scholarly journals Incidental germline findings during molecular profiling of tumor tissues for precision oncology: molecular survey and methodological obstacles

2022 ◽  
Vol 20 (1) ◽  
Author(s):  
Alexandra Lebedeva ◽  
Yulia Shaykhutdinova ◽  
Daria Seriak ◽  
Ekaterina Ignatova ◽  
Ekaterina Rozhavskaya ◽  
...  
Keyword(s):  
Normal Tissue ◽  
Sanger Sequencing ◽  
Computational Prediction ◽  
Bioinformatic Analysis ◽  
Molecular Profiling ◽  
Precision Oncology ◽  
Germline Variants ◽  
Manual Curation ◽  
Uncertain Significance ◽  
Tumor Types

Abstract Background A fraction of patients referred for complex molecular profiling of biopsied tumors may harbor germline variants in genes associated with the development of hereditary cancer syndromes (HCS). Neither the bioinformatic analysis nor the reporting of such incidental germline findings are standardized. Methods Data from Next-Generation Sequencing (NGS) of biopsied tumor samples referred for complex molecular profiling were analyzed for germline variants in HCS-associated genes. Analysis of variant origin was performed employing bioinformatic algorithms followed by manual curation. When possible, the origin of the variant was validated by Sanger sequencing of the sample of normal tissue. The variants’ pathogenicity was assessed according to ACMG/AMP. Results Tumors were sampled from 183 patients (Males: 75 [41.0%]; Females: 108 [59.0%]; mean [SD] age, 57.7 [13.3] years) and analysed by targeted NGS. The most common tumor types were colorectal (19%), pancreatic (13%), and lung cancer (10%). A total of 56 sequence variants in genes associated with HCS were detected in 40 patients. Of them, 17 variants found in 14 patients were predicted to be of germline origin, with 6 variants interpreted as pathogenic (PV) or likely pathogenic (LPV), and 9 as variants of uncertain significance (VUS). For the 41 out of 42 (97%) missense variants in HCS-associated genes, the results of computational prediction of variant origin were concordant with that of experimental examination. We estimate that Sanger sequencing of a sample of normal tissue would be required for ~ 1–7% of the total assessed cases with PV or LPV, when necessity to follow with genetic counselling referral in ~ 2–15% of total assessed cases (PV, LPV or VUS found in HCS genes). Conclusion Incidental findings of pathogenic germline variants are common in data from cancer patients referred for complex molecular profiling. We propose an algorithm for the management of patients with newly detected variants in genes associated with HCS.

scholarly journals Individualized Molecular Profiling for Allocation to Clinical Trials Singapore Study—An Asian Tertiary Cancer Center Experience

2021 ◽  
pp. 859-875
Author(s):  
Amanda O. L. Seet ◽  
Aaron C. Tan ◽  
Tira J. Tan ◽  
Matthew C. H. Ng ◽  
David W. M. Tai ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Tumor Tissue ◽  
Molecular Profiling ◽  
Tumor Board ◽  
Cancer Center ◽  
Precision Oncology ◽  
Molecular Tumor Board ◽  
Tumor Types ◽  
Tertiary Cancer Center

PURPOSE Precision oncology has transformed the management of advanced cancers through implementation of advanced molecular profiling technologies to identify increasingly defined subsets of patients and match them to appropriate therapy. We report outcomes of a prospective molecular profiling study in a high-volume Asian tertiary cancer center. PATIENTS AND METHODS Patients with advanced cancer were enrolled onto a prospective protocol for genomic profiling, the Individualized Molecular Profiling for Allocation to Clinical Trials Singapore study, at the National Cancer Center Singapore. Primary objective was to identify molecular biomarkers in patient's tumors for allocation to clinical trials. The study commenced in February 2012 and is ongoing, with the results of all patients who underwent multiplex next-generation sequencing (NGS) testing until December 2018 presented here. The results were discussed at a molecular tumor board where recommendations for allocation to biomarker-directed trials or targeted therapies were made. RESULTS One thousand fifteen patients were enrolled with a median age of 58 years (range 20-83 years). Most common tumor types were lung adenocarcinoma (26%), colorectal cancer (15%), and breast cancer (12%). A total of 1,064 NGS assays were performed, on fresh tumor tissue for 369 (35%) and archival tumor tissue for 687 (65%) assays. TP53 (39%) alterations were most common, followed by EGFR (21%), KRAS (14%), and PIK3CA (10%). Of 405 NGS assays with potentially actionable alterations, 111 (27%) were allocated to a clinical trial after molecular tumor board and 20 (4.9%) were enrolled on a molecularly matched clinical trial. Gene fusions were detected in 23 of 311 (7%) patients tested, including rare fusions in new tumor types and known fusions in rare tumors. CONCLUSION Individualized Molecular Profiling for Allocation to Clinical Trials Singapore demonstrates the feasibility of a prospective broad molecular profiling program in an Asian tertiary cancer center, with the ability to develop and adapt to a dynamic landscape of precision oncology.

Identification and prioritization of myeloid malignancy germline variants in a large cohort of adult AML patients

Blood ◽  
2021 ◽  
Author(s):  
Fei Yang ◽  
Nicola Long ◽  
Tauangtham Anekpuritanang ◽  
Daniel Bottomly ◽  
Jonathan C. Savage ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Sequencing Data ◽  
Germline Variants ◽  
Variant Of Uncertain Significance ◽  
Functional Studies ◽  
Variants Of Unknown Significance ◽  
Manual Curation ◽  
Unknown Significance ◽  
Uncertain Significance ◽  
Whole Exome Sequencing Data

Inherited predisposition to myeloid malignancies is more common than previously appreciated. We analyzed the whole-exome sequencing data of paired leukemia and skin biopsy samples from 391 adult patients from the Beat AML 1.0 consortium. Using the 2015 ACMG guidelines for variant interpretation, we curated 1,547 unique variants from 228 genes. The pathogenic/likely pathogenic (P/LP) germline variants were identified in 53 AML patients (13.6%) in 34 genes. 41% of variants were in DNA damage response genes, and the most frequently mutated genes were CHEK2 (8 patients) and DDX41 (7 patients). 44% of the pathogenic germline variants were in genes considered clinically actionable (tier 1). Pathogenic germline variants were also found in new candidate genes (DNAH5, DNAH9, DNMT3A, SUZ12). No strong correlation was found between the germline mutational rate and age of AML onset. Among 49 patients who have a reported history of at least one family member affected with hematological malignancies, six patients harbored known P/LP germline variants and the remaining patients had at least one variant of uncertain significance, suggesting a need for further functional validation studies. Using CHEK2 as an example, we show that three-dimensional protein modeling can be one of the effective methodologies to prioritize variants of unknown significance for functional studies. Further, we evaluated an in-silico approach that applies ACMG/AMP curation in an automated manner using the tool for assessment and prioritization in exome studies (TAPES), which can minimize manual curation time for variants. Overall, our findings suggest a need to comprehensively understand the predisposition potential of many germline variants in order to enable closer monitoring for disease management and treatment interventions for affected patients and families.

Rare Germline GLMN Variants Identified from Blue Rubber Bleb Nevus Syndrome Might Impact mTOR Signaling

2020 ◽  
Vol 22 (10) ◽  
pp. 675-682 ◽  
Author(s):  
Jie Yin ◽  
Zhongping Qin ◽  
Kai Wu ◽  
Yufei Zhu ◽  
Landian Hu ◽  
...  
Keyword(s):  
Gastrointestinal Tract ◽  
Sanger Sequencing ◽  
Somatic Mutations ◽  
Venous Malformation ◽  
Underlying Disease ◽  
Mtor Signaling ◽  
Functional Effect ◽  
Germline Variants ◽  
Whole Exome

Backgrounds and Objective: Blue rubber bleb nevus syndrome (BRBN) or Bean syndrome is a rare Venous Malformation (VM)-associated disorder, which mostly affects the skin and gastrointestinal tract in early childhood. Somatic mutations in TEK have been identified from BRBN patients; however, the etiology of TEK mutation-negative patients of BRBN need further investigation. Method: Two unrelated sporadic BRBNs and one sporadic VM were firstly screened for any rare nonsilent mutation in TEK by Sanger sequencing and subsequently applied to whole-exome sequencing to identify underlying disease causative variants. Overexpression assay and immunoblotting were used to evaluate the functional effect of the candidate disease causative variants. Results: In the VM case, we identified the known causative somatic mutation in the TEK gene c.2740C>T (p.Leu914Phe). In the BRBN patients, we identified two rare germline variants in GLMN gene c.761C>G (p.Pro254Arg) and c.1630G>T(p.Glu544*). The GLMN-P254R-expressing and GLMN-E544X-expressing HUVECs exhibited increased phosphorylation of mTOR-Ser-2448 in comparison with GLMN-WTexpressing HUVECs in vitro. Conclusion: Our results demonstrated that rare germline variants in GLMN might contribute to the pathogenesis of BRBN. Moreover, abnormal mTOR signaling might be the pathogenesis mechanism underlying the dysfunction of GLMN protein.

Germline EGFR variants are over-represented in adolescents and young adults (AYA) with adrenocortical carcinoma

2020 ◽  
Author(s):  
Sara Akhavanfard ◽  
Lamis Yehia ◽  
Roshan Padmanabhan ◽  
Jordan P Reynolds ◽  
Ying Ni ◽  
...  
Keyword(s):  
Young Adults ◽  
Adrenocortical Carcinoma ◽  
Kinase Inhibitor ◽  
Mapk Pathway ◽  
Adolescents And Young Adults ◽  
Control Group ◽  
Precision Oncology ◽  
Sequencing Data ◽  
Germline Variants ◽  
Mutant Cells

Abstract Adrenocortical Carcinoma (ACC) is a rare endocrine tumor with poor overall prognosis and 1.5-fold overrepresentation in females. In children, ACC is associated with inherited cancer syndromes with 50–80% of childhood-ACC associated with TP53 germline variants. ACC in adolescents and young adults (AYA) is rarely due to germline TP53, IGF2, PRKAR1A and MEN1 variants. We analyzed exome sequencing data from 21 children (<15y), 32 AYA (15-39y), and 60 adults (>39y) with ACC, and retained all pathogenic, likely pathogenic, and highly prioritized variants of uncertain significance. We engineered a stable lentiviral-mutant ACC cell line, harboring an EGFR variant (p.Asp1080Asn) from a 21-year-old female without germline-TP53-variant and with aggressive ACC. We found that 4.8% of the children (P = 0.004) and 6.2% of AYA (P < 0.0001), all-female participants, harbored germline EGFR variants, compared to only 0.3% of the control group. Expanding our analysis to the RTK-RAS-MAPK pathway, we found that the RTK genes have the highest number of highly prioritized germline variants in these individuals amongst all three arms of this pathway. We showed EGFR mutant cells migrate faster and are characterized by a stem-like phenotype compared to wild type cells. While EGFR inhibitors did not affect the stemness of mutant cells, Sunitinib, a multireceptor tyrosine kinase inhibitor, significantly reduced their stem-like behavior. Our data suggest that EGFR could be a novel underlying germline predisposition factor for ACC, especially in the Childhood-AYA (C-AYA) population. Further clinical validation can improve precision oncology management of this disease, which is known to have limited therapeutic options.

13P Incidental germline findings from tumor molecular profiling for precision oncology: Is it common and how to manage?

2021 ◽  
Vol 32 ◽  
pp. S1349-S1350
Author(s):  
M. Ivanov ◽  
A. Lebedeva ◽  
D. Seriak ◽  
E. Rozhavskaya ◽  
M. Sharova ◽  
...  
Keyword(s):  
Molecular Profiling ◽  
Precision Oncology

scholarly journals Bioinformatics of Metalloproteins and Metalloproteomes

Molecules ◽  
2020 ◽  
Vol 25 (15) ◽  
pp. 3366
Author(s):  
Yan Zhang ◽  
Junge Zheng
Keyword(s):  
Comparative Genomics ◽  
Metal Binding ◽  
Computational Prediction ◽  
Bioinformatic Analysis ◽  
Research Progress ◽  
Evolutionary Patterns ◽  
Cellular Processes ◽  
Metal Binding Sites ◽  
Domains Of Life ◽  
Systematic Understanding

Trace metals are inorganic elements that are required for all organisms in very low quantities. They serve as cofactors and activators of metalloproteins involved in a variety of key cellular processes. While substantial effort has been made in experimental characterization of metalloproteins and their functions, the application of bioinformatics in the research of metalloproteins and metalloproteomes is still limited. In the last few years, computational prediction and comparative genomics of metalloprotein genes have arisen, which provide significant insights into their distribution, function, and evolution in nature. This review aims to offer an overview of recent advances in bioinformatic analysis of metalloproteins, mainly focusing on metalloprotein prediction and the use of different metals across the tree of life. We describe current computational approaches for the identification of metalloprotein genes and metal-binding sites/patterns in proteins, and then introduce a set of related databases. Furthermore, we discuss the latest research progress in comparative genomics of several important metals in both prokaryotes and eukaryotes, which demonstrates divergent and dynamic evolutionary patterns of different metalloprotein families and metalloproteomes. Overall, bioinformatic studies of metalloproteins provide a foundation for systematic understanding of trace metal utilization in all three domains of life.

A community-based program for personalized cancer care using next-generation sequencing (NGS).

2013 ◽  
Vol 31 (15_suppl) ◽  
pp. 11102-11102
Author(s):  
Shile Liang ◽  
Pranil Chandra ◽  
Zeqiang Ma ◽  
Debbie Haynes ◽  
James Prescott ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Cancer Patients ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Molecular Profiling ◽  
Targeted Agents ◽  
Community Based ◽  
Off Label ◽  
Molecular Abnormalities ◽  
Tumor Types

11102 Background: Despite growing interest and need, molecular profiling of tumor samples is largely unavailable in community cancer centers, where nearly 80% of cancer patients (pts) are treated. In 10/12, Sarah Cannon Research Institute (SCRI) launched a community-based molecular profiling program to: 1) better understand the molecular constituency of cancer patients, 2) identify appropriate pts for phase I and II clinical trials of targeted agents, and 3) identify pts with molecular abnormalities responsive to FDA-approved agents. Methods: Eligible pts consented to testing of available biospecimens, which were interrogated for alterations in 35 cancer-related genes using NGS (1000X average coverage) in a CLIA/CAP laboratory. Results were reported to the treating physician within 14 days and stored in a database to enable correlation with clinical outcomes. Results: As of 1/13, 209 pts had been enrolled with 84% having sufficient material for assay. At least 1 mutation was detected in 46% of tumors. Results in the 3 most commonly assayed tumor types are summarized (Table). Mutations for which there are FDA-approved targeted agents were found in 14 off-label tumors (EGFR 4, KIT 3, SMO 3, BRAF 2, HER2 2). 40 pts (27%) were subsequently enrolled in clinical trials; in 19 of these, assay results influenced clinical trial selection. Conclusions: This program provides molecular profiling data to community oncologists for clinical decision making. Experience to date indicates this information can be provided in a timely manner for incorporation into clinical practice. Profiling results will enable: 1) selection of pts with appropriate tumor targets for investigational targeted agents, 2) enhanced study enrollment, 3) evaluation of FDA approved targeted agents in off-label tumor types, and 4) correlation of treatment outcomes with patterns of tumor molecular abnormalities. [Table: see text]

Pathogenicity of mutation analyzer (PathoMAN): A fast automation of germline genomic variant curation in clinical sequencing.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1529-1529
Author(s):  
Vijai Joseph ◽  
Vignesh Ravichandran ◽  
Kenneth Offit
Keyword(s):  
Specific Information ◽  
Web Based ◽  
Clinical Sequencing ◽  
Bioinformatic Tools ◽  
Manual Curation ◽  
Lack Of Information ◽  
Public Resources ◽  
Uncertain Significance ◽  
Patients At Risk ◽  
Genomic Variant

1529 Background: A challenge in clinical oncology is interpretation of multiplexed gene sequencing of patients at risk. The plethora of variants to be curated for pathogenicity or actionability poses a growing burden for cancer care professionals. Current guidelines by the ACMG requires the aggregation of multiple lines of genomic data evidences from diverse resources. A computational tool that automates, provide uniformity and significantly speed the interpretive process is thus necessary. Methods: The Pathogenicity of Mutation Analyzer (PathoMAN), is a tool that automates germline genomic variant curation from clinical sequencing based on ACMG guidelines. PathoMAN aggregates multiple tracks of genomic, protein and disease specific information from public sources such as ClinVar, ExAC, UniProt, 1000 genomes, dbNSFP and locus specific databases. Variant specific and gene specific annotations are used to classify variants to model the ACMG rubric. We analyzed 2500 manually curated and classified, high quality variants in 180 genes from 3 large, published studies to quantify the performance of PathoMAN; analyzing 242 pathogenic/likely pathogenic (P/LP), 1272 benign/likely benign (B/LB) and 1261 variants of uncertain significance (VUS). We report the summary of PathoMAN classifications in four categories contrasted against the manual curation. Results: PathoMan achieves an average of 75% concordance and 1.5% discordance for P/LP mutations and 60% and 0.1% for B/LB variants. PathoMAN is able to resolve 12% of reported VUS as either P/LP or B/LB. It loses resolution to classify 25% of P/LP and B/LB variants due to lack of information and due to inconsistencies in available data from public resources. Conclusions: PathoMAN provides a breakthrough in rapid classification of genetic variants by generation of robust models using a knowledgebase of diverse genetic data. It is easily accessible, web-based resource that allows the community to rapidly test a large number of variants for pathogenicity. Such bioinformatic tools are essential to reduce manual workload of a domain level experts. We propose, a new nosology for the 5 ACMG classes to facilitate better reporting to ClinVar.

FoundationOne as a relevant tool for comprehensive genomic profiling and assessment of tumor mutation burden in the era of precision oncology in India.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23096-e23096
Author(s):  
Amit Verma ◽  
Nitesh Rohatgi ◽  
Pramod Kumar Julka ◽  
Meenu Walia ◽  
Ankur Bahl ◽  
...  
Keyword(s):  
Tyrosine Kinases ◽  
Mutation Frequency ◽  
Unknown Primary ◽  
Precision Oncology ◽  
Tumor Type ◽  
Genomic Profiling ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Comprehensive Genomic Profiling ◽  
Tumor Types

e23096 Background: Comprehensive genomic profiling (CGP) is gaining acceptability globally, but clinical experience in developing countries like India is limited. CGP identifies genomic alterations (GA), with tumor mutation burden (TMB) and microsatellite status (MSI), revealing therapeutic options such as targeted inhibitors and immunotherapies. We sought to evaluate the mutation frequency and actionability across tumors. Methods: Metastatic and/or refractory patients (referred to Personalized Cancer Medicine Clinic) underwent CGP analysis, including calculation of TMB and MSI, using a targeted NGS panel (FoundationOne, 53 samples; FoundationOne Heme, 4 samples). This panel detects all relevant classes of GA: base substitutions, small indels, rearrangements and copy number changes. Mutation frequencies were compared with the larger Foundation database. TMB status was reported as low (≤5 mutations/Mb), intermediate (6-19 mut/Mb) or high (≥20 mut/Mb). Results: The most common tumor types were lung (23%), breast (14%) and sarcoma (12%); other tumor types, including unknown primary constituted the rest (51%). Most samples were from metastatic sites (60%). Oncogenic GA were found in 131 genes across all tumor subtypes and affected major pathways: apoptosis/cell cycle (31%), PI3K (14%), transcriptional regulation (13%), and receptor tyrosine kinases (10%). Among these GA, 38 were considered actionable and were distributed across 43 (75%) samples. Therapies with FDA approval for the tumor type analyzed were indicated for 18 samples; an additional 25 samples had GA associated with therapies FDA approved for another indication. More than 1 actionable GA was identified in 24/43 (56%). TMB status was low in 36 (63%), intermediate in 19 (33%) and high in 2 (3.5%). High TMB status correlated with high MSI status (p < 0.001). Trend observed in the mutation frequency was comparable with the larger Foundation database. Conclusions: This is the first study in India showing CGP identified actionable targets associated with FDA approved therapies in approx. 32% of cases. TMB status identified 2/57 samples with high mutation burden for whom immunotherapy might be relevant.

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