Publications by authors named "Aijazuddin Syed"

Cytomorphological analysis of the bone marrow aspirate (BMA) is pivotal for the diagnostic workup of a broad range of hematological disorders. However, this skill is error prone, highly complex, and time consuming. Deep learning-based models for the automatic classification of bone marrow cell morphology demonstrate the potential to improve diagnostic efficiency and accuracy.

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Clinical bioinformaticians have come to play an essential role in clinical molecular diagnostic laboratories. However, the core knowledge needed for the clinical practice and training of this emerging group of professionals has not been previously established. Clinical laboratories are subject to a complex set of legal and accreditation requirements from numerous governmental and nongovernmental bodies that cover the generation, processing, storage, and distribution of patient data in the form of test results and intermediate data files.

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Background: Craniofacial osteosarcomas (CFOS) are uncommon malignant neoplasms of the head and neck with different clinical presentation, biological behavior and prognosis from conventional osteosarcomas of long bones. Very limited genetic data have been published on CFOS.

Methods: In the current study, we performed comprehensive genomic studies in 15 cases of high-grade CFOS by SNP array and targeted next generation sequencing.

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Article Synopsis
  • The study introduces a new model called Genome-Derived-Diagnosis Ensemble (GDD-ENS) that uses genomic features from a large dataset of solid tumors (39,787 samples) to accurately classify tumor types.
  • GDD-ENS achieves 93% accuracy predicting 38 different cancer types, making it a promising alternative to traditional whole-genome sequencing methods that are less practical for clinical use.
  • The model not only classifies common tumor types but also aids in diagnosing rare cancers and incorporates patient-specific clinical information, enhancing its utility in real-time treatment decisions.
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Unlabelled: There is a continuing debate about the proportion of cancer patients that benefit from precision oncology, attributable in part to conflicting views as to which molecular alterations are clinically actionable. To quantify the expansion of clinical actionability since 2017, we annotated 47,271 solid tumors sequenced with the MSK-IMPACT clinical assay using two temporally distinct versions of the OncoKB knowledge base deployed 5 years apart. Between 2017 and 2022, we observed an increase from 8.

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Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a dataset of 39,787 solid tumors sequenced using a clinical targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks.

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Background: Genetic testing (GT) for hereditary cancer predisposition is traditionally performed on selected genes based on established guidelines for each cancer type. Recently, expanded GT (eGT) using large hereditary cancer gene panels uncovered hereditary predisposition in a greater proportion of patients than previously anticipated. We sought to define the diagnostic yield of eGT and its clinical relevance in a broad cancer patient population over a 5-year period.

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Human cancers arise from environmental, heritable and somatic factors, but how these mechanisms interact in tumorigenesis is poorly understood. Studying 17,152 prospectively sequenced patients with cancer, we identified pathogenic germline variants in cancer predisposition genes, and assessed their zygosity and co-occurring somatic alterations in the concomitant tumors. Two major routes to tumorigenesis were apparent.

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Circulating cell-free DNA from blood plasma of cancer patients can be used to non-invasively interrogate somatic tumor alterations. Here we develop MSK-ACCESS (Memorial Sloan Kettering - Analysis of Circulating cfDNA to Examine Somatic Status), an NGS assay for detection of very low frequency somatic alterations in 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.

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Article Synopsis
  • * Researchers found that exposure to different environments, like smoking or specific cancer treatments, influences which mutations are selected, with notable differences in mutation types related to those exposures.
  • * Analysis of sequential samples shows that clones with mutations linked to DNA damage response can outcompete others during treatment, highlighting the importance of clinical sequencing to identify patients at higher risk for tMNs.
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Importance: Diagnosing the site of origin for cancer is a pillar of disease classification that has directed clinical care for more than a century. Even in an era of precision oncologic practice, in which treatment is increasingly informed by the presence or absence of mutant genes responsible for cancer growth and progression, tumor origin remains a critical factor in tumor biologic characteristics and therapeutic sensitivity.

Objective: To evaluate whether data derived from routine clinical DNA sequencing of tumors could complement conventional approaches to enable improved diagnostic accuracy.

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Driver mutations in oncogenes encode proteins with gain-of-function properties that enhance fitness. Heterozygous mutations are thus viewed as sufficient for tumorigenesis. We describe widespread oncogenic mutant allele imbalance in 13,448 prospectively characterized cancers.

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Metastatic colorectal cancers (mCRCs) are clinically heterogeneous, but the genomic basis of this variability remains poorly understood. We performed prospective targeted sequencing of 1,134 CRCs. We identified splice alterations in intronic regions of APC and large in-frame deletions in CTNNB1, increasing oncogenic WNT pathway alterations to 96% of CRCs.

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Importance: Guidelines for cancer genetic testing based on family history may miss clinically actionable genetic changes with established implications for cancer screening or prevention.

Objective: To determine the proportion and potential clinical implications of inherited variants detected using simultaneous sequencing of the tumor and normal tissue ("tumor-normal sequencing") compared with genetic test results based on current guidelines.

Design, Setting, And Participants: From January 2014 until May 2016 at Memorial Sloan Kettering Cancer Center, 10 336 patients consented to tumor DNA sequencing.

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Purpose: A long natural history and a predominant osseous pattern of metastatic spread are impediments to the adoption of precision medicine in patients with prostate cancer. To establish the feasibility of clinical genomic profiling in the disease, we performed targeted deep sequencing of tumor and normal DNA from patients with locoregional, metastatic non-castrate, and metastatic castration-resistant prostate cancer (CRPC).

Methods: Patients consented to genomic analysis of their tumor and germline DNA.

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Clonal hematopoiesis (CH), as evidenced by recurrent somatic mutations in leukemia-associated genes, commonly occurs among aging human hematopoietic stem cells. We analyzed deep-coverage, targeted, next-generation sequencing (NGS) data of paired tumor and blood samples from 8,810 individuals to assess the frequency and clinical relevance of CH in patients with non-hematologic malignancies. We identified CH in 25% of cancer patients, with 4.

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Background: The growing number of Next Generation Sequencing (NGS) tests is transforming the routine clinical diagnosis of hereditary cancers. Identifying whether a cancer is the result of an underlying disease-causing mutation in a cancer predisposition gene is not only diagnostic for a cancer predisposition syndrome, but also has significant clinical implications in the clinical management of patients and their families.

Methods: Here, we evaluated the performance of MSK-IMPACT (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) in detecting genetic alterations in 76 genes implicated in cancer predisposition syndromes.

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Tumor molecular profiling is a fundamental component of precision oncology, enabling the identification of genomic alterations in genes and pathways that can be targeted therapeutically. The existence of recurrent targetable alterations across distinct histologically defined tumor types, coupled with an expanding portfolio of molecularly targeted therapies, demands flexible and comprehensive approaches to profile clinically relevant genes across the full spectrum of cancers. We established a large-scale, prospective clinical sequencing initiative using a comprehensive assay, MSK-IMPACT, through which we have compiled tumor and matched normal sequence data from a unique cohort of more than 10,000 patients with advanced cancer and available pathological and clinical annotations.

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Purpose Owing to its exquisite chemotherapy sensitivity, most patients with metastatic germ cell tumors (GCTs) are cured with cisplatin-based chemotherapy. However, up to 30% of patients with advanced GCT exhibit cisplatin resistance, which requires intensive salvage treatment, and have a 50% risk of cancer-related death. To identify a genetic basis for cisplatin resistance, we performed whole-exome and targeted sequencing of cisplatin-sensitive and cisplatin-resistant GCTs.

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Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease.

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Translational bioinformatics and clinical research (biomedical) informatics are the primary domains related to informatics activities that support translational research. Translational bioinformatics focuses on computational techniques in genetics, molecular biology, and systems biology. Clinical research (biomedical) informatics involves the use of informatics in discovery and management of new knowledge relating to health and disease.

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The identification of specific genetic alterations as key oncogenic drivers and the development of targeted therapies are together transforming clinical oncology and creating a pressing need for increased breadth and throughput of clinical genotyping. Next-generation sequencing assays allow the efficient and unbiased detection of clinically actionable mutations. To enable precision oncology in patients with solid tumors, we developed Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT), a hybridization capture-based next-generation sequencing assay for targeted deep sequencing of all exons and selected introns of 341 key cancer genes in formalin-fixed, paraffin-embedded tumors.

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Amplicon-based methods for targeted resequencing of cancer genes have gained traction in the clinic as a strategy for molecular diagnostic testing. An 847-amplicon panel was designed with the RainDance DeepSeq system, covering most exons of 28 genes relevant to acute myeloid leukemia and myeloproliferative neoplasms. We developed a paired-sample analysis pipeline for variant calling and sought to assess its sensitivity and specificity relative to a set of samples with previously identified mutations.

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In the current genomics era, protein and DNA sequence databases are continuously growing at an exponential rate. It has become increasingly important and useful to repeat similarity searches at frequent intervals, which then retrieve larger and larger sets of results. In addition, sequence similarity searches are now often performed with many sequences or even whole genomes.

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