused by variants in mismatch repair genes. This study describes a novel MSH6 variant affecting transcript structure in a Taiwanese family meeting the Amsterdam II criteria for Lynch syndrome. A 67-year-old male presented with jejunal adenocarcinoma and a strong family history of colorectal cancer. Immunohistochemistry revealed loss of MSH6 expression, while next-generation sequencing performed on tumor tissue failed to detect any MSH6 variants. Comprehensive genetic analysis, including RT-PCR and Sanger sequencing of both cDNA and genomic DNA, identified a novel exon 5-6 skipping variant in the MSH6 gene transcript (NM_000179.3:r.3262_3645del), linked to a 2268 bp deletion from the 3' portion of intron 4 to the middle of intron 6 of the MSH6 gene (NC_000002.12:g.47803007_47805274del). This variant was also detected in two of the patient's asymptomatic sons, highlighting its heritability and potential cancer predisposition. The study emphasizes the limitations of capture-enrichment NGS panels in detecting certain types of variants and underscores the value of orthogonal confirmation using cDNA analysis for transcript aberrations. The identification of this novel variant expands our understanding of Lynch syndrome's mutational spectrum and has implications for genetic diagnosis and counseling. Based on these findings, the patient was treated with pembrolizumab, resulting in stable disease for 8 months. This case highlights the importance of comprehensive genetic approaches in suspected Lynch syndrome cases and the potential utility of mRNA-based screening as an additional method when NGS analysis is negative and the clinical presentation strongly suggests Lynch syndrome.

The challenges and opportunities of applying tumour mutational burden analysis to precision cancer medicine

The discovery and development of immune checkpoint inhibitors (ICIs) has revolutionised the management of human cancers. However, only a subset of patients responds to ICI therapy, even though immune evasion is a hallmark of cancer. Initially, treatment was administered to patients on the basis of expression levels of one of the targets of ICI therapy, programmed cell death ligand 1. In clinical trials, the high response rate of melanoma and non-small cell lung cancer patients to ICI therapy supported the basic premise of cancer immunotherapy, that tumour-specific mutated proteins trigger an immune response. Tumour mutational burden subsequently emerged as a potential biomarker for response to ICI therapy. This review summarises the evidence supporting the scientific rationale for TMB as a biomarker for ICI therapy and focuses on some of the major challenges associated with incorporation of TMB into routine clinical practice.

Germline Variants in DNA Interstrand-Cross Link Repair Genes May Contribute to Increased Susceptibility for Serrated Polyposis Syndrome

Serrated polyposis syndrome (SPS) is characterized by the development of multiple colorectal serrated polyps and increased predisposition to colorectal cancer (CRC). However, the molecular basis of SPS, especially in cases presenting family history of SPS and/or polyps and/or CRC in first-degree relatives (SPS-FHP/CRC), is still poorly understood. In a previous study, we proposed the existence of two molecular entities amongst SPS-FHP/CRC families, proximal/whole-colon and distal SPS-FHP/CRC, according to the preferential location of lesions and somatic events involved in tumor initiation. In the present study, we aimed to investigate these distinct subgroups of SPS patients in a larger cohort at the germline level and to identify the genetic defects underlying an inherited susceptibility for these two entities. Next-generation sequencing was performed using multigene analysis with a custom-designed panel in a Miseq platform in 60 SPS patients (with and without/unknown FHP/CRC). We found germline pathogenic variants in 6/60 patients (ATM, FANCM, MITF, RAD50, RAD51C, and RNF43). We also found variants of unknown significance (VUS), with prediction of probable damaging effect in 23/60 patients (ATM, BLM, BRCA1, FAN1, ERCC2, ERCC3, FANCA, FANCD2, FANCL, MSH2, MSH6, NTHL1, PALB2, PDGFRA, PMS2, PTCH1, RAD51C, RAD51D, RECQL4, TSC2, WRN, and XRCC5 genes). Most variants were detected in gene coding for proteins of the Fanconi Anemia (FA) pathway involved in the DNA Interstrand-Cross Link repair (ICLR). Notably, variants in ICLR genes were significantly more frequent in the proximal/whole-colon than in the distal subgroup [15/44 (34%) vs 1/16 (6%), p = 0.025], as opposed to the non-ICLR genes that were slightly more frequent in the distal group [8/44 (18%) vs. 5/16 (31%), p > 0.05]. Germline defects in the DNA-ICLR genes may contribute to increased serrated colorectal polyps/carcinoma risk in SPS patients, particularly in proximal/whole-colon SPS. The inclusion of DNA-ICLR genes in the genetic diagnosis of SPS patients, mainly in those with proximal/whole-colon lesions, should be considered and validated by other studies. In addition, patients with germline defects in the DNA-ICLR genes may be more sensitive to treatment with platinum-based therapeutics, which can have implications in the clinical management of these patients.

How to Keep Up With Molecular Testing and Targeted Therapies in Lung Cancer

Until the early 2000s, advanced or metastatic non-small cell lung cancer (NSCLC) was treated as a single disease with all histologic subtypes treated alike with standard chemotherapy agents. Over the past two decades, the treatment paradigms for advanced NSCLC have changed dramatically with the discovery of multiple targeted therapies that are now approved for the treatment of NSCLC tumors with specific oncogene drivers or molecular alterations. Molecular testing has become integrated and critical for the clinical management of advanced NSCLC. The discovery and success of these targeted therapies have reshaped the classification of NSCLC on the basis of molecular classification and enabled a personalized approach in thoracic oncology. In this review, we discuss recent developments in the molecular profiling of NSCLC, and approved and emerging targeted therapies for the treatment of NSCLC.

Comparing the Diagnostic Yield of Germline Exome Versus Panel Sequencing in the Diverse Population of the Texas KidsCanSeq Pediatric Cancer Study

PURPOSE

To evaluate the relative diagnostic yield of clinical germline genomic tests in a diverse pediatric cancer population.

PATIENTS AND METHODS

The KidsCanSeq study enrolled pediatric cancer patients across six sites in Texas. Germline analysis included both exome sequencing and a therapy-focused pediatric cancer gene panel. The results were categorized by participants demographics, the presence of pathogenic or likely pathogenic (P/LP) variants, and variants of uncertain significance (VUS) in cancer predisposition genes (CPGs). Pediatric actionable CPGs were defined as those with cancer surveillance recommendations during childhood.

RESULTS

Cancer P/LP variants were reported by at least one platform in 103 of 578 (17.8%) participants of which 76 were dominant cancer genes (13.1%) with no significant differences by self-described race or Hispanic ethnicity. However, the proportion of participants with VUS was greater in Asian and African American participants (P = .0029). Diagnostic yield was 16.6% for exome versus 8.5% for panel (P < .0001) with 42 participants with concordant germline results. Exome-only results included P/LP variants in 30 different CPGs in 54 participants, whereas panel-only results included seven participants with a copy number or structural P/LP variants in CPGs. There was no significant difference in diagnostic yield limited to pediatric actionable CPGs (P = .6171).

CONCLUSION

Approximately 18% of a diverse pediatric cancer population had germline diagnostic findings with 50% of P/LP variants reported by only one platform because of CPGs not on the targeted panel and copy number variants (CNVs)/rearrangements not reported by exome. Although diagnostic yields were similar in this diverse population, increases in VUS results were observed in Asian and African American populations. Given the clinical significance of CNVs/rearrangements in this cohort, detection is critical to optimize germline analysis of pediatric cancer populations.

Germline Sequencing of DNA Damage Repair Genes in Two Hereditary Prostate Cancer Cohorts Reveals New Disease Risk-Associated Gene Variants

Rare, inherited variants in DNA damage repair (DDR) genes have a recognised role in prostate cancer (PrCa) susceptibility. In addition, these genes are therapeutically targetable. While rare variants are informing clinical management in other common cancers, defining the rare disease-associated variants in PrCa has been challenging. Here, whole-genome and -exome sequencing data from two independent, high-risk Australian and North American familial PrCa datasets were interrogated for novel DDR risk variants. Rare DDR gene variants (predicted to be damaging and present in two or more family members) were identified and subsequently genotyped in 1963 individuals (700 familial and 459 sporadic PrCa cases, 482 unaffected relatives, and 322 screened controls), and association analyses accounting for relatedness (MQLS) undertaken. In the combined datasets, rare ERCC3 (rs145201970, p = 2.57 × 10-4) and BRIP1 (rs4988345, p = 0.025) variants were significantly associated with PrCa risk. A PARP2 (rs200603922, p = 0.028) variant in the Australian dataset and a MUTYH (rs36053993, p = 0.031) variant in the North American dataset were also associated with risk. Evaluation of clinicopathological characteristics provided no evidence for a younger age or higher-grade disease at diagnosis in variant carriers, which should be taken into consideration when determining genetic screening eligibility criteria for targeted, gene-based treatments in the future. This study adds valuable knowledge to our understanding of PrCa-associated DDR genes, which will underpin effective clinical screening and treatment strategies.

Tumor mutational burden predicts the efficacy of pembrolizumab monotherapy: a pan-tumor retrospective analysis of participants with advanced solid tumors

BACKGROUND

Several studies have evaluated the relationship between tumor mutational burden (TMB) and outcomes of immune checkpoint inhibitors. In the phase II KEYNOTE-158 study of pembrolizumab monotherapy for previously treated recurrent or metastatic cancer, high TMB as assessed by the FoundationOne CDx was associated with an improved objective response rate (ORR).

METHODS

We retrospectively assessed the relationship between TMB and efficacy in participants with previously treated advanced solid tumors enrolled in 12 trials that evaluated pembrolizumab monotherapy, including 3 randomized trials that compared pembrolizumab with chemotherapy. TMB was assessed in formalin-fixed, paraffin-embedded pretreatment tumor samples by whole-exome sequencing. High TMB was defined as ≥175 mutations/exome. Microsatellite instability (MSI) phenotype was based on whole-exome sequencing results. Programmed death ligand 1 (PD-L1) expression was assessed by immunohistochemistry. The primary end point was ORR assessed per RECIST V.1.1 by independent central review. Other end points included progression-free survival (PFS) assessed per RECIST V.1.1 by independent central review and overall survival (OS).

RESULTS

Of the 2234 participants in the analysis, 1772 received pembrolizumab monotherapy and 462 received chemotherapy. Among the pembrolizumab-treated participants, ORR was 31.4% (95% CI 27.1 to 36.0) in the 433 participants with TMB ≥175 mutations/exome and 9.5% (95% CI 8.0 to 11.2) in the 1339 participants with TMB <175 mutations/exome. The association of TMB with ORR was observed regardless of PD-L1 expression and not driven by specific tumor types or participants with very high TMB or high MSI. In the 3 randomized controlled trials, TMB was associated with ORR (p≤0.016), PFS (p≤0.005), and OS (p≤0.029) of pembrolizumab but not of chemotherapy (p≥0.340, p≥0.643, and p≥0.174, respectively), and pembrolizumab improved efficacy versus chemotherapy in participants with TMB ≥175 mutations/exome.

CONCLUSIONS

TMB ≥175 mutations/exome is associated with clinically meaningful improvement in the efficacy of pembrolizumab monotherapy and improved outcomes for pembrolizumab versus chemotherapy across a wide range of previously treated advanced solid tumor types. These data suggest TMB has broad clinical utility irrespective of tumor type, PD-L1 expression, or MSI status and support its use as a predictive biomarker for pembrolizumab monotherapy in participants with previously treated advanced solid tumors.

Digital pathology and artificial intelligence in translational medicine and clinical practice

Traditional pathology approaches have played an integral role in the delivery of diagnosis, semi-quantitative or qualitative assessment of protein expression, and classification of disease. Technological advances and the increased focus on precision medicine have recently paved the way for the development of digital pathology-based approaches for quantitative pathologic assessments, namely whole slide imaging and artificial intelligence (AI)-based solutions, allowing us to explore and extract information beyond human visual perception. Within the field of immuno-oncology, the application of such methodologies in drug development and translational research have created invaluable opportunities for deciphering complex pathophysiology and the discovery of novel biomarkers and drug targets. With an increasing number of treatment options available for any given disease, practitioners face the growing challenge of selecting the most appropriate treatment for each patient. The ever-increasing utilization of AI-based approaches substantially expands our understanding of the tumor microenvironment, with digital approaches to patient stratification and selection for diagnostic assays supporting the identification of the optimal treatment regimen based on patient profiles. This review provides an overview of the opportunities and limitations around implementing AI-based methods in biomarker discovery and patient selection and discusses how advances in digital pathology and AI should be considered in the current landscape of translational medicine, touching on challenges this technology may face if adopted in clinical settings. The traditional role of pathologists in delivering accurate diagnoses or assessing biomarkers for companion diagnostics may be enhanced in precision, reproducibility, and scale by AI-powered analysis tools.

A catalog of curated breast cancer genes

Purpose

Decades of research have identified multiple genetic variants associated with breast cancer etiology. However, there is no database that archives breast cancer genes and variants responsible for predisposition. We set out to build a dynamic repository of curated breast cancer genes.

Methods

A comprehensive literature search was performed in PubMed and Google Scholar, followed by data extraction and harmonization for downstream analysis.

Results

Using a subset of 345 studies, we cataloged 652 breast cancer-associated loci across the genome. A majority of these were present in the non-coding region (i.e., intergenic (101) and intronic (345)), whereas only 158 were located within an exon. Using the odds ratio, we identified 429 loci to increase the disease risk and 198 to confer protection against breast cancer, whereas 25 were identified to both increase disease risk and confer protection against breast cancer. Chromosomal ideogram analysis indicated that chromosomes 17 and 19 have the highest density of breast cancer loci. We manually annotated and collated breast cancer genes in which a previous association between rare-monogenic variant and breast cancer has been documented. Finally, network and functional enrichment analysis revealed that steroid metabolism and DNA repair pathways were predominant among breast cancer genes and variants.

Conclusions

We have built an online interactive catalog of curated breast cancer genes (https://cbcg.dk). This will expedite clinical diagnostics and support the ongoing efforts in managing breast cancer etiology. Moreover, the database will serve as an essential repository when designing new breast cancer multigene panels.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-021-06441-y.

The fellowship of the RING: BRCA1, its partner BARD1 and their liaison in DNA repair and cancer

The breast cancer type 1 susceptibility protein (BRCA1) and its partner - the BRCA1-associated RING domain protein 1 (BARD1) - are key players in a plethora of fundamental biological functions including, among others, DNA repair, replication fork protection, cell cycle progression, telomere maintenance, chromatin remodeling, apoptosis and tumor suppression. However, mutations in their encoding genes transform them into dangerous threats, and substantially increase the risk of developing cancer and other malignancies during the lifetime of the affected individuals. Understanding how BRCA1 and BARD1 perform their biological activities therefore not only provides a powerful mean to prevent such fatal occurrences but can also pave the way to the development of new targeted therapeutics. Thus, through this review work we aim at presenting the major efforts focused on the functional characterization and structural insights of BRCA1 and BARD1, per se and in combination with all their principal mediators and regulators, and on the multifaceted roles these proteins play in the maintenance of human genome integrity.

Next-generation sequencing of BRCA1 and BRCA2 genes in Moroccan prostate cancer patients with positive family history

Prostate cancer is the most common male cancer in Morocco. Although sporadic forms account for a large proportion of patients, familial forms of prostate cancer are observed in 20% of cases and about 5% are due to hereditary transmission. Indeed, germline mutations in BRCA1/2 genes have been associated with prostate cancer risk. However, the spectrum of these mutations was not investigated in Moroccan Prostate cancer patients. Thereby, the aim of this study was to characterize and to estimate the prevalence of germline BRCA1/2 mutations and large rearrangements in Moroccan patients with familial prostate cancer. The entire coding regions and intron/exon boundaries of BRCA1 and BRCA2 genes have been analyzed by next generation sequencing (NGS) in a total of 30 familial prostate cancer patients. Three pathogenic mutations were detected in four unrelated patients (13.3%). One BRCA1 mutation (c.1953_1956delGAAA) and two BRCA2 mutations (c.7234_7235insG and BRCA2ΔE12). In addition, sixty-three distinct polymorphisms and unclassified variants have been found. Early identification of germline BRCA1/2 mutations may be relevant for the management of Moroccan prostate cancer patients.

Pathologists at the Leading Edge of Optimizing the Tumor Tissue Journey for Diagnostic Accuracy and Molecular Testing

OBJECTIVES

Tumor biomarker analyses accompanying immuno-oncology therapies are coupled with a tumor tissue journey aiming to guide tissue procurement and allow for accurate diagnosis and delivery of test results. The engagement of pathologists in the tumor tissue journey is essential because they are able to link the preanalytic requirements of this process with pathologic evaluation and clinical information, ultimately influencing treatment decisions for patients with cancer. The aim of this review is to provide suggestions on how cancer diagnosis and the delivery of molecular test results may be optimized, based on the needs and available resources of institutions, by placing the tumor tissue journey under the leadership of pathologists.

METHODS

Literature searches on PubMed and personal experience provided the necessary material to satisfy the objectives of this review.

RESULTS

Pathologists are usually involved across many steps of the tumor tissue journey and have the requisite knowledge to ensure its efficiency.

CONCLUSIONS

The expansion of oncology diagnostic testing emphasizes the need for pathologists to acquire a leadership role in the multidisciplinary effort to optimize the accuracy, completeness, and delivery of diagnoses guiding personalized treatments.

BARD1 Pathogenic Variants are Associated with Triple-Negative Breast Cancer in a Spanish Hereditary Breast and Ovarian Cancer Cohort

Only a small fraction of hereditary breast and/or ovarian cancer (HBOC) cases are caused by germline variants in the high-penetrance breast cancer 1 and 2 genes (BRCA1 and BRCA2). BRCA1-associated ring domain 1 (BARD1), nuclear partner of BRCA1, has been suggested as a potential HBOC risk gene, although its prevalence and penetrance are variable according to populations and type of tumor. We aimed to investigate the prevalence of BARD1 truncating variants in a cohort of patients with clinical suspicion of HBOC. A comprehensive BARD1 screening by multigene panel analysis was performed in 4015 unrelated patients according to our regional guidelines for genetic testing in hereditary cancer. In addition, 51,202 Genome Aggregation Database (gnomAD) non-Finnish, non-cancer European individuals were used as a control population. In our patient cohort, we identified 19 patients with heterozygous BARD1 truncating variants (0.47%), whereas the frequency observed in the gnomAD controls was 0.12%. We found a statistically significant association of truncating BARD1 variants with overall risk (odds ratio (OR) = 3.78; CI = 2.10–6.48; p = 1.16 × 10⁻⁵). This association remained significant in the hereditary breast cancer (HBC) group (OR = 4.18; CI = 2.10–7.70; p = 5.45 × 10⁻⁵). Furthermore, deleterious BARD1 variants were enriched among triple-negative BC patients (OR = 5.40; CI = 1.77–18.15; p = 0.001) compared to other BC subtypes. Our results support the role of BARD1 as a moderate penetrance BC predisposing gene and highlight a stronger association with triple-negative tumors.

Current scenario of the genetic testing for rare neurological disorders exploiting next generation sequencing

Next generation sequencing is currently a cornerstone of genetic testing in routine diagnostics, allowing for the detection of sequence variants with so far unprecedented large scale, mainly in genetically heterogenous diseases, such as neurological disorders. It is a fast-moving field, where new wet enrichment protocols and bioinformatics tools are constantly being developed to overcome initial limitations. Despite the as yet undiscussed advantages, however, there are still some challenges in data analysis and the interpretation of variants. In this review, we address the current state of next generation sequencing diagnostic testing for inherited human disorders, particularly giving an overview of the available high-throughput sequencing approaches; including targeted, whole-exome and whole-genome sequencing; and discussing the main critical aspects of the bioinformatic process, from raw data analysis to molecular diagnosis.

Screening of CNVs using NGS data improves mutation detection yield and decreases costs in genetic testing for hereditary cancer

INTRODUCTION

Germline CNVs are important contributors to hereditary cancer. In genetic diagnostics, multiplex ligation-dependent probe amplification (MLPA) is commonly used to identify them. However, MLPA is time-consuming and expensive if applied to many genes, hence many routine laboratories test only a subset of genes of interest.

METHODS AND RESULTS

We evaluated a next-generation sequencing (NGS)-based CNV detection tool (DECoN) as first-tier screening to decrease costs and turnaround time and expand CNV analysis to all genes of clinical interest in our diagnostics routine. We used DECoN in a retrospective cohort of 1860 patients where a limited number of genes were previously analysed by MLPA, and in a prospective cohort of 2041 patients, without MLPA analysis. In the retrospective cohort, 6 new CNVs were identified and confirmed by MLPA. In the prospective cohort, 19 CNVs were identified and confirmed by MLPA, 8 of these would have been lost in our previous MLPA-restricted detection strategy. Also, the number of genes tested by MLPA across all samples decreased by 93.0% in the prospective cohort.

CONCLUSION

Including an in silico germline NGS CNV detection tool improved our genetic diagnostics strategy in hereditary cancer, both increasing the number of CNVs detected and reducing turnaround time and costs.

Comprehensive analysis and ACMG-based classification of CHEK2 variants in hereditary cancer patients

CHEK2 variants are associated with intermediate breast cancer risk, among other cancers. We aimed to comprehensively describe CHEK2 variants in a Spanish hereditary cancer (HC) cohort and adjust the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP) guidelines for their classification. First, three CHEK2 frequent variants were screened in a retrospective Hereditary Breast and Ovarian Cancer cohort of 516 patients. After, the whole CHEK2 coding region was analyzed by next-generation sequencing in 1848 prospective patients with HC suspicion. We refined ACMG-AMP criteria and applied different combined rules to classify CHEK2 variants and define risk alleles. We identified 10 CHEK2 null variants, 6 missense variants with discordant interpretation in ClinVar database, and 35 additional variants of unknown significance. Twelve variants were classified as (likely)-pathogenic; two can also be considered "established risk-alleles" and one as "likely risk-allele." The prevalence of (likely)-pathogenic variants in the HC cohort was 0.8% (1.3% in breast cancer patients and 1.0% in hereditary nonpolyposis colorectal cancer patients). Here, we provide ACMG adjustment guidelines to classify CHEK2 variants. We hope that this study would be useful for variant classification of other genes with low effect variants.

Role of POLE and POLD1 in familial cancer

Purpose

Germline pathogenic variants in the exonuclease domain (ED) of polymerases POLE and POLD1 predispose to adenomatous polyps, colorectal cancer (CRC), endometrial tumors, and other malignancies, and exhibit increased mutation rate and highly specific associated mutational signatures. The tumor spectrum and prevalence of POLE and POLD1 variants in hereditary cancer are evaluated in this study.

Methods

POLE and POLD1 were sequenced in 2813 unrelated probands referred for genetic counseling (2309 hereditary cancer patients subjected to a multigene panel, and 504 patients selected based on phenotypic characteristics). Cosegregation and case–control studies, yeast-based functional assays, and tumor mutational analyses were performed for variant interpretation.

Results

Twelve ED missense variants, 6 loss-of-function, and 23 outside-ED predicted-deleterious missense variants, all with population allele frequencies <1%, were identified. One ED variant (POLE p.Met294Arg) was classified as likely pathogenic, four as likely benign, and seven as variants of unknown significance. The most commonly associated tumor types were colorectal, endometrial and ovarian cancers. Loss-of-function and outside-ED variants are likely not pathogenic for this syndrome.

Conclusions

Polymerase proofreading–associated syndrome constitutes 0.1–0.4% of familial cancer cases, reaching 0.3–0.7% when only CRC and polyposis are considered. ED variant interpretation is challenging and should include multiple pieces of evidence.

The Effects of Genetic and Epigenetic Alterations of BARD1 on the Development of Non-Breast and Non-Gynecological Cancers

Breast Cancer 1 (BRCA1) gene is a well-characterized tumor suppressor gene, mutations of which are primarily found in women with breast and ovarian cancers. BRCA1-associated RING domain 1 (BARD1) gene has also been identified as an important tumor suppressor gene in breast, ovarian, and uterine cancers. Underscoring the functional significance of the BRCA1 and BARD1 interactions, prevalent mutations in the BRCA1 gene are found in its RING domain, through which it binds the RING domain of BARD1. BARD1-BRCA1 heterodimer plays a crucial role in a variety of DNA damage response (DDR) pathways, including DNA damage checkpoint and homologous recombination (HR). However, many mutations in both BARD1 and BRCA1 also exist in other domains that significantly affect their biological functions. Intriguingly, recent genome-wide studies have identified various single nucleotide polymorphisms (SNPs), genetic alterations, and epigenetic modifications in or near the BARD1 gene that manifested profound effects on tumorigenesis in a variety of non-breast and non-gynecological cancers. In this review, we will briefly discuss the molecular functions of BARD1, including its BRCA1-dependent as well as BRCA1-independent functions. We will then focus on evaluating the common BARD1 related SNPs as well as genetic and epigenetic changes that occur in the non-BRCA1-dominant cancers, including neuroblastoma, lung, and gastrointestinal cancers. Furthermore, the pro- and anti-tumorigenic functions of different SNPs and BARD1 variants will also be discussed.

A comprehensive custom panel evaluation for routine hereditary cancer testing: improving the yield of germline mutation detection

Background

In the context of our Regional Program of Hereditary Cancer, individuals fulfilling the criteria are tested for germline mutations to subsequently establish the clinical management. Our standard diagnostic approach focuses on sequencing a few classic high-risk genes, a method that frequently renders uninformative genetic results. This study aims to examine the improved yield offered by an On-Demand panel.

Methods

We designed an On-Demand panel for the analysis of 35-genes associated with inherited cancer susceptibility in a total of 128 cases of Hereditary Breast and Ovarian Cancer (HBOC) and Hereditary Nonpolyposis Colorectal Cancer (HNPCC).

Results

Eighteen deleterious mutations were detected, in both routinely (BRCA2, MLH1, MSH2, PMS2) and non-routinely (ATM, BLM, BRIP1, CHEK2, MUTYH) tested genes. The screening extended to 35 genes rendered by patients carrying several- up to 6-Variants of Unknown Significance (VUS). Moreover, we confirmed the splicing disruption at RNA level for a not previously reported BRIP1 splicing mutation. Using an On-Demand panel, we identified 18 pathogenic mutation carriers, seven of which would have gone unnoticed with traditional analysis.

Conclusions

Our results reinforce the utility of NGS gene panels in the diagnostic routine to increase the performance of genetic testing, especially in individuals from families with overlapping cancer phenotypes.

Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small-Cell Lung Cancer

Introduction

Tumor mutational burden (TMB) has emerged as a clinically relevant biomarker that may be associated with immune checkpoint inhibitor efficacy. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment.

Objective

Here we describe the in-depth evaluation of bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples from a phase III clinical trial.

Methods

In the CheckMate 026 clinical trial, TMB was retrospectively assessed in 312 patients with non-small-cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or standard-of-care chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne^® CDx assay.

Results

TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90).

Conclusions

Parameter variation can impact TMB calculations, highlighting the need for standardization. Encouragingly, differences between assays could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms, and centers is achievable.

BRIP1, RAD51C, and RAD51D mutations are associated with high susceptibility to ovarian cancer: mutation prevalence and precise risk estimates based on a pooled analysis of ~30,000 cases

Background

It is estimated that more than 20% of ovarian cancer cases are associated with a genetic predisposition that is only partially explained by germline mutations in the BRCA1 and BRCA2 genes. Recently, several pieces of evidence showed that mutations in three genes involved in the homologous recombination DNA repair pathway, i.e., BRIP1, RAD51C, and RAD51D, are associated with a high risk of ovarian cancer. To more precisely estimate the ovarian cancer risk attributed to BRIP1, RAD51C, and RAD51D mutations, we performed a meta-analysis based on a comparison of a total of ~ 29,400 ovarian cancer patients from 63 studies and a total of ~ 116,000 controls from the gnomAD database.

Results

The analysis allowed precise estimation of ovarian cancer risks attributed to mutations in BRIP1, RAD51C, and RAD51D, confirming that all three genes are ovarian cancer high-risk genes (odds ratio (OR) = 4.94, 95%CIs:4.07–6.00, p < 0.0001; OR = 5.59, 95%CIs:4.42–7.07, p < 0.0001; and OR = 6.94, 95%CIs:5.10–9.44, p < 0.0001, respectively). In the present report, we show, for the first time, a mutation-specific risk analysis associated with distinct, recurrent, mutations in the genes.

Conclusions

The meta-analysis provides evidence supporting the pathogenicity of BRIP1, RAD51C, and RAD51D mutations in relation to ovarian cancer. The level of ovarian cancer risk conferred by these mutations is relatively high, indicating that after BRCA1 and BRCA2, the BRIP1, RAD51C, and RAD51D genes are the most important ovarian cancer risk genes, cumulatively contributing to ~ 2% of ovarian cancer cases. The inclusion of the genes into routine diagnostic tests may influence both the prevention and the potential treatment of ovarian cancer.

Mosaicism in genodermatoses

Genodermatoses are inherited disorders presenting with cutaneous manifestations with or without the involvement of other systems. The majority of these disorders, particularly in cases that present with a cutaneous patterning, may be explained in the context of genetic mosaicism. Despite the barriers to the genetic analysis of mosaic disorders, next-generation sequencing has led to a substantial progress in understanding their pathogenesis, which has significant implications for the clinical management and genetic counseling. Advances in paired and deep sequencing technologies in particular have made the study of mosaic disorders more feasible. In this review, we provide an overview of genetic mosaicism as well as mosaic cutaneous disorders and the techniques required to study them.

Genome analysis and knowledge-driven variant interpretation with TGex

BACKGROUND

The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient's phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants.

RESULTS

We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex's main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex's broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards' recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. Examining use-cases from a variety of TGex users world-wide, we demonstrate its high diagnostic yields (42% for single exome and 50% for trios in 1500 rare genetic disease cases) and critical actionable genetic findings. The platform's support for integration with EHR and LIMS through dedicated APIs facilitates automated retrieval of patient data for TGex's customizable reporting engine, establishing a rapid and cost-effective workflow for an entire range of clinical genetic testing, including rare disorders, cancer predisposition, tumor biopsies and health screening.

CONCLUSIONS

TGex is an innovative tool for the annotation, analysis and prioritization of coding and non-coding genomic variants. It provides access to an extensive knowledgebase of genomic annotations, with intuitive and flexible configuration options, allows quick adaptation, and addresses various workflow requirements. It thus simplifies and accelerates variant interpretation in clinical genetics workflows, with remarkable diagnostic yield, as exemplified in the described use cases. TGex is available at http://tgex.genecards.org/.

Clinical sequencing: From raw data to diagnosis with lifetime value

High-throughput sequencing (HTS) has revolutionized genetics by enabling the detection of sequence variants at hitherto unprecedented large scale. Despite these advances, however, there are still remaining challenges in the complete coverage of targeted regions (genes, exome or genome) as well as in HTS data analysis and interpretation. Moreover, it is easy to get overwhelmed by the plethora of available methods and tools for HTS. Here, we review the step-by-step process from the generation of sequence data to molecular diagnosis of Mendelian diseases. Highlighting advantages and limitations, this review addresses the current state of (1) HTS technologies, considering targeted, whole-exome, and whole-genome sequencing on short- and long-read platforms; (2) read alignment, variant calling and interpretation; as well as (3) regulatory issues related to genetic counseling, reimbursement, and data storage.

Preanalytic Variables and Tissue Stewardship for Reliable Next-Generation Sequencing (NGS) Clinical Analysis

An enduring goal of personalized medicine in cancer is the ability to identify patients who are likely to respond to specific therapies. Our growing understanding of the biology and molecular signatures of individual tumor types has facilitated the identification of predictive biomarkers and has led to an increasing number of diagnostic tests to be performed, often as serial and distinct assays on limited tumor specimens. The biomarker diagnostics field has been revolutionized by next-generation sequencing (NGS), which provides a comprehensive overview of the genomic profile of a tumor. Many preanalytic variables can influence the accuracy and reliability of NGS results. Standardization of preanalytic variables is, however, complicated by the plethora of specimen acquisition and processing methods. Variables across the tissue journey, including specimen acquisition, specimen fixation, and sectioning, as well as postfixation processing, such as nucleic acid extraction, library preparation, and choice of sequencing methods, are critical for the reliability of NGS analysis; thus, standardization would be beneficial. In this article, each step in the tissue journey is outlined, with specific focus on preanalytic variables that can influence NGS results. Practical considerations for standardization of these variables are provided to facilitate accurate, reliable, and reproducible NGS-based molecular characterization of tumors, ultimately informing diagnosis and guiding treatment.

Tumor mutational burden standardization initiatives: Recommendations for consistent tumor mutational burden assessment in clinical samples to guide immunotherapy treatment decisions

Characterization of tumors utilizing next‐generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence‐based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

Implementing TMB measurement in clinical practice: considerations on assay requirements

Clinical evidence demonstrates that treatment with immune checkpoint inhibitor immunotherapy agents can have considerable benefit across multiple tumours. However, there is a need for the development of predictive biomarkers that identify patients who are most likely to respond to immunotherapy. Comprehensive characterisation of tumours using genomic, transcriptomic, and proteomic approaches continues to lead the way in advancing precision medicine. Genetic correlates of response to therapy have been known for some time, but recent clinical evidence has strengthened the significance of high tumour mutational burden (TMB) as a biomarker of response and hence a rational target for immunotherapy. Concordantly, immune checkpoint inhibitors have changed clinical practice for lung cancer and melanoma, which are tumour types with some of the highest mutational burdens. TMB is an implementable approach for molecular biology and/or pathology laboratories that provides a quantitative measure of the total number of mutations in tumour tissue of patients and can be assessed by whole genome, whole exome, or large targeted gene panel sequencing of biopsied material. Currently, TMB assessment is not standardised across research and clinical studies. As a biomarker that affects treatment decisions, it is essential to unify TMB assessment approaches to allow for reliable, comparable results across studies. When implementing TMB measurement assays, it is important to consider factors that may impact the method workflow, the results of the assay, and the interpretation of the data. Such factors include biopsy sample type, sample quality and quantity, genome coverage, sequencing platform, bioinformatic pipeline, and the definitions of the final threshold that determines high TMB. This review outlines the factors for adoption of TMB measurement into clinical practice, providing an understanding of TMB assay considerations throughout the sample journey, and suggests principles to effectively implement TMB assays in a clinical setting to aid and optimise treatment decisions.

Targeted Therapies in Non-small-Cell Lung Cancer

The treatment landscape for non-small-cell lung cancer (NSCLC) has dramatically shifted over the past two decades. Targeted or precision medicine has primarily been responsible for this shift. Older paradigms of treating metastatic NSCLC with cytotoxic chemotherapy, while still important, have given way to evaluating tumor tissues for specific driver mutations that can be treated with targeted agents. Patients treated with targeted agents frequently have improved progression-free survival and overall survival compared to patients without a targetable driver mutation, highlighting the clinical benefit of precision medicine. In this chapter, we explore the historic landmark trials, the current state of the field, and potential future targets under investigation, in this exciting, rapidly evolving discipline of precision medicine in lung cancer.

Multigene panel testing beyond BRCA1/2 in breast/ovarian cancer Spanish families and clinical actionability of findings

PURPOSE

Few and small studies have been reported about multigene testing usage by massively parallel sequencing in European cancer families. There is an open debate about what genes should be tested, and the actionability of some included genes is under research.

METHODS

We investigated a panel of 34 known high/moderate-risk cancer genes, including 16 related to breast or ovarian cancer (BC/OC) genes, and 63 candidate genes to BC/OC in 192 clinically suspicious of hereditary breast/ovarian cancer (HBOC) Spanish families without pathogenic variants in BRCA1 or BRCA2 (BRCA1/2).

RESULTS

We identified 16 patients who carried a high- or moderate-risk pathogenic variant in eight genes: 4 PALB2, 3 ATM, 2 RAD51D, 2 TP53, 2 APC, 1 BRIP1, 1 PTEN and 1 PMS2. These findings led to increased surveillance or prevention options in 12 patients and predictive testing in their family members. We detected 383 unique variants of uncertain significance in known cancer genes, of which 35 were prioritized in silico. Eighteen loss-of-function variants were detected in candidate BC/OC genes in 17 patients (1 BARD1, 1 ERCC3, 1 ERCC5, 2 FANCE, 1 FANCI, 2 FANCL, 1 FANCM, 1 MCPH1, 1 PPM1D, 2 RBBP8, 3 RECQL4 and 1 with SLX4 and XRCC2), three of which also carry pathogenic variants in known cancer genes.

CONCLUSIONS

Eight percent of the BRCA1/2 negative patients carry pathogenic variants in other actionable genes. The multigene panel usage improves the diagnostic yield in HBOC testing and it is an effective tool to identify potentially new candidate genes.

Value-based genomics

Advancements in next-generation sequencing have greatly enhanced the development of biomarker-driven cancer therapies. The affordability and availability of next-generation sequencers have allowed for the commercialization of next-generation sequencing platforms that have found widespread use for clinical-decision making and research purposes. Despite the greater availability of tumor molecular profiling by next-generation sequencing at our doorsteps, the achievement of value-based care, or improving patient outcomes while reducing overall costs or risks, in the era of precision oncology remains a looming challenge. In this review, we highlight available data through a pre-established and conceptualized framework for evaluating value-based medicine to assess the cost (efficiency), clinical benefit (effectiveness), and toxicity (safety) of genomic profiling in cancer care. We also provide perspectives on future directions of next-generation sequencing from targeted panels to whole-exome or whole-genome sequencing and describe potential strategies needed to attain value-based genomics.

The impact of hereditary cancer gene panels on clinical care and lessons learned

Mutations in hereditary cancer syndromes account for a modest fraction of all cancers; however, identifying patients with these germline mutations offers tremendous health benefits to both patients and their family members. There are about 60 genes that confer a high lifetime risk of specific cancers, and this information can be used to tailor prevention, surveillance, and treatment. With advances in next-generation sequencing technologies and the elimination of gene patents for evaluating genetic information, we are now able to analyze multiple genes simultaneously, leading to the widespread clinical use of gene panels for germline cancer testing. Over the last 4 years since these panels were introduced, we have learned about the diagnostic yield of testing, the expanded phenotypes of the patients with mutations, and the clinical utility of genetic testing in patients with cancer and/or without cancer but with a family history of cancer. We have also experienced challenges including the large number of variants of unknown significance (VUSs), identification of somatic mutations and need to differentiate these from germline mutations, technical issues with particular genes and mutations, insurance coverage and reimbursement issues, lack of access to data, and lack of clinical management guidelines for newer and, especially, moderate and low-penetrance genes. The lessons learned from cancer genetic testing panels are applicable to other clinical areas as well and highlight the problems to be solved as we advance genomic medicine.

Whole-exome analysis of a Li-Fraumeni family trio with a novel TP53 PRD mutation and anticipation profile

Li-Fraumeni syndrome is a clinically heterogeneous familial cancer predisposition syndrome with autosomal-dominant inheritance caused by heterozygous germline mutations in the TP53 gene. We here analyze the genetic background of a family with a 4-year-proband presented with a Li-Fraumeni tumor. The mother developed breast cancer at age 37 and the proband died at age 8. We performed Sanger sequencing and whole-exome sequencing on peripheral blood DNA from proband and relatives. Data analysis selected only high-quality score and depth reads, rare variants and protein impact involving missense, non-sense, frameshift and splice disrupt mutations. Disease implicated variants and predicted deleterious alterations were also chosen. TP53 genetic testing revealed a never reported TP53 deletion arose as de novo mutation in the mother and inherited by the proband. We then performed whole-exome analysis of the trio to uncover inherited variants from the father that potentially worsen the already altered genetic background in the proband. No pathogenic variants were inherited in autosomal recessive, de novo dominant or X-linked recessive manner. Comparing proband and father exome we detected 25 predicted deleterious variants including a nonsense mutation in ERCC3. Those inherited mutations are possible candidate modifiers linked to TP53, explaining the proband accelerated tumor onset compared to the mother and providing a possible explanation of the genetic anticipation event in this Li-Fraumeni family.

The ICR96 exon CNV validation series: a resource for orthogonal assessment of exon CNV calling in NGS data

Detection of deletions and duplications of whole exons (exon CNVs) is a key requirement of genetic testing. Accurate detection of this variant type has proved very challenging in targeted next-generation sequencing (NGS) data, particularly if only a single exon is involved. Many different NGS exon CNV calling methods have been developed over the last five years. Such methods are usually evaluated using simulated and/or in-house data due to a lack of publicly-available datasets with orthogonally generated results. This hinders tool comparisons, transparency and reproducibility. To provide a community resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM or PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs, the most difficult type of exon CNV to detect. The FASTQ files for the ICR96 exon CNV validation series can be accessed through the European-Genome phenome Archive (EGA) under the accession number EGAS00001002428.

A comprehensive custom panel design for routine hereditary cancer testing: preserving control, improving diagnostics and revealing a complex variation landscape

We wanted to implement an NGS strategy to globally analyze hereditary cancer with diagnostic quality while retaining the same degree of understanding and control we had in pre-NGS strategies. To do this, we developed the I2HCP panel, a custom bait library covering 122 hereditary cancer genes. We improved bait design, tested different NGS platforms and created a clinically driven custom data analysis pipeline. The I2HCP panel was developed using a training set of hereditary colorectal cancer, hereditary breast and ovarian cancer and neurofibromatosis patients and reached an accuracy, analytical sensitivity and specificity greater than 99%, which was maintained in a validation set. I2HCP changed our diagnostic approach, involving clinicians and a genetic diagnostics team from panel design to reporting. The new strategy improved diagnostic sensitivity, solved uncertain clinical diagnoses and identified mutations in new genes. We assessed the genetic variation in the complete set of hereditary cancer genes, revealing a complex variation landscape that coexists with the disease-causing mutation. We developed, validated and implemented a custom NGS-based strategy for hereditary cancer diagnostics that improved our previous workflows. Additionally, the existence of a rich genetic variation in hereditary cancer genes favors the use of this panel to investigate their role in cancer risk.