Hong Guo
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Hong Guo has a total of 11 co-authors. Here are the top co-authors by number of shared publications:
Huaijuan Guo
Department of Oncology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China
2 shared publicationsJiaxin Wang
Department of Oncology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China
2 shared publicationsJingjing Yang
Department of Oncology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China
2 shared publicationsJingxian Mao
Department of Oncology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, Jiangsu, China
2 shared publications- Xuebing Yan
Department of Oncology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China
2 shared publications Hong Qiao
Department of Oncology, Baoying Traditional Chinese Medicine Hospital, Yangzhou University, Yangzhou, Jiangsu, China
1 shared publication
Latest Publications
- Open Access
- 29 July 2024
- Published by Frontiers Media SA in Frontiers in Pharmacology
- Vol. 15, 1419498
Prognostic impact of metformin in solid cancer patients receiving immune checkpoint inhibitors: novel evidences from a multicenter retrospective study
Objective: Metformin as a common antidiabetic drug, has recently found to exert its anti-cancer and immunomodulatory effect in numerous preclinical studies. This study aims to clarify the prognostic impact of metformin use in solid cancer patients receiving immune checkpoint inhibitors (ICIs).Methods: A retrospective cohort enrolling 516 solid cancer patients who received ICI-based therapy between 2018 and 2023 at three hospitals was analyzed. The primary endpoints included overall survival (OS) and progression-free survival (PFS). In addition, a bioinformatics analysis based on TCGA and GSE cohort was performed to investigate the prognostic significance of metformin target genes (MTGs) and their correlation with immune infiltration in non-small cell lung cancer (NSCLC) patients.Results: In the entire cohort, a total of 76 patients received metformin before and/or during ICI therapy. The global analysis demonstrated that metformin use was unrelated with the OS (p = 0.064) and PFS (p = 0.059) of ICI-treated cancer patients, which was confirmed in the subgroups of esophagus, hepatobiliary or pancreatic cancer (all p > 0.05). However, metformin use was significantly correlated with better OS (p = 0.012) and PFS (p = 0.005) in ICI-treated lung cancer patients. Metformin use was also identified as an independent favorable prognostic factor for these patients. The bioinformatics analysis identified five favorable prognostic MTGs (RPS6KA5, RORA, SH3BP5, NUPR1, and CD40LG) for NSCLC patients, all of which was downregulated in lung cancer tissues as compared with normal tissues. The expressions of five MTGs not only could effectively stratify the OS of NSCLC patients, but also was correlated with infiltration of immune cells such as CD4+ and CD8+ T cells.Conclusion: Metformin use was significantly correlated with better OS and PFS in ICI-treated lung cancer patients. MTGs has the potential to serve as novel clinical biomarkers or druggable targets for cancer immunotherapy. Considering study limitations, the actual impact of metformin use on ICI therapy needs to be clarified by more clinical trials.
- 29 July 2024
- Published by Frontiers Media SA in Frontiers in Pharmacology
- Vol. 15, 1419498
Open AccessPrognostic impact of metformin in solid cancer patients receiving immune checkpoint inhibitors: novel evidences from a multicenter retrospective study
Objective: Metformin as a common antidiabetic drug, has recently found to exert its anti-cancer and immunomodulatory effect in numerous preclinical studies. This study aims to clarify the prognostic impact of metformin use in solid cancer patients receiving immune checkpoint inhibitors (ICIs).Methods: A retrospective cohort enrolling 516 solid cancer patients who received ICI-based therapy between 2018 and 2023 at three hospitals was analyzed. The primary endpoints included overall survival (OS) and progression-free survival (PFS). In addition, a bioinformatics analysis based on TCGA and GSE cohort was performed to investigate the prognostic significance of metformin target genes (MTGs) and their correlation with immune infiltration in non-small cell lung cancer (NSCLC) patients.Results: In the entire cohort, a total of 76 patients received metformin before and/or during ICI therapy. The global analysis demonstrated that metformin use was unrelated with the OS (p = 0.064) and PFS (p = 0.059) of ICI-treated cancer patients, which was confirmed in the subgroups of esophagus, hepatobiliary or pancreatic cancer (all p > 0.05). However, metformin use was significantly correlated with better OS (p = 0.012) and PFS (p = 0.005) in ICI-treated lung cancer patients. Metformin use was also identified as an independent favorable prognostic factor for these patients. The bioinformatics analysis identified five favorable prognostic MTGs (RPS6KA5, RORA, SH3BP5, NUPR1, and CD40LG) for NSCLC patients, all of which was downregulated in lung cancer tissues as compared with normal tissues. The expressions of five MTGs not only could effectively stratify the OS of NSCLC patients, but also was correlated with infiltration of immune cells such as CD4+ and CD8+ T cells.Conclusion: Metformin use was significantly correlated with better OS and PFS in ICI-treated lung cancer patients. MTGs has the potential to serve as novel clinical biomarkers or druggable targets for cancer immunotherapy. Considering study limitations, the actual impact of metformin use on ICI therapy needs to be clarified by more clinical trials.
- Open Access
- 8 February 2024
- Published by Frontiers Media SA in Frontiers in Oncology
- Vol. 14, 1339729
Identification of C-PLAN index as a novel prognostic predictor for advanced lung cancer patients receiving immune checkpoint inhibitors
Objective: Increasing studies have highlighted the potential utility of non-invasive prognostic biomarkers in advanced lung cancer patients receiving immune checkpoint inhibitor (ICI) based anti-cancer therapies. Here, a novel prognostic predictor named as C-PLAN integrating C-reactive protein (CRP), Performance status (PS), Lactate dehydrogenase (LDH), Albumin (ALB), and derived Neutrophil-to-lymphocyte ratio (dNLR) was identified and validated in a single-center retrospective cohort.Methods: The clinical data of 192 ICI-treated lung cancer patients was retrospectively analyzed. The pretreatment levels of CRP, PS, LDH, ALB and dNLR were scored respectively and then their scores were added up to form C-PLAN index. The correlation of C-PLAN index with the progression-free survival (PFS) or overall survival (OS) was analyzed by a Kaplan–Meier model. The multivariate analysis was used to identify whether C-PLAN index was an independent prognostic predictor.Results: A total of 88 and 104 patients were included in the low and high C-PLAN index group respectively. High C-PLAN index was significantly correlated with worse PFS and OS in ICI-treated lung cancer patients (both p<0.001). The multivariate analysis revealed high C-PLAN index was an independent unfavorable factor affecting PFS (hazard ratio (HR)=1.821; 95%confidence interval (CI)=1.291-2.568) and OS (HR=2.058, 95%CI=1.431-2.959). The high C-PLAN index group had a significantly lower disease control rate than the low C-PLAN index group (p=0.024), while no significant difference was found for objective response rate (p=0.172). The subgroup analysis based on clinical features (pathological type, therapy strategy, TNM stage and age) confirmed the prognostic value of C-PLAN index, except for patients receiving ICI monotherapy or with age ranging from 18 to 65 years old. Finally, a nomogram was constructed based on C-PLAN index, age, gender, TNM stage and smoking status, which could predict well the 1-, 2- and 3-year survival of ICI-treated lung cancer patients.Conclusion: The C-PLAN index has great potential to be utilized as a non-invasive, inexpensive and reliable prognostic predictor for advanced lung cancer patients receiving ICI-based anti-cancer therapies.
- 8 February 2024
- Published by Frontiers Media SA in Frontiers in Oncology
- Vol. 14, 1339729
Open AccessIdentification of C-PLAN index as a novel prognostic predictor for advanced lung cancer patients receiving immune checkpoint inhibitors
Objective: Increasing studies have highlighted the potential utility of non-invasive prognostic biomarkers in advanced lung cancer patients receiving immune checkpoint inhibitor (ICI) based anti-cancer therapies. Here, a novel prognostic predictor named as C-PLAN integrating C-reactive protein (CRP), Performance status (PS), Lactate dehydrogenase (LDH), Albumin (ALB), and derived Neutrophil-to-lymphocyte ratio (dNLR) was identified and validated in a single-center retrospective cohort.Methods: The clinical data of 192 ICI-treated lung cancer patients was retrospectively analyzed. The pretreatment levels of CRP, PS, LDH, ALB and dNLR were scored respectively and then their scores were added up to form C-PLAN index. The correlation of C-PLAN index with the progression-free survival (PFS) or overall survival (OS) was analyzed by a Kaplan–Meier model. The multivariate analysis was used to identify whether C-PLAN index was an independent prognostic predictor.Results: A total of 88 and 104 patients were included in the low and high C-PLAN index group respectively. High C-PLAN index was significantly correlated with worse PFS and OS in ICI-treated lung cancer patients (both p<0.001). The multivariate analysis revealed high C-PLAN index was an independent unfavorable factor affecting PFS (hazard ratio (HR)=1.821; 95%confidence interval (CI)=1.291-2.568) and OS (HR=2.058, 95%CI=1.431-2.959). The high C-PLAN index group had a significantly lower disease control rate than the low C-PLAN index group (p=0.024), while no significant difference was found for objective response rate (p=0.172). The subgroup analysis based on clinical features (pathological type, therapy strategy, TNM stage and age) confirmed the prognostic value of C-PLAN index, except for patients receiving ICI monotherapy or with age ranging from 18 to 65 years old. Finally, a nomogram was constructed based on C-PLAN index, age, gender, TNM stage and smoking status, which could predict well the 1-, 2- and 3-year survival of ICI-treated lung cancer patients.Conclusion: The C-PLAN index has great potential to be utilized as a non-invasive, inexpensive and reliable prognostic predictor for advanced lung cancer patients receiving ICI-based anti-cancer therapies.