Publications by authors named "Olivier Elemento"

324 Publications

Artificial intelligence in cancer research, diagnosis and therapy.

Nat Rev Cancer 2021 Sep 17. Epub 2021 Sep 17.

National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, TN, USA.

Standfirst: Artificial intelligence and machine learning techniques are breaking into biomedical research and health care, which importantly includes cancer research and oncology, where the potential applications are vast. These include detection and diagnosis of cancer, subtype classification, optimization of cancer treatment and identification of new therapeutic targets in drug discovery. While big data used to train machine learning models may already exist, leveraging this opportunity to realize the full promise of artificial intelligence in both the cancer research space and the clinical space will first require significant obstacles to be surmounted. In this Viewpoint article, we asked four experts for their opinions on how we can begin to implement artificial intelligence while ensuring standards are maintained so as transform cancer diagnosis and the prognosis and treatment of patients with cancer and to drive biological discovery.
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http://dx.doi.org/10.1038/s41568-021-00399-1DOI Listing
September 2021

The NF-κB transcriptional footprint is essential for SARS-CoV-2 replication.

J Virol 2021 Sep 15:JVI0125721. Epub 2021 Sep 15.

Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

SARS-CoV-2, the etiological agent of COVID-19, is characterized by a delay in Type I interferon (IFN-I)-mediated antiviral defenses alongside robust cytokine production. Here we investigate the underlying molecular basis for this imbalance and implicate virus-mediated activation of NF-κB in the absence of other canonical IFN-I-related transcription factors. Epigenetic and single cell transcriptomic analyses show a selective NF-κB signature that was most prominent in infected cells. Disruption of NF-κB signaling through the silencing of the NF-κB transcription factors p65 or p50 resulted in loss of virus replication that was rescued upon reconstitution. These findings could be further corroborated with the use of NF-κB inhibitors, which reduced SARS-CoV-2 replication . These data suggest that the robust cytokine production in response to SARS-CoV-2, despite a diminished IFN-I response, is the product of a dependency on NF-κB for viral replication. The COVID-19 pandemic has caused significant mortality and morbidity around the world. Although effective vaccines have been developed, large parts of the world remain unvaccinated while new SARS-CoV-2 strains keep emerging. Furthermore, despite extensive efforts and large-scale drug screenings, no fully effective antiviral treatment options have been discovered yet. Therefore, it is of the utmost importance to gain a better understanding of essential factors driving SARS-CoV-2 replication in order to be able to develop novel approaches to target SARS-CoV-2 biology.
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http://dx.doi.org/10.1128/JVI.01257-21DOI Listing
September 2021

Multi-platform profiling characterizes molecular subgroups and resistance networks in chronic lymphocytic leukemia.

Nat Commun 2021 Sep 13;12(1):5395. Epub 2021 Sep 13.

Department I for Internal Medicine and Centre for Integrated Oncology, University of Cologne, Cologne, Germany.

Knowledge of the genomic landscape of chronic lymphocytic leukemia (CLL) grows increasingly detailed, providing challenges in contextualizing the accumulated information. To define the underlying networks, we here perform a multi-platform molecular characterization. We identify major subgroups characterized by genomic instability (GI) or activation of epithelial-mesenchymal-transition (EMT)-like programs, which subdivide into non-inflammatory and inflammatory subtypes. GI CLL exhibit disruption of genome integrity, DNA-damage response and are associated with mutagenesis mediated through activation-induced cytidine deaminase or defective mismatch repair. TP53 wild-type and mutated/deleted cases constitute a transcriptionally uniform entity in GI CLL and show similarly poor progression-free survival at relapse. EMT-like CLL exhibit high genomic stability, reduced benefit from the addition of rituximab and EMT-like differentiation is inhibited by induction of DNA damage. This work extends the perspective on CLL biology and risk categories in TP53 wild-type CLL. Furthermore, molecular targets identified within each subgroup provide opportunities for new treatment approaches.
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http://dx.doi.org/10.1038/s41467-021-25403-yDOI Listing
September 2021

Reshaping of the androgen-driven chromatin landscape in normal prostate cells by early cancer drivers and effect on therapeutic sensitivity.

Cell Rep 2021 Sep;36(10):109625

Department of Urology, Weill Cornell Medicine, New York, NY 10065, USA; Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY 10065, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10065, USA. Electronic address:

The normal androgen receptor (AR) cistrome and transcriptional program are fundamentally altered in prostate cancer (PCa). Here, we profile the chromatin landscape and AR-directed transcriptional program in normal prostate cells and show the impact of SPOP mutations, an early event in prostate tumorigenesis. In genetically normal mouse prostate organoids, SPOP mutation results in accessibility and AR binding patterns similar to that of human PCa. Consistent with dependence on AR signaling, castration of SPOP mutant mouse models results in the loss of neoplastic phenotypes, and human SPOP mutant PCa shows a favorable response to AR-targeted therapies. Together, these data validate mouse prostate organoids as a robust model for studying epigenomic and transcriptional alterations in normal prostate, provide valuable datasets for further studies, and show that a single genomic alteration may be sufficient to reprogram the chromatin of normal prostate cells toward oncogenic phenotypes, with potential therapeutic implications for AR-targeting therapies.
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http://dx.doi.org/10.1016/j.celrep.2021.109625DOI Listing
September 2021

Molecular Evaluation of Low-grade Low-stage Endometrial Cancer With and Without Recurrence.

Int J Gynecol Pathol 2021 Sep 6. Epub 2021 Sep 6.

Department of Pathology and Laboratory Medicine (C.E.M., K.O., S.Motanagh, S.Mirabelli, B.H., L.H.E., J.M.M.) Institute for Computational Biomedicine (K.W.E., P.C., A.S., O.E.); Departments of Obstetrics and Gynecology (S.C.P., D.G., E.C.D., K.H., A.S.); Physiology and Biophysics (A.S.), Weill Cornell Medicine Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine and NewYork Presbyterian (K.O., K.W.E., P.C., S.M., A.Sigaras, A.Sboner, O.E., L.H.E., J.M.M.) Weill Cornell Medicine (S.M.G.), New York, New York Cancer Genetics Incorporated, Rutherford, New Jersey (B.K.).

Low-grade, low-stage endometrioid carcinomas (LGLS EC) demonstrate 5-yr survival rates up to 95%. However, a small subset of these tumors recur, and little is known about prognostic markers or established mutation profiles associated with recurrence. The goal of the current study was to identify the molecular profiles of the primary carcinomas and the genomic differences between primary tumors and subsequent recurrences. Four cases of LGLS EC with recurrence and 8 cases without recurrence were evaluated via whole-exome sequencing. Three of the 4 recurrent tumors were evaluated via Oncomine Comprehensive Assay. The resulting molecular profiles of the primary and recurrent tumors were compared. Two of the 3 recurrent cases showed additional mutations in the recurrence. One recurrent tumor included an additional TP53 mutation and the other recurrent tumor showed POLE and DDR2 kinase gene mutation. The POLE mutation occurred outside the exonuclease domain. PIK3CA mutations were detected in 4 of 4 primary LGLS EC with recurrence and in 3 of 8 disease-free cases. LGLS EC with recurrence showed higher MSIsensor scores compared with LGLS without recurrence. The level of copy number gains in LGLS EC with recurrence was larger than LGLS EC without recurrence. This pilot study showed 1 of 3 recurrent cases gained a mutation associated with genetic instability (TP53) and 1 of them also acquired a mutation in the DDR2 kinase, a potential therapeutic target. We also noted a higher level of copy number gains, MSIsensor scores and PIK3CA mutations in the primary tumors that later recurred.
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http://dx.doi.org/10.1097/PGP.0000000000000798DOI Listing
September 2021

The role of machine learning in clinical research: transforming the future of evidence generation.

Trials 2021 Aug 16;22(1):537. Epub 2021 Aug 16.

Vector Institute, University of Toronto, Toronto, Ontario, Canada.

Background: Interest in the application of machine learning (ML) to the design, conduct, and analysis of clinical trials has grown, but the evidence base for such applications has not been surveyed. This manuscript reviews the proceedings of a multi-stakeholder conference to discuss the current and future state of ML for clinical research. Key areas of clinical trial methodology in which ML holds particular promise and priority areas for further investigation are presented alongside a narrative review of evidence supporting the use of ML across the clinical trial spectrum.

Results: Conference attendees included stakeholders, such as biomedical and ML researchers, representatives from the US Food and Drug Administration (FDA), artificial intelligence technology and data analytics companies, non-profit organizations, patient advocacy groups, and pharmaceutical companies. ML contributions to clinical research were highlighted in the pre-trial phase, cohort selection and participant management, and data collection and analysis. A particular focus was paid to the operational and philosophical barriers to ML in clinical research. Peer-reviewed evidence was noted to be lacking in several areas.

Conclusions: ML holds great promise for improving the efficiency and quality of clinical research, but substantial barriers remain, the surmounting of which will require addressing significant gaps in evidence.
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http://dx.doi.org/10.1186/s13063-021-05489-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8365941PMC
August 2021

Functional comparison of exome capture-based methods for transcriptomic profiling of formalin-fixed paraffin-embedded tumors.

NPJ Genom Med 2021 Aug 12;6(1):66. Epub 2021 Aug 12.

Department of Medicine, Division of Hematology and Medical Oncology, Weill Cornell Medicine, New York, NY, USA.

The availability of fresh frozen (FF) tissue is a barrier for implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. We performed transcriptomic analysis of 32 FFPE tumor samples from 11 patients using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to the TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable gene transcripts, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). The Agilent and IDT assays detected all the clinically relevant fusions that were initially identified in FF-TruSeq. All FFPE exome capture-based methods had comparable performance and concordance with FF-TruSeq. Our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.
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http://dx.doi.org/10.1038/s41525-021-00231-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8360986PMC
August 2021

A polygenic-score-based approach for identification of gene-drug interactions stratifying breast cancer risk.

Am J Hum Genet 2021 09 6;108(9):1752-1764. Epub 2021 Aug 6.

Tri-Institutional Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY 10021, USA; Institute of Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA. Electronic address:

An individual's genetics can dramatically influence breast cancer (BC) risk. Although clinical measures for prevention do exist, non-invasive personalized measures for reducing BC risk are limited. Commonly used medications are a promising set of modifiable factors, but no previous study has explored whether a range of widely taken approved drugs modulate BC genetics. In this study, we describe a quantitative framework for exploring the interaction between the genetic susceptibility of BC and medication usage among UK Biobank women. We computed BC polygenic scores (PGSs) that summarize BC genetic risk and find that the PGS explains nearly three-times greater variation in disease risk within corticosteroid users compared to non-users. We map 35 genes significantly interacting with corticosteroid use (FDR < 0.1), highlighting the transcription factor NRF2 as a common regulator of gene-corticosteroid interactions in BC. Finally, we discover a regulatory variant strongly stratifying BC risk according to corticosteroid use. Within risk allele carriers, 18.2% of women taking corticosteroids developed BC, compared to 5.1% of the non-users (with an HR = 3.41 per-allele within corticosteroid users). In comparison, there are no differences in BC risk within the reference allele homozygotes. Overall, this work highlights the clinical relevance of gene-drug interactions in disease risk and provides a roadmap for repurposing biobanks in drug repositioning and precision medicine.
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http://dx.doi.org/10.1016/j.ajhg.2021.07.008DOI Listing
September 2021

Blood Biomarkers Reflect the Effects of Obesity and Inflammation on the Human Breast Transcriptome.

Carcinogenesis 2021 Jul 27. Epub 2021 Jul 27.

Retired, Department of Medicine, Weill Cornell Medical College, New York, New York.

Obesity is a risk factor for the development of post-menopausal breast cancer. Breast white adipose tissue (WAT) inflammation, which is commonly found in women with excess body fat, is also associated with increased breast cancer risk. Both local and systemic effects are likely to be important for explaining the link between excess body fat, adipose inflammation and breast cancer. The first goal of this cross-sectional study of 196 women was to carry out transcriptome profiling to define the molecular changes that occur in the breast related to excess body fat and WAT inflammation. A second objective was to determine if commonly measured blood biomarkers of risk and prognosis reflect molecular changes in the breast. Breast WAT inflammation was assessed by immunohistochemistry. Bulk RNA-sequencing was carried out to assess gene expression in non-tumorous breast. Obesity and WAT inflammation were associated with a large number of differentially expressed genes and changes in multiple pathways linked to the development and progression of breast cancer. Altered pathways included inflammatory response, complement, KRAS signaling, TNFα signaling via NFкB, IL6-JAK-STAT3 signaling, epithelial mesenchymal transition, angiogenesis, interferon γ response, and TGF-β signaling. Increased expression of several drug targets such as aromatase, TGF-β1, IDO-1 and PD-1 were observed. Levels of various blood biomarkers including hsCRP, IL6, leptin, adiponectin, triglycerides, HDL cholesterol and insulin were altered and correlated with molecular changes in the breast. Collectively, this study helps to explain both the link between obesity and breast cancer and the utility of blood biomarkers for determining risk and prognosis.
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http://dx.doi.org/10.1093/carcin/bgab066DOI Listing
July 2021

Validation of a Circulating Tumor DNA-Based Next-Generation Sequencing Assay in a Cohort of Patients with Solid tumors: A Proposed Solution for Decentralized Plasma Testing.

Oncologist 2021 Jul 19. Epub 2021 Jul 19.

Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, New York, New York, USA.

Background: Characterization of circulating tumor DNA (ctDNA) has been integrated into clinical practice. Although labs have standardized validation procedures to develop single locus tests, the efficacy of on-site plasma-based next-generation sequencing (NGS) assays still needs to be proved.

Materials And Methods: In this retrospective study, we profiled DNA from matched tissue and plasma samples from 75 patients with cancer. We applied an NGS test that detects clinically relevant alterations in 33 genes and microsatellite instability (MSI) to analyze plasma cell-free DNA (cfDNA).

Results: The concordance between alterations detected in both tissue and plasma samples was higher in patients with metastatic disease. The NGS test detected 77% of sequence alterations, amplifications, and fusions that were found in metastatic samples compared with 45% of those alterations found in the primary tumor samples (p = .00005). There was 87% agreement on MSI status between the NGS test and tumor tissue results. In three patients, MSI-high ctDNA correlated with response to immunotherapy. In addition, the NGS test revealed an FGFR2 amplification that was not detected in tumor tissue from a patient with metastatic gastric cancer, emphasizing the importance of profiling plasma samples in patients with advanced cancer.

Conclusion: Our validation experience of a plasma-based NGS assay advances current knowledge about translating cfDNA testing into clinical practice and supports the application of plasma assays in the management of oncology patients with metastatic disease. With an in-house method that minimizes the need for invasive procedures, on-site cfDNA testing supplements tissue biopsy to guide precision therapy and is entitled to become a routine practice.

Implications For Practice: This study proposes a solution for decentralized liquid biopsy testing based on validation of a next-generation sequencing (NGS) test that detects four classes of genomic alterations in blood: sequence mutations (single nucleotide substitutions or insertions and deletions), fusions, amplifications, and microsatellite instability (MSI). Although there are reference labs that perform single-site comprehensive liquid biopsy testing, the targeted assay this study validated can be established locally in any lab with capacity to offer clinical molecular pathology assays. To the authors' knowledge, this is the first report that validates evaluating an on-site plasma-based NGS test that detects the MSI status along with common sequence alterations encountered in solid tumors.
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http://dx.doi.org/10.1002/onco.13905DOI Listing
July 2021

Clinical interpretation of whole-genome and whole-transcriptome sequencing for precision oncology.

Semin Cancer Biol 2021 Jul 10. Epub 2021 Jul 10.

Institute for Computational Biomedicine, Weill Cornell Medicine, New York, United States; Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, United States. Electronic address:

Whole-genome sequencing either alone or in combination with whole-transcriptome sequencing has started to be used to analyze clinical tumor samples to improve diagnosis, provide risk stratification, and select patient-specific therapies. Compared with current genomic testing strategies, largely focused on small number of genes tested individually or targeted panels, whole-genome and transcriptome sequencing (WGTS) provides novel opportunities to identify and report a potentially much larger number of actionable alterations with diagnostic, prognostic, and/or predictive impact. Such alterations include point mutations, indels, copy- number aberrations and structural variants, but also germline variants, fusion genes, noncoding alterations and mutational signatures. Nevertheless, these comprehensive tests are accompanied by many challenges ranging from the extent and diversity of sequence alterations detected by these methods to the complexity and limited existing standardization in interpreting them. We describe the challenges of WGTS interpretation and the opportunities with comprehensive genomic testing.
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http://dx.doi.org/10.1016/j.semcancer.2021.07.003DOI Listing
July 2021

Diet-regulated production of PDGFcc by macrophages controls energy storage.

Science 2021 07;373(6550)

Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA.

The mechanisms by which macrophages regulate energy storage remain poorly understood. We identify in a genetic screen a platelet-derived growth factor (PDGF)/vascular endothelial growth factor (VEGF)-family ortholog, Pvf3, that is produced by macrophages and is required for lipid storage in fat-body cells of larvae. Genetic and pharmacological experiments indicate that the mouse Pvf3 ortholog PDGFcc, produced by adipose tissue-resident macrophages, controls lipid storage in adipocytes in a leptin receptor- and C-C chemokine receptor type 2-independent manner. PDGFcc production is regulated by diet and acts in a paracrine manner to control lipid storage in adipose tissues of newborn and adult mice. At the organismal level upon PDGFcc blockade, excess lipids are redirected toward thermogenesis in brown fat. These data identify a macrophage-dependent mechanism, conducive to the design of pharmacological interventions, that controls energy storage in metazoans.
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http://dx.doi.org/10.1126/science.abe9383DOI Listing
July 2021

Building biorepositories in the midst of a pandemic.

J Clin Transl Sci 2021 Feb 5;5(1):e92. Epub 2021 Feb 5.

Clinical & Translational Science Center, Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, USA.

Biospecimen repositories play a vital role in enabling investigation of biologic mechanisms, identification of disease-related biomarkers, advances in diagnostic assays, recognition of microbial evolution, and characterization of new therapeutic targets for intervention. They rely on the complex integration of scientific need, regulatory oversight, quality control in collection, processing and tracking, and linkage to robust phenotype information. The COVID-19 pandemic amplified many of these considerations and illuminated new challenges, all while academic health centers were trying to adapt to unprecedented clinical demands and heightened research constraints not witnessed in over 100 years. The outbreak demanded rapid understanding of SARS-CoV-2 to develop diagnostics and therapeutics, prompting the immediate need for access to high quality, well-characterized COVID-19-associated biospecimens. We surveyed 60 Clinical and Translational Science Award (CTSA) hubs to better understand the strategies and barriers encountered in biobanking before and in response to the COVID-19 pandemic. Feedback revealed a major shift in biorepository model, specimen-acquisition and consent process from a combination of investigator-initiated and institutional protocols to an enterprise-serving strategy. CTSA hubs were well equipped to leverage established capacities and expertise to quickly respond to the scientific needs of this crisis through support of institutional approaches in biorepository management.
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http://dx.doi.org/10.1017/cts.2021.6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134891PMC
February 2021

Clinical utility of whole-genome sequencing in precision oncology.

Semin Cancer Biol 2021 Jun 25. Epub 2021 Jun 25.

NIHR Oxford Biomedical Research Centre and Department of Oncology, University of Oxford, Oxford, United Kingdom. Electronic address:

Precision diagnostics is one of the two pillars of precision medicine. Sequencing efforts in the past decade have firmly established cancer as a primarily genetically driven disease. This concept is supported by therapeutic successes aimed at particular pathways that are perturbed by specific driver mutations in protein-coding domains and reflected in three recent FDA tissue agnostic cancer drug approvals. In addition, there is increasing evidence from studies that interrogate the entire genome by whole-genome sequencing that acquired global and complex genomic aberrations including those in non-coding regions of the genome might also reflect clinical outcome. After addressing technical, logistical, financial and ethical challenges, national initiatives now aim to introduce clinical whole-genome sequencing into real-world diagnostics as a rational and potentially cost-effective tool for response prediction in cancer and to identify patients who would benefit most from 'expensive' targeted therapies and recruitment into clinical trials. However, so far, this has not been accompanied by a systematic and prospective evaluation of the clinical utility of whole-genome sequencing within clinical trials of uniformly treated patients of defined clinical outcome. This approach would also greatly facilitate novel predictive biomarker discovery and validation, ultimately reducing size and duration of clinical trials and cost of drug development. This manuscript is the third in a series of three to review and critically appraise the potential and challenges of clinical whole-genome sequencing in solid tumors and hematological malignancies.
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http://dx.doi.org/10.1016/j.semcancer.2021.06.018DOI Listing
June 2021

Characterization of GECPAR, a noncoding RNA that regulates the transcriptional program of diffuse large B cell lymphoma.

Haematologica 2021 Jun 24. Epub 2021 Jun 24.

Institute of Oncology Research, Faculty of Biomedical Sciences, USI, Bellinzona, Switzerland; Oncology Institute of Southern Switzerland, Bellinzona.

Enhancers are regulatory regions of DNA, which play a key role in cell-type specific differentiation and development. Most active enhancers are transcribed into enhancer RNAs (eRNAs) that can regulate transcription of target genes by means of in cis as well as in trans action. eRNAs stabilize contacts between distal genomic regions and mediate the interaction of DNA with master transcription factors. Here, we characterised an enhancer RNA, GECPAR (GErminal Center Proliferative Adapter RNA), that is specifically transcribed in normal and neoplastic germinal center B-cells from the super-enhancer of POU2AF1, a key regulatory gene of the germinal center reaction. Using diffuse large B cell lymphoma cell line models, we demonstrated the tumor suppressor activity of GECPAR, which is mediated via its transcriptional regulation of proliferation and differentiation genes, particularly MYC and the Wnt pathway.
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http://dx.doi.org/10.3324/haematol.2020.267096DOI Listing
June 2021

Analytical demands to use whole-genome sequencing in precision oncology.

Semin Cancer Biol 2021 Jun 10. Epub 2021 Jun 10.

MLL Munich Leukemia Laboratory, Munich, Germany. Electronic address:

Interrogating the tumor genome in its entirety by whole-genome sequencing (WGS) offers an unprecedented insight into the biology and pathogenesis of cancer, with potential impact on diagnostics, prognostication and therapy selection. WGS is able to detect sequence as well as structural variants and thereby combines central domains of cytogenetics and molecular genetics. Given the potential of WGS in directing targeted therapeutics and clinical decision-making, we envision a gradual transition of the method from research to clinical routine. This review is one out of three within this issue aimed at facilitating this effort, by discussing in-depth analytical validation, clinical interpretation and clinical utility of WGS. The review highlights the requirements for implementing, validating and maintaining a clinical WGS pipeline to obtain high-quality patient-specific data in accordance with the local regulatory landscape. Every step of the WGS pipeline, which includes DNA extraction, library preparation, sequencing, bioinformatics analysis, and data storage, is considered with respect to its logistics, necessities, potential pitfalls, and the required quality management. WGS is likely to drive clinical diagnostics and patient care forward, if requirements and challenges of the technique are recognized and met.
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http://dx.doi.org/10.1016/j.semcancer.2021.06.009DOI Listing
June 2021

Temporal evolution of cellular heterogeneity during the progression to advanced AR-negative prostate cancer.

Nat Commun 2021 06 7;12(1):3372. Epub 2021 Jun 7.

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.

Despite advances in the development of highly effective androgen receptor (AR)-directed therapies for the treatment of men with advanced prostate cancer, acquired resistance to such therapies frequently ensues. A significant subset of patients with resistant disease develop AR-negative tumors that lose their luminal identity and display neuroendocrine features (neuroendocrine prostate cancer (NEPC)). The cellular heterogeneity and the molecular evolution during the progression from AR-positive adenocarcinoma to AR-negative NEPC has yet to be characterized. Utilizing a new genetically engineered mouse model, we have characterized the synergy between Rb1 loss and MYCN (encodes N-Myc) overexpression which results in the formation of AR-negative, poorly differentiated tumors with high metastatic potential. Single-cell-based approaches revealed striking temporal changes to the transcriptome and chromatin accessibility which have identified the emergence of distinct cell populations, marked by differential expression of Ascl1 and Pou2f3, during the transition to NEPC. Moreover, global DNA methylation and the N-Myc cistrome are redirected following Rb1 loss. Altogether, our data provide insight into the progression of prostate adenocarcinoma to NEPC.
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http://dx.doi.org/10.1038/s41467-021-23780-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185096PMC
June 2021

Targeting the epichaperome as an effective precision medicine approach in a novel PML-SYK fusion acute myeloid leukemia.

NPJ Precis Oncol 2021 May 26;5(1):44. Epub 2021 May 26.

Department of Medicine, Division of Hematology/Oncology, Weill Cornell Medicine, New York, NY, USA.

The epichaperome is a new cancer target composed of hyperconnected networks of chaperome members that facilitate cell survival. Cancers with an altered chaperone configuration may be susceptible to epichaperome inhibitors. We developed a flow cytometry-based assay for evaluation and monitoring of epichaperome abundance at the single cell level, with the goal of prospectively identifying patients likely to respond to epichaperome inhibitors, to measure target engagement, and dependency during treatment. As proof of principle, we describe a patient with an unclassified myeloproliferative neoplasm harboring a novel PML-SYK fusion, who progressed to acute myeloid leukemia despite chemotherapy and allogeneic stem cell transplant. The leukemia was identified as having high epichaperome abundance. We obtained compassionate access to an investigational epichaperome inhibitor, PU-H71. After 16 doses, the patient achieved durable complete remission. These encouraging results suggest that further investigation of epichaperome inhibitors in patients with abundant baseline epichaperome levels is warranted.
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http://dx.doi.org/10.1038/s41698-021-00183-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8155064PMC
May 2021

Towards artificial intelligence-driven pathology assessment for hematological malignancies.

Authors:
Olivier Elemento

Blood Cancer Discov 2021 May 22;2(3):195-197. Epub 2021 Mar 22.

Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021.

In this issue of Blood Cancer Discovery, Brück applied unsupervised and supervised machine learning to bone marrow histopathology images from Myelodysplastic Syndrome (MDS) patients. Their study provides new insights into the pathobiology of MDS and paves the way for increased use of artificial intelligence for the assessment and diagnosis of hematological malignancies.
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http://dx.doi.org/10.1158/2643-3230.bcd-21-0048DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8133372PMC
May 2021

Neoadjuvant durvalumab with or without stereotactic body radiotherapy in patients with early-stage non-small-cell lung cancer: a single-centre, randomised phase 2 trial.

Lancet Oncol 2021 06 18;22(6):824-835. Epub 2021 May 18.

Department of Radiation Oncology, Weill Cornell Medicine-New York Presbyterian Hospital, New York, NY, USA.

Background: Previous phase 2 trials of neoadjuvant anti-PD-1 or anti-PD-L1 monotherapy in patients with early-stage non-small-cell lung cancer have reported major pathological response rates in the range of 15-45%. Evidence suggests that stereotactic body radiotherapy might be a potent immunomodulator in advanced non-small-cell lung cancer (NSCLC). In this trial, we aimed to evaluate the use of stereotactic body radiotherapy in patients with early-stage NSCLC as an immunomodulator to enhance the anti-tumour immune response associated with the anti-PD-L1 antibody durvalumab.

Methods: We did a single-centre, open-label, randomised, controlled, phase 2 trial, comparing neoadjuvant durvalumab alone with neoadjuvant durvalumab plus stereotactic radiotherapy in patients with early-stage NSCLC, at NewYork-Presbyterian and Weill Cornell Medical Center (New York, NY, USA). We enrolled patients with potentially resectable early-stage NSCLC (clinical stages I-IIIA as per the 7th edition of the American Joint Committee on Cancer) who were aged 18 years or older with an Eastern Cooperative Oncology Group performance status of 0 or 1. Eligible patients were randomly assigned (1:1) to either neoadjuvant durvalumab monotherapy or neoadjuvant durvalumab plus stereotactic body radiotherapy (8 Gy × 3 fractions), using permuted blocks with varied sizes and no stratification for clinical or molecular variables. Patients, treating physicians, and all study personnel were unmasked to treatment assignment after all patients were randomly assigned. All patients received two cycles of durvalumab 3 weeks apart at a dose of 1·12 g by intravenous infusion over 60 min. Those in the durvalumab plus radiotherapy group also received three consecutive daily fractions of 8 Gy stereotactic body radiotherapy delivered to the primary tumour immediately before the first cycle of durvalumab. Patients without systemic disease progression proceeded to surgical resection. The primary endpoint was major pathological response in the primary tumour. All analyses were done on an intention-to-treat basis. This trial is registered with ClinicalTrial.gov, NCT02904954, and is ongoing but closed to accrual.

Findings: Between Jan 25, 2017, and Sept 15, 2020, 96 patients were screened and 60 were enrolled and randomly assigned to either the durvalumab monotherapy group (n=30) or the durvalumab plus radiotherapy group (n=30). 26 (87%) of 30 patients in each group had their tumours surgically resected. Major pathological response was observed in two (6·7% [95% CI 0·8-22·1]) of 30 patients in the durvalumab monotherapy group and 16 (53·3% [34·3-71·7]) of 30 patients in the durvalumab plus radiotherapy group. The difference in the major pathological response rates between both groups was significant (crude odds ratio 16·0 [95% CI 3·2-79·6]; p<0·0001). In the 16 patients in the dual therapy group with a major pathological response, eight (50%) had a complete pathological response. The second cycle of durvalumab was withheld in three (10%) of 30 patients in the dual therapy group due to immune-related adverse events (grade 3 hepatitis, grade 2 pancreatitis, and grade 3 fatigue and thrombocytopaenia). Grade 3-4 adverse events occurred in five (17%) of 30 patients in the durvalumab monotherapy group and six (20%) of 30 patients in the durvalumab plus radiotherapy group. The most frequent grade 3-4 events were hyponatraemia (three [10%] patients in the durvalumab monotherapy group) and hyperlipasaemia (three [10%] patients in the durvalumab plus radiotherapy group). Two patients in each group had serious adverse events (pulmonary embolism [n=1] and stroke [n=1] in the durvalumab monotherapy group, and pancreatitis [n=1] and fatigue [n=1] in the durvalumab plus radiotherapy group). No treatment-related deaths or deaths within 30 days of surgery were reported.

Interpretation: Neoadjuvant durvalumab combined with stereotactic body radiotherapy is well tolerated, safe, and associated with a high major pathological response rate. This neoadjuvant strategy should be validated in a larger trial.

Funding: AstraZeneca.
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http://dx.doi.org/10.1016/S1470-2045(21)00149-2DOI Listing
June 2021

Deep learning predicts chromosomal instability from histopathology images.

iScience 2021 May 3;24(5):102394. Epub 2021 Apr 3.

Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York 10065, USA.

Chromosomal instability (CIN) is a hallmark of human cancer yet not readily testable for patients with cancer in routine clinical setting. In this study, we sought to explore whether CIN status can be predicted using ubiquitously available hematoxylin and eosin histology through a deep learning-based model. When applied to a cohort of 1,010 patients with breast cancer (Training set: n = 858, Test set: n = 152) from The Cancer Genome Atlas where 485 patients have high CIN status, our model accurately classified CIN status, achieving an area under the curve of 0.822 with 81.2% sensitivity and 68.7% specificity in the test set. Patch-level predictions of CIN status suggested intra-tumor heterogeneity within slides. Moreover, presence of patches with high predicted CIN score within an entire slide was more predictive of clinical outcome than the average CIN score of the slide, thus underscoring the clinical importance of intra-tumor heterogeneity.
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http://dx.doi.org/10.1016/j.isci.2021.102394DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099498PMC
May 2021

Discovery of Candidate DNA Methylation Cancer Driver Genes.

Cancer Discov 2021 Sep 10;11(9):2266-2281. Epub 2021 May 10.

Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York.

Epigenetic alterations, such as promoter hypermethylation, may drive cancer through tumor suppressor gene inactivation. However, we have limited ability to differentiate driver DNA methylation (DNAme) changes from passenger events. We developed DNAme driver inference-MethSig-accounting for the varying stochastic hypermethylation rate across the genome and between samples. We applied MethSig to bisulfite sequencing data of chronic lymphocytic leukemia (CLL), multiple myeloma, ductal carcinoma , glioblastoma, and to methylation array data across 18 tumor types in TCGA. MethSig resulted in well-calibrated quantile-quantile plots and reproducible inference of likely DNAme drivers with increased sensitivity/specificity compared with benchmarked methods. CRISPR/Cas9 knockout of selected candidate CLL DNAme drivers provided a fitness advantage with and without therapeutic intervention. Notably, DNAme driver risk score was closely associated with adverse outcome in independent CLL cohorts. Collectively, MethSig represents a novel inference framework for DNAme driver discovery to chart the role of aberrant DNAme in cancer. SIGNIFICANCE: MethSig provides a novel statistical framework for the analysis of DNA methylation changes in cancer, to specifically identify candidate DNA methylation driver genes of cancer progression and relapse, empowering the discovery of epigenetic mechanisms that enhance cancer cell fitness..
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http://dx.doi.org/10.1158/2159-8290.CD-20-1334DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419066PMC
September 2021

Incorporating cytologic adequacy assessment into precision oncology workflow using telepathology: An institutional experience.

Cancer Cytopathol 2021 Apr 30. Epub 2021 Apr 30.

Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York.

Background: Tumor sample quality and quantity determine the success of somatic mutation analysis. Thus, a rapid on-site evaluation (ROSE) tumor cytology adequacy assessment was incorporated into the workflow of precision oncology at Weill Cornell Medicine in New York City. Optimal samples were obtained from 68 patients with metastatic cancer.

Methods: Cytopathologists performed ROSE on fine-needle aspirate samples via telepathology, and subsequently core-needle biopsies were obtained. In a retrospective manner, the concordance between adequacy assessment and the success rate of the procedure was evaluated to obtain sufficient tumor tissue for next-generation sequencing (NGS).

Results: Out of the 68 procedures, 43 were documented as adequate and 25 were documented as inadequate. The diagnostic yield of adequate procedures was 100%. Adequacy evaluation predicted the success rate of molecular profiling in 40 of 43 procedures (93%; 95% CI, 80.9-98.5 procedures). The success rate of molecular testing was significantly higher in the adequate group: 93% compared with 32% in the inadequate group (P < .0005). Seven procedures that failed to provide quality material for mutational analysis and pathological diagnosis were evaluated as inadequate. Cell block provided sufficient DNA for NGS in 6 cases. In 2 cases, a core biopsy could not be performed; hence, the fine-needle aspirate material confirmed the diagnosis and was used for NGS testing.

Conclusion: These results support the incorporation of ROSE into the workflow of precision oncology to obtain high-quality tissue samples from metastatic lesions. In addition, NGS testing of concurrent cytology specimens with adequate cellularity can be a surrogate for NGS testing of biopsy specimens.
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http://dx.doi.org/10.1002/cncy.22441DOI Listing
April 2021

A molecular single-cell lung atlas of lethal COVID-19.

Nature 2021 07 29;595(7865):114-119. Epub 2021 Apr 29.

Human Immune Monitoring Core, Columbia University Irving Medical Center, New York, NY, USA.

Respiratory failure is the leading cause of death in patients with severe SARS-CoV-2 infection, but the host response at the lung tissue level is poorly understood. Here we performed single-nucleus RNA sequencing of about 116,000 nuclei from the lungs of nineteen individuals who died of COVID-19 and underwent rapid autopsy and seven control individuals. Integrated analyses identified substantial alterations in cellular composition, transcriptional cell states, and cell-to-cell interactions, thereby providing insight into the biology of lethal COVID-19. The lungs from individuals with COVID-19 were highly inflamed, with dense infiltration of aberrantly activated monocyte-derived macrophages and alveolar macrophages, but had impaired T cell responses. Monocyte/macrophage-derived interleukin-1β and epithelial cell-derived interleukin-6 were unique features of SARS-CoV-2 infection compared to other viral and bacterial causes of pneumonia. Alveolar type 2 cells adopted an inflammation-associated transient progenitor cell state and failed to undergo full transition into alveolar type 1 cells, resulting in impaired lung regeneration. Furthermore, we identified expansion of recently described CTHRC1 pathological fibroblasts contributing to rapidly ensuing pulmonary fibrosis in COVID-19. Inference of protein activity and ligand-receptor interactions identified putative drug targets to disrupt deleterious circuits. This atlas enables the dissection of lethal COVID-19, may inform our understanding of long-term complications of COVID-19 survivors, and provides an important resource for therapeutic development.
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http://dx.doi.org/10.1038/s41586-021-03569-1DOI Listing
July 2021

Artificial intelligence in oncology: From bench to clinic.

Semin Cancer Biol 2021 Apr 26. Epub 2021 Apr 26.

HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Dept. of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10021, USA; Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA; Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, 10065, USA; Tri-Institutional Training Program in Computational Biology and Medicine, New York, NY, 10065, USA. Electronic address:

In the past few years, Artificial Intelligence (AI) techniques have been applied to almost every facet of oncology, from basic research to drug development and clinical care. In the clinical arena where AI has perhaps received the most attention, AI is showing promise in enhancing and automating image-based diagnostic approaches in fields such as radiology and pathology. Robust AI applications, which retain high performance and reproducibility over multiple datasets, extend from predicting indications for drug development to improving clinical decision support using electronic health record data. In this article, we review some of these advances. We also introduce common concepts and fundamentals of AI and its various uses, along with its caveats, to provide an overview of the opportunities and challenges in the field of oncology. Leveraging AI techniques productively to provide better care throughout a patient's medical journey can fuel the predictive promise of precision medicine.
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http://dx.doi.org/10.1016/j.semcancer.2021.04.013DOI Listing
April 2021

Social and Clinical Determinants of COVID-19 Outcomes: Modeling Real-World Data from a Pandemic Epicenter.

medRxiv 2021 Apr 7. Epub 2021 Apr 7.

Importance: As the United States continues to accumulate COVID-19 cases and deaths, and disparities persist, defining the impact of risk factors for poor outcomes across patient groups is imperative.

Objective: Our objective is to use real-world healthcare data to quantify the impact of demographic, clinical, and social determinants associated with adverse COVID-19 outcomes, to identify high-risk scenarios and dynamics of risk among racial and ethnic groups.

Design: A retrospective cohort of COVID-19 patients diagnosed between March 1 and August 20, 2020. Fully adjusted logistical regression models for hospitalization, severe disease and mortality outcomes across 1-the entire cohort and 2-within self-reported race/ethnicity groups.

Setting: Three sites of the NewYork-Presbyterian health care system serving all boroughs of New York City. Data was obtained through automated data abstraction from electronic medical records.

Participants: During the study timeframe, 110,498 individuals were tested for SARS-CoV-2 in the NewYork-Presbyterian health care system; 11,930 patients were confirmed for COVID-19 by RT-PCR or covid-19 clinical diagnosis.

Main Outcomes And Measures: The predictors of interest were patient race/ethnicity, and covariates included demographics, comorbidities, and census tract neighborhood socio-economic status. The outcomes of interest were COVID-19 hospitalization, severe disease, and death.

Results: Of confirmed COVID-19 patients, 4,895 were hospitalized, 1,070 developed severe disease and 1,654 suffered COVID-19 related death. Clinical factors had stronger impacts than social determinants and several showed race-group specificities, which varied among outcomes. The most significant factors in our all-patients models included: age over 80 (OR=5.78, p= 2.29×10 ) and hypertension (OR=1.89, p=1.26×10 ) having the highest impact on hospitalization, while Type 2 Diabetes was associated with all three outcomes (hospitalization: OR=1.48, p=1.39×10 ; severe disease: OR=1.46, p=4.47×10 ; mortality: OR=1.27, p=0.001). In race-specific models, COPD increased risk of hospitalization only in Non-Hispanics (NH)-Whites (OR=2.70, p=0.009). Obesity (BMI 30+) showed race-specific risk with severe disease NH-Whites (OR=1.48, p=0.038) and NH-Blacks (OR=1.77, p=0.025). For mortality, Cancer was the only risk factor in Hispanics (OR=1.97, p=0.043), and heart failure was only a risk in NH-Asians (OR=2.62, p=0.001).

Conclusions And Relevance: Comorbidities were more influential on COVID-19 outcomes than social determinants, suggesting clinical factors are more predictive of adverse trajectory than social factors.

Key Points: What is the impact of patient self-reported race, ethnicity, socioeconomic status, and clinical profile on COVID-19 hospitalizations, severity, and mortality? In patients diagnosed with COVID-19, being over 50 years of age, having type 2 diabetes and hypertension were the most important risk factors for hospitalization and severe outcomes regardless of patient race or socioeconomic status. In this large sample pf patients diagnosed with COVID-19 in New York City, we found that clinical comorbidity, more so than social determinants of health, was associated with important patient outcomes.
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http://dx.doi.org/10.1101/2021.04.06.21254728DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043490PMC
April 2021

QSER1 protects DNA methylation valleys from de novo methylation.

Science 2021 04;372(6538)

Developmental Biology Program, Sloan Kettering Institute, 1275 York Avenue, New York, NY 10065, USA.

DNA methylation is essential to mammalian development, and dysregulation can cause serious pathological conditions. Key enzymes responsible for deposition and removal of DNA methylation are known, but how they cooperate to regulate the methylation landscape remains a central question. Using a knockin DNA methylation reporter, we performed a genome-wide CRISPR-Cas9 screen in human embryonic stem cells to discover DNA methylation regulators. The top screen hit was an uncharacterized gene, , which proved to be a key guardian of bivalent promoters and poised enhancers of developmental genes, especially those residing in DNA methylation valleys (or canyons). We further demonstrate genetic and biochemical interactions of QSER1 and TET1, supporting their cooperation to safeguard transcriptional and developmental programs from DNMT3-mediated de novo methylation.
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http://dx.doi.org/10.1126/science.abd0875DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8185639PMC
April 2021

RNA-sequencing data-driven dissection of human plasma cell differentiation reveals new potential transcription regulators.

Leukemia 2021 05 6;35(5):1451-1462. Epub 2021 Apr 6.

Department of Biological Hematology, CHU Montpellier, Montpellier, France.

Plasma cells (PCs) play an important role in the adaptive immune system through a continuous production of antibodies. We have demonstrated that PC differentiation can be modeled in vitro using complex multistep culture systems reproducing sequential differentiation process occurring in vivo. Here we present a comprehensive, temporal program of gene expression data encompassing human PC differentiation (PCD) using RNA sequencing (RNA-seq). Our results reveal 6374 differentially expressed genes classified into four temporal gene expression patterns. A stringent pathway enrichment analysis of these gene clusters highlights known pathways but also pathways largely unknown in PCD, including the heme biosynthesis and the glutathione conjugation pathways. Additionally, our analysis revealed numerous novel transcriptional networks with significant stage-specific overexpression and potential importance in PCD, including BATF2, BHLHA15/MIST1, EZH2, WHSC1/MMSET, and BLM. We have experimentally validated a potent role for BLM in regulating cell survival and proliferation during human PCD. Taken together, this RNA-seq analysis of PCD temporal stages helped identify coexpressed gene modules with associated up/downregulated transcription regulator genes that could represent major regulatory nodes for human PC maturation. These data constitute a unique resource of human PCD gene expression programs in support of future studies for understanding the underlying mechanisms that control PCD.
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http://dx.doi.org/10.1038/s41375-021-01234-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102200PMC
May 2021

Artificial Intelligence in Cancer Research and Precision Medicine.

Cancer Discov 2021 Apr;11(4):900-915

Caryl and Israel Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York.

Artificial intelligence (AI) is rapidly reshaping cancer research and personalized clinical care. Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has led to an explosion of AI use in various aspects of oncology research. These applications range from detection and classification of cancer, to molecular characterization of tumors and their microenvironment, to drug discovery and repurposing, to predicting treatment outcomes for patients. As these advances start penetrating the clinic, we foresee a shifting paradigm in cancer care becoming strongly driven by AI. SIGNIFICANCE: AI has the potential to dramatically affect nearly all aspects of oncology-from enhancing diagnosis to personalizing treatment and discovering novel anticancer drugs. Here, we review the recent enormous progress in the application of AI to oncology, highlight limitations and pitfalls, and chart a path for adoption of AI in the cancer clinic.
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http://dx.doi.org/10.1158/2159-8290.CD-21-0090DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034385PMC
April 2021
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