Guidance for securing approvals for new biomarkers: from discovery to clinical implementation.

The journey of translating a molecular discovery into the clinic involves multiple steps and requires planning, time, effort, and money. In this review, we provide a quick guide on the technical and clinical validation parameters that are necessary for successful commercialization of molecular and other markers. We also briefly address the different options for regulatory approvals. Successful clinical implantation depends on rigorous technical and clinical validation, and the ability to develop clear guidelines for the indications for testing (i.e. which patients are eligible to have this test), the frequency of testing, and also a clear interpretation of test results. Successful implementation requires providing evidence that the results of this test can be used to improve patient care. There are currently multiple routes for implementation of clinical molecular tests, which include regulatory agency- approved companion diagnostics, laboratory developed tests, or direct-to-consumer testing. Regulatory approval is considered the gold-standard, but it requires time and resources. There is an ongoing debate about the need for regulatory approval of laboratory developed testing. Ongoing oversight is maintained through lab accreditation and proficiency testing programs, which provide a common approach to ensuring high standards and consistent performance in clinical molecular labs. Before moving into the clinic, confirmation of both the clinical and analytic validity of a new molecular test is essential.

Development of a comprehensive approach to adult hereditary cancer testing in Ontario.

BACKGROUND: Genetic testing for hereditary cancer susceptibility has advanced over time due to the discovery of new risk genes, improved technology and decreased cost. In the province of Ontario, testing eligibility criteria were initially developed to include hereditary breast, ovarian and colorectal cancer syndromes. The rapid evolution of genetic technologies has facilitated the ability to interrogate a large number of genes concurrently. This, coupled with new knowledge about risk genes, necessitated a coordinated approach to expanding the scope of genes and indications tested and synchronisation of access and test utilisation across the province as required in a publicly funded universal healthcare system. METHODS: Ontario Health-Cancer Care Ontario convened expert working groups to develop a standardised and comprehensive cancer gene list for adults and accompanying hereditary cancer testing (HCT) criteria using an evidence-based framework and broad laboratory and clinical genetics engagement. RESULTS: A standardised 76-cancer-gene panel, organised into 13 larger disease site panels and 25 single/small gene panels, was developed and endorsed by the working groups. Provincial genetic testing eligibility criteria were updated to align with the new panels and to guide clinical decision-making. In the first year following the implementation of these changes, 10 564 HCT panels were performed with an overall mutation detection rate of 12.2%. CONCLUSION: Using an evidence framework and broad clinical engagement to develop and endorse an updated guidance document, cancer genetic testing for adults in Ontario is now standardised and coordinated across the province.

Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository.

BACKGROUND: This study aimed to identify and resolve discordant variant interpretations across clinical molecular genetic laboratories through the Canadian Open Genetics Repository (COGR), an online collaborative effort for variant sharing and interpretation. METHODS: Laboratories uploaded variant data to the Franklin Genoox platform. Reports were issued to each laboratory, summarising variants where conflicting classifications with another laboratory were noted. Laboratories could then reassess variants to resolve discordances. Discordance was calculated using a five-tier model (pathogenic (P), likely pathogenic (LP), variant of uncertain significance (VUS), likely benign (LB), benign (B)), a three-tier model (LP/P are positive, VUS are inconclusive, LB/B are negative) and a two-tier model (LP/P are clinically actionable, VUS/LB/B are not). We compared the COGR classifications to automated classifications generated by Franklin. RESULTS: Twelve laboratories submitted classifications for 44 510 unique variants. 2419 variants (5.4%) were classified by two or more laboratories. From baseline to after reassessment, the number of discordant variants decreased from 833 (34.4% of variants reported by two or more laboratories) to 723 (29.9%) based on the five-tier model, 403 (16.7%) to 279 (11.5%) based on the three-tier model and 77 (3.2%) to 37 (1.5%) based on the two-tier model. Compared with the COGR classification, the automated Franklin classifications had 94.5% sensitivity and 96.6% specificity for identifying actionable (P or LP) variants. CONCLUSIONS: The COGR provides a standardised mechanism for laboratories to identify discordant variant interpretations and reduce discordance in genetic test result delivery. Such quality assurance programmes are important as genetic testing is implemented more widely in clinical care.

Evaluation of gene validity for CPVT and short QT syndrome in sudden arrhythmic death.

AIMS: Catecholaminergic polymorphic ventricular tachycardia (CPVT) and short QT syndrome (SQTS) are inherited arrhythmogenic disorders that can cause sudden death. Numerous genes have been reported to cause these conditions, but evidence supporting these gene-disease relationships varies considerably. To ensure appropriate utilization of genetic information for CPVT and SQTS patients, we applied an evidence-based reappraisal of previously reported genes. METHODS AND RESULTS: Three teams independently curated all published evidence for 11 CPVT and 9 SQTS implicated genes using the ClinGen gene curation framework. The results were reviewed by a Channelopathy Expert Panel who provided the final classifications. Seven genes had definitive to moderate evidence for disease causation in CPVT, with either autosomal dominant (RYR2, CALM1, CALM2, CALM3) or autosomal recessive (CASQ2, TRDN, TECRL) inheritance. Three of the four disputed genes for CPVT (KCNJ2, PKP2, SCN5A) were deemed by the Expert Panel to be reported for phenotypes that were not representative of CPVT, while reported variants in a fourth gene (ANK2) were too common in the population to be disease-causing. For SQTS, only one gene (KCNH2) was classified as definitive, with three others (KCNQ1, KCNJ2, SLC4A3) having strong to moderate evidence. The majority of genetic evidence for SQTS genes was derived from very few variants (five in KCNJ2, two in KCNH2, one in KCNQ1/SLC4A3). CONCLUSIONS: Seven CPVT and four SQTS genes have valid evidence for disease causation and should be included in genetic testing panels. Additional genes associated with conditions that may mimic clinical features of CPVT/SQTS have potential utility for differential diagnosis.

An International, Multicentered, Evidence-Based Reappraisal of Genes Reported to Cause Congenital Long QT Syndrome.

BACKGROUND: Long QT syndrome (LQTS) is the first described and most common inherited arrhythmia. Over the last 25 years, multiple genes have been reported to cause this condition and are routinely tested in patients. Because of dramatic changes in our understanding of human genetic variation, reappraisal of reported genetic causes for LQTS is required. METHODS: Utilizing an evidence-based framework, 3 gene curation teams blinded to each other's work scored the level of evidence for 17 genes reported to cause LQTS. A Clinical Domain Channelopathy Working Group provided a final classification of these genes for causation of LQTS after assessment of the evidence scored by the independent curation teams. RESULTS: Of 17 genes reported as being causative for LQTS, 9 (AKAP9, ANK2, CAV3, KCNE1, KCNE2, KCNJ2, KCNJ5, SCN4B, SNTA1) were classified as having limited or disputed evidence as LQTS-causative genes. Only 3 genes (KCNQ1, KCNH2, SCN5A) were curated as definitive genes for typical LQTS. Another 4 genes (CALM1, CALM2, CALM3, TRDN) were found to have strong or definitive evidence for causality in LQTS with atypical features, including neonatal atrioventricular block. The remaining gene (CACNA1C) had moderate level evidence for causing LQTS. CONCLUSIONS: More than half of the genes reported as causing LQTS have limited or disputed evidence to support their disease causation. Genetic variants in these genes should not be used for clinical decision-making, unless accompanied by new and sufficient genetic evidence. The findings of insufficient evidence to support gene-disease associations may extend to other disciplines of medicine and warrants a contemporary evidence-based evaluation for previously reported disease-causing genes to ensure their appropriate use in precision medicine.

CCMG practice guideline: laboratory guidelines for next-generation sequencing.

PurposeThe purpose of this document is to provide guidance for the use of next-generation sequencing (NGS, also known as massively parallel sequencing or MPS) in Canadian clinical genetic laboratories for detection of genetic variants in genomic DNA and mitochondrial DNA for inherited disorders, as well as somatic variants in tumour DNA for acquired cancers. They are intended for Canadian clinical laboratories engaged in developing, validating and using NGS methods. METHODS OF STATEMENT DEVELOPMENT: The document was drafted by the Canadian College of Medical Geneticists (CCMG) Ad Hoc Working Group on NGS Guidelines to make recommendations relevant to NGS. The statement was circulated for comment to the CCMG Laboratory Practice and Clinical Practice committees, and to the CCMG membership. Following incorporation of feedback, the document was approved by the CCMG Board of Directors. DISCLAIMER: The CCMG is a Canadian organisation responsible for certifying medical geneticists and clinical laboratory geneticists, and for establishing professional and ethical standards for clinical genetics services in Canada. The current CCMG Practice Guidelines were developed as a resource for clinical laboratories in Canada and should not be considered to be inclusive of all information laboratories should consider in the validation and use of NGS for a clinical laboratory service.

Implementation of an NGS-based sequencing and gene fusion panel for clinical screening of patients with suspected hematologic malignancies.

OBJECTIVES: The diagnosis of hematologic malignancies integrates multiple diagnostic and clinical disciplines. Historically, targeted (single-analyte) genetic testing has been used as reflex to initial prescreening by other diagnostic modalities including flow cytometry, anatomic pathology, and clinical cytogenetics. Given the wide range of mutations associated with hematologic malignancies a DNA/RNA-based NGS panel can provide a more effective and economical approach to comprehensive testing of patients as an initial, tier-1 screen. METHODS: Using a cohort of 380 patients, we performed clinical validation of a gene panel designed to assess 40 genes (DNA), and 29 fusion driver genes with over 600 gene fusion partners (RNA), including sample exchange data across three clinical laboratories, and correlation with cytogenetic testing results. RESULTS: The clinical validation of this technology demonstrated that its accuracy, sensitivity, and specificity are comparable to the majority of targeted single-gene approaches, while assessment of the initial patient cohort data demonstrated a high diagnostic yield of 50.5%. CONCLUSIONS: Implementation of a tier-1 NGS-based protocol for gene panel screening provides a comprehensive alternative to targeted molecular testing in patients with suspected hematologic malignancies, with increased diagnostic yield, scalability, reproducibility, and cost effectiveness, making it ideally suited for implementation in clinical laboratories.

Data sharing as a national quality improvement program: reporting on BRCA1 and BRCA2 variant-interpretation comparisons through the Canadian Open Genetics Repository (COGR).

PurposeThe purpose of this study was to develop a national program for Canadian diagnostic laboratories to compare DNA-variant interpretations and resolve discordant-variant classifications using the BRCA1 and BRCA2 genes as a case study.MethodsBRCA1 and BRCA2 variant data were uploaded and shared through the Canadian Open Genetics Repository (COGR; http://www.opengenetics.ca). A total of 5,554 variant observations were submitted; classification differences were identified and comparison reports were sent to participating laboratories. Each site had the opportunity to reclassify variants. The data were analyzed before and after the comparison report process to track concordant- or discordant-variant classifications by three different models.ResultsVariant-discordance rates varied by classification model: 38.9% of variants were discordant when using a five-tier model, 26.7% with a three-tier model, and 5.0% with a two-tier model. After the comparison report process, the proportion of discordant variants dropped to 30.7% with the five-tier model, to 14.2% with the three-tier model, and to 0.9% using the two-tier model.ConclusionWe present a Canadian interinstitutional quality improvement program for DNA-variant interpretations. Sharing of variant knowledge by clinical diagnostic laboratories will allow clinicians and patients to make more informed decisions and lead to better patient outcomes.

Simultaneous detection of lung fusions using a multiplex RT-PCR next generation sequencing-based approach: a multi-institutional research study.

BACKGROUND: Gene fusion events resulting from chromosomal rearrangements play an important role in initiation of lung adenocarcinoma. The recent association of four oncogenic driver genes, ALK, ROS1, RET, and NTRK1, as lung tumor predictive biomarkers has increased the need for development of up-to-date technologies for detection of these biomarkers in limited amounts of material. METHODS: We describe here a multi-institutional study using the Ion AmpliSeq™ RNA Fusion Lung Cancer Research Panel to interrogate previously characterized lung tumor samples. RESULTS: Reproducibility between laboratories using diluted fusion-positive cell lines was 100%. A cohort of lung clinical research samples from different origins (tissue biopsies, tissue resections, lymph nodes and pleural fluid samples) were used to evaluate the panel. We observed 97% concordance for ALK (28/30 positive; 71/70 negative samples), 95% for ROS1 (3/4 positive; 19/18 negative samples), and 93% for RET (2/1 positive; 13/14 negative samples) between the AmpliSeq assay and other methodologies. CONCLUSION: This methodology enables simultaneous detection of multiple ALK, ROS1, RET, and NTRK1 gene fusion transcripts in a single panel, enhanced by an integrated analysis solution. The assay performs well on limited amounts of input RNA (10 ng) and offers an integrated single assay solution for detection of actionable fusions in lung adenocarcinoma, with potential savings in both cost and turn-around-time compared to the combination of all four assays by other methods.

Roles for miR-375 in Neuroendocrine Differentiation and Tumor Suppression via Notch Pathway Suppression in Merkel Cell Carcinoma.

Dysfunction of key miRNA pathways regulating basic cellular processes is a common driver of many cancers. However, the biological roles and/or clinical applications of such pathways in Merkel cell carcinoma (MCC), a rare but lethal cutaneous neuroendocrine (NE) malignancy, have yet to be determined. Previous work has established that miR-375 is highly expressed in MCC tumors, but its biological role in MCC remains unknown. Herein, we show that elevated miR-375 expression is a specific feature of well-differentiated MCC cell lines that express NE markers. In contrast, miR-375 is strikingly down-regulated in highly aggressive, undifferentiated MCC cell lines. Enforced miR-375 expression in these cells induced NE differentiation, and opposed cancer cell viability, migration, invasion, and survival, pointing to tumor-suppressive roles for miR-375. Mechanistically, miR-375-driven phenotypes were caused by the direct post-transcriptional repression of multiple Notch pathway proteins (Notch2 and RBPJ) linked to cancer and regulation of cell fate. Thus, we detail a novel molecular axis linking tumor-suppressive miR-375 and Notch with NE differentiation and cancer cell behavior in MCC. Our findings identify miR-375 as a putative regulator of NE differentiation, provide insight into the cell of origin of MCC, and suggest that miR-375 silencing may promote aggressive cancer cell behavior through Notch disinhibition.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort.

BACKGROUND: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. METHODS: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. DISCUSSION: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.

Exploring high dimensional data with Butterfly: a novel classification algorithm based on discrete dynamical systems.

MOTIVATION: We introduce a novel method for visualizing high dimensional data via a discrete dynamical system. This method provides a 2D representation of the relationship between subjects according to a set of variables without geometric projections, transformed axes or principal components. The algorithm exploits a memory-type mechanism inherent in a certain class of discrete dynamical systems collectively referred to as the chaos game that are closely related to iterative function systems. The goal of the algorithm was to create a human readable representation of high dimensional patient data that was capable of detecting unrevealed subclusters of patients from within anticipated classifications. This provides a mechanism to further pursue a more personalized exploration of pathology when used with medical data. For clustering and classification protocols, the dynamical system portion of the algorithm is designed to come after some feature selection filter and before some model evaluation (e.g. clustering accuracy) protocol. In the version given here, a univariate features selection step is performed (in practice more complex feature selection methods are used), a discrete dynamical system is driven by this reduced set of variables (which results in a set of 2D cluster models), these models are evaluated for their accuracy (according to a user-defined binary classification) and finally a visual representation of the top classification models are returned. Thus, in addition to the visualization component, this methodology can be used for both supervised and unsupervised machine learning as the top performing models are returned in the protocol we describe here. RESULTS: Butterfly, the algorithm we introduce and provide working code for, uses a discrete dynamical system to classify high dimensional data and provide a 2D representation of the relationship between subjects. We report results on three datasets (two in the article; one in the appendix) including a public lung cancer dataset that comes along with the included Butterfly R package. In the included R script, a univariate feature selection method is used for the dimension reduction step, but in the future we wish to use a more powerful multivariate feature reduction method based on neural networks (Kriesel, 2007). AVAILABILITY AND IMPLEMENTATION: A script written in R (designed to run on R studio) accompanies this article that implements this algorithm and is available at http://butterflygeraci.codeplex.com/. For details on the R package or for help installing the software refer to the accompanying document, Supporting Material and Appendix.

Variant Classification Discordance: Contributing Factors and Predictive Models.

An ever-growing catalog of human variants is hosted in the ClinVar database. In this database, submissions on a variant are combined into a multisubmitter record; and in the case of discordance in variant classification between submitters, the record is labeled as conflicting. The current study used ClinVar data to identify characteristics that would make variants more likely to be associated with the conflict class of variants. Furthermore, the Extreme Gradient Boosting algorithm was used to train classifier models to provide prediction of classification discordance for single submission variants in ClinVar database. Population allele frequency, the gene harboring the variant, variant type, consequence on protein, variant deleteriousness score, first submitter identity, and submission count were associated with conflict in variant classification. Using such features, the optimized classifier showed accuracy on the test set of 88% with the weighted average of precision, recall, and f1-score of 0.84, 0.88, and 0.85, respectively. There were pronounced associations between variant classification discordance and allele frequency, gene type, and the identity of the first submitter. The study provides the predicted discordance status for single-submitter variants deposited in ClinVar. This approach can be used to assess whether single-submitter variants are likely to be supported, or in conflict with, future entries; this knowledge may help laboratories with clinical variant assessment.

Implementing Next-Generation Sequencing Process Changes to Increase Capacity and Improve Timeliness of Molecular Biomarker Profiling for Lung Cancer Patients.

BACKGROUND: Faced with expansion of molecular tumor biomarker profiling, the molecular genetics laboratory at Kingston Health Science Centre experienced significant pressures to maintain the provincially mandated 2-week turnaround time (TAT) for lung cancer (LC) patients. We used quality improvement methodology to identify opportunities for improved efficiencies and report the impact of the initiative. METHODS: We set a target of reducing average TAT from accessioning to clinical molecular lab report for LC patients. Process measures included percentage of cases reaching TAT within target and number of cases. We developed a value stream map and used lean methodology to identify baseline inefficiencies. Plan-Do-Study-Act cycles were implemented to streamline, standardize, and automate laboratory workflows. Statistical process control (SPC) charts assessed for significance by special cause variation. RESULTS: A total of 257 LC cases were included (39 baseline January-May 2021; 218 post-expansion of testing June 2021). The average time for baseline TAT was 12.8 days, peaking at 23.4 days after expansion of testing, and improved to 13.9 days following improvement interventions, demonstrating statistical significance by special cause variation (nonrandom variation) on SPC charts. CONCLUSIONS: The implementation of standardized manual and automated laboratory processes improved timeliness of biomarker reporting despite the increasing volume of testing at our center.

Plasma versus Tissue Tumor Mutational Burden as Biomarkers of Durvalumab plus Tremelimumab Response in Patients with Metastatic Colorectal Cancer in the CO.26 Trial.

PURPOSE: Tissue-derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology-agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset in which this was validated lacked colorectal cancers (CRC), and there is limited evidence for immunotherapy benefits in CRC using this threshold. PATIENTS AND METHODS: CO.26 was a randomized phase II study of 180 patients, comparing durvalumab and tremelimumab (D + T, n = 119 patients) versus best supportive care (BSC; n = 61 patients). ctDNA sequencing was available for 168 patients (n = 118 D + T; n = 50), of whom 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on OS were determined using a minimal P value approach. This report includes the final OS analysis. RESULTS: Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D + T compared with BSC in microsatellite stable (MSS) metastatic CRC [HR, 0.71 (95% CI, 0.28-1.80); P = 0.47]. No tissue TMB threshold could identify a high TMB group that benefited from ICI. By contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D + T [HR, 0.34 (95% CI, 0.13-0.85); P = 0.022], as was clonal pTMB ≥10.6 mutations/Mb [HR, 0.10 (95% CI, 0.014-0.79); P = 0.029] and subclonal pTMB ≥25.9/Mb [HR, 0.20 (95% CI, 0.061-0.69); P = 0.010]. Higher pTMB was associated with length of time on cytotoxic agents (P = 0.021) and prior anti-EGFR exposure (P = 2.44 × 10-06). CONCLUSIONS: pTMB derived from either clonal or subclonal mutations may identify a group likely to benefit from immunotherapy, although validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.

Identification of the IGF1/PI3K/NF κB/ERK gene signalling networks associated with chemotherapy resistance and treatment response in high-grade serous epithelial ovarian cancer.

BACKGROUND: Resistance to platinum-based chemotherapy remains a major impediment in the treatment of serous epithelial ovarian cancer. The objective of this study was to use gene expression profiling to delineate major deregulated pathways and biomarkers associated with the development of intrinsic chemotherapy resistance upon exposure to standard first-line therapy for ovarian cancer. METHODS: The study cohort comprised 28 patients divided into two groups based on their varying sensitivity to first-line chemotherapy using progression free survival (PFS) as a surrogate of response. All 28 patients had advanced stage, high-grade serous ovarian cancer, and were treated with standard platinum-based chemotherapy. Twelve patient tumours demonstrating relative resistance to platinum chemotherapy corresponding to shorter PFS (< eight months) were compared to sixteen tumours from platinum-sensitive patients (PFS > eighteen months). Whole transcriptome profiling was performed using an Affymetrix high-resolution microarray platform to permit global comparisons of gene expression profiles between tumours from the resistant group and the sensitive group. RESULTS: Microarray data analysis revealed a set of 204 discriminating genes possessing expression levels which could influence differential chemotherapy response between the two groups. Robust statistical testing was then performed which eliminated a dependence on the normalization algorithm employed, producing a restricted list of differentially regulated genes, and which found IGF1 to be the most strongly differentially expressed gene. Pathway analysis, based on the list of 204 genes, revealed enrichment in genes primarily involved in the IGF1/PI3K/NF κB/ERK gene signalling networks. CONCLUSIONS: This study has identified pathway specific prognostic biomarkers possibly underlying a differential chemotherapy response in patients undergoing standard platinum-based treatment of serous epithelial ovarian cancer. In addition, our results provide a pathway context for further experimental validations, and the findings are a significant step towards future therapeutic interventions.

A Novel Approach to Detect IDH Point Mutations in Gliomas Using Nanopore Sequencing: Test Validation for the Clinical Laboratory.

The use of standard next-generation sequencing technologies to detect key mutations in IDH genes for glioma diagnosis imposes several challenges, including high capital cost and turnaround delays associated with the need for batch testing. For both glioma testing and testing in other tumor types where highly specific mutation identification is required, the high-throughput nature of next-generation sequencing limits the feasibility of using it as a primary approach in clinical laboratories. We hypothesized that third-generation nanopore sequencing by Oxford Nanopore Technologies has the capability to overcome these limitations. This study aimed to develop and validate a nanopore-based IDH mutation detection assay for clinical practice using glioma formalin-fixed, paraffin-embedded (FFPE) tissue. Glioma FFPE (n = 66) samples with confirmed IDH gene mutational status were sequenced on the MinION device using an amplicon-based approach. All cases were concordant when compared with the reference results. Limit of blank and limit of detection for the variant allele fraction were 1.5% and 3.3%, respectively, at 500× read depth per gene. Total sequencing cost per sample was CAD$50 to CAD$134 with results being available in 9 to 15 hours. These findings demonstrate that nanopore-sequencing technology can be leveraged to develop low-cost, high-performance clinical sequencing-based assays with quick turnaround times to support the detection of targeted mutations in FFPE tumor tissue.

Circulating Tumor DNA Identifies Diverse Landscape of Acquired Resistance to Anti-Epidermal Growth Factor Receptor Therapy in Metastatic Colorectal Cancer.

PURPOSE: Anti-epidermal growth factor receptor (EGFR) antibodies are effective treatments for metastatic colorectal cancer. Improved understanding of acquired resistance mechanisms may facilitate circulating tumor DNA (ctDNA) monitoring, anti-EGFR rechallenge, and combinatorial strategies to delay resistance. METHODS: Patients with treatment-refractory metastatic colorectal cancer (n = 169) enrolled on the CO.26 trial had pre-anti-EGFR tissue whole-exome sequencing (WES) compared with baseline and week 8 ctDNA assessments with the GuardantOMNI assay. Acquired alterations were compared between patients with prior anti-EGFR therapy (n = 66) and those without. Anti-EGFR therapy occurred a median of 111 days before ctDNA assessment. RESULTS: ctDNA identified 12 genes with increased mutation frequency after anti-EGFR therapy, including EGFR (P = .0007), KRAS (P = .0017), LRP1B (P = .0046), ZNF217 (P = .0086), MAP2K1 (P = .018), PIK3CG (P = .018), BRAF (P = .048), and NRAS (P = .048). Acquired mutations appeared as multiple concurrent subclonal alterations, with most showing decay over time. Significant increases in copy-gain frequency were noted in 29 genes after anti-EGFR exposure, with notable alterations including EGFR (P < .0001), SMO (P < .0001), BRAF (P < .0001), MET (P = .0002), FLT3 (P = .0002), NOTCH4 (P = .0006), ERBB2 (P = .004), and FGFR1 (P = .006). Copy gains appeared stable without decay 8 weeks later. There were 13 gene fusions noted among 11 patients, all but one of which was associated with prior anti-EGFR therapy. Polyclonal resistance was common with acquisition of ≥ 10 resistance related alterations noted in 21% of patients with previous anti-EGFR therapy compared with 5% in those without (P = .010). Although tumor mutation burden (TMB) did not differ pretreatment (P = .63), anti-EGFR exposure increased TMB (P = .028), whereas lack of anti-EGFR exposure resulted in declining TMB (P = .014). CONCLUSION: Paired tissue and ctDNA sequencing identified multiple novel mutations, copy gains, and fusions associated with anti-EGFR therapy that frequently co-occur as subclonal alterations in the same patient.

Prevalence of NTRK Fusions in Canadian Solid Tumour Cancer Patients.

INTRODUCTION: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions occur in ~ 0.3% of all solid tumours but are enriched in some rare tumour types. Tropomyosin receptor kinase (TRK) inhibitors larotrectinib and entrectinib are approved as tumour-agnostic therapies for solid tumours harbouring NTRK fusions. METHODS: This study investigated the prevalence of NTRK fusions in Canadian patients and also aimed to help guide NTRK testing paradigms through analysis of data reported from a national clinical diagnostic testing program between September 2019 and July 2021. RESULTS: Of 1,687 patients included in the final analysis, NTRK fusions were detected in 0.71% (n = 12) of patients representing salivary gland carcinoma (n = 3), soft tissue sarcoma (n = 3), CNS (n = 3), and one in each of melanoma, lung, and colorectal cancer. All three salivary gland carcinomas contained ETV6-NTRK3 fusions. Thirteen (0.77%) clinically actionable incidental findings were also detected. Two of the 13 samples containing incidental findings were NTRK fusion-positive (GFOD1-NTRK2, FGFR3-TACC3 in a glioblastoma and AFAP1-NTRK2, BRAF c.1799T>A in a glioma). The testing algorithm screened most patient samples via pan-TRK immunohistochemistry (IHC), whereas samples from the central nervous system (CNS), pathognomonic cancers, and confirmed/ putative NTRK fusion-positive samples identified under research protocols were reflexed straight to next-generation sequencing (NGS). CONCLUSION: These findings highlight the benefit and practicality of a diagnostic testing program to identify patients suitable for tumour-agnostic TRK inhibitor therapies, as well as other targeted therapies, due to clinically actionable incidental findings identified. Collectively, these findings may inform future guidance on selecting the appropriate testing approach per tumour type and on optimal NTRK testing algorithms.