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Purpose: The volume of data produced by the biomedical research community continues to grow rapidly. Efficient collection, curation, and sharing of these data are expected to enable researchers to synthesize larger datasets and apply novel methods to discover new patterns for diagnosis, treatment, and care of disease. Consequently, data platforms that support these functionalities have become an important instrument for the biomedical research community. The National Cancer Institute’s (NCI’s) Cancer Research Data Commons (CRDC) is a data platform for the cancer research community that provides cloud-based, secure storage and analytic tools for cancer data, including genomics, proteomics, imaging, and clinical trial data. CRDC has been funded by multiple sources, including the Beau Biden Cancer Moonshot program. Achieving long-term sustainability of the CRDC program is the focus of our study. Methods: We applied a Financial Operations (FinOps) framework to map all costs to functionalities provided by the CRDC, including processes such as data intake, storage, compute, user support, and project management. We established a comprehensive financial baseline for the operations of the CRDC, identified opportunities for optimization across multiple dimensions (people, processes, technology), projected future costs based on trends for cancer data, and evaluated sustainability under defined funding scenarios. Results: We identified 15 recommendations for optimization of the CRDC, including automation and centralization of core services (e.g., intake, curation, indexing), optimization of storage (e.g., compression, archiving), and harmonization of common services across the CRDC components (e.g., common architecture, governance). If implemented, we could demonstrate that these recommendations offer a path to long-term sustainability of the CRDC program under a variety of funding scenarios. Conclusion: Data platforms such as the CRDC will see rapid increases in operational costs due to the growing data volumes and demand from researchers. Optimizing governance and operational frameworks will result in efficiency gains that can ensure long-term sustainability. Taking these steps will be critical to provide the necessary infrastructure to advance the field of data-driven biomedical research. Citation Format: Juergen A. Klenk, Angela Maggio, Bhavani S. Singh, Erin N. Byrne, Erika Kim, Tanja M. Davidsen. A path to sustainability for the National Cancer Institute's Cancer Research Data Commons. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6582.

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

DHX15, a DEAH box containing RNA helicase, is a splicing factor required for the last step of splicing. Recent studies identified a recurrent mutational hotspot, R222G, in DHX15 in ∼ 6% of acute myeloid leukemia (AML) patients that carry the fusion protein RUNX1-RUNX1T1 produced by t (8;21) (q22;q22). Studies using yeast mutants showed that substitution of G for the residue equivalent to R222 leads to loss of its helicase function, suggesting that it is a loss-of-function mutation. To elucidate the role of DHX15 during development, we established the first vertebrate knockout model with CRISPR/Cas9 in zebrafish. Our data showed that dhx15 expression is enriched in the brain, eyes, pectoral fin primordia, liver and intestinal bulb during embryonic development. Dhx15 deficiency leads to pleiotropic morphological phenotypes in homozygous mutant embryos starting at 3 days post fertilization (dpf) that result in lethality by 7 dpf, revealing an essential role during embryonic development. RNA-seq analysis suggested important roles of Dhx15 in chromatin and nucleosome assembly and regulation of the Mdm2-p53 pathway. Interestingly, exons corresponding to the alternate transcriptional start sites for tp53 and mdm2 were preferentially expressed in the mutant embryos, leading to significant upregulation of their alternate isoforms, Δ113p53 (orthologous to Δ133p53 isoform in human) and mdm2-P2 (isoform using distal promoter P2), respectively. We speculate that these alterations in the Mdm2-p53 pathway contribute to the development of AML in patients with t(8;21) and somatically mutated DHX15.

BACKGROUND Telemedicine delivers health care services between two distant locations through the use of information and communication technology. Several medical specializations, such as dermatology, have incorporated telemedicine into their practice. Since dermatologists are trained to diagnose skin, hair and nail conditions with a clinical eye, teledermatology may be an alternative when a traditional face-to-face clinic visit is not feasible. OBJECTIVE The purpose of this study is to evaluate the diagnostic reliability of teledermatology. METHODS A cross-sectional study was conducted among patients from Culion Sanitarium and General Hospital and Rizal Medical Center. Thirty-nine patients were seen face-to-face and diagnosed by a consultant dermatologist. A written history of their present illness and accompanying photographs were taken, and were shown to three consultant teledermatologists who then diagnosed their condition. Two senior dermatology residents then rated the face-to-face and teledermatology diagnoses as either complete agreement, partial agreement, or no agreement. Descriptive statistics was used to summarize the general and clinical characteristics of the participants. Cohen’s Kappa was used to determine the agreement of the evaluations between the teledermatology and face to face diagnoses by senior residents 1 and 2. RESULTS Over 70% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater 1. Similarly, over 80% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater 2. The agreement between the agreement ratings of senior residents 1 and 2 were fair to substantial. CONCLUSIONS The findings of the study show that the diagnostic concordance of in-person clinicians and teledermatologists are fair to substantial, with over 70% of the diagnoses in partial or complete agreement. Though face-to-face consultations remain the gold standard, teledermatology is an important alternative where dermatologic care is not accessible.

BACKGROUND Telemedicine delivers health care services between two distant locations through the use of information and communication technology. Several medical specializations, such as dermatology, have incorporated telemedicine into their practice. Since dermatologists are trained to diagnose skin, hair, and nail conditions with a clinical eye, teledermatology may be an alternative when a traditional face-to-face clinic visit is not feasible. OBJECTIVE The purpose of this study was to evaluate the diagnostic reliability of teledermatology. METHODS A cross-sectional study was conducted among patients from 2 government hospitals. A total of 39 patients were seen in a face-to-face setting and diagnosed by a consultant dermatologist. A written history of their present illness and accompanying photographs were taken and were shown to 3 consultant teledermatologists, who then diagnosed their condition. Two senior dermatology residents then rated the face-to-face and teledermatology diagnoses as either complete agreement, partial agreement, or no agreement. Descriptive statistics was used to summarize the general and clinical characteristics of the participants. The Cohen kappa was used to assess agreement in the evaluations between the teledermatology and face-to-face diagnoses by senior resident raters #1 and #2. RESULTS Over 70% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater #1. Similarly, over 80% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater #2. The agreement between the ratings of senior residents #1 and #2 ranged from fair to substantial. CONCLUSIONS The findings of the study showed that the diagnostic concordance of in-person clinicians and teledermatologists ranges from fair to substantial, with over 70% of the diagnoses in partial or complete agreement. Although face-to-face consultations remain the gold standard, teledermatology is an important alternative where dermatologic care is not accessible.

Currently, there are at least a dozen recognized hereditary hematopoietic malignancies (HHMs), some of which phenocopy others. Among these, three HHMs driven by germline mutations in ANKRD26, ETV6, or RUNX1 share a phenotype of thrombocytopenia, qualitative platelet defects, and an increased lifetime risk of hematopoietic malignancies (HMs). Prior work has demonstrated that RUNX1 germline mutation carriers experience an elevated lifetime risk (66%) for developing clonal hematopoiesis (CH) prior to age 50. Germline mutations in ANKRD26 or ETV6 phenocopy RUNX1 germline mutations, but no studies have focused on the risk of CH in individuals with germline mutations in ANKRD26 or ETV6.To determine the prevalence of CH in individuals with germline mutations in ANKRD26 or ETV6, we performed next generation sequencing on hematopoietic tissue from twelve individuals with either germline ANKRD26 or germline ETV6 mutations. Each patient had thrombocytopenia but had not developed HMs. Among the seven individuals with germline ANKRD26 mutations, one patient had a CH clone driven by a somatic SF3B1 mutation (p.Lys700Glu). This mutation increased from a variant allele frequency (VAF) of 9.4% at age 56 to 17.4% at age 60. None of the germline ETV6 mutation carriers had evidence of CH at the limits of detection of the NGS assay (5% VAF). Unlike individuals with germline mutations in RUNX1, no individuals under the age of 50 with germline mutations in ANKRD26 or ETV6 had detectable CH. This work demonstrates that ANKRD26 germline mutation carriers, but not ETV6 mutation carriers, experience elevated risk for CH.

Background Telemedicine delivers health care services between two distant locations through the use of information and communication technology. Several medical specializations, such as dermatology, have incorporated telemedicine into their practice. Since dermatologists are trained to diagnose skin, hair, and nail conditions with a clinical eye, teledermatology may be an alternative when a traditional face-to-face clinic visit is not feasible. Objective The purpose of this study was to evaluate the diagnostic reliability of teledermatology. Methods A cross-sectional study was conducted among patients from 2 government hospitals. A total of 39 patients were seen in a face-to-face setting and diagnosed by a consultant dermatologist. A written history of their present illness and accompanying photographs were taken and were shown to 3 consultant teledermatologists, who then diagnosed their condition. Two senior dermatology residents then rated the face-to-face and teledermatology diagnoses as either complete agreement, partial agreement, or no agreement. Descriptive statistics was used to summarize the general and clinical characteristics of the participants. The Cohen kappa was used to assess agreement in the evaluations between the teledermatology and face-to-face diagnoses by senior resident raters #1 and #2. Results Over 70% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater #1. Similarly, over 80% of the diagnoses were deemed as either partial or in complete agreement with the face-to-face diagnosis for senior resident rater #2. The agreement between the ratings of senior residents #1 and #2 ranged from fair to substantial. Conclusions The findings of the study showed that the diagnostic concordance of in-person clinicians and teledermatologists ranges from fair to substantial, with over 70% of the diagnoses in partial or complete agreement. Although face-to-face consultations remain the gold standard, teledermatology is an important alternative where dermatologic care is not accessible. Conflicts of Interest None declared.

Inversion of chromosome 16 (inv(16)) generates a fusion gene CBFB-MYH11, which is a driver mutation for acute myeloid leukemia (AML). Gene expression profiling suggests that Gata2, a hematopoietic transcription factor, is a top upregulated genes in preleukemic Cbfb-MYH11 knockin mice and is expressed in human inv(16) AML. On the other hand, we have also identified recurrent monoallelic deletions of GATA2 in relapsed human CBF-AML patients. To clarify the role of Gata2 in leukemogenesis by Cbfb-MYH11, we generated conditional Cbfb-MYH11 knockin mice with Gata2 heterozygous knockout. Gata2 heterozygous knockout reduced abnormal myeloid progenitors, which are capable of inducing leukemia in the Cbfb-MYH11 mice. Consequently, Cbfb-MYH11 mice with Gata2 heterozygous knockout developed leukemia with longer latencies than those with intact Gata2. Interestingly, leukemic cells with Gata2 heterozygous knockout gained higher number of mutations and showed more aggressive phenotype in both primary and transplanted mice. Moreover, leukemic cells with Gata2 heterozygous knockout showed higher repopulating capacity in competitive transplantation experiments. In summary, reduction of Gata2 activity affects mutational dynamics of leukemia with delayed leukemia onset in Cbfb-MYH11 knockin mice, but paradoxically results in a more aggressive leukemia phenotype, which may be correlated with leukemia relapse or poor prognosis in human patients.

The objective of the National Cancer Institutes' Proteomic Data Commons (PDC) is to make cancer-related proteomic datasets accessible to the public. The PDC provides the cancer research community with a unified data repository that enables data sharing across cancer proteomic studies and also enables multi-omic integration in support of precision medicine. As a domain-specific repository within the Cancer Research Data Commons (CRDC), the vision for the PDC is to provide researchers the ability to find and analyze proteomic data across a wide variety of tumor types. Currently, the PDC houses data, supported by a large collection of metadata attributes, for nearly 40 datasets from over 12 cancer types produced by several large-scale cancer research programs, each with cohort sizes greater than 100 patients. The PDC facilitates the analysis of proteomic, genomic, and imaging data derived from the same tumor. Most of the datasets in the PDC also have corresponding genomic and imaging data available in the Genomic Data Commons and The Cancer Imaging Archive respectively. Researchers can discover which genomic variants are detectable at the protein-level or better understand associations between gene expression, copy number variation, and protein abundance. The resource is currently available to the public in beta phase (https://pdc.esacinc.com) and will be officially launched on the cancer.gov domain in March 2020. The PDC data portal is supported by a robust and extensible data model and provides user-friendly exploration, visualization and data analysis. This allows researchers to search for and visualize expression of proteins (through their mapped genes) across all studies, analyze protein abundance for all cases in a study through heatmaps, build and explore pan-cancer cohorts using highly curated, clinical metadata, and comprehensively view a study without needing to download the data. The PDC provides quick access to mapping of peptide identities and quantities on the human genome as well as protein databases containing patient/tumor-specific variants and novel splicing events. It also enables fast, accurate, and convenient proteomic validation of novel genomic alterations through the PepQuery algorithm. Through a highly versatile application programming interface (API), PDC allows users to interact with data programmatically and facilitates integration with data from other resources in their scripts for multi-omic analysis. Big data interoperability is critical for progress in precision medicine. PDC is designed to interoperate with other resources including the CRDC nodes, allowing users to analyze PDC data with the tools and pipelines available on the NCI cloud resources. It further allows users to use their own tools to co-analyze genomic and proteomic data available from a common sample on Amazon Web Services (AWS) platform or on a local system. The presentation will provide an overview of the PDC and it's available datasets, as well as a discussion of how it facilitates multi-omic data analyses. Citation Format: Ratna Rajesh Thangudu, Paul A. Rudnick, Michael Holck, Deepak Singhal, Michael J. MacCoss, Nathan J. Edwards, Karen A. Ketchum, Christopher R. Kinsinger, Erika Kim, Anand Basu. Proteomic Data Commons: A resource for proteogenomic analysis [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr LB-242.

Objectives The presence of HIV, tuberculosis and non-communicable diseases result in a double burden of disease in the East African community. Most studies have focused on urban Nairobi and western Kenya, leading to a lack of information on rural regions that make up 75% of the population. This study determined baseline rates and barriers to medication self-management in rural Meru County. Design A cross-sectional, descriptive community survey focused on Meru, Kenya. Setting Participants were surveyed at a local Kithoka dispensary and the government operated Meru Level 5 Hospital. Participants Seventy-five chronic illness patients between June 2016 and July 2016. Intervention Twelve-question Measures of Drug Self-Management Scale (MeDS). Main Outcome Measure Baseline rates of medication self-management. A score of 10 or more defined ‘adequate’ medication drug self-management. Results The average MeDS score was 8.16 ± 2.4, indicating inadequate medication self-management. There was no significant difference across age (P = 0.75), and between the scores of males and females (8.1 ± 2.4 and 8.2 ± 2.5, respectively, P = 0.89). Minor side effects and the idea that taking medicines disrupt life were highly associated with inadequate drug self-management (r = 0.58). Forgetfulness and non-adherence had the highest correlation (r = 0.64). Cost is a large barrier, with 64% agreeing that they have a hard time paying for their medicines. Conclusions All questions on the MeDS survey had statistically significant correlations with the overall score, while gender and age did not. The MeDS questionnaire showed to be an effective tool to evaluate risk of long-term non-adherence globally in rural populations.