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A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer

Preoperative chemoradiotherapy (PCRT) and subsequent surgery is the standard multimodal treatment for locally advanced rectal cancer (LARC), albeit PCRT response varies among the individuals. This creates a dire necessity to identify a predictive model to forecast treatment response outcomes and ide...

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Autores principales: Park, In Ja, Yu, Yun Suk, Mustafa, Bilal, Park, Jin Young, Seo, Yong Bae, Kim, Gun-Do, Kim, Jinpyo, Kim, Chang Min, Noh, Hyun Deok, Hong, Seung-Mo, Kim, Yeon Wook, Kim, Mi-Ju, Ansari, Adnan Ahmad, Buonaguro, Luigi, Ahn, Sung-Min, Yu, Chang-Sik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226472/
https://www.ncbi.nlm.nih.gov/pubmed/32225122
http://dx.doi.org/10.3390/cancers12040800
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author Park, In Ja
Yu, Yun Suk
Mustafa, Bilal
Park, Jin Young
Seo, Yong Bae
Kim, Gun-Do
Kim, Jinpyo
Kim, Chang Min
Noh, Hyun Deok
Hong, Seung-Mo
Kim, Yeon Wook
Kim, Mi-Ju
Ansari, Adnan Ahmad
Buonaguro, Luigi
Ahn, Sung-Min
Yu, Chang-Sik
author_facet Park, In Ja
Yu, Yun Suk
Mustafa, Bilal
Park, Jin Young
Seo, Yong Bae
Kim, Gun-Do
Kim, Jinpyo
Kim, Chang Min
Noh, Hyun Deok
Hong, Seung-Mo
Kim, Yeon Wook
Kim, Mi-Ju
Ansari, Adnan Ahmad
Buonaguro, Luigi
Ahn, Sung-Min
Yu, Chang-Sik
author_sort Park, In Ja
collection PubMed
description Preoperative chemoradiotherapy (PCRT) and subsequent surgery is the standard multimodal treatment for locally advanced rectal cancer (LARC), albeit PCRT response varies among the individuals. This creates a dire necessity to identify a predictive model to forecast treatment response outcomes and identify patients who would benefit from PCRT. In this study, we performed a gene expression study using formalin-fixed paraffin-embedded (FFPE) tumor biopsy samples from 156 LARC patients (training cohort n = 60; validation cohort n = 96); we identified the nine-gene signature (FGFR3, GNA11, H3F3A, IL12A, IL1R1, IL2RB, NKD1, SGK2, and SPRY2) that distinctively differentiated responders from non-responders in the training cohort (accuracy = 86.9%, specificity = 84.8%, sensitivity = 81.5%) as well as in an independent validation cohort (accuracy = 81.0%, specificity = 79.4%, sensitivity = 82.3%). The signature was independent of all pathological and clinical features and was robust in predicting PCRT response. It is readily applicable to the clinical setting using FFPE samples and Food and Drug Administration (FDA) approved hardware and reagents. Predicting the response to PCRT may aid in tailored therapies for respective responders to PCRT and improve the oncologic outcomes for LARC patients.
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spelling pubmed-72264722020-05-18 A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer Park, In Ja Yu, Yun Suk Mustafa, Bilal Park, Jin Young Seo, Yong Bae Kim, Gun-Do Kim, Jinpyo Kim, Chang Min Noh, Hyun Deok Hong, Seung-Mo Kim, Yeon Wook Kim, Mi-Ju Ansari, Adnan Ahmad Buonaguro, Luigi Ahn, Sung-Min Yu, Chang-Sik Cancers (Basel) Article Preoperative chemoradiotherapy (PCRT) and subsequent surgery is the standard multimodal treatment for locally advanced rectal cancer (LARC), albeit PCRT response varies among the individuals. This creates a dire necessity to identify a predictive model to forecast treatment response outcomes and identify patients who would benefit from PCRT. In this study, we performed a gene expression study using formalin-fixed paraffin-embedded (FFPE) tumor biopsy samples from 156 LARC patients (training cohort n = 60; validation cohort n = 96); we identified the nine-gene signature (FGFR3, GNA11, H3F3A, IL12A, IL1R1, IL2RB, NKD1, SGK2, and SPRY2) that distinctively differentiated responders from non-responders in the training cohort (accuracy = 86.9%, specificity = 84.8%, sensitivity = 81.5%) as well as in an independent validation cohort (accuracy = 81.0%, specificity = 79.4%, sensitivity = 82.3%). The signature was independent of all pathological and clinical features and was robust in predicting PCRT response. It is readily applicable to the clinical setting using FFPE samples and Food and Drug Administration (FDA) approved hardware and reagents. Predicting the response to PCRT may aid in tailored therapies for respective responders to PCRT and improve the oncologic outcomes for LARC patients. MDPI 2020-03-26 /pmc/articles/PMC7226472/ /pubmed/32225122 http://dx.doi.org/10.3390/cancers12040800 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Park, In Ja
Yu, Yun Suk
Mustafa, Bilal
Park, Jin Young
Seo, Yong Bae
Kim, Gun-Do
Kim, Jinpyo
Kim, Chang Min
Noh, Hyun Deok
Hong, Seung-Mo
Kim, Yeon Wook
Kim, Mi-Ju
Ansari, Adnan Ahmad
Buonaguro, Luigi
Ahn, Sung-Min
Yu, Chang-Sik
A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer
title A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer
title_full A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer
title_fullStr A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer
title_full_unstemmed A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer
title_short A Nine-Gene Signature for Predicting the Response to Preoperative Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer
title_sort nine-gene signature for predicting the response to preoperative chemoradiotherapy in patients with locally advanced rectal cancer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226472/
https://www.ncbi.nlm.nih.gov/pubmed/32225122
http://dx.doi.org/10.3390/cancers12040800
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