Mariam Thomas

A classification system for clinical relevance of somatic variants identified in molecular profiling of cancer

Purpose:Interpretation systems for clinical laboratory reporting of genetic variants for inherited conditions have been widely published. By contrast, there are no existing systems for interpretation and classification of somatic variants found from molecular testing of cancer.Methods:We designed an assessment protocol and classification system for somatic variants identified through next-generation sequencing molecular profiling of tumor-derived samples and applied these to a pilot dataset of somatic variants found by next-generation sequencing profiling of 158 tumor samples derived from advanced cancer patients examined at the Princess Margaret Cancer Centre.Results:We present a classification system to interpret the significance of genetic variants in molecular analysis of cancer, including the following key factors: (i) known or predicted pathogenicity of the variant; (ii) primary site and tumor histology in which the variant is found; (iii) recurrence of the variant; and (iv) evidence of clinical actionability. We used these factors to develop a five-category somatic variant classification for simplified reporting of variant interpretations to treating oncologists.Conclusion:Our somatic variant classification can be of practical value to other clinical molecular laboratories performing cancer genetic profiling by promoting consistent reporting of somatic variants and permitting harmonization of variant data among laboratories and clinical studies.Genet Med 18 2, 128–136.

Integration of Technical, Bioinformatic, and Variant Assessment Approaches in the Validation of a Targeted Next-Generation Sequencing Panel for Myeloid Malignancies

CONTEXT - Detection of variants in hematologic malignancies is increasingly important because of a growing number of variants impacting diagnosis, prognosis, and treatment response, and as potential therapeutic targets. The use of next-generation sequencing technologies to detect variants in hematologic malignancies in a clinical diagnostic laboratory setting allows for efficient identification of routinely tested markers in multiple genes simultaneously, as well as the identification of novel and rare variants in other clinically relevant genes. OBJECTIVE - To apply a systematic approach to evaluate and validate a commercially available next-generation sequencing panel (TruSight Myeloid Sequencing Panel, Illumina, San Diego, California) targeting 54 genes. In this manuscript, we focused on the parameters that were used to evaluate assay performance characteristics. DATA SOURCES - Analytical validation was performed using samples containing known variants that had been identified previously. Cases were selected from different disease types, with variants in a range of genes. Panel performance characteristics were assessed and genomic regions requiring additional analysis or wet-bench approaches identified. CONCLUSIONS - We validated the performance characteristics of a myeloid next-generation sequencing panel for detection of variants. The TruSight Myeloid Sequencing Panel covers more than 95% of target regions with depth greater than 500×. However, because of unique variant types such as large insertions or deletions or genomic regions of high GC content, variants in CEBPA, FLT3, and CALR required supplementation with non-next-generation sequencing assays or with informatics approaches to address deficiencies in performance. The use of multiple bioinformatics approaches (2 variant callers and informatics scripts) allows for maximizing calling of true positives, while identifying limitations in using either method alone.

Applications of Microarray Technology to Acute Myelogenous Leukemia

Microarray technology is a powerful tool, which has been applied to further the understanding of gene expression changes in disease. Array technology has been applied to the diagnosis and prognosis of Acute Myelogenous Leukemia (AML). Arrays have also been used extensively in elucidating the mechanism of and predicting therapeutic response in AML, as well as to further define the mechanism of AML pathogenesis. In this review, we discuss the major paradigms of gene expression array analysis, and provide insights into the use of software tools to annotate the array dataset and elucidate deregulated pathways and gene interaction networks. We present the application of gene expression array technology to questions in acute myelogenous leukemia; specifically, disease diagnosis, treatment and prognosis, and disease pathogenesis. Finally, we discuss several new and emerging array technologies, and how they can be further utilized to improve our understanding of AML.

Impact of genomic alterations on outcomes in myelofibrosis patients undergoing JAK1/2 inhibitor therapy

In myelofibrosis (MF), driver mutations in JAK2, MPL, or CALR impact survival and progression to blast phase, with the greatest risk conferred by triple-negative status. Subclonal mutations, including mutations in high-molecular risk (HMR) genes, such as ASXL1, EZH2, IDH1/2, and SRSF2 have also been associated with inferior prognosis. However, data evaluating the impact of next-generation sequencing in MF patients treated with JAK1/2 inhibitors are lacking. Using a 54-gene myeloid panel, we performed targeted sequencing on 100 MF patients treated with ruxolitinib (n = 77) or momelotinib (n = 23) and correlated mutational profiles with treatment outcomes. Ninety-nine patients had at least 1 mutation identified, 46 (46%) had 2 mutations, and 34 (34%) patients had ≥3 mutations. Seventy-nine patients carried a mutation in JAK2V617F, 14 patients had mutations in CALR, 6 patients had an MPL mutation, and 2 patients were triple negative. No mutation was significantly associated with spleen or anemia response. A high Dynamic International Prognostic Scoring System score and pretreatment transfusion dependence were associated with a shorter time to treatment failure (TTF), and this association retained significance on multivariable analysis. Patients with ASXL1 (hazard ratio [HR], 1.86; P = .03) and EZH2 mutations (HR, 2.94; P = .009) and an HMR profile (HR, 2.06; P = .01) had shorter TTF. On multivariate analysis, ASXL1 or EZH2 mutations were independently associated with shorter TTF and overall survival. These findings help identify patients unlikely to have a durable response with current JAK1/2 inhibitors and provide a framework for future studies.

Abstract 4765: Impact of TP53 status and functional classification on molecular profiles in breast cancer subtypes

Breast cancer is a multifaceted disease with several clinical, pathological and molecular attributes contributing to disease prognosis or treatment outcome. Treatment measures in breast cancer are based on hormone/growth factor receptor -estrogen/progesterone receptor (ER/PR) or human epidermal growth factor receptor 2 (Her2) status. TP53 pathway inactivation in breast cancer is well-established. Although TP539s therapeutic relevance is well-recognized, it remains under-utilized in patient-management, since all TP53 mutants are treated equally in the diagnostic context. In reality, enormous heterogeneity exists in nature, type and functional impact of TP53 variants. Therefore, understanding the diversity of TP53 variants in breast cancer subtypes may enhance its diagnostic utility in this cancer. We utilized clinical NGS data, obtained using commercially available targeted panels, TruSeq Amplicon Cancer Panel (Illumina) and Ion AmpliSeq Cancer Hotspot Panel v2 (Thermofisher) to analyze tumor DNAs from cancer patients at the Advanced Molecular Diagnostic Laboratory (Princess Margaret Cancer Centre, Toronto, Canada). We focused on data from 105 advanced breast cancer patients. We consolidated several schemes proposed in the literature to classify TP53 variants, and evaluated patient molecular profiling and pathology data based on: (1) presence of TP53 variants; (b) coding effect; and (c) transcriptional activity. We further investigated whether TP53 variants were associated with reportable variant load, co-occurrence with other molecular changes and hormone/growth-factor receptor status. In our study group, 70.4% cases carried one or more variants. TP53 alterations were prevalent (40.9%) in our cohort, followed by PIK3CA variants (36.2%). 15/105 cases (14.3%) carried variants in both genes. Unlike in other cancer types, where missense TP53 variants predominate (e.g., colorectal, 72.6%), missense (49%) and nonsense/frameshift (42%) variants were similarly distributed in breast cancers. Gain-of-Function (GOF) and Loss-of-Function (LOF) TP53 variants were also equally distributed (32% vs. 33%). However, TP53mut PIK3CAmut breast cancer cases were more likely to carry missense and/or LOF variants (10/15 cases). TP53 variants were also associated with hormone/growth-factor receptor status. A greater proportion of ER- vs ER+, PR- vs PR+, and ER-PR-Her2- vs ER+PR+Her2- breast cancer cases carried missense GOF TP53 variants respectively when compared to missense LOF and variants of unknown significance taken together(80-85% vs 50-55%; p Taken together, we define a stratification strategy for TP53 that takes into account the diversity of TP53 variants, and demonstrate its application to molecular profiling and clinico-pathological data in breast cancer. Citation Format: Swati Garg, Mahadeo A. Sukhai, Maksym Misyura, Mariam Thomas, Tong Zhang, Lillian L. Siu, Philippe L. Bedard, Tracy L. Stockley, Suzanne Kamel-Reid. Impact of TP53 status and functional classification on molecular profiles in breast cancer subtypes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4765.

Abstract A2-38: Interpretation and classification system for somatic variants identified in solid tumor molecular profiling

Variant classification schemes for clinical laboratory reporting of inherited variants from molecular diagnostic tests for germline conditions have been widely published. These group variants by pathogenicity, distinguishing benign variants from those known or likely to be pathogenic. In contrast, there are no published schemes for somatic variant classification in acquired cancer. Factors such as histology, cancer type and actionability must be considered to determine the variant9s clinical significance. We present a somatic variant classification scheme based on our experience in solid tumor molecular profiling using next-generation sequencing (NGS). Our protocol for somatic variant assessment from solid tumor NGS molecular profiling is comprised of: a) Determination of frequency of the variant in population databases, b) Information gathering on the variant from publicly available databases, c) Functional prediction using in silico tools for missense variants, d) Literature searches for publications relevant to variant function and actionability in the context of tumor type. Grading of Recommendations Assessment, Development and Evaluation (GRADE) principles are applied to determine whether evidence is sufficient to classify a given variant based on actionability. We applied this protocol to classify a pilot set of 258 variants in 158 consecutive patients tested using NGS. We present a classification system to interpret significance of genetic variants in molecular analysis of cancer, utilizing key factors: a) known or predicted pathogenicity of the variant; b) primary site and tumor histology in which the variant is found; c) whether the variant is recurrent in the specific gene; and, d) evidence of clinical actionability for patient management including targeted therapies. We used these factors to develop a 5-category Somatic Variant Classification scheme, for simplified reporting of variant interpretations to treating oncologists. Using this system, we classified 258 variants identified in 158 patients tested using NGS, and evaluated factors impacting the classification. In addition to the subset of findings with known clinical significance (37% of variants), a majority of the findings were potentially clinically actionable by extrapolating from evidence in other tumour types and recurrent variants of the same gene (49%). Classification depended on: Definition of “actionability”; primary tumor site and histology; level and type of evidence available; and, variant frequency. The pathogenicity of a specific gene/variant was distinct from its actionability; although both were indicative of biological relevance, only the latter informed patient management. By focusing on actionability, the SVC attempts to gauge the impact of genomic findings on patient management and care, bringing the most clinically relevant findings to the forefront of a list identified by NGS. Our Somatic Variant Classification scheme uses objective criteria to provide a structured stratification of the clinical significance of a somatic variant in a given histopathology, for a given patient, and for guiding laboratory procedures with respect to reporting. The distinction between “actionability” and “pathogenicity,” and the relevance of the former to the oncology setting, distinguishes our proposed categorization system from previously published classifications. The SVC can be applied to genomic datasets using various detection platforms, to track over time how advances in the field and new knowledge are affecting clinical care. This classification system enables an objective assessment over time of the relationship between available genomic information and the number of actionable findings which may impact patient care. Citation Format: Mahadeo A. Sukhai, Mariam Thomas, Kenneth J. Craddock, Tong Zhang, Tracy L. Stockley, Suzanne Kamel-Reid. Interpretation and classification system for somatic variants identified in solid tumor molecular profiling. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-38.

Abstract 628: Determinants of quality of next-generation sequencing output from the strand-specific TruSight Tumor Sequencing Panel in a clinical diagnostic setting

The use of Next-Generation Sequencing (NGS) technologies is increasingly prevalent within diagnostic labs. As genomic regions are sequenced to greater depth in cancer diagnostics, it is critical to differentiate clinically actionable variants from artifacts arising from sequencing-errors, sample- processing or sample-age, and to identify samples that will be difficult to evaluate. We sought to determine whether strand-specific sequencing approaches, such as the TruSight Tumor Sequencing Panel (Illumina) could enable sample and variant triage in a clinical diagnostic settingTruSight Tumor Sequencing Panel allows for paired-end sequencing of individual strands of DNA and analyzing them either together (Paired) or separately (Pool A and Pool B). Variants identified in one pool, but not the other, are putative artifacts; variants identified in both pools are considered true calls. Combined analysis of both pools was performed in two ways: By summing variant calls across pools, and by informatically determining overlapping variant calls between pools. In a test cohort of 44 FFPE samples of varying age and tumor type, we assessed whether age of sample, strand bias, and fixation impacted the detection of high confidence variants using the TruSight Tumor Sequencing panel. Data were compared to the results of analysis of the same samples using the established Illumina TruSeq Amplicon Cancer Panel and/or Sanger Sequencing.Sample age, tumor cellularity, tumor type and template DNA quality were not found to be associated with quality of NGS output in our study. We also evaluated the overall transition/transversion (Ti/Tv) ratios for variants detected either uniquely in one pool or in combined analysis. Interestingly, for variants detected in both pools, the Ti/Tv ratio was 1.97, compared to 0.52-0.60 for those detected in only 1 pool (p A:C>T transition > 62.5% and Ti/Tv ratios of > 4.0 (p A:C>T transitions were significantly over-represented in these samples. The overall%G>A:C>T transitions were equivalent (44-52%) in individual pools or in paired analysis. However, when inconclusive samples were accounted for, the%G>A:C>T transitions differed between the two analyses: 49.7% (paired) vs. 30.1-32.1% (individual pools). In summary, the Ti/Tv ratio can act as a critical determinant of variant call quality - Ti/Tv ratios ∼0.5 represent sequencing artifacts, while Ti/Tv ratios > 4.0 are indicative of inconclusive sequencing output.We conclude that variant Ti/Tv ratio as well as%G>A:C>T transition in variants detected by the TruSight Tumor Sequencing Panel may be helpful evaluators of quality and clinical utility of sequencing output for FFPE tumor samples tested in a clinical diagnostic setting. Citation Format: Swati Garg, Mahadeo A. Sukhai, Mariam Thomas, Michelle Mah, Tong Zhang, Trevor Pugh, Suzanne Kamel-Reid, Tracey L. Stockley. Determinants of quality of next-generation sequencing output from the strand-specific TruSight Tumor Sequencing Panel in a clinical diagnostic setting. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 628. doi:10.1158/1538-7445.AM2015-628

Abstract 4260: Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies

Recent cancer genome profiling studies have increased our understanding of the somatic mutation landscape of myeloid malignancies. A number of genes and variants are known to have prognostic/predictive utility in several myeloid malignancies, allowing for more accurate stratification, and enhanced patient management. This has led to consideration of NGS for detection of somatic mutations in myeloid malignancies in the clinical diagnostic setting, to supplant single-gene molecular testing assays in current use. Building on our prior work establishing a novel mass spectrometry-based high throughput mutation detection assay for hematologic malignancies, we investigated the application of NGS to myeloid malignancy diagnostics. To do this, we validated the Illumina TruSight Myeloid Sequencing Panel (54 genes, 568 amplicons) on 71 acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myeloproliferative neoplasm (MPN) patient samples, alongside relevant controls. NGS Libraries were prepared using standard protocols, and sequencing performed on the Illumina MiSeq platform. Concordance among NGS calls, single gene tests, and Sanger verification was tested as part of the clinical validation process. Analysis of 41 cases tested in our previously developed mass spectrometry assay indicated 100% concordance (70/70) for reportable variants mutually covered in both assays. Single nucleotide variations detectable in lab-standard single gene assays were all found by NGS (100% concordance). 58/71 (82%) cases had at least one additional potentially clinically relevant variant that would not have been identified in the existing assay (mean 1.95 additional variants/case; range 1-9). Additionally, we determined that AMLs carrying IDH1, IDH2 or TET2 mutations had a higher mutation burden (mean 4.6 mutations/case, range 2-7), compared to AMLs wild-type for these three genes (mean 3.1 mutations/case, range 2-4; p = 0.008). Clinically relevant insertions (up to 33 bp) and deletions (up to 52 bp) associated with AML and MPN, including FLT3 ITD and CALR deletions, were detected in known positive cases. In these cases, our analysis was supplemented with a custom bioinformatics algorithm allowing for alignment against an artificial reference sequence to detect larger indels. Due to low coverage of the clinically actionable CEBPA, we supplemented the NGS assay with Sanger sequencing for this locus. Therefore, we report the validation of an NGS panel for high throughput detection of mutations in myeloid malignancies, and the development of a wet-bench and informatics workflow enabling maximal information benefit in the diagnostic setting. This pipeline allows the detection of variants that impact diagnosis and patient management, with significantly improved information benefit over current tests. Citation Format: Mariam Thomas, Mahadeo Sukhai, Tong Zhang, Djamel Harbi, Justin De Souza, Katherine MacDonald, Trevor Pugh, Mark Minden, Andre Schuh, Tracy L. Stockley, Suzanne Kamel-Reid. Clinical testing and implementation of the TruSight Myeloid Next Generation Sequencing (NGS) panel for identification of clinically relevant variants in hematological malignancies. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4260. doi:10.1158/1538-7445.AM2015-4260

Abstract 4713: High-throughput multiplex Sequenom MassARRAY clinical diagnostic assay for the identification of actionable genetic variants in hematologic malignancies

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Recent cancer genome sequencing efforts have led to an enhanced understanding of the somatic mutation profile of hematologic malignancies in the context of known cytogenetic abnormalities. For cytogenetically normal acute myeloid leukemia (AML), mutations in NPM1, DNMT3A, CEBPA, TET2 and IDH1/2 are thought to have potential predictive utility and may impact patient management with regard to initial and consolidation therapy, including stem cell transplantation. As most potentially clinically relevant variants currently are not tested for within the diagnostic setting, we established a high-throughput multiplex assay capable of simultaneous detection of a range of somatic mutations in hematologic malignancies. Using iPlex chemistry and the Sequenom MassARRAY platform, we established the Princess Margaret Cancer Centre (PM) Hematologic Malignancies Panel v1.0, comprised of 110 individual assays profiling 186 mutations in 22 relevant genes, in a 16-well assay format. We conducted an in silico analysis to identify genes with hotspot mutations capable of being analyzed by Sequenom; genes with mutations distributed throughout the coding sequence (e.g., CEBPA, TET2) were excluded from the panel. To best integrate this technology in the workflow of our routine clinical molecular diagnostic testing we developed the PM Panel as an RNA-based test, requiring 1 μg of patient RNA for the initial reverse transcription reaction. To validate the assay we tested 222 patient-derived samples, including 5 normal samples, 82 AML (57 with normal cytogenetics, 24 with cytogenetic changes and 1 therapy-related), 44 myelodysplastic syndromes, 32 myeloproliferative neoplasms, 21 additional cases tested for KIT mutation, and 38 B-lymphoid malignancies (including 3 multiple myeloma cases),. Concordance with established lab assays for NPM1, FLT3-TKD and JAK2 mutations was 100%; other identified mutations were verified by Sanger sequencing at 98% concordance (2% of cases were below the limit of sensitivity of Sanger technology). Approximately 50% of samples were positive for at least one mutation with 174 mutations detected overall. Cytogenetically normal AMLs and myelodysplastic syndromes were most informative, with 2.3 and 1.8 mutations per positive case respectively. Samples already known to carry a leukemogenic driver fusion protein (e.g., PML-RARα, AML1-ETO, or BCR-ABL) had a significantly decreased identified somatic mutation load than their cytogenetically normal counterparts (average of 1.4 mutations per case, compared to 0.3, p < 10^-6). The PM Hematologic Malignancies Panel v1.0 is now being integrated into the current clinical diagnostic workflow. We therefore report the development of a versatile, RNA-based high-throughput multiplex platform for the identification of somatic mutations present in hematologic malignancies for use in a clinical diagnostic setting. Citation Format: Mahadeo A. Sukhai, Mariam Thomas, Tong Zhang, Cuihong Wei, Suzanne Trudel, Karen Yee, Mark D. Minden, Andre Schuh, Tracy Stockley, Suzanne Kamel-Reid. High-throughput multiplex Sequenom MassARRAY clinical diagnostic assay for the identification of actionable genetic variants in hematologic malignancies. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4713. doi:10.1158/1538-7445.AM2014-4713

Abstract 1240: Functional deregulation of NF-kB and abnormal TNFa response in acute promyelocytic leukemia

Acute promyelocytic leukemia (APL) accounts for approximately 10% of acute myelogenous leukemia (AML) cases, and is characterized by accumulation of abnormal promyelocytes in patient bone marrow and peripheral blood. APL is associated with balanced chromosomal translocations involving retinoic acid receptor alpha (RARA), giving rise to fusion oncoproteins referred to as X-RARA. As deregulation of retinoid signaling is insufficient for leukemia development, our studies aim to determine other signaling pathways involved in APL by assessing the gene expression profiles and cell biology of X-RARA. We previously determined, using gene expression microarray analysis, common downstream targets of the variant APL fusion proteins NPM- and NuMA-RARA. We observed an over-representation of NF-κB target genes within this dataset. In these cells, a number of NF-κB target genes were commonly over-expressed. A subset of commonly deregulated genes were validated in our APL cell lines and 23 primary APL patient samples by real-time quantitative RT-PCR (RQ-PCR). 13/16 genes that were tested were significantly altered in APL compared to normal BM (n=11) p + cells to survive and proliferate in the presence of TNFα. Our data provides the first evidence of the functional deregulation of the NF-κB-mediated signaling pathway and the TNFα response in cells expressing the variant APL fusion proteins. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 1240.