Publications by authors named "Debyani Chakravarty"

Nearly all pancreatic adenocarcinomas (PDAC) are genomically characterized by KRAS exon 2 mutations. Most patients with PDAC present with advanced disease and are treated with cytotoxic therapy. Genomic biomarkers prognostic of disease outcomes have been challenging to identify.

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The canonical model of tumor suppressor gene (TSG)-mediated oncogenesis posits that loss of both alleles is necessary for inactivation. Here, through allele-specific analysis of sequencing data from 48,179 cancer patients, we define the prevalence, selective pressure for, and functional consequences of biallelic inactivation across TSGs. TSGs largely assort into distinct classes associated with either pan-cancer (Class 1) or lineage-specific (Class 2) patterns of selection for biallelic loss, although some TSGs are predominantly monoallelically inactivated (Class 3/4).

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This article discusses the specific advances made in precision oncology in 2024. We comment on the evolving nature of predictive molecular events used to select patients who will most benefit clinically from treatment. We also discuss advances in the development of strategic treatment regimens for combination therapies, rational drug design of small-molecule inhibitors, and structurally informed drug repurposing.

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Article Synopsis
  • Researchers are merging unstructured patient data with structured health records to create the MSK-CHORD dataset, consisting of varied cancer types from nearly 25,000 patients at Memorial Sloan Kettering Cancer Center.
  • This dataset allows for in-depth analysis of cancer outcomes using advanced techniques like natural language processing, revealing new relationships that smaller datasets may not show.
  • Using MSK-CHORD for machine learning models, findings suggest that incorporating features from these unstructured texts can better predict patient survival than relying solely on genomic data or cancer staging.
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Genomic profiles and prognostic biomarkers in patients with acute myeloid leukemia (AML) from ancestry-diverse populations are underexplored. We analyzed the exomes and transcriptomes of 100 patients with AML with genomically confirmed African ancestry (Black; Alliance) and compared their somatic mutation frequencies with those of 323 self-reported white patients with AML, 55% of whom had genomically confirmed European ancestry (white; BeatAML). Here we find that 73% of 162 gene mutations recurrent in Black patients, including a hitherto unreported PHIP alteration detected in 7% of patients, were found in one white patient or not detected.

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  • The study investigates the role of microsatellite instability (MSI-H) in pancreatic cancer (PC) associated with Lynch syndrome (LS), focusing on both germline and somatic variants that affect mismatch repair genes.
  • It involves a retrospective analysis of 55 PC patients at Memorial Sloan Kettering Cancer Center, revealing that a significant portion of those with LS and somatic MMR variants exhibit MSI-H status, which could impact treatment responses to immune therapy.
  • Results showed that 59% of LS cohort patients had MSI-H, whereas 43% in the somatic MMR cohort had the same status, suggesting distinct genetic characteristics and age differences at diagnosis between the two groups.
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  • The last decade has seen significant advancements in genomic testing for cancer, leading to the discovery of driver mutations that can reveal treatment vulnerabilities in cancer cells.
  • These developments have fostered precision oncology, which tailors cancer care to individual molecular profiles, resulting in improved outcomes, yet genomic tests are still underused in routine care due to interpretation challenges.
  • The authors aim to provide practical guidelines to help clinicians understand and utilize genomic information effectively, while also addressing barriers to broader implementation of precision oncology in medical practice.
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This article presents a review of recent major advances in precision oncology and the future implications of these advances, specifying the iterative progress achieved from the end of 2022 through 2023. We discuss the different classes of precision oncology drugs and associated biomarkers as well as the improvements in clinical trial design that have enabled the efficient testing of these drugs.

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  • Genomic profiling of blood cancers has improved our understanding of the genetic changes that drive these diseases and has helped create better tools for patient treatment planning.*
  • Tumor-only sequencing methods often struggle to provide clear information on genetic variants, which can complicate clinical decisions for patient care.*
  • The MSK-IMPACT Heme cohort offers a detailed analysis of genetic alterations by comparing tumor and normal DNA, revealing key mutation patterns and enhancing our ability to make precise genetic diagnoses.*
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Cancer genomes from patients with African (AFR) ancestry have been poorly studied in clinical research. We leverage two large genomic cohorts to investigate the relationship between genomic alterations and AFR ancestry in six common cancers. Cross-cancer type associations, such as an enrichment of MYC amplification with AFR ancestry in lung, breast, and prostate cancers, and depletion of BRAF alterations are observed in colorectal and pancreatic cancers.

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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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Unlabelled: Although the incidence of endometrial carcinoma (EC) is similar in Black and White women, racial disparities are stark, with the highest mortality rates observed among Black patients. Here, analysis of 1,882 prospectively sequenced ECs using a clinical FDA-authorized tumor-normal panel revealed a significantly higher prevalence of high-risk histologic and molecular EC subtypes in self-identified Black (n = 259) compared with White (n = 1,623) patients. Clinically actionable alterations, including high tumor mutational burden/microsatellite instability, which confer benefit from immunotherapy, were less frequent in ECs from Black than from White patients.

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This article presents a review of the major advances and future implications in precision oncology accomplished in 2022 and centers on three primary pillars: advances in (i) rational drug design, (ii) study design, and (iii) novel biomarkers.

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Circulating tumor DNA (ctDNA) sequencing guides therapy decisions but has been studied mostly in small cohorts without sufficient follow-up to determine its influence on overall survival. We prospectively followed an international cohort of 1,127 patients with non-small-cell lung cancer and ctDNA-guided therapy. ctDNA detection was associated with shorter survival (hazard ratio (HR), 2.

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Purpose: Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications.

Experimental Design: GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes).

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Article Synopsis
  • - Accurate understanding of genetic ancestry is essential for addressing cancer disparities, and new methods using clinical sequencing panels allow for better integration of ancestry analysis in diagnostic settings.
  • - In a study of over 45,000 cancer patients, researchers found that ancestry influences the frequency of genetic mutations, revealing some known and novel associations, as well as differences in clinically actionable alterations.
  • - Despite similar rates of key genetic changes by ancestry group, a lower percentage of patients with African ancestry had actionable alterations compared to those with European ancestry, highlighting inequities in how precision oncology serves different populations.
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  • AKT is a crucial player in the PI-3K signaling pathway, and mutations in AKT are linked to various solid tumors, affecting cancer cell behavior and response to therapies.
  • The most common mutation, AKT1 E17K, makes tumors more responsive to AKT inhibitors, but other mutations' effects are not fully understood, complicating treatment approaches.
  • A study tested the AKT inhibitor capivasertib in patients with different AKT mutations, showing that while some mutations responded well to treatment, the effectiveness varied based on the mutation type and its activation mechanism.
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  • The ASCO provisional clinical opinion provides guidance on the use of tumor genomic testing for patients with metastatic or advanced solid tumors, especially following new research findings.
  • There is a growing number of cancer treatments that depend on specific genomic biomarkers, but there’s confusion regarding when and how to conduct genomic sequencing and interpret results.
  • Patients should get genomic sequencing from certified labs, especially if there are approved therapies tied to certain genomic alterations, and multigene panel assays are recommended when multiple treatment options are available.
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Base editing can be applied to characterize single nucleotide variants of unknown function, yet defining effective combinations of single guide RNAs (sgRNAs) and base editors remains challenging. Here, we describe modular base-editing-activity 'sensors' that link sgRNAs and cognate target sites in cis and use them to systematically measure the editing efficiency and precision of thousands of sgRNAs paired with functionally distinct base editors. By quantifying sensor editing across >200,000 editor-sgRNA combinations, we provide a comprehensive resource of sgRNAs for introducing and interrogating cancer-associated single nucleotide variants in multiple model systems.

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  • Metastatic progression is the leading cause of death in cancer patients, yet the specific genomic mechanisms behind it are not well understood.
  • Researchers analyzed data from over 25,000 cancer patients in the MSK-MET cohort, discovering connections between genomic changes and how various tumors spread in 50 different cancer types.
  • The study revealed that chromosomal instability is linked to metastatic spread in certain cancers (like prostate and lung adenocarcinomas) but not others (like colorectal cancer), providing insights into how these genomic alterations affect cancer progression and spread to specific organs.
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Purpose: Several professional societies have published guidelines for the clinical interpretation of somatic variants, which specifically address diagnostic, prognostic, and therapeutic implications. Although these guidelines for the clinical interpretation of variants include data types that may be used to determine the oncogenicity of a variant (eg, population frequency, functional, and in silico data or somatic frequency), they do not provide a direct, systematic, and comprehensive set of standards and rules to classify the oncogenicity of a somatic variant. This insufficient guidance leads to inconsistent classification of rare somatic variants in cancer, generates variability in their clinical interpretation, and, importantly, affects patient care.

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The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution.

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During the past decade, next-generation sequencing (NGS) technologies have become widely adopted in cancer research and clinical care. Common applications within the clinical setting include patient stratification into relevant molecular subtypes, identification of biomarkers of response and resistance to targeted and systemic therapies, assessment of heritable cancer risk based on known pathogenic variants, and longitudinal monitoring of treatment response. The need for efficient downstream processing and reliable interpretation of sequencing data has led to the development of novel algorithms and computational pipelines, as well as structured knowledge bases that link genomic alterations to currently available drugs and ongoing clinical trials.

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