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Tang FH, Fong YW, Yung SH, Wong CK, Tu CL, Chan MT. Radiomics-Clinical AI Model with Probability Weighted Strategy for Prognosis Prediction in Non-Small Cell Lung Cancer. Biomedicines 2023; 11:2093. [PMID: 37626590 PMCID: PMC10452490 DOI: 10.3390/biomedicines11082093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 06/29/2023] [Accepted: 07/19/2023] [Indexed: 08/27/2023] Open
Abstract
In this study, we propose a radiomics clinical probability-weighted model for the prediction of prognosis for non-small cell lung cancer (NSCLC). The model combines radiomics features extracted from radiotherapy (RT) planning images with clinical factors such as age, gender, histology, and tumor stage. CT images with radiotherapy structures of 422 NSCLC patients were retrieved from The Cancer Imaging Archive (TCIA). Radiomic features were extracted from gross tumor volumes (GTVs). Five machine learning algorithms, namely decision trees (DT), random forests (RF), extreme boost (EB), support vector machine (SVM) and generalized linear model (GLM) were optimized by a voted ensemble machine learning (VEML) model. A probabilistic weighted approach is used to incorporate the uncertainty associated with both radiomic and clinical features and to generate a probabilistic risk score for each patient. The performance of the model is evaluated using a receiver operating characteristic (ROC). The Radiomic model, clinical factor model, and combined radiomic clinical probability-weighted model demonstrated good performance in predicting NSCLC survival with AUC of 0.941, 0.856 and 0.949, respectively. The combined radiomics clinical probability-weighted enhanced model achieved significantly better performance than the radiomic model in 1-year survival prediction (chi-square test, p < 0.05). The proposed model has the potential to improve NSCLC prognosis and facilitate personalized treatment decisions.
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Affiliation(s)
- Fuk-Hay Tang
- School of Medical and Health Sciences, Tung Wah College, Hong Kong, China
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2
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Zhou J, Shi S, Qiu Y, Jin Z, Yu W, Xie R, Zhang H. Integrative bioinformatics approaches to establish potential prognostic immune-related genes signature and drugs in the non-small cell lung cancer microenvironment. Front Pharmacol 2023; 14:1153565. [PMID: 37077811 PMCID: PMC10106634 DOI: 10.3389/fphar.2023.1153565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 03/23/2023] [Indexed: 04/05/2023] Open
Abstract
Introduction: Research has revealed that the tumor microenvironment (TME) is associated with the progression of malignancy. The combination of meaningful prognostic biomarkers related to the TME is expected to be a reliable direction for improving the diagnosis and treatment of non-small cell lung cancer (NSCLC).Method and Result: Therefore, to better understand the connection between the TME and survival outcomes of NSCLC, we used the “DESeq2” R package to mine the differentially expressed genes (DEGs) of two groups of NSCLC samples according to the optimal cutoff value of the immune score through the ESTIMATE algorithm. A total of 978 up-DEGs and 828 down-DEGs were eventually identified. A fifteen-gene prognostic signature was established via LASSO and Cox regression analysis and further divided the patients into two risk sets. The survival outcome of high-risk patients was significantly worse than that of low-risk patients in both the TCGA and two external validation sets (p-value < 0.05). The gene signature showed high predictive accuracy in TCGA (1-year area under the time-dependent ROC curve (AUC) = 0.722, 2-year AUC = 0.708, 3-year AUC = 0.686). The nomogram comprised of the risk score and related clinicopathological information was constructed, and calibration plots and ROC curves were applied, KEGG and GSEA analyses showed that the epithelial-mesenchymal transition (EMT) pathway, E2F target pathway and immune-associated pathway were mainly involved in the high-risk group. Further somatic mutation and immune analyses were conducted to compare the differences between the two groups. Drug sensitivity provides a potential treatment basis for clinical treatment. Finally, EREG and ADH1C were selected as the key prognostic genes of the two overlapping results from PPI and multiple Cox analyses. They were verified by comparing the mRNA expression in cell lines and protein expression in the HPA database, and clinical validation further confirmed the effectiveness of key genes.Conclusion: In conclusion, we obtained an immune-related fifteen-gene prognostic signature and potential mechanism and sensitive drugs underling the prognosis model, which may provide accurate prognosis prediction and available strategies for NSCLC.
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Affiliation(s)
- Jiao Zhou
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Shan Shi
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Yeqing Qiu
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Zhongwen Jin
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Wenyan Yu
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Rongzhi Xie
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Cancer Center, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- *Correspondence: Rongzhi Xie, ; Hongyu Zhang,
| | - Hongyu Zhang
- The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- Cancer Center, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, China
- *Correspondence: Rongzhi Xie, ; Hongyu Zhang,
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Shao F, Ling L, Li C, Huang X, Ye Y, Zhang M, Huang K, Pan J, Chen J, Wang Y. Establishing a metastasis-related diagnosis and prognosis model for lung adenocarcinoma through CRISPR library and TCGA database. J Cancer Res Clin Oncol 2023; 149:885-899. [PMID: 36574046 DOI: 10.1007/s00432-022-04495-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 11/23/2022] [Indexed: 12/28/2022]
Abstract
PURPOSE Existing biomarkers for diagnosing and predicting metastasis of lung adenocarcinoma (LUAD) may not meet the demands of clinical practice. Risk prediction models with multiple markers may provide better prognostic factors for accurate diagnosis and prediction of metastatic LUAD. METHODS An animal model of LUAD metastasis was constructed using CRISPR technology, and genes related to LUAD metastasis were screened by mRNA sequencing of normal and metastatic tissues. The immune characteristics of different subtypes were analyzed, and differentially expressed genes were subjected to survival and Cox regression analyses to identify the specific genes involved in metastasis for constructing a prediction model. The biological function of RFLNA was verified by analyzing CCK-8, migration, invasion, and apoptosis in LUAD cell lines. RESULTS We identified 108 differentially expressed genes related to metastasis and classified LUAD samples into two subtypes according to gene expression. Subsequently, a prediction model composed of eight metastasis-related genes (RHOBTB2, KIAA1524, CENPW, DEPDC1, RFLNA, COL7A1, MMP12, and HOXB9) was constructed. The areas under the curves of the logistic regression and neural network were 0.946 and 0.856, respectively. The model effectively classified patients into low- and high-risk groups. The low-risk group had a better prognosis in both the training and test cohorts, indicating that the prediction model had good diagnostic and predictive power. Upregulation of RFLNA successfully promoted cell proliferation, migration, invasion, and attenuated apoptosis, suggesting that RFLNA plays a role in promoting LUAD development and metastasis. CONCLUSION The model has important diagnostic and prognostic value for metastatic LUAD and may be useful in clinical applications.
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Affiliation(s)
- Fanggui Shao
- Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,Department of Clinical Laboratory, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Liqun Ling
- Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,Department of Clinical Laboratory, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Changhong Li
- Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,Department of Clinical Laboratory, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xiaolu Huang
- Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,Department of Clinical Laboratory, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yincai Ye
- Department of Blood Transfusion, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Meijuan Zhang
- Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.,Department of Clinical Laboratory, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kate Huang
- Department of Pathology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jingye Pan
- Key Laboratory of Intelligent Treatment and Life Support for Critical Diseases of Zhejiang Provincial, Wenzhou, China. .,Department of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
| | - Jie Chen
- Department of ICU, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
| | - Yumin Wang
- Department of Laboratory Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. .,Department of Clinical Laboratory, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
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Li J, Ma C, Yuan X, Wang X, Li N, Yu R, Liao H. Preoperative Serum Triglyceride to High-Density Lipoprotein Cholesterol Ratio Can Predict Prognosis in Non-Small Cell Lung Cancer: A Multicenter Retrospective Cohort Study. Curr Oncol 2022; 29:6125-6136. [PMID: 36135050 PMCID: PMC9497812 DOI: 10.3390/curroncol29090481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/14/2022] [Accepted: 08/23/2022] [Indexed: 01/17/2023] Open
Abstract
Background: Previously, research has reported associations of lipid and lipoprotein imbalances with carcinogenesis and cancer progression, so they have been considered as promising prognostic biomarkers for cancer in recent years. However, the correlation of preoperative serum triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) with non-small cell lung carcinoma (NSCLC) prognosis remains under exploration. Here, the study investigated the prognostic function of TG/HDL-C for NSCLC. Methods: The total combined group of this retrospective study enrolled 479 NSCLC patients from two tertiary referral hospitals, of which 223 patients were defined as the training group (Nanchang) and the remaining 256 were defined as the validation group (Wuhan). The cut-off of preoperative TG/HDL-C was determined through ROC curve in the training group and verified in the validation and combined groups subsequently. With one Cox proportional hazards model and K-M survival curves, a survival analysis was conducted. Results: In the training group, the optimal cut-off of TG/HDL-C was 1.02. Furthermore, the data based on the training group revealed a greater, shorter, overall survival (OS) in patients having a high TG/HDL-C (>1.02) than those having low TG/HDL-C (≤1.02). Meanwhile, in univariate and multivariate analysis, for prognostic OS among NSCLC patients, TG/HDL-C acted as one independent factor. All the results above were confirmed in the validation and combined groups. Conclusion: NSCLC patients with a comparatively low preoperative serum TG/HDL-C level had a correlation with well OS. TG/HDL-C possibly acted as one novel, effective prognostic biomarker for NSCLC patients.
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Affiliation(s)
- Junhong Li
- Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Cong Ma
- Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xuhui Yuan
- Department of Surgery, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
- Department of Surgery, Third Affiliated Hospital of Nanchang University, Nanchang 330008, China
| | - Xiaoyan Wang
- Department of Surgery, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Na Li
- Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Ronghui Yu
- Department of Surgery, First Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Hui Liao
- Department of Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
- Correspondence:
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Choi J, Sarker A, Choi H, Lee DS, Im HJ. Prognostic impact of an integrative analysis of [ 18F]FDG PET parameters and infiltrating immune cell scores in lung adenocarcinoma. EJNMMI Res 2022; 12:38. [PMID: 35759068 PMCID: PMC9237200 DOI: 10.1186/s13550-022-00908-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 06/15/2022] [Indexed: 09/28/2023] Open
Abstract
Background High levels of 18F-fluorodeoxyglucose (18F-FDG) tumor uptake are associated with worse prognosis in patients with non-small cell lung cancer (NSCLC). Meanwhile, high levels of immune cell infiltration in primary tumor have been linked to better prognosis in NSCLC. We conducted this study for precisely stratified prognosis of the lung adenocarcinoma patients using the integration of 18F-FDG positron emission tomography (PET) parameters and infiltrating immune cell scores as assessed by a genomic analysis. Results Using an RNA sequencing dataset, the patients were divided into three subtype groups. Additionally, 24 different immune cell scores and cytolytic scores (CYT) were obtained. In 18F-FDG PET scans, PET parameters of the primary tumors were obtained. An ANOVA test, a Chi-square test and a correlation analysis were also conducted. A Kaplan–Meier survival analysis with the log-rank test and multivariable Cox regression test was performed to evaluate prognostic values of the parameters. The terminal respiratory unit (TRU) group demonstrated lower 18F-FDG PET parameters, more females, and lower stages than the other groups. Meanwhile, the proximal inflammatory (PI) group showed a significantly higher CYT score compared to the other groups (P = .001). Also, CYT showed a positive correlation with tumor-to-liver maximum standardized uptake value ratio (TLR) in the PI group (P = .027). A high TLR (P = .01) score of 18F-FDG PET parameters and a high T follicular helper cell (TFH) score (P = .005) of immune cell scores were associated with prognosis with opposite tendencies. Furthermore, TLR and TFH were predictive of overall survival even after adjusting for clinicopathologic features and others (P = .024 and .047). Conclusions A high TLR score was found to be associated with worse prognosis, while high CD8 T cell and TFH scores predicted better prognosis in lung adenocarcinoma. Furthermore, TLR and TFH can be used to predict prognosis independently in patients with lung adenocarcinoma.
Supplementary Information The online version contains supplementary material available at 10.1186/s13550-022-00908-9.
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Affiliation(s)
- Jinyeong Choi
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea
| | - Azmal Sarker
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyung-Jun Im
- Department of Applied Bioengineering, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea. .,Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, 08826, Republic of Korea. .,Cancer Research Institute, Seoul National University, 03080, Seoul, Republic of Korea. .,Research Institute for Convergence Science, Seoul National University, Seoul, 08826, Republic of Korea.
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Cao J, Luo F, Zeng K, Ma W, Lu F, Huang Y, Zhang L, Zhao H. Predictive Value of High Preoperative Serum Total Protein and Elevated Hematocrit in Patients with Non-Small-Cell Lung Cancer after Radical Resection. Nutr Cancer 2022; 74:3533-3545. [PMID: 35642624 DOI: 10.1080/01635581.2022.2079683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND The relationship between the dynamic alterations of nutritional indexes before and after surgery, and the prognosis of non-small-cell lung cancer (NSCLC) after radical surgery are unclear. Methods: This study enrolled 100 NSCLC patients in stages I-III who received radical surgery. The preoperative and postoperative 6-month levels of nine nutrition-related indicators were assessed in patients. Survival was analyzed using Kaplan-Meier curves as well as Cox regression models. RESULTS Patients had better disease-free survival (DFS) with baseline total protein (TP) >76.66 g/L (75% vs. 50%, P = .027), baseline albumin (ALB) >37.7 g/L (60% vs. 26.7%, P = .002), baseline albumin to globulin ratio (AGR) >1.31 (63.5% vs. 40.5%, P = .006), or baseline globulin (GLOB) <31.42 g/L (39.4% vs. 62.7%, P = .037). Moreover, patients with increased hematocrit (HCT) (69.8% vs. 43.9% P = .013) and mean corpuscular volume (MCV) (73.2% vs. 42.4%, P = .014) at the postoperative 6-month examination had superior DFS. Cox proportional hazards regression analyses demonstrated that age >65 years, adenocarcinoma (pathological type), higher baseline TP, and post-surgery elevated HCT independently predicted favorable DFS. CONCLUSION Lower baseline TP and decreased postoperative HCT levels are independent predictors of prognosis in NSCLC following radical surgical procedures.
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Affiliation(s)
- Jiaxin Cao
- Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Fan Luo
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Kangmei Zeng
- Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wenjuan Ma
- Department of Intensive Care Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Feiteng Lu
- Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yan Huang
- Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Li Zhang
- Department of Medical Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Hongyun Zhao
- Department of Clinical Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
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Huang X, Hu P, Yan F, Zhang J. Establishment and Validation of a Nomogram Based on Negative Lymph Nodes to Predict Survival in Postoperative Patients with non-Small Cell Lung Cancer. Technol Cancer Res Treat 2022; 21:15330338221074506. [PMID: 35060800 PMCID: PMC8796078 DOI: 10.1177/15330338221074506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/09/2022] Open
Abstract
Background: The importance of the negative lymph node (NLN) count has recently attracted attention. This study aimed to determine the prognostic value of NLN count in patients with non-small cell lung cancer (NSCLC) after radical surgery by constructing NLN-based prognostic models. Methods: This study included 33 756 patients pooled from the case listing session of the US Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015 and 545 patients collected from The First Affiliated Hospital of Shandong First Medical University between 2012 and 2016. X-tile software was used to calculate the optimal cutoff value for the NLN count. The associated clinical factors were determined using univariate and multivariate Cox analyses. Nomograms were developed using the SEER database and validated using hospital data. Results: The training cohort was divided into high and low NLN count subgroups based on the cancer-specific survival (CSS) and overall survival (OS), respectively. Multivariate analysis showed that NLN count was an independent prognostic factor, and the high NLN count subgroup had better CSS and OS than those of the low NLN count subgroup (HR = 0.632, 95% CI 0.551-0.724, P < .001 for CSS and HR = 0.641, 95% CI 0.571-0.720, P < .001 for OS). Nomograms were established, exhibiting good discrimination ability with a C-index of 0.789 (95% CI 0.778 −0.798) for CSS and 0.704 (95% CI, 0.694 −0.714) for OS. The calibration plots of the validation cohorts showed optimal agreement with the training cohort, with a C-index of 0.681 (95% CI 0.646 −0.716) for CSS and 0.645 (95% CI 0.614 −0.676) for OS. Conclusions: NLN count is a strong prognostic factor for OS and CSS in NSCLC patients and the prognostic model provides a useful risk stratification for NSCLC patients when applied to clinical practice.
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Affiliation(s)
- Xinyi Huang
- The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
- Shandong Cancer Hospital and Institute, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, China
- The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, China
| | - Pingping Hu
- The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, China
| | - Fei Yan
- Dezhou Seventh People’s Hospital, Dezhou, China
| | - Jiandong Zhang
- The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, Shandong Lung Cancer Institute, Jinan, China
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Zhang Y, Chen J, Zhao Y, Weng L, Xu Y. Ceramide Pathway Regulators Predict Clinical Prognostic Risk and Affect the Tumor Immune Microenvironment in Lung Adenocarcinoma. Front Oncol 2020; 10:562574. [PMID: 33194633 PMCID: PMC7653182 DOI: 10.3389/fonc.2020.562574] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/28/2020] [Indexed: 01/29/2023] Open
Abstract
Purpose The ceramide pathway is strongly associated with the regulation of tumor proliferation, differentiation, senescence, and apoptosis. This study aimed to explore the gene signatures, prognostic value, and immune-related effects of ceramide-regulated genes in lung adenocarcinoma (LUAD). Methods Public datasets of LUAD from The Cancer Genome Atlas and Gene Expression Omnibus were selected. Consensus clustering was adopted to classify LUAD patients, and a least absolute shrinkage and selection operator (LASSO) regression model was employed to develop a prognostic risk signature. CIBERSORT algorithm was used to estimate the association between the risk signature and the tumor immune microenvironment. Results Most of the 22 ceramide-regulated genes were differentially expressed between LUAD and normal samples. LUAD patients were classified into two subgroups (cluster 1 and 2) and cluster 2 was associated with a poor prognosis. Furthermore, a prognostic risk signature was developed based on the three ceramide-regulated genes, Cytochrome C (CYCS), V-rel reticuloendotheliosis viral oncogene homolog A (RELA) and Fas-associated via death domain (FADD). LUAD patients with low- and high-risk scores differed concerning the subtypes of tumor-infiltrating immune cells. A moderate to weak correlation was observed between the risk score and tumor-infiltrating immune cells. Conclusions Ceramide-regulated genes could predict clinical prognostic risk and affect the tumor immune microenvironment in LUAD.
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Affiliation(s)
- Yuan Zhang
- The First Affiliated Hospital of Xiamen University, Xiamen, China
| | - Jianbo Chen
- Department of Medical Oncology, Xiamen Key Laboratory of Antitumor Drug Transformation Research, The First Affiliated Hospital of Xiamen University, School of Clinical Medicine, Fujian Medical University, Xiamen, China
| | - Yunan Zhao
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
| | - Lihong Weng
- Shengli Clinical Medical College of Fujian Medical University, Fuzhou, China
| | - Yiquan Xu
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Xiamen University, Xiamen, China
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Chen RL, Zhou JX, Cao Y, Sun LL, Su S, Deng XJ, Lin JT, Xiao ZW, Chen ZZ, Wang SY, Lin LZ. Construction of a Prognostic Immune Signature for Squamous-Cell Lung Cancer to Predict Survival. Front Immunol 2020; 11:1933. [PMID: 33072067 PMCID: PMC7533590 DOI: 10.3389/fimmu.2020.01933] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 07/17/2020] [Indexed: 12/25/2022] Open
Abstract
Background Limited treatment strategies are available for squamous-cell lung cancer (SQLC) patients. Few studies have addressed whether immune-related genes (IRGs) or the tumor immune microenvironment can predict the prognosis for SQLC patients. Our study aimed to construct a signature predict prognosis for SQLC patients based on IRGs. Methods We constructed and validated a signature from SQLC patients in The Cancer Genome Atlas (TCGA) using bioinformatics analysis. The underlying mechanisms of the signature were also explored with immune cells and mutation profiles. Results A total of 464 eligible SQLC patients from TCGA dataset were enrolled and were randomly divided into the training cohort (n = 232) and the testing cohort (n = 232). Eight differentially expressed IRGs were identified and applied to construct the immune signature in the training cohort. The signature showed a significant difference in overall survival (OS) between low-risk and high-risk cohorts (P < 0.001), with an area under the curve of 0.76. The predictive capability was verified with the testing and total cohorts. Multivariate analysis revealed that the 8-IRG signature served as an independent prognostic factor for OS in SQLC patients. Naive B cells, resting memory CD4 T cells, follicular helper T cells, and M2 macrophages were found to significantly associate with OS. There was no statistical difference in terms of tumor mutational burden between the high-risk and low-risk cohorts. Conclusion Our study constructed and validated an 8-IRG signature prognostic model that predicts clinical outcomes for SQLC patients. However, this signature model needs further validation with a larger number of patients.
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Affiliation(s)
- Rui-Lian Chen
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jing-Xu Zhou
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yang Cao
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Ling-Ling Sun
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shan Su
- Department of Oncology, Guangzhou Chest Hospital, Guangzhou, China
| | - Xiao-Jie Deng
- Department of Oncology, Shenzhen People's Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, China
| | - Jie-Tao Lin
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhi-Wei Xiao
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhuang-Zhong Chen
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Si-Yu Wang
- Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Li-Zhu Lin
- Integrative Cancer Centre, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
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Jing L, Feng L, Zhou Z, Shi S, Deng R, Wang Z, Zhang Y, Ren Z, Liu Y. TNNT2 as a potential biomarker for the progression and prognosis of colorectal cancer. Oncol Rep 2020; 44:628-636. [PMID: 32627044 PMCID: PMC7336514 DOI: 10.3892/or.2020.7637] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 02/26/2020] [Indexed: 12/15/2022] Open
Abstract
Colorectal cancer (CRC) is the third most common cancer worldwide. At present, there are limited effective biomarkers of CRC. The present study aimed to identify potential signatures associated with the tumorigenesis and prognosis of CRC using publicly available databases, and further validate the identified biomarkers in CRC cell lines. Identification of differentially expressed mRNAs between CRC and paracancerous samples was conducted based on data from The Cancer Genome Atlas (TCGA; 471 tumor samples and 41 normal samples). Survival analysis was performed to explore the prognostic value of troponin 2 (TNNT2) in the TCGA training set, which was further validated in an external dataset, GSE17531. Functional enrichment analysis was conducted to determine the possible biological functions using GSEA 3.0. Reverse transcription-quantitative PCR (RT-qPCR) and western blotting were utilized to detect the mRNA and protein expression levels of TNNT2 between CRC and normal colorectal cells. Immunohistochemistry was performed to detect the protein expression of TNNT2 in CRC and normal tissues. TNNT2 was significantly upregulated in CRC samples compared with adjacent normal samples in the TCGA dataset. Increased expression of TNNT2 was associated with inferior prognosis in the TCGA training dataset and GSE17531 validation dataset. Functional enrichment analysis revealed that the ErbB signaling pathway and glycerophospholipid metabolism pathway were significantly activated in the TNNT2 high expression group. Overexpression of TNNT2 mRNA and TNNT2 protein in CRC tumor cells was confirmed by RT-qPCR and western blotting, respectively. Immunohistochemistry indicated increased protein expression levels of TNNT2 in CRC tissues in comparison with normal tissues. TNNT2 was associated with the tumorigenesis and prognosis of CRC, which may be useful for novel biomarker identification and targeted therapeutic strategy development.
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Affiliation(s)
- Li Jing
- Department of Medical Oncology, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Li Feng
- Department of Medical Oncology, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Zhiguo Zhou
- Department of Radiotherapy, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Shuai Shi
- Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Ruoying Deng
- Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Zhicong Wang
- Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Yi Zhang
- Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
| | - Zhixue Ren
- The Seven People's Hospital of Hebei Province, Dingzhou, Hebei 073000, P.R. China
| | - Yibing Liu
- Department of Medical Oncology, Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei 050011, P.R. China
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Luo F, Zeng KM, Zhang ZH, Zhou T, Zhan JH, Lu FT, Yang YP, Huang Y, Zhang L, Zhao HY. Prognostic value of serum high-density lipoprotein cholesterol elevation in nonsmall cell lung cancer patients receiving radical surgery. Clin Transl Med 2020; 10:e94. [PMID: 32508010 PMCID: PMC7403695 DOI: 10.1002/ctm2.94] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 05/20/2020] [Indexed: 02/01/2023] Open
Affiliation(s)
- Fan Luo
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Kang-Mei Zeng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Zhong-Han Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Ting Zhou
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Jian-Hua Zhan
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Fei-Teng Lu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Yun-Peng Yang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Yan Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Li Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
| | - Hong-Yun Zhao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, P. R. China
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Affiliation(s)
- Siddhartha Devarakonda
- Section of Medical Oncology, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, St Louis, Missouri
| | - Ramaswamy Govindan
- Section of Medical Oncology, Division of Oncology, Washington University School of Medicine, St Louis, Missouri
- Siteman Cancer Center, St Louis, Missouri
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