Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients

Peizhun Du; Cheng’en Hu; Pengcheng Liu; Xuan Wang; Nikita Patel; Yi Liu; Guangjian Huang

doi:doi:10.11648/j.ijcocr.20220702.12

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Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients

Peizhun Du, Cheng’en Hu, Pengcheng Liu, Xuan Wang, Nikita Patel, Yi Liu, Guangjian Huang

Published in International Journal of Clinical Oncology and Cancer Research (Volume 7, Issue 2)

Received: 11 March 2022 Accepted: 6 April 2022 Published: 28 April 2022

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Abstract

Background: Gastric cancer (GC) is one of the most frequently occurring malignant tumors in the world with poor prognosis in digestive tract. LncRNA PVT1 is a potential oncogene, which is crucial for the occurrence and development of GC. The purpose of this study is to investigate the prognostic value of PVT1 associated genes in GC. Methods: PVT1 associated gene (PAG) expression was evaluated on cBioPortal. The gene expression data of PAGs and its corresponding clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) database. Kaplan–Meier survival analysis was performed to assess the prognostic value of PAG in GC. Risk score model was built by lasso COX regression analysis and its prognostic efficacy was evaluated by the Receiver-operator Characteristic (ROC) curve. Cox regression analyses were conducted to investigate risk factors related to GC patient prognosis. Results: There were 10 postively and 5 negatively associated genes that showed a significant difference between normal and GC tissue. Based on the 8 gene signature, the GC patients could be classified into high- or low-risk subgroups with different OS (P<0.001). Cox regression analyses indicated that the PAG risk model score was an independent prognostic factor for OS. Further analysis showed that adding chemotherapy drugs can not prolong the survival of high-risk GC patients. For low-risk patients, chemotherapy combined with radiotherapy is recommended. Even if distant metastasis has occurred, low-risk patients are worthy of active treatment, because their prognosis is often better. Conclusion: PAGs are potential biomarkers to predict the prognosis of GC patients and may assist oncologists to formulate individualized treatment plans for this patient population.

Published in	International Journal of Clinical Oncology and Cancer Research (Volume 7, Issue 2)
DOI	10.11648/j.ijcocr.20220702.12
Page(s)	21-28
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

LncRNA PVT1, Gastric Cancer, Prognostic, Risk Model

References

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APA Style

Peizhun Du, Cheng’en Hu, Pengcheng Liu, Xuan Wang, Nikita Patel, et al. (2022). Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients. International Journal of Clinical Oncology and Cancer Research, 7(2), 21-28. https://doi.org/10.11648/j.ijcocr.20220702.12

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ACS Style

Peizhun Du; Cheng’en Hu; Pengcheng Liu; Xuan Wang; Nikita Patel, et al. Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients. Int. J. Clin. Oncol. Cancer Res. 2022, 7(2), 21-28. doi: 10.11648/j.ijcocr.20220702.12

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AMA Style

Peizhun Du, Cheng’en Hu, Pengcheng Liu, Xuan Wang, Nikita Patel, et al. Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients. Int J Clin Oncol Cancer Res. 2022;7(2):21-28. doi: 10.11648/j.ijcocr.20220702.12

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@article{10.11648/j.ijcocr.20220702.12,
  author = {Peizhun Du and Cheng’en Hu and Pengcheng Liu and Xuan Wang and Nikita Patel and Yi Liu and Guangjian Huang},
  title = {Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients},
  journal = {International Journal of Clinical Oncology and Cancer Research},
  volume = {7},
  number = {2},
  pages = {21-28},
  doi = {10.11648/j.ijcocr.20220702.12},
  url = {https://doi.org/10.11648/j.ijcocr.20220702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijcocr.20220702.12},
  abstract = {Background: Gastric cancer (GC) is one of the most frequently occurring malignant tumors in the world with poor prognosis in digestive tract. LncRNA PVT1 is a potential oncogene, which is crucial for the occurrence and development of GC. The purpose of this study is to investigate the prognostic value of PVT1 associated genes in GC. Methods: PVT1 associated gene (PAG) expression was evaluated on cBioPortal. The gene expression data of PAGs and its corresponding clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) database. Kaplan–Meier survival analysis was performed to assess the prognostic value of PAG in GC. Risk score model was built by lasso COX regression analysis and its prognostic efficacy was evaluated by the Receiver-operator Characteristic (ROC) curve. Cox regression analyses were conducted to investigate risk factors related to GC patient prognosis. Results: There were 10 postively and 5 negatively associated genes that showed a significant difference between normal and GC tissue. Based on the 8 gene signature, the GC patients could be classified into high- or low-risk subgroups with different OS (P<0.001). Cox regression analyses indicated that the PAG risk model score was an independent prognostic factor for OS. Further analysis showed that adding chemotherapy drugs can not prolong the survival of high-risk GC patients. For low-risk patients, chemotherapy combined with radiotherapy is recommended. Even if distant metastasis has occurred, low-risk patients are worthy of active treatment, because their prognosis is often better. Conclusion: PAGs are potential biomarkers to predict the prognosis of GC patients and may assist oncologists to formulate individualized treatment plans for this patient population.},
 year = {2022}
}

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TY - JOUR
T1 - Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients
AU - Peizhun Du
AU - Cheng’en Hu
AU - Pengcheng Liu
AU - Xuan Wang
AU - Nikita Patel
AU - Yi Liu
AU - Guangjian Huang
Y1 - 2022/04/28
PY - 2022
N1 - https://doi.org/10.11648/j.ijcocr.20220702.12
DO - 10.11648/j.ijcocr.20220702.12
T2 - International Journal of Clinical Oncology and Cancer Research
JF - International Journal of Clinical Oncology and Cancer Research
JO - International Journal of Clinical Oncology and Cancer Research
SP - 21
EP - 28
PB - Science Publishing Group
SN - 2578-9511
UR - https://doi.org/10.11648/j.ijcocr.20220702.12
AB - Background: Gastric cancer (GC) is one of the most frequently occurring malignant tumors in the world with poor prognosis in digestive tract. LncRNA PVT1 is a potential oncogene, which is crucial for the occurrence and development of GC. The purpose of this study is to investigate the prognostic value of PVT1 associated genes in GC. Methods: PVT1 associated gene (PAG) expression was evaluated on cBioPortal. The gene expression data of PAGs and its corresponding clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) database. Kaplan–Meier survival analysis was performed to assess the prognostic value of PAG in GC. Risk score model was built by lasso COX regression analysis and its prognostic efficacy was evaluated by the Receiver-operator Characteristic (ROC) curve. Cox regression analyses were conducted to investigate risk factors related to GC patient prognosis. Results: There were 10 postively and 5 negatively associated genes that showed a significant difference between normal and GC tissue. Based on the 8 gene signature, the GC patients could be classified into high- or low-risk subgroups with different OS (P<0.001). Cox regression analyses indicated that the PAG risk model score was an independent prognostic factor for OS. Further analysis showed that adding chemotherapy drugs can not prolong the survival of high-risk GC patients. For low-risk patients, chemotherapy combined with radiotherapy is recommended. Even if distant metastasis has occurred, low-risk patients are worthy of active treatment, because their prognosis is often better. Conclusion: PAGs are potential biomarkers to predict the prognosis of GC patients and may assist oncologists to formulate individualized treatment plans for this patient population.
VL - 7
IS - 2
ER -

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Author Information

Peizhun Du

Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
Cheng’en Hu

Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
Pengcheng Liu

Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China
Xuan Wang

Department of Thoracic Surgery, Huashan Hospital, Fudan University, Shanghai, China
Nikita Patel

Dental Dreams, Baltimore Maryland, Unites States of America
Yi Liu

Department of Digestive Disease, Huashan Hospital, Fudan University, Shanghai, China
Guangjian Huang

Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, China

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APA Style

Peizhun Du, Cheng’en Hu, Pengcheng Liu, Xuan Wang, Nikita Patel, et al. (2022). Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients. International Journal of Clinical Oncology and Cancer Research, 7(2), 21-28. https://doi.org/10.11648/j.ijcocr.20220702.12

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ACS Style

Peizhun Du; Cheng’en Hu; Pengcheng Liu; Xuan Wang; Nikita Patel, et al. Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients. Int. J. Clin. Oncol. Cancer Res. 2022, 7(2), 21-28. doi: 10.11648/j.ijcocr.20220702.12

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AMA Style

Peizhun Du, Cheng’en Hu, Pengcheng Liu, Xuan Wang, Nikita Patel, et al. Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients. Int J Clin Oncol Cancer Res. 2022;7(2):21-28. doi: 10.11648/j.ijcocr.20220702.12

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@article{10.11648/j.ijcocr.20220702.12,
  author = {Peizhun Du and Cheng’en Hu and Pengcheng Liu and Xuan Wang and Nikita Patel and Yi Liu and Guangjian Huang},
  title = {Evaluating the Clinical Value of PVT1 Associated Genes in Predicting Prognosis and Guiding Treatment of Gastric Cancer Patients},
  journal = {International Journal of Clinical Oncology and Cancer Research},
  volume = {7},
  number = {2},
  pages = {21-28},
  doi = {10.11648/j.ijcocr.20220702.12},
  url = {https://doi.org/10.11648/j.ijcocr.20220702.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijcocr.20220702.12},
  abstract = {Background: Gastric cancer (GC) is one of the most frequently occurring malignant tumors in the world with poor prognosis in digestive tract. LncRNA PVT1 is a potential oncogene, which is crucial for the occurrence and development of GC. The purpose of this study is to investigate the prognostic value of PVT1 associated genes in GC. Methods: PVT1 associated gene (PAG) expression was evaluated on cBioPortal. The gene expression data of PAGs and its corresponding clinical characteristics were extracted from The Cancer Genome Atlas (TCGA) database. Kaplan–Meier survival analysis was performed to assess the prognostic value of PAG in GC. Risk score model was built by lasso COX regression analysis and its prognostic efficacy was evaluated by the Receiver-operator Characteristic (ROC) curve. Cox regression analyses were conducted to investigate risk factors related to GC patient prognosis. Results: There were 10 postively and 5 negatively associated genes that showed a significant difference between normal and GC tissue. Based on the 8 gene signature, the GC patients could be classified into high- or low-risk subgroups with different OS (P<0.001). Cox regression analyses indicated that the PAG risk model score was an independent prognostic factor for OS. Further analysis showed that adding chemotherapy drugs can not prolong the survival of high-risk GC patients. For low-risk patients, chemotherapy combined with radiotherapy is recommended. Even if distant metastasis has occurred, low-risk patients are worthy of active treatment, because their prognosis is often better. Conclusion: PAGs are potential biomarkers to predict the prognosis of GC patients and may assist oncologists to formulate individualized treatment plans for this patient population.},
 year = {2022}
}

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