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Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers
BACKGROUND: High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4696808/ https://www.ncbi.nlm.nih.gov/pubmed/26717006 http://dx.doi.org/10.1371/journal.pone.0145754 |
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author | Pereira, Elena Camacho-Vanegas, Olga Anand, Sanya Sebra, Robert Catalina Camacho, Sandra Garnar-Wortzel, Leopold Nair, Navya Moshier, Erin Wooten, Melissa Uzilov, Andrew Chen, Rong Prasad-Hayes, Monica Zakashansky, Konstantin Beddoe, Ann Marie Schadt, Eric Dottino, Peter Martignetti, John A. |
author_facet | Pereira, Elena Camacho-Vanegas, Olga Anand, Sanya Sebra, Robert Catalina Camacho, Sandra Garnar-Wortzel, Leopold Nair, Navya Moshier, Erin Wooten, Melissa Uzilov, Andrew Chen, Rong Prasad-Hayes, Monica Zakashansky, Konstantin Beddoe, Ann Marie Schadt, Eric Dottino, Peter Martignetti, John A. |
author_sort | Pereira, Elena |
collection | PubMed |
description | BACKGROUND: High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools. METHODS AND FINDINGS: Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival. CONCLUSIONS: Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection point in precision medicine. This study suggests that the use of personalized ctDNA biomarkers in gynecologic cancers can identify the presence of residual tumor while also more dynamically predicting response to treatment relative to currently used serum and imaging studies. Of particular interest, ctDNA was an independent predictor of survival in patients with ovarian and endometrial cancers. Earlier recognition of disease persistence and/or recurrence and the ability to stratify into better and worse outcome groups through ctDNA surveillance may open the window for improved survival and quality and life in these cancers. |
format | Online Article Text |
id | pubmed-4696808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-46968082016-01-13 Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers Pereira, Elena Camacho-Vanegas, Olga Anand, Sanya Sebra, Robert Catalina Camacho, Sandra Garnar-Wortzel, Leopold Nair, Navya Moshier, Erin Wooten, Melissa Uzilov, Andrew Chen, Rong Prasad-Hayes, Monica Zakashansky, Konstantin Beddoe, Ann Marie Schadt, Eric Dottino, Peter Martignetti, John A. PLoS One Research Article BACKGROUND: High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools. METHODS AND FINDINGS: Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival. CONCLUSIONS: Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection point in precision medicine. This study suggests that the use of personalized ctDNA biomarkers in gynecologic cancers can identify the presence of residual tumor while also more dynamically predicting response to treatment relative to currently used serum and imaging studies. Of particular interest, ctDNA was an independent predictor of survival in patients with ovarian and endometrial cancers. Earlier recognition of disease persistence and/or recurrence and the ability to stratify into better and worse outcome groups through ctDNA surveillance may open the window for improved survival and quality and life in these cancers. Public Library of Science 2015-12-30 /pmc/articles/PMC4696808/ /pubmed/26717006 http://dx.doi.org/10.1371/journal.pone.0145754 Text en © 2015 Pereira et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Pereira, Elena Camacho-Vanegas, Olga Anand, Sanya Sebra, Robert Catalina Camacho, Sandra Garnar-Wortzel, Leopold Nair, Navya Moshier, Erin Wooten, Melissa Uzilov, Andrew Chen, Rong Prasad-Hayes, Monica Zakashansky, Konstantin Beddoe, Ann Marie Schadt, Eric Dottino, Peter Martignetti, John A. Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers |
title | Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers |
title_full | Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers |
title_fullStr | Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers |
title_full_unstemmed | Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers |
title_short | Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers |
title_sort | personalized circulating tumor dna biomarkers dynamically predict treatment response and survival in gynecologic cancers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4696808/ https://www.ncbi.nlm.nih.gov/pubmed/26717006 http://dx.doi.org/10.1371/journal.pone.0145754 |
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