A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer
Cervical cancer is the fourth most common cancer in women worldwide. The current approaches still have limitations in predicting the therapy outcome of each individual because of cancer heterogeneity. The goal of this study was to establish a gene expression signature that could help when choosing t...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020-12-01
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| Series: | Molecular Therapy: Oncolytics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2372770520301388 |
| _version_ | 1829134375102447616 |
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| author | Ngoc Ngo Yen Nguyen Tae Gyu Choi Jieun Kim Min Hyung Jung Seok Hoon Ko Yoonhwa Shin Insug Kang Joohun Ha Sung Soo Kim Yong Hwa Jo |
| author_facet | Ngoc Ngo Yen Nguyen Tae Gyu Choi Jieun Kim Min Hyung Jung Seok Hoon Ko Yoonhwa Shin Insug Kang Joohun Ha Sung Soo Kim Yong Hwa Jo |
| author_sort | Ngoc Ngo Yen Nguyen |
| collection | DOAJ |
| description | Cervical cancer is the fourth most common cancer in women worldwide. The current approaches still have limitations in predicting the therapy outcome of each individual because of cancer heterogeneity. The goal of this study was to establish a gene expression signature that could help when choosing the right therapeutic method for the treatment of advanced-stage cervical cancer. The 666 patients were collected from four independent datasets. The 70-gene expression signature was established using univariate Cox proportional hazard regression analysis. The 70-gene signature was significantly different between low- and high-risk groups in the training dataset (p = 4.24e−6) and in the combined three validation datasets (p = 4.37e−3). Treatment of advanced-stage cancer patients in the high-risk group with molecular-targeted therapy combined with chemoradiotherapy yielded a better survival rate than with only chemoradiotherapy (p = 0.0746). However, treatment of the patients in the low-risk group with the combined therapy resulted in significantly lower survival (p = 0.00283). Functional classification of 70 genes revealed involvement of the angiogenesis pathway, specifically phosphatidylinositol 3-kinase signaling (p = 0.040), extracellular matrix organization (p = 0.0452), and cell adhesion (p = 0.011). The 70-gene signature could predict the prognosis and indicate an optimal therapeutic modality in molecular-targeted therapy or chemotherapy for advanced-stage cervical cancer. |
| first_indexed | 2024-12-14T17:59:49Z |
| format | Article |
| id | doaj.art-a7b8101bf78b4e84ac994481c0ad0731 |
| institution | Directory Open Access Journal |
| issn | 2372-7705 |
| language | English |
| last_indexed | 2024-12-14T17:59:49Z |
| publishDate | 2020-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Molecular Therapy: Oncolytics |
| spelling | doaj.art-a7b8101bf78b4e84ac994481c0ad07312022-12-21T22:52:28ZengElsevierMolecular Therapy: Oncolytics2372-77052020-12-01194756A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical CancerNgoc Ngo Yen Nguyen0Tae Gyu Choi1Jieun Kim2Min Hyung Jung3Seok Hoon Ko4Yoonhwa Shin5Insug Kang6Joohun Ha7Sung Soo Kim8Yong Hwa Jo9Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of KoreaBiomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of KoreaDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of KoreaDepartment of Obstetrics and Gynecology, School of Medicine, Kyung Hee Medical Center, Kyung Hee University, Seoul 02447, Republic of KoreaDepartment of Emergency Medicine, School of Medicine, Kyung Hee Medical Center, Kyung Hee University, Seoul 02447, Republic of KoreaDepartment of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea; Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of KoreaBiomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of KoreaBiomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of KoreaBiomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea; Corresponding author: Sung Soo Kim, Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea; Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea; Corresponding author: Yong Hwa Jo, Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, 26 Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.Cervical cancer is the fourth most common cancer in women worldwide. The current approaches still have limitations in predicting the therapy outcome of each individual because of cancer heterogeneity. The goal of this study was to establish a gene expression signature that could help when choosing the right therapeutic method for the treatment of advanced-stage cervical cancer. The 666 patients were collected from four independent datasets. The 70-gene expression signature was established using univariate Cox proportional hazard regression analysis. The 70-gene signature was significantly different between low- and high-risk groups in the training dataset (p = 4.24e−6) and in the combined three validation datasets (p = 4.37e−3). Treatment of advanced-stage cancer patients in the high-risk group with molecular-targeted therapy combined with chemoradiotherapy yielded a better survival rate than with only chemoradiotherapy (p = 0.0746). However, treatment of the patients in the low-risk group with the combined therapy resulted in significantly lower survival (p = 0.00283). Functional classification of 70 genes revealed involvement of the angiogenesis pathway, specifically phosphatidylinositol 3-kinase signaling (p = 0.040), extracellular matrix organization (p = 0.0452), and cell adhesion (p = 0.011). The 70-gene signature could predict the prognosis and indicate an optimal therapeutic modality in molecular-targeted therapy or chemotherapy for advanced-stage cervical cancer.http://www.sciencedirect.com/science/article/pii/S2372770520301388cervical cancergene signaturesurvivaladvanced stagemolecular-targeted therapy |
| spellingShingle | Ngoc Ngo Yen Nguyen Tae Gyu Choi Jieun Kim Min Hyung Jung Seok Hoon Ko Yoonhwa Shin Insug Kang Joohun Ha Sung Soo Kim Yong Hwa Jo A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer Molecular Therapy: Oncolytics cervical cancer gene signature survival advanced stage molecular-targeted therapy |
| title | A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer |
| title_full | A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer |
| title_fullStr | A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer |
| title_full_unstemmed | A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer |
| title_short | A 70-Gene Signature for Predicting Treatment Outcome in Advanced-Stage Cervical Cancer |
| title_sort | 70 gene signature for predicting treatment outcome in advanced stage cervical cancer |
| topic | cervical cancer gene signature survival advanced stage molecular-targeted therapy |
| url | http://www.sciencedirect.com/science/article/pii/S2372770520301388 |
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