Publications by authors named "Tali Mazor"

Tumors may contain billions of cells, including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA).

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Article Synopsis
  • A study conducted at Dana-Farber/Boston Children's Cancer and Blood Disorders Center focused on classifying pediatric solid tumor diagnoses and analyzing genomic mutations to improve clinical trial design and treatment options.
  • Over 6.5 years, the research included 888 pediatric cancer patients, revealing that 33% had genomic variants that aligned with precision oncology trials, while 14% received targeted therapies.
  • The findings stress the significance of using genomic data for enhancing treatment strategies and the necessity for data sharing, particularly for addressing rare pediatric cancers in clinical settings.
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Purpose: Precision oncology clinical trials often struggle to accrue, partly because it is difficult to find potentially eligible patients at moments when they need new treatment. We piloted deployment of artificial intelligence tools to identify such patients at a large academic cancer center.

Patients And Methods: Neural networks that process radiology reports to identify patients likely to start new systemic therapy were applied prospectively for patients with solid tumors that had undergone next-generation sequencing at our center.

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Article Synopsis
  • International cancer registries, like AACR Project GENIE, provide access to genomic and clinical data from over 130,000 cancer patients, but analyzing this combined data can be tricky.
  • The cBioPortal for Cancer Genomics has improved its features to help visualize and analyze longitudinal clinical and genomic data, allowing users to see how treatment impacts patient outcomes over time.
  • These enhancements enable researchers and clinicians to explore complex datasets, fostering discoveries on how specific genomic changes affect cancer prognosis and treatment effectiveness.
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Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA).

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Purpose: With the growing number of available targeted therapeutics and molecular biomarkers, the optimal care of patients with cancer now depends on a comprehensive understanding of the rapidly evolving landscape of precision oncology, which can be challenging for oncologists to navigate alone.

Methods: We developed and implemented a precision oncology decision support system, GI TARGET, (Gastrointestinal Treatment Assistance Regarding Genomic Evaluation of Tumors) within the Gastrointestinal Cancer Center at the Dana-Farber Cancer Institute. With a multidisciplinary team, we systematically reviewed tumor molecular profiling for GI tumors and provided molecularly informed clinical recommendations, which included identifying appropriate clinical trials aided by the computational matching platform MatchMiner, suggesting targeted therapy options on or off the US Food and Drug Administration-approved label, and consideration of additional or orthogonal molecular testing.

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Widespread, comprehensive sequencing of patient tumors has facilitated the usage of precision medicine (PM) drugs to target specific genomic alterations. Therapeutic clinical trials are necessary to test new PM drugs to advance precision medicine, however, the abundance of patient sequencing data coupled with complex clinical trial eligibility has made it challenging to match patients to PM trials. To facilitate enrollment onto PM trials, we developed MatchMiner, an open-source platform to computationally match genomically profiled cancer patients to PM trials.

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Unlabelled: The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain.

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A growing number of longitudinal cohort studies are generating data with extensive patient observations across multiple timepoints. Such data offers promising opportunities to better understand the progression of diseases. However, these observations are usually treated as general events in existing visual analysis tools.

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Motivation: Molecular profiling of patient tumors and liquid biopsies over time with next-generation sequencing technologies and new immuno-profile assays are becoming part of standard research and clinical practice. With the wealth of new longitudinal data, there is a critical need for visualizations for cancer researchers to explore and interpret temporal patterns not just in a single patient but across cohorts.

Results: To address this need we developed OncoThreads, a tool for the visualization of longitudinal clinical and cancer genomics and other molecular data in patient cohorts.

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The human placenta and its specialized cytotrophoblasts rapidly develop, have a compressed lifespan, govern pregnancy outcomes, and program the offspring's health. Understanding the molecular underpinnings of these behaviors informs development and disease. Profiling the extraembryonic epigenome and transcriptome during the 2nd and 3rd trimesters revealed H3K9 trimethylation overlapping deeply DNA hypomethylated domains with reduced gene expression and compartment-specific patterns that illuminated their functions.

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Background: Chemotherapy improves overall survival after surgery and radiotherapy for newly diagnosed high-risk IDH-mutant low-grade gliomas (LGGs), but a proportion of patients treated with temozolomide (TMZ) will develop recurrent tumors with TMZ-induced hypermutation. We aimed to determine the prevalence of TMZ-induced hypermutation at recurrence and prognostic implications.

Methods: We sequenced recurrent tumors from 82 patients with initially low-grade IDH-mutant gliomas who underwent reoperation and correlated hypermutation status with grade at recurrence and subsequent clinical outcomes.

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Article Synopsis
  • The development of OncoTree addresses the shortcomings of existing cancer classification systems, such as ICD-O and SNOMED-CT, by providing a modern platform suited for genomic sequencing results and oncology research.
  • OncoTree is an open-source system supported by a collaborative team of experts and is accessible through a web interface and API, making it user-friendly for various stakeholders in oncology.
  • With 868 tumor types across 32 organ sites, OncoTree is already being used by prominent institutions like AACR and Memorial Sloan Kettering, proving its utility in clinical and research settings.
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Background: mutant lower-grade gliomas (LGGs) evolve under the selective pressure of therapy, but well-characterized patient-derived cells (PDCs) modeling evolutionary stages are lacking. -mutant LGGs may develop therapeutic resistance associated with chemotherapy-driven hypermutation and malignant progression. The aim of this study was to establish and characterize PDCs, single-cell-derived PDCs (scPDCs), and xenografts (PDX) of -mutant recurrences representing distinct stages of tumor evolution.

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The evolutionary processes that drive universal therapeutic resistance in adult patients with diffuse glioma remain unclear. Here we analysed temporally separated DNA-sequencing data and matched clinical annotation from 222 adult patients with glioma. By analysing mutations and copy numbers across the three major subtypes of diffuse glioma, we found that driver genes detected at the initial stage of disease were retained at recurrence, whereas there was little evidence of recurrence-specific gene alterations.

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Background: Most patients with juvenile myelomonocytic leukemia (JMML) are curable only with allogeneic hematopoietic cell transplantation (HCT). However, the current standard conditioning regimen, busulfan-cyclophosphamide-melphalan (Bu-Cy-Mel), may be associated with higher risks of morbidity and mortality. ASCT1221 was designed to test whether the potentially less-toxic myeloablative conditioning regimen containing busulfan-fludarabine (Bu-Flu) would be associated with equivalent outcomes.

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Juvenile myelomonocytic leukemia (JMML) is a myeloproliferative disorder of childhood caused by mutations in the Ras pathway. Outcomes in JMML vary markedly from spontaneous resolution to rapid relapse after hematopoietic stem cell transplantation. Here, we hypothesized that DNA methylation patterns would help predict disease outcome and therefore performed genome-wide DNA methylation profiling in a cohort of 39 patients.

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Background: Rare multicentric lower-grade gliomas (LGGs) represent a unique opportunity to study the heterogeneity among distinct tumor foci in a single patient and to infer their origins and parallel patterns of evolution.

Methods: In this study, we integrate clinical features, histology, and immunohistochemistry for 4 patients with multicentric LGG, arising both synchronously and metachronously. For 3 patients we analyze the phylogeny of the lesions using exome sequencing, including one case with a total of 8 samples from the 2 lesions.

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mutation is the earliest genetic alteration in low-grade gliomas (LGGs), but its role in tumor recurrence is unclear. Mutant IDH1 drives overproduction of the oncometabolite d-2-hydroxyglutarate (2HG) and a CpG island (CGI) hypermethylation phenotype (G-CIMP). To investigate the role of mutant IDH1 at recurrence, we performed a longitudinal analysis of 50 mutant LGGs.

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Background: Activation of the phosphatidylinositol 3-kinase (PI3K)/mammalian target of rapamycin (mTOR) pathway is common in patients with low-grade gliomas (LGGs), but agents that inhibit this pathway, including mTOR inhibitors, have not been studied in this population.

Methods: Fifty-eight patients with pathologic evidence of recurrence after they had initially been diagnosed with World Health Organization (WHO) grade II gliomas were enrolled into a prospective phase 2 clinical trial and received daily everolimus (RAD001) for 1 year or until progression. Tissue at the time of enrollment was analyzed for markers of PI3K/mTOR pathway activation.

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Mutations in the isocitrate dehydrogenase genes IDH1 and IDH2 are among the first genetic alterations observed during the development of lower-grade glioma (LGG). LGG-associated IDH mutations confer gain-of-function activity by converting α-ketoglutarate to the oncometabolite R-2-hydroxyglutarate (2HG). Clinical samples and gene expression data from The Cancer Genome Atlas (TCGA) demonstrate reduced expression of cytotoxic T lymphocyte-associated genes and IFN-γ-inducible chemokines, including CXCL10, in IDH-mutated (IDH-MUT) tumors compared with IDH-WT tumors.

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Mutations in the isocitrate dehydrogenase gene IDH1 are common in low-grade glioma, where they result in the production of 2-hydroxyglutarate (2HG), disrupted patterns of histone methylation, and gliomagenesis. IDH1 mutations also cosegregate with mutations in the ATRX gene and the TERT promoter, suggesting that IDH mutation may drive the creation or selection of telomere-stabilizing events as part of immortalization/transformation process. To determine whether and how this may occur, we investigated the phenotype of pRb-/p53-deficient human astrocytes engineered with IDH1 wild-type (WT) or R132H-mutant (IDH1) genes as they progressed through their lifespan.

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