Project description:Childhood Cancer Data Initiative (CCDI): NCI P30 Cancer Center Support Grants to Enhance Data Sharing in Pediatric, Adolescent, and Young Adult Cancers (Funded to MSKCC)

| PRJNA750820 | ENA

Expression data from NCI-H1299 and NCI-H1299/CDDP cells

Project description:Expression data from NCI-H1299 and NCI-H1299/CDDP cells

| PRJNA1062721 | ENA

Expression data from NCI-H1299 and NCI-H1299/CDDP cells

Project description:Non-small cell lung cancer (NSCLC) patients are prone to drug resistance during chemotherapy. Therefore, in order to compare the changes in the gene expression profiles of NSCLC cells before and after drug resistance, we constructed cisplatin-resistant cells (NCI-H1299/CDDP), and compared the gene expression profiles with those of the parental NCI-H1299 cells. We used microarrays to study in detail the global gene expression changes before and after drug resistance in NSCLC cells and identified genes that were up- or down-regulated during this process.

2024-01-14 | GSE252795 | GEO

Delivering on NIH data sharing requirements: avoiding Open Data in Appearance Only.

Project description:Introduction In January, the National Institutes of Health (NIH) implemented a Data Management and Sharing Policy aiming to leverage data collected during NIH-funded research. The COVID-19 pandemic illustrated that this practice is equally vital for augmenting patient research. In addition, data sharing acts as a necessary safeguard against the introduction of analytical biases. While the pandemic provided an opportunity to curtail critical research issues such as reproducibility and validity through data sharing, this did not materialise in practice and became an example of 'Open Data in Appearance Only' (ODIAO). Here, we define ODIAO as the intent of data sharing without the occurrence of actual data sharing (eg, material or digital data transfers).Objective Propose a framework that states the main risks associated with data sharing, systematically present risk mitigation strategies and provide examples through a healthcare lens.Methods This framework was informed by critical aspects of both the Open Data Institute and the NIH's 2023 Data Management and Sharing Policy plan guidelines.Results Through our examination of legal, technical, reputational and commercial categories, we find barriers to data sharing ranging from misinterpretation of General Data Privacy Rule to lack of technical personnel able to execute large data transfers. From this, we deduce that at numerous touchpoints, data sharing is presently too disincentivised to become the norm.Conclusion In order to move towards Open Data, we propose the creation of mechanisms for incentivisation, beginning with recentring data sharing on patient benefits, additional clauses in grant requirements and committees to encourage adherence to data reporting practices.

| S-EPMC10314418 | biostudies-literature

Data use under the NIH GWAS data sharing policy and future directions.

Project description: Not available

| S-EPMC4182942 | biostudies-literature