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State of the Biomarker Science in Ovarian Cancer: A National Cancer Institute Clinical Trials Planning Meeting Report.
Ethier, Josee-Lyne; Fuh, Katherine C; Arend, Rebecca; Konecny, Gottfried E; Konstantinopoulos, Panagiotis A; Odunsi, Kunle; Swisher, Elizabeth M; Kohn, Elise C; Zamarin, Dmitriy.
Afiliação
  • Ethier JL; Department of Oncology, Cancer Centre of Southeastern Ontario, Queen's University, Kingston, ON, Canada.
  • Fuh KC; Division of Gynecologic Oncology, Washington University St Louis, St Louis, MO.
  • Arend R; Division of Gynecologic Oncology, University of Alabama at Birmingham, Birmingam, AL.
  • Konecny GE; Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, CA.
  • Konstantinopoulos PA; Division of Gynecologic Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA.
  • Odunsi K; Department of Obstetrics and Gynecology, University of Chicago, Chicago, IL.
  • Swisher EM; Division of Gynecologic Oncology, University of Washington, Seattle, WA.
  • Kohn EC; Clinical Investigations Branch of The Cancer Therapy Evaluation Program, National Cancer Institute, Rockville, ML.
  • Zamarin D; Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY.
JCO Precis Oncol ; 6: e2200355, 2022 Oct.
Article em En | MEDLINE | ID: mdl-36240472
PURPOSE: Despite therapeutic advances in the treatment of ovarian cancer (OC), 5-year survival remains low, and patients eventually die from recurrent, chemotherapy-resistant disease. The National Cancer Gynecologic Cancer Steering Committee identified the integration of scientifically defined subgroups as a top strategic priority in clinical trial planning. METHODS: A group of experts was convened to review the scientific literature in OC to identify validated predictive biomarkers that could inform patient selection and treatment stratification. Here, we report on these findings and their potential for use in future clinical trial design on the basis of hierarchal evidence grading. RESULTS: The biomarkers were classified on the basis of mechanistic targeting, including DNA repair and replication stress, immunotherapy and tumor microenvironment, oncogenic signaling, and angiogenesis. Currently, BRCA mutations and homologous recombination deficiency to predict poly (ADP-ribose) polymerase inhibitor response are supported in OC by the highest level of evidence. Additional biomarkers of response to agents targeting the pathways above have been identified but require prospective validation. CONCLUSION: Although a number of biomarkers of response to various agents in OC have been described in the literature, high-level evidence for the majority is lacking. This report highlights the unmet need for identification and validation of predictive biomarkers to guide therapy and future trial design in OC.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Biomarcadores / Ensaios Clínicos como Assunto Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Ovarianas / Biomarcadores / Ensaios Clínicos como Assunto Idioma: En Ano de publicação: 2022 Tipo de documento: Article