Citations 2
Dissection of PIK3CA Aberration for Cervical Adenocarcinoma Outcomes
Doran, Graeme, Cheung, Tak-Hong, Yim, So‐Fan, Yu, Mei‐Yung, Thorner, Aaron R. , Pedamallu, Chandra Sekhar , Lau, Kei-Man, Ducar, Matthew D. , Wong, Raymond R.Y., Wang, Vivian W., Nag, Anwesha , Wollison, Bruce M. , Dalgarno, Audrey, Lee, Jacqueline Ho Sze , Yeung, Suet-Ying, Wong, Lo , Leung, Shuk-On A., Mu, Yi , Mok, Samuel C. , Crum, Christopher P. , Chiu, Rossa W. K. , Berkowitz, Ross S. , Wong, Yick‐Fu, Thorner, Aaron R , Ducar, Matthew D , Lee, Jacqueline H S , Mok, Samuel C , Chung, Tony K.H. , Yim, So Fan, Worley, Michael J. , Elias, Kevin M. , Ojesina, Akinyemi I. , Yeung, Suet Ying, Horowitz, Neil S. , Davis, Michelle , Leung, Shuk On Annie , Chan, Paul K.S. , Lawrence, Michael S.
Cancers | June 28, 2021 | Volume: 13 | Issue: 13 | Pages: 3218
Personalized treatment of genetically stratified subgroups has the potential to improve outcomes in many malignant tumors. This study distills clinically meaningful prognostic/predictive genomic marker for cervical adenocarcinoma using signature genomic aberrations and single-point nonsynonymous mutation-specific droplet digital PCR (ddPCR). Mutations in PIK3CA E542K, E545K, or H1047R were detected in 41.7% of tumors. PIK3CA mutation detected in the patient’s circulating DNA collected before treatment or during follow-up was significantly associated with decreased progression-free survival or overall survival. PIK3CA mutation in the circulating DNA during follow-up after treatment predicted recurrence with 100% sensitivity and 64.29% specificity. It is the first indication of the predictive power of PIK3CA mutations in cervical adenocarcinoma. The work contributes to the development of liquid biopsies for follow up surveillance and a possibility of tailoring management of this particular women’s cancer.
Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation
Rosner, Bernard , Tamimi, Rulla M. , Gao, Chi , Mu, Yi , Scott, Christopher G. , Winham, Stacey J. , Vachon, Celine M. , Colditz, Graham A. , Scott, Christopher , Winham, Stacey J , Vachon, Celine M. , Colditz, Graham A , Tamimi, Rulla M , Kraft, Peter
Cancer Epidemiology, Biomarkers & Prevention | December 4, 2020 | Volume: 30 | Issue: 4 | Pages: 600-607
Abstract Background: Clinical use of breast cancer risk prediction requires simplified models. We evaluate a simplified version of the validated Rosner–Colditz model and add percent mammographic density (MD) and polygenic risk score (PRS), to assess performance from ages 45–74. We validate using the Mayo Mammography Health Study (MMHS). Methods: We derived the model in the Nurses' Health Study (NHS) based on: MD, 77 SNP PRS and a questionnaire score (QS; lifestyle and reproductive factors). A total of 2,799 invasive breast cancer cases were diagnosed from 1990–2000. MD (using Cumulus software) and PRS were assessed in a nested case–control study. We assess model performance using this case–control dataset and evaluate 10-year absolute breast cancer risk. The prospective MMHS validation dataset includes 21.8% of women age <50, and 434 incident cases identified over 10 years of follow-up. Results: In the NHS, MD has the highest odds ratio (OR) for 10-year risk prediction: ORper SD = 1.48 [95% confidence interval (CI): 1.31–1.68], followed by PRS, ORper SD = 1.37 (95% CI: 1.21–1.55) and QS, ORper SD = 1.25 (95% CI: 1.11–1.41). In MMHS, the AUC adjusted for age + MD + QS 0.650; for age + MD + QS + PRS 0.687, and the NRI was 6% in cases and 16% in controls. Conclusion: A simplified assessment of QS, MD, and PRS performs consistently to discriminate those at high 10-year breast cancer risk. Impact: This simplified model provides accurate estimation of 10-year risk of invasive breast cancer that can be used in a clinical setting to identify women who may benefit from chemopreventive intervention. See related commentary by Tehranifar et al., p. 587