Project description:We compared the prediction powers for disease recurrence between gene set prognostic model and clinical prognostic model developed in a single large population to see whether genetic quantitative approach will have significant prognostic role in early cervical cancer patients who underwent radical hysterectomy with or without adjuvant therapies. Gene set model to predict disease free survival of early cervical cancer was developed using DASL assay dataset from the cohort of early cervical cancer patients who were treated with radical surgery with or without adjuvant therapies at the Samsung Medical Center of Sungkyunkwan University School of Medicine in Seoul, Korea, between January 2002 and September 2008. Clinical prediction model was also developed in the same cohort and the ability of predicting recurrence from each model was compared.

2013-05-01 | GSE44001 | GEO

Molecular and pathological subtypes related to prostate cancer disparities and disease outcomes in African American and European American patients

Project description:To investigate genetic and molecular differences that may exist between prostate cancers of African American and European American origin. Gene expression profile analysis was performed comparing RNA seq data of African American prostate cancer cell lines (inhouse) and European American prostate cancer cell lines (public repository)

2022-08-05 | GSE203338 | GEO

Genetic ancestry contributes to somatic mutations in lung cancers from admixed Latin American populations

Project description:Inherited lung cancer risk, particularly in non-smokers, is poorly understood. Genomic and ancestry analysis of 1,153 lung cancers from Latin America revealed striking associations between Native American ancestry and their somatic landscape, including tumor mutational burden (TMB), and specific driver mutations in EGFR, KRAS, and STK11. A local Native American ancestry risk score predicted EGFR and KRAS mutation frequency more strongly than global ancestry, suggesting that germline genetics (rather than environmental exposure) underlie these disparities.

| EGAS00001004752 | EGA

Cervical cancer

Project description:Cervical cancer

| PRJNA144107 | ENA