scholarly journals cbpManager: a web application to streamline the integration of clinical and genomic data in cBioPortal to support the Molecular Tumor Board

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Arsenij Ustjanzew ◽  
Alexander Desuki ◽  
Christoph Ritzel ◽  
Alina Corinna Dolezilek ◽  
Daniel-Christoph Wagner ◽  
...  
Keyword(s):  
Clinical Data ◽  
Web Application ◽  
Cancer Biology ◽  
Data Privacy ◽  
Large Scale ◽  
Cancer Genomics ◽  
Tumor Board ◽  
Data Formats ◽  
Tumor Boards ◽  
Data Files

Abstract Background Extensive sequencing of tumor tissues has greatly improved our understanding of cancer biology over the past years. The integration of genomic and clinical data is increasingly used to select personalized therapies in dedicated tumor boards (Molecular Tumor Boards) or to identify patients for basket studies. Genomic alterations and clinical information can be stored, integrated and visualized in the open-access resource cBioPortal for Cancer Genomics. cBioPortal can be run as a local instance enabling storage and analysis of patient data in single institutions, in the respect of data privacy. However, uploading clinical input data and genetic aberrations requires the elaboration of multiple data files and specific data formats, which makes it difficult to integrate this system into clinical practice. To solve this problem, we developed cbpManager. Results cbpManager is an R package providing a web-based interactive graphical user interface intended to facilitate the maintenance of mutations data and clinical data, including patient and sample information, as well as timeline data. cbpManager enables a large spectrum of researchers and physicians, regardless of their informatics skills to intuitively create data files ready for upload in cBioPortal for Cancer Genomics on a daily basis or in batch. Due to its modular structure based on R Shiny, further data formats such as copy number and fusion data can be covered in future versions. Further, we provide cbpManager as a containerized solution, enabling a straightforward large-scale deployment in clinical systems and secure access in combination with ShinyProxy. cbpManager is freely available via the Bioconductor project at https://bioconductor.org/packages/cbpManager/ under the AGPL-3 license. It is already used at six University Hospitals in Germany (Mainz, Gießen, Lübeck, Halle, Freiburg, and Marburg). Conclusion In summary, our package cbpManager is currently a unique software solution in the workflow with cBioPortal for Cancer Genomics, to assist the user in the interactive generation and management of study files suited for the later upload in cBioPortal.

Characteristics of the Multi Disciplinary Cancer Conference (Tumor Boards) in the COVID 19 era.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13561-e13561
Author(s):  
Lijo Simpson ◽  
Anju Mathew ◽  
Robert Wojciechowski
Keyword(s):  
Clinical Trials ◽  
Web Application ◽  
Large Scale ◽  
The United States ◽  
Quality Metrics ◽  
Care Team ◽  
Tumor Board ◽  
Case Conference ◽  
Tumor Boards ◽  
Virtual Platform

e13561 Background: Cancer centers in the US are required to discuss a minimum of 15% analytic cases and prospective presentation (minimum 80%) in the multidisciplinary case conference (tumor board, MDCC), per the Commission on Cancer accrediting standards. Tumor board discussion have been shown to improve treatment decision making and patient outcomes. These meetings were in person meetings in the Pre-COVID era. The COVID 19 pandemic and the subsequent requirements for social distancing forced hospitals to move most MDCCs to a virtual format. We report on the large scale utilization of a propriety Care-Coordination platform OncoLens to run MDCCs across the country. Methods: Technology quality metrics were collected from the ongoing daily usage of the platform including time characteristics, care team utilization metrics, average attendance, quality metrics collected for accreditation and clinical trials matching on the OncoLens platform. Results: The virtual platform was accessible to around 8000 providers across the United States. On average per month there were 250 virtual meetings with over 290,000 meeting minutes. Conferences ranged from 30 minutes to 4 hours. 75% of users used the web application 25% of users utilized their smart phones .System uptime was 99.99%. Hospitals were able to conduct General and Site specific conferences. Virtual attendance of the required specialties of Medical Oncology, Radiation Oncology, Surgery, Pathology and Radiology was attained, with the average conference attendance being 14. On average hospitals required 2 administrative training sessions. Most of the case presentations were prospective. This format does enable cancer programs to collect quality metrics around Cancer program accreditation by the American College of Surgeons. A wide variety of common and rare cancer types were discussed in the virtual format. 66% of patients discussed potentially matched to clinical trials during the discussion. Conclusions: The shift of MDCCs to a mostly virtual environment occurred quickly in response to the COVID 19 pandemic. It took an average of 2 training classes to get the cancer care team on board with the use of new technology. It is possible to have high quality discussions and attain metrics for Commission On Cancer accreditation utilizing a virtual platform.

scholarly journals HeartBioPortal: an internet-of-omics for human cardiovascular disease data

2018 ◽  
Author(s):  
Bohdan Khomtchouk ◽  
Kasra A Vand ◽  
William C Koehler ◽  
Diem-Trang Tran ◽  
Kai Middlebrook ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Web Application ◽  
Large Scale ◽  
Data Science ◽  
Cancer Genomics ◽  
Clinical Information ◽  
Visual Access ◽  
Public Resources ◽  
User Friendly ◽  
Computational Platform

Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17M deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, the state-of-the-art in computational infrastructure to study datasets associated with CVD has lagged far behind public resources widely available in the oncology field, where improved data science and visualization methods have led to the development of large-scale cancer genomics resources like MSKCC's cBioPortal or NCI's Genomic Data Commons (GDC) Portal. Developing a similar user-friendly computational platform could significantly lower the barriers between complex CVD data and researchers who want rapid, intuitive, and high-quality visual access to molecular profiles and clinical attributes from existing CVD projects. Here we present HeartBioPortal: a publicly available web application that provides intuitive visualization, analysis, and downloads of large-scale CVD data currently focused on gene expression, genetic association, and ancestry information. By democratizing access to anonymized CVD data, HeartBioPortal's aim is to integrate relevant omics and clinical information across the biological dataverse to support CVD clinicians and researchers.

scholarly journals Cytogenetics and Cytogenomics Evaluation in Cancer

2019 ◽  
Vol 20 (19) ◽  
pp. 4711 ◽  
Author(s):  
Ilda Patrícia Ribeiro ◽  
Joana Barbosa Melo ◽  
Isabel Marques Carreira
Keyword(s):  
High Throughput ◽  
Cancer Biology ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clonal Evolution ◽  
Chromosomal Rearrangements ◽  
Therapy Resistance ◽  
Cellular Heterogeneity ◽  
Comparative Genomic ◽  
Driver Genes

The availability of cytogenetics and cytogenomics technologies improved the detection and identification of tumor molecular signatures as well as the understanding of cancer initiation and progression. The use of large-scale and high-throughput cytogenomics technologies has led to a fast identification of several cancer candidate biomarkers associated with diagnosis, prognosis, and therapeutics. The advent of array comparative genomic hybridization and next-generation sequencing technologies has significantly improved the knowledge about cancer biology, underlining driver genes to guide targeted therapy development, drug-resistance prediction, and pharmacogenetics. However, few of these candidate biomarkers have made the transition to the clinic with a clear benefit for the patients. Technological progress helped to demonstrate that cellular heterogeneity plays a significant role in tumor progression and resistance/sensitivity to cancer therapies, representing the major challenge of precision cancer therapy. A paradigm shift has been introduced in cancer genomics with the recent advent of single-cell sequencing, since it presents a lot of applications with a clear benefit to oncological patients, namely, detection of intra-tumoral heterogeneity, mapping clonal evolution, monitoring the development of therapy resistance, and detection of rare tumor cell populations. It seems now evident that no single biomarker could provide the whole information necessary to early detect and predict the behavior and prognosis of tumors. The promise of precision medicine is based on the molecular profiling of tumors being vital the continuous progress of high-throughput technologies and the multidisciplinary efforts to catalogue chromosomal rearrangements and genomic alterations of human cancers and to do a good interpretation of the relation genotype—phenotype.

scholarly journals How Cancer Genomics Drives Cancer Biology: Does Synthetic Lethality Explain Mutually Exclusive Oncogenic Mutations?

2016 ◽  
Author(s):  
Harold Varmus ◽  
Arun M. Unni ◽  
William W. Lockwood
Keyword(s):  
Cancer Biology ◽  
Large Scale ◽  
Cancer Genomics ◽  
Synthetic Lethality ◽  
Mutual Exclusivity ◽  
Physiological Basis ◽  
Oncogenic Mutations ◽  
Mutational Pattern ◽  
Cancer Multiple ◽  
Lung Adenocarcinomas

AbstractLarge-scale analyses of cancer genomes are revealing patterns of mutations that suggest biologically significant ideas about many aspects of cancer, including carcinogenesis, classification, and preventive and therapeutic strategies. Among those patterns is “mutual exclusivity”, a phenomenon observed when two or more mutations that are commonly observed in samples of a type of cancer are not found combined in individual tumors. We have been studying a striking example of mutual exclusivity: the absence of co-existing mutations in theKRASandEGFRproto-oncogenes in human lung adenocarcinomas, despite the high individual frequencies of such mutations in this common type of cancer. Multiple lines of evidence suggest that toxic effects of the joint expression ofKRASandEGFRmutant oncogenes, rather than loss of any selective advantages conferred by a second oncogene that operates through the same signaling pathway, are responsible for the observed mutational pattern. We discuss the potential for understanding the physiological basis of such toxicity, for exploiting it therapeutically, and for extending the studies to other examples of mutual exclusivity.

scholarly journals Challenges and Experiences Extending the cBioPortal for Cancer Genomics to a Molecular Tumor Board Platform

2021 ◽  
Author(s):  
Niklas Reimer ◽  
Philipp Unberath ◽  
Hauke Busch ◽  
Melanie Börries ◽  
Patrick Metzger ◽  
...  
Keyword(s):  
Decision Making ◽  
Cancer Patients ◽  
Cancer Genomics ◽  
Tumor Board ◽  
Molecular Profile ◽  
Therapy Recommendations ◽  
Tumor Boards ◽  
Research Platform ◽  
Molecular Tumor Board ◽  
Aid Decision

In Molecular Tumor Boards (MTBs), therapy recommendations for cancer patients are discussed. To aid decision-making based on the patient’s molecular profile, the research platform cBioPortal was extended based on users’ requirements. Additionally, a comprehensive dockerized workflow was developed to support the deployment of cBioPortal and connected services. In this work, we present the challenges and experiences of nearly two years of implementing and deploying an MTB platform based on cBioPortal and compare those to findings of a previous study.

Comparison of treatment plans feasible through AI enabled multidisciplinary online tumor board solution versus NCCN-based clinical decision support system (CDSS).

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 816-816
Author(s):  
Bhawna Sirohi ◽  
Sushil Beriwal ◽  
C. S. Pramesh ◽  
Supriya Chopra ◽  
Mahesh Goel ◽  
...  
Keyword(s):  
Large Scale ◽  
Treatment Plan ◽  
Specific Treatment ◽  
Treatment Decisions ◽  
Added Value ◽  
Tumor Board ◽  
Patient Specific ◽  
Clinical Scenarios ◽  
Tumor Boards ◽  
Treatment Plans

816 Background: Multidisciplinary tumor boards at Academic Medical Centers (AMC) maximize cancer outcomes. Guidelines based CDSS are alternatives to determine care pathways. Since 2015, 300 AMC cancer experts in USA and India use an AI enabled online tumor board solution, “NAVYA,” to scale low cost access to multidisciplinary expertise, on 1-2 minutes of expert time per decision (ASCO 2017). Methods: GI patients who used NAVYA between 5/1/15-8/31/19 were analyzed. Actionable treatment plans generated by NAVYA were compared to NCCN. Actionable treatment plans include chemotherapy protocols (doses, frequencies), radiation protocols (sites, fractions), etc. Inactionable specialty level decisions (CT-RT vs. surgery) lack specificity. Results: 1302 patients (4638 treatment decisions) were analyzed: 61% (794) male, 80% between age 45 to 75, mostly with Colon, Pancreas, Gallbladder, Rectum, or Stomach cancer; 49.7% non-metastatic. Cohort was comparable to GLOBOCAN estimates. In 82.2% (3812/4638) decisions, NAVYA added value beyond NCCN. First, in 4.5% (212/4638), NAVYA recommended a patient-specific treatment plan that was not part of NCCN. Second, in 3.2% (148/4638), NAVYA recommended treatments plan for clinical scenarios not covered by NCCN, (for eg. 3rd line therapies). Third, in 74.5% (3452/4638), NAVYA used patient specific criteria including resource constraints and patient preference to choose a treatment plan amongst the multiple pathways provided by NCCN and added actionable treatment details. Conclusions: Guideline based CDSS are insufficient to make the vast majority of actionable treatment decisions. Scaling rapid access to multidisciplinary experts is critical. Leapfrogging existing guidelines based CDSS, NAVYA online tumor board makes actionable expert treatment plans possible at a large scale.

Virtual Clinical and Precision Medicine Tumor Boards: A Cloud-based Platform-mediated Implementation of Multidisciplinary Reviews among Oncology Centers in the Covid-19 Era. (Preprint)

2020 ◽  
Author(s):  
Livio Blasi ◽  
Roberto Bordonaro ◽  
Vincenzo Serretta ◽  
Dario Piazza ◽  
Alberto Firenze ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Professionals ◽  
Clinical Pathways ◽  
Prospective Trial ◽  
Banking System ◽  
Outcome Data ◽  
Tumor Board ◽  
Time Saving ◽  
Tumor Boards ◽  
Multidisciplinary Tumor Board

BACKGROUND Multidisciplinary tumor boards play a pivotal role in the patients -centered clinical management and in the decision-making process to provide best evidence -based, diagnostic and therapeutic care to cancer patients. Among the barriers to achieve an efficient multidisciplinary tumor board, lack of time and geographical distance play a major role. Therefore the elaboration of an efficient virtual multidisciplinary tumor board (VMTB) is a key-point to reach a successful oncology team and implement a network among health professionals and institutions. This need is stronger than ever in a Covid-19 pandemic scenario. OBJECTIVE This paper presents a research protocol for an observational study focused on exploring the structuring process and the implementation of a multi-institutional VMTB in Sicily. Other endpoints include analysis of cooperation between participants, adherence to guidelines, patients’ outcomes, and patients satisfaction METHODS This protocol encompasses a pragmatic, observational, multicenter, non-interventional, prospective trial. The study's programmed duration is five years, with a half-yearly analysis of the primary and secondary objectives' measurements. Oncology care health-professionals from various oncology subspecialties at oncology departments in multiple hospitals (academic and general hospitals as well as tertiary centers and community hospitals) are involved in a non-hierarchic fashion. VMTB employ an innovative, virtual, cloud-based platform to share anonymized medical data which are discussed via a videoconferencing system both satisfying security criteria and HIPAA compliance. RESULTS The protocol is part of a larger research project on communication and multidisciplinary collaboration in oncology units and departments spread in the Sicily region in Italy. Results of this study will particularly focus on the organization of VMTB involving oncology units present in different hospitals spread in the area and create a network to allow best patients care pathways and a hub and spoke relationship. Results will also include data concerning organization skills and pitfalls, barriers, efficiency, number and type con clinical cases, and customers’ satisfaction. CONCLUSIONS VMTB represents a unique opportunity to optimize patient’s management in a patient centered approach. An efficient virtualization and data banking system is potentially time-saving, a source for outcome data, and a detector of possible holes in the hull of clinical pathways. The observations and results from this VMTB study may hopefully useful to design nonclinical and organizational interventions that enhance multidisciplinary decision-making in oncology.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-192 ◽  
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

A High-Fidelity Model to Predict Length of Stay in the Neonatal Intensive Care Unit

2021 ◽  
Author(s):  
Kanix Wang ◽  
Walid Hussain ◽  
John R. Birge ◽  
Michael D. Schreiber ◽  
Daniel Adelman
Keyword(s):  
Length Of Stay ◽  
Clinical Data ◽  
Neonatal Intensive Care ◽  
Large Scale ◽  
Expert Knowledge ◽  
Clinical Analysis ◽  
Healthcare Operations ◽  
Lengths Of Stay ◽  
Health Trajectories ◽  
Widespread Implementation

Having an interpretable, dynamic length-of-stay model can help hospital administrators and clinicians make better decisions and improve the quality of care. The widespread implementation of electronic medical record (EMR) systems has enabled hospitals to collect massive amounts of health data. However, how to integrate this deluge of data into healthcare operations remains unclear. We propose a framework grounded in established clinical knowledge to model patients’ lengths of stay. In particular, we impose expert knowledge when grouping raw clinical data into medically meaningful variables that summarize patients’ health trajectories. We use dynamic, predictive models to output patients’ remaining lengths of stay, future discharges, and census probability distributions based on their health trajectories up to the current stay. Evaluated with large-scale EMR data, the dynamic model significantly improves predictive power over the performance of any model in previous literature and remains medically interpretable. Summary of Contribution: The widespread implementation of electronic health systems has created opportunities and challenges to best utilize mounting clinical data for healthcare operations. In this study, we propose a new approach that integrates clinical analysis in generating variables and implementations of computational methods. This approach allows our model to remain interpretable to the medical professionals while being accurate. We believe our study has broader relevance to researchers and practitioners of healthcare operations.

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