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 s...
Main Authors: | , , , , , , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2015-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4696808?pdf=render |
_version_ | 1817994625630076928 |
---|---|
author | Elena Pereira Olga Camacho-Vanegas Sanya Anand Robert Sebra Sandra Catalina Camacho Leopold Garnar-Wortzel Navya Nair Erin Moshier Melissa Wooten Andrew Uzilov Rong Chen Monica Prasad-Hayes Konstantin Zakashansky Ann Marie Beddoe Eric Schadt Peter Dottino John A Martignetti |
author_facet | Elena Pereira Olga Camacho-Vanegas Sanya Anand Robert Sebra Sandra Catalina Camacho Leopold Garnar-Wortzel Navya Nair Erin Moshier Melissa Wooten Andrew Uzilov Rong Chen Monica Prasad-Hayes Konstantin Zakashansky Ann Marie Beddoe Eric Schadt Peter Dottino John A Martignetti |
author_sort | Elena Pereira |
collection | DOAJ |
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. |
first_indexed | 2024-04-14T01:55:28Z |
format | Article |
id | doaj.art-9c3dffebfa4d46e4b9673bbaa1836c2f |
institution | Directory Open Access Journal |
issn | 1932-6203 |
language | English |
last_indexed | 2024-04-14T01:55:28Z |
publishDate | 2015-01-01 |
publisher | Public Library of Science (PLoS) |
record_format | Article |
series | PLoS ONE |
spelling | doaj.art-9c3dffebfa4d46e4b9673bbaa1836c2f2022-12-22T02:19:07ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011012e014575410.1371/journal.pone.0145754Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers.Elena PereiraOlga Camacho-VanegasSanya AnandRobert SebraSandra Catalina CamachoLeopold Garnar-WortzelNavya NairErin MoshierMelissa WootenAndrew UzilovRong ChenMonica Prasad-HayesKonstantin ZakashanskyAnn Marie BeddoeEric SchadtPeter DottinoJohn A MartignettiBACKGROUND: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.http://europepmc.org/articles/PMC4696808?pdf=render |
spellingShingle | Elena Pereira Olga Camacho-Vanegas Sanya Anand Robert Sebra Sandra Catalina Camacho Leopold Garnar-Wortzel Navya Nair Erin Moshier Melissa Wooten Andrew Uzilov Rong Chen Monica Prasad-Hayes Konstantin Zakashansky Ann Marie Beddoe Eric Schadt Peter Dottino John A Martignetti Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers. PLoS ONE |
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 |
url | http://europepmc.org/articles/PMC4696808?pdf=render |
work_keys_str_mv | AT elenapereira personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT olgacamachovanegas personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT sanyaanand personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT robertsebra personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT sandracatalinacamacho personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT leopoldgarnarwortzel personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT navyanair personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT erinmoshier personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT melissawooten personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT andrewuzilov personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT rongchen personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT monicaprasadhayes personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT konstantinzakashansky personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT annmariebeddoe personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT ericschadt personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT peterdottino personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers AT johnamartignetti personalizedcirculatingtumordnabiomarkersdynamicallypredicttreatmentresponseandsurvivalingynecologiccancers |