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Pan L, Mu L, Lei H, Miao S, Hu X, Tang Z, Chen W, Wang X. Predicting survival benefits of immune checkpoint inhibitor therapy in lung cancer patients: a machine learning approach using real-world data. Int J Clin Pharm 2024:10.1007/s11096-024-01818-7. [PMID: 39470981 DOI: 10.1007/s11096-024-01818-7] [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: 07/26/2024] [Accepted: 10/04/2024] [Indexed: 11/01/2024]
Abstract
BACKGROUND Due to the heterogeneity in the effectiveness of immunotherapy for lung cancer, identifying predictors is crucial. AIM This study aimed to develop a machine learning model to identify predictors of overall survival in lung cancer patients treated with immune checkpoint inhibitors (ICIs). METHOD A retrospective analysis was performed on data from 1314 lung cancer patients at the Chongqing University Cancer Hospital from September 2018 to September 2022. We used the random survival forest (RSF) model to identify survival-influencing factors, using backward elimination for variable selection. A Cox proportional hazards (CPH) model was constructed using the most significant predictors. We assessed model performance and generalizability using time-dependent receiver operating characteristics (ROC) and predictive error curves. RESULTS The RSF model demonstrated better predictive accuracy than the CPH (IBS 0.17 vs. 0.17; C-index 0.91 vs. 0.68), with better discrimination and prediction performance. The influential variables identified included D-dimer, Karnofsky performance status, albumin, surgery, TNM stage, platelet count, and age. The RSF model, which incorporated these variables, achieved area under the curve (AUC) scores of 0.95, 0.94, and 0.98 for 1-, 3-, and 5-year survival predictions, respectively, in the training set. The validation set showed AUCs of 0.94, 0.90, and 0.95, respectively, exceeding the performance of the CPH model. CONCLUSION The study successfully developed a machine learning model that accurately predicted the survival benefits of ICI therapy in lung cancer patients, supporting clinical decision-making in lung cancer treatment.
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Affiliation(s)
- Lingyun Pan
- Department of Pharmacy, Chongqing University Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, China
| | - Li Mu
- Department of Pharmacy, Chongqing University Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, China
| | - Haike Lei
- Chongqing Cancer Multi-Omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, China
| | - Siwei Miao
- Centre for Medical Big Data and Artificial Intelligence, First Affiliated Hospital of Third Military Medical University: Southwest Hospital, Chongqing, China
| | - Xiaogang Hu
- Department of Pharmacy, Chongqing University Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, China
| | - Zongwei Tang
- Department of Pharmacy, Chongqing University Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, China
| | - Wanyi Chen
- Department of Pharmacy, Chongqing University Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, China.
- Chongqing University, Chongqing, China.
| | - Xiaoxiao Wang
- Department of Pharmacy, Chongqing University Cancer Hospital, No. 181 Hanyu Road, Shapingba District, Chongqing, China.
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Zhang J, Du B, Wang Y, Cui Y, Wang S, Zhao Y, Li Y, Li X. The role of CD8 PET imaging in guiding cancer immunotherapy. Front Immunol 2024; 15:1428541. [PMID: 39072335 PMCID: PMC11272484 DOI: 10.3389/fimmu.2024.1428541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 06/27/2024] [Indexed: 07/30/2024] Open
Abstract
Currently, immunotherapy is being widely used for treating cancers. However, the significant heterogeneity in patient responses is a major challenge for its successful application. CD8-positive T cells (CD8+ T cells) play a critical role in immunotherapy. Both their infiltration and functional status in tumors contribute to treatment outcomes. Therefore, accurate monitoring of CD8+ T cells, a potential biomarker, may improve therapeutic strategy. Positron emission tomography (PET) is an optimal option which can provide molecular imaging with enhanced specificity. This review summarizes the mechanism of action of CD8+ T cells in immunotherapy, and highlights the recent advancements in PET-based tracers that can visualize CD8+ T cells and discusses their clinical applications to elucidate their potential role in cancer immunotherapy.
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Affiliation(s)
| | | | | | | | | | | | - Yaming Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Xuena Li
- Department of Nuclear Medicine, The First Hospital of China Medical University, Shenyang, Liaoning, China
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Zeng Y, Hu CH, Li YZ, Zhou JS, Wang SX, Liu MD, Qiu ZH, Deng C, Ma F, Xia CF, Liang F, Peng YR, Liang AX, Shi SH, Yao SJ, Liu JQ, Xiao WJ, Lin XQ, Tian XY, Zhang YZ, Tian ZY, Zou JA, Li YS, Xiao CY, Xu T, Zhang XJ, Wang XP, Liu XL, Wu F. Association between pretreatment emotional distress and immune checkpoint inhibitor response in non-small-cell lung cancer. Nat Med 2024; 30:1680-1688. [PMID: 38740994 PMCID: PMC11186781 DOI: 10.1038/s41591-024-02929-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/18/2024] [Indexed: 05/16/2024]
Abstract
Emotional distress (ED), commonly characterized by symptoms of depression and/or anxiety, is prevalent in patients with cancer. Preclinical studies suggest that ED can impair antitumor immune responses, but few clinical studies have explored its relationship with response to immune checkpoint inhibitors (ICIs). Here we report results from cohort 1 of the prospective observational STRESS-LUNG study, which investigated the association between ED and clinical efficacy of first-line treatment of ICIs in patients with advanced non-small-cell lung cancer. ED was assessed by Patient Health Questionnaire-9 and Generalized Anxiety Disorder 7-item scale. The study included 227 patients with 111 (48.9%) exhibiting ED who presented depression (Patient Health Questionnaire-9 score ≥5) and/or anxiety (Generalized Anxiety Disorder 7-item score ≥5) symptoms at baseline. On the primary endpoint analysis, patients with baseline ED exhibited a significantly shorter median progression-free survival compared with those without ED (7.9 months versus 15.5 months, hazard ratio 1.73, 95% confidence interval 1.23 to 2.43, P = 0.002). On the secondary endpoint analysis, ED was associated with lower objective response rate (46.8% versus 62.1%, odds ratio 0.54, P = 0.022), reduced 2-year overall survival rate of 46.5% versus 64.9% (hazard ratio for death 1.82, 95% confidence interval 1.12 to 2.97, P = 0.016) and detriments in quality of life. The exploratory analysis indicated that the ED group showed elevated blood cortisol levels, which was associated with adverse survival outcomes. This study suggests that there is an association between ED and worse clinical outcomes in patients with advanced non-small-cell lung cancer treated with ICIs, highlighting the potential significance of addressing ED in cancer management. ClinicalTrials.gov registration: NCT05477979 .
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Affiliation(s)
- Yue Zeng
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Chun-Hong Hu
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre, Changsha, China
| | - Yi-Zheng Li
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Key Laboratory of Molecular Radiation Oncology Hunan Province, Xiangya Hospital, Central South University, Changsha, China
| | - Jian-Song Zhou
- National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Shu-Xing Wang
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Meng-Dong Liu
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Zhen-Hua Qiu
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chao Deng
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fang Ma
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Chun-Fang Xia
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fei Liang
- Department of Biostatistics, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yu-Rong Peng
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ao-Xi Liang
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Sheng-Hao Shi
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Shi-Jiao Yao
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jun-Qi Liu
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Wen-Jie Xiao
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Xiao-Qiao Lin
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Xin-Yu Tian
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Ying-Zhe Zhang
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Zhuo-Ying Tian
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ji-An Zou
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Yun-Shu Li
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
- Xiangya School of Medicine, Central South University, Changsha, China
| | - Chao-Yue Xiao
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Tian Xu
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Xiao-Jie Zhang
- National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xiao-Ping Wang
- National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Xian-Ling Liu
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Fang Wu
- Department of Oncology, The Second Xiangya Hospital, Central South University, Changsha, China.
- National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China.
- Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre, Changsha, China.
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital, Central South University, Changsha, China.
- Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer, The Second Xiangya Hospital, Central South University, Changsha, China.
- FuRong Laboratory, Changsha, China.
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Yang K, Lu R, Mei J, Cao K, Zeng T, Hua Y, Huang X, Li W, Yin Y. The war between the immune system and the tumor - using immune biomarkers as tracers. Biomark Res 2024; 12:51. [PMID: 38816871 PMCID: PMC11137916 DOI: 10.1186/s40364-024-00599-5] [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: 12/06/2023] [Accepted: 05/10/2024] [Indexed: 06/01/2024] Open
Abstract
Nowadays, immunotherapy is one of the most promising anti-tumor therapeutic strategy. Specifically, immune-related targets can be used to predict the efficacy and side effects of immunotherapy and monitor the tumor immune response. In the past few decades, increasing numbers of novel immune biomarkers have been found to participate in certain links of the tumor immunity to contribute to the formation of immunosuppression and have entered clinical trials. Here, we systematically reviewed the oncogenesis and progression of cancer in the view of anti-tumor immunity, particularly in terms of tumor antigen expression (related to tumor immunogenicity) and tumor innate immunity to complement the cancer-immune cycle. From the perspective of integrated management of chronic cancer, we also appraised emerging factors affecting tumor immunity (including metabolic, microbial, and exercise-related markers). We finally summarized the clinical studies and applications based on immune biomarkers. Overall, immune biomarkers participate in promoting the development of more precise and individualized immunotherapy by predicting, monitoring, and regulating tumor immune response. Therefore, targeting immune biomarkers may lead to the development of innovative clinical applications.
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Affiliation(s)
- Kai Yang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Rongrong Lu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Jie Mei
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Kai Cao
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Tianyu Zeng
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
| | - Yijia Hua
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China
- Gusu School, Nanjing Medical University, Nanjing, China
| | - Xiang Huang
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China.
| | - Wei Li
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China.
| | - Yongmei Yin
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, P. R. China.
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Song LN, Wang B, Cai JL, Zhang PL, Chen SP, Zhou ZJ, Dai Z. Stratifying ICIs-responsive tumor microenvironment in HCC: from parsing out immune-hypoxic crosstalk to clinically applicable MRI-radiomics models. Br J Cancer 2024; 130:1356-1364. [PMID: 38355839 PMCID: PMC11014931 DOI: 10.1038/s41416-023-02463-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 10/04/2023] [Indexed: 02/16/2024] Open
Abstract
BACKGROUND We aimed to redefine Immune checkpoint inhibitors (ICIs)-responsive "hot" TME and develop a corresponding stratification model to maximize ICIs-efficacy in Hepatocellular Carcinoma (HCC). METHODS Hypoxic scores were designed, and the relevance to immunotherapy responses were validated in pan-cancers through single cell analysis. Multi-omics analysis using the hypoxic scores and immune infiltrate abundance was performed to redefine the ICIs-responsive TME subtype in HCC patients from TCGA (n = 363) and HCCDB database (n = 228). The immune hypoxic stress index (IHSI) was constructed to stratify the ICIs-responsive TME subtype, with exploring biological mechanism in vitro and in vivo. MRI-radiomics models were built for clinical applicability. RESULTS The hypoxic scores were lower in the dominant cell-subclusters of responders in pan-cancers. The higher immune infiltrate-normoxic (HIN) subtype was redefined as the ICIs-responsive TME. Stratification of the HIN subtype using IHSI effectively identified ICIs-responders in Melanoma (n = 122) and urological cancer (n = 22). TRAF3IP3, the constituent gene of IHSI, was implicated in ICIs-relevant "immune-hypoxic" crosstalk by stimulating MAVS/IFN-I pathway under normoxic condition. MRI-radiomics models assessing TRAF3IP3 with HIF1A expression (AUC > 0.80) screened ICIs-Responders in HCC cohort (n = 75). CONCLUSION The hypoxic-immune stratification redefined ICIs-responsive TME and provided MRI-Radiomics models for initial ICIs-responders screening, with IHSI facilitating further identification.
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Affiliation(s)
- Li-Na Song
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai, 200032, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Biao Wang
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China
| | - Jia-Liang Cai
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai, 200032, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Pei-Ling Zhang
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai, 200032, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Shi-Ping Chen
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai, 200032, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Zheng-Jun Zhou
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
- Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai, 200032, China
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China
| | - Zhi Dai
- Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
- Key Laboratory of Carcinogenesis and Cancer Invasion of Ministry of Education, Fudan University, Shanghai, 200032, China.
- State Key Laboratory of Genetic Engineering, Fudan University, Shanghai, 200032, China.
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Zheng L, Hu F, Huang L, Lu J, Yang X, Xu J, Wang S, Shen Y, Zhong R, Chu T, Zhang W, Li Y, Zheng X, Han B, Zhong H, Nie W, Zhang X. Association of metabolomics with PD-1 inhibitor plus chemotherapy outcomes in patients with advanced non-small-cell lung cancer. J Immunother Cancer 2024; 12:e008190. [PMID: 38641349 PMCID: PMC11029260 DOI: 10.1136/jitc-2023-008190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/02/2024] [Indexed: 04/21/2024] Open
Abstract
BACKGROUND Combining immune checkpoint inhibitors (ICIs) with chemotherapy has become a standard treatment for patients with non-small cell lung cancer (NSCLC) lacking driver gene mutations. Reliable biomarkers are essential for predicting treatment outcomes. Emerging evidence from various cancers suggests that early assessment of serum metabolites could serve as valuable biomarkers for predicting outcomes. This study aims to identify metabolites linked to treatment outcomes in patients with advanced NSCLC undergoing first-line or second-line therapy with programmed cell death 1 (PD-1) inhibitors plus chemotherapy. METHOD 200 patients with advanced NSCLC receiving either first-line or second-line PD-1 inhibitor plus chemotherapy, and 50 patients undergoing first-line chemotherapy were enrolled in this study. The 200 patients receiving combination therapy were divided into a Discovery set (n=50) and a Validation set (n=150). These sets were further categorized into respond and non-respond groups based on progression-free survival PFS criteria (PFS≥12 and PFS<12 months). Serum samples were collected from all patients before treatment initiation for untargeted metabolomics analysis, with the goal of identifying and validating biomarkers that can predict the efficacy of immunotherapy plus chemotherapy. Additionally, the validated metabolites were grouped into high and low categories based on their medians, and their relationship with PFS was analyzed using Cox regression models in patients receiving combination therapy. RESULTS After the impact of chemotherapy was accounted for, two significant differential metabolites were identified in both the Discovery and Validation sets: N-(3-Indolylacetyl)-L-alanine and methomyl (VIP>1 and p<0.05). Notably, upregulation of both metabolites was observed in the group with a poorer prognosis. In the univariate analysis of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were associated with longer PFS (HR=0.59, 95% CI, 0.41 to 0.84, p=0.003), and a prolonged PFS was also indicated by lower levels of methomyl (HR=0.67, 95% CI, 0.47 to 0.96, p=0.029). In multivariate analyses of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were significantly associated with a longer PFS (HR=0.60, 95% CI, 0.37 to 0.98, p=0.041). CONCLUSION Improved outcomes were associated with lower levels of N-(3-Indolylacetyl)-L-alanine in patients with stage IIIB-IV NSCLC lacking driver gene mutations, who underwent first-line or second-line therapy with PD-1 inhibitors combined with chemotherapy. Further exploration of the potential predictive value of pretreatment detection of N-(3-Indolylacetyl)-L-alanine in peripheral blood for the efficacy of combination therapy is warranted. STATEMENT The combination of ICIs and chemotherapy has established itself as the new standard of care for first-line or second-line treatment in patients with advanced NSCLC lacking oncogenic driver alterations. Therefore, identifying biomarkers that can predict the efficacy and prognosis of immunotherapy plus chemotherapy is of paramount importance. Currently, the only validated predictive biomarker is programmed cell death ligand-1 (PD-L1), but its predictive value is not absolute. Our study suggests that the detection of N-(3-Indolylacetyl)-L-alanine in patient serum with untargeted metabolomics prior to combined therapy may predict the efficacy of treatment. Compared with detecting PD-L1 expression, the advantage of our biomarker is that it is more convenient, more dynamic, and seems to work synergistically with PD-L1 expression.
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Affiliation(s)
- Liang Zheng
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Fang Hu
- Department of Thoracic Medical Oncology, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Zhejiang, China
- Hangzhou Institute of Medicine (HlM), Chinese Academy of Sciences, Zhejiang, China
| | - Lin Huang
- Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
- Shanghai Institute of Thoracic Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Jun Lu
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Xiaohua Yang
- Central Laboratory, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Jianlin Xu
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Shuyuan Wang
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Yinchen Shen
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Runbo Zhong
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Tianqing Chu
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Wei Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Ying Li
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Xiaoxuan Zheng
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Baohui Han
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Hua Zhong
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Wei Nie
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
| | - Xueyan Zhang
- Department of Respiratory and Critical Care Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University School Of Medicine, Shanghai, China
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Zhen S, Wang W, Qin G, Lu T, Yang L, Zhang Y. Dynamic surveillance of lymphocyte subsets in patients with non-small cell lung cancer during chemotherapy or combination immunotherapy for early prediction of efficacy. Front Immunol 2024; 15:1316778. [PMID: 38482008 PMCID: PMC10933068 DOI: 10.3389/fimmu.2024.1316778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 02/14/2024] [Indexed: 04/05/2024] Open
Abstract
Background Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths worldwide. Lymphocytes are the primary executors of the immune system and play essential roles in tumorigenesis and development. We investigated the dynamic changes in peripheral blood lymphocyte subsets to predict the efficacy of chemotherapy or combination immunotherapy in NSCLC. Methods This retrospective study collected data from 81 patients with NSCLC who received treatments at the First Affiliated Hospital of Zhengzhou University from May 2021 to May 2023. Patients were divided into response and non-response groups, chemotherapy and combination immunotherapy groups, and first-line and multiline groups. We analyzed the absolute counts of each lymphocyte subset in the peripheral blood at baseline and after each treatment cycle. Within-group and between-group differences were analyzed using paired Wilcoxon signed-rank and Mann-Whitney U tests, respectively. The ability of lymphocyte subsets to predict treatment efficacy was analyzed using receiver operating characteristic curve and logistic regression. Results The absolute counts of lymphocyte subsets in the response group significantly increased after the first cycle of chemotherapy or combination immunotherapy, whereas those in the non-response group showed persistent decreases. Ratios of lymphocyte subsets after the first treatment cycle to those at baseline were able to predict treatment efficacy early. Combination immunotherapy could increase lymphocyte counts compared to chemotherapy alone. In addition, patients with NSCLC receiving chemotherapy or combination immunotherapy for the first time mainly presented with elevated lymphocyte levels, whereas multiline patients showed continuous reductions. Conclusion Dynamic surveillance of lymphocyte subsets could reflect a more actual immune status and predict efficacy early. Combination immunotherapy protected lymphocyte levels from rapid decrease and patients undergoing multiline treatments were more prone to lymphopenia than those receiving first-line treatment. This study provides a reference for the early prediction of the efficacy of clinical tumor treatment for timely combination of immunotherapy or the improvement of immune status.
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Affiliation(s)
- Shanshan Zhen
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Oncology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Wenqian Wang
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- Department of Oncology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Guohui Qin
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Taiying Lu
- Department of Oncology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Li Yang
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan, China
| | - Yi Zhang
- Biotherapy Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
- School of Life Sciences, Zhengzhou University, Zhengzhou, Henan, China
- State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan, China
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Chai Y, Ma Y, Feng W, Xiang H, Lu H, Jin L. Identification and validation of a 4-extracellular matrix gene signature associated with prognosis and immune infiltration in lung adenocarcinoma. Heliyon 2024; 10:e24162. [PMID: 38293522 PMCID: PMC10827462 DOI: 10.1016/j.heliyon.2024.e24162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 11/27/2023] [Accepted: 01/04/2024] [Indexed: 02/01/2024] Open
Abstract
Background The extracellular matrix (ECM) plays a crucial role in the development and tumor microenvironment of lung adenocarcinoma (LUAD). This study aimed to establish a risk score of ECM-related genes in LUAD and explore the association between the risk score and patient survival as well as immune cell infiltration, somatic mutations, and therapy response. Methods Gene expression data from The Cancer Genome Atlas (TGCA) and eight Gene Expression Omnibus (GEO) databases were used to analyze and identify differentially expressed genes (DEGs). Prognostic ECM-related genes were identified and utilized to formulate a prognostic signature. A nomogram was constructed using TCGA dataset and validated in two GEO datasets. Differences between high- and low-risk patients were analyzed for function enrichment, immune cell infiltration, somatic mutations, and therapy response. Finally, Quantitative real-time PCR (qRT-PCR) was used to detect the mRNA expression of DEGs in LUAD. Results A risk score based on four ECM-related genes, ANOS1, CD36, COL11A1, and HMMR, was identified as an independent prognostic factor for overall survival (OS) compared to other clinical variables. Subsequently, a nomogram incorporating the risk score and TNM staging was developed using the TCGA dataset. Internal and external validation of the nomogram, conducted through calibration plots, C-index, time-dependent receiver operating characteristics (ROC), integrated discrimination improvement (IDI), and decision curve analyses (DCA), demonstrated the excellent discriminatory ability and clinical practicability of this nomogram. The risk score correlated with the distribution of function enrichment, immune cell infiltration, and immune checkpoint expression. More somatic mutations occurred in the high-risk group. The risk score also demonstrated a favorable ability to predict immunotherapy response and drug sensitivity. Conclusion A novel signature based on four ECM-related genes is developed to help predict LUAD prognosis. This signature correlates with tumor immune microenvironment and can predict the response to different therapies in LUAD patients.
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Affiliation(s)
- Yanfei Chai
- Department of Health Management Center, The Third Xiangya Hospital of Central South University, Changsha, China
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Yuchao Ma
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Wei Feng
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Hong Xiang
- Department of Health Management Center, The Third Xiangya Hospital of Central South University, Changsha, China
- Center for Experimental Medicine, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Hongwei Lu
- Department of Health Management Center, The Third Xiangya Hospital of Central South University, Changsha, China
- Center for Experimental Medicine, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Longyu Jin
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
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9
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Lin Z, Liu M, Xing W, Wang F, Zhang H, Wei X, Schmitthenner H, Xie X, Xia X, Yang J. A near-infrared fluorescence-enhancing plasmonic biosensing microarray identifies soluble PD-L1 and ICAM-1 as predictive checkpoint biomarkers for cancer immunotherapy. Biosens Bioelectron 2023; 240:115633. [PMID: 37683502 DOI: 10.1016/j.bios.2023.115633] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 07/29/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023]
Abstract
Sensitive and accurate biomarker-driven assay guidance has been widely adopted to identify responsive patients for immune checkpoint blockade (ICB) therapy to impede disease progression and extend survival. However, most current assays are invasive, requiring surgical pathology specimens and only informing monochronic information. Here, we report a multiplexed enhanced fluorescence microarray immunoassay (eFMIA) based on a nanostructured gold nanoisland substrate (AuNIS), which macroscopically amplifies near-infrared fluorescence (NIRF) of a structurally symmetric IRDye78 fluorophore by over two orders of magnitude of 202.6-fold. Aided by non-contact piezo-driven micro-dispensing (PDMD), eFMIA simultaneously and semi-quantitatively detected intracellular and secreted programmed death-ligand 1 (PD-L1) and intercellular adhesion molecule-1 (ICAM-1) in human nasopharyngeal carcinoma (NPC) cells. The assay performance was superior to fluorescence immunoassays (FIA) and enzyme-linked immunosorbent assays (ELISA), with lower detection limits. Using eFMIA, we found significantly differential levels of soluble PD-L1 (sPD-L1) and sICAM-1 in the sera of 28 cancer patients, with different clinical outcomes following anti-PD-1 ICB therapy. With a well-characterized mechanism, the high-performance plasmonic multiplexed assay with the composite biomarkers may be a valuable tool to assist clinicians with decision-making and patient stratification to afford predictive ICB therapy responses.
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Affiliation(s)
- Zhijun Lin
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Mengyao Liu
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Wei Xing
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China; Department of Anesthesiology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Fenghua Wang
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Hongxia Zhang
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Xiaoli Wei
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China; Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China
| | - Hans Schmitthenner
- School of Chemistry and Materials Science, Rochester Institute of Technology, Rochester, NY, 14623, United States
| | - Xi Xie
- State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, 510275, China
| | - Xiaojun Xia
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
| | - Jiang Yang
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
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10
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Yang F, Tang M, Cui L, Bai J, Yu J, Gao J, Nie X, Li X, Xia X, Yi X, Zhang P, Li L. Prognostic and predictive impact of molecular tumor burden index in non-small cell lung cancer patients. Thorac Cancer 2023; 14:3097-3107. [PMID: 37724484 PMCID: PMC10626252 DOI: 10.1111/1759-7714.15098] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/20/2023] Open
Abstract
BACKGROUND The biomarkers of immune checkpoint inhibitors in the treatment of non-small cell lung cancer (NSCLC) patients have limited predictive performance. In this study we aimed to investigate the feasibility of molecular tumor burden index (mTBI) in circulating tumor DNA (ctDNA) as a predictor for immunotherapy in patients with NSCLC. METHODS From February 2017 to November 2020, pretreatment and on-treatment (3~6 weeks after first cycle of immunotherapy) dynamic plasma ctDNA samples from NSCLC patients receiving immune monotherapy or combination therapy were analyzed by targeted capture sequencing of 1021 genes. PyClone was used to infer the mTBI. The impact of pretreatment mTBI on survival outcomes was verified in the POPLAR/OAK trials. RESULTS We found that patients without detectable baseline ctDNA had better survival outcomes (median overall survival [OS]: not reached vs. 12.8 months; hazard ratio [HR], 0.15; p = 0.035]). RB1 and SMARCA4 mutations were remarkably associated with worse survival outcomes. Furthermore, lower pretreatment mTBI was associated with superior OS (median: not reached vs. 8.1 months; HR, 0.22; p = 0.024) and PFS (median: 32.9 vs. 5.4 months; HR, 0.35; p = 0.045), but not objective response, which was validated in the POPLAR/OAK cohort, suggesting that baseline mTBI was a prognostic factor for NSCLC immunotherapy. Early dynamic changes of mTBI (ΔmTBI) significantly distinguished responsive patients, and patients with mTBI decrease to more than 68% at the final tumor evaluation had longer OS (median: 38.2 vs. 4.0 months; HR, 0.18; p = 0.017) and PFS (median: not reached vs. 2.3 months; HR, 0.24; p = 0.030). CONCLUSION ΔmTBI had a good sensitivity to identify potential beneficial patients based on the best effect CT scans, demonstrating that mTBI dynamics were predictive of benefit from immune checkpoint blockade.
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Affiliation(s)
- Fan Yang
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Min Tang
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Liang Cui
- Geneplus‐Beijing InstituteBeijingPeople's Republic of China
| | - Jing Bai
- Geneplus‐Beijing InstituteBeijingPeople's Republic of China
| | - Jiangyong Yu
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Jiayi Gao
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Xin Nie
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Xu Li
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Xuefeng Xia
- Geneplus‐Beijing InstituteBeijingPeople's Republic of China
| | - Xin Yi
- Geneplus‐Beijing InstituteBeijingPeople's Republic of China
| | - Ping Zhang
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
| | - Lin Li
- Department of Medical OncologyBeijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical SciencesBeijingPeople's Republic of China
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Yang N, Yue H, Zhang B, Chen J, Chu Q, Wang J, Yu X, Jian L, Bin Y, Liu S, Liu J, Zeng L, Yang H, Zhou C, Jiang W, Liu L, Zhang Y, Xiong Y, Wang Z. Predicting pathological response to neoadjuvant or conversion chemoimmunotherapy in stage IB-III non-small cell lung cancer patients using radiomic features. Thorac Cancer 2023; 14:2869-2876. [PMID: 37596822 PMCID: PMC10542462 DOI: 10.1111/1759-7714.15052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/12/2023] [Accepted: 07/14/2023] [Indexed: 08/20/2023] Open
Abstract
BACKGROUND To develop a radiomics model based on chest computed tomography (CT) for the prediction of a pathological complete response (pCR) after neoadjuvant or conversion chemoimmunotherapy (CIT) in patients with non-small cell lung cancer (NSCLC). METHODS Patients with stage IB-III NSCLC who received neoadjuvant or conversion CIT between September 2019 and July 2021 at Hunan Cancer Hospital, Xiangya Hospital, and Union Hospital were retrospectively collected. The least absolute shrinkage and selection operator (LASSO) were used to screen features. Then, model 1 (five radiomics features before CIT), model 2 (four radiomics features after CIT and before surgery) and model 3 were constructed for the prediction of pCR. Model 3 included all nine features of model 1 and 2 and was later named the neoadjuvant chemoimmunotherapy-related pathological response prediction model (NACIP). RESULTS This study included 110 patients: 77 in the training set and 33 in the validation set. Thirty-nine (35.5%) patients achieved a pCR. Model 1 showed area under the curve (AUC) = 0.65, 64% accuracy, 71% specificity, and 50% sensitivity, while model 2 displayed AUC = 0.81, 73% accuracy, 62% specificity, and 92% sensitivity. In comparison, NACIP yielded a good predictive value, with an AUC of 0.85, 81% accuracy, 81% specificity, and 83% sensitivity in the validation set. CONCLUSION NACIP may be a potential model for the early prediction of pCR in patients with NSCLC treated with neoadjuvant/conversion CIT.
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Affiliation(s)
- Nong Yang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
- Lung Cancer and Gastrointestinal Unit, Department of Medical Oncology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaChina
| | - Hai‐Lin Yue
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Bai‐Hua Zhang
- Department of Thoracic SurgeryHunan Cancer HospitalChangshaChina
| | - Juan Chen
- Department of Pharmacy, Xiangya HospitalCentral South UniversityChangshaChina
| | - Qian Chu
- Department of Oncology, Tongji Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Jian‐Xin Wang
- Lung Cancer and Gastrointestinal Unit, Department of Medical Oncology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaChina
| | - Xiao‐Ping Yu
- Department of Diagnostic Radiology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaChina
| | - Lian Jian
- Department of Diagnostic Radiology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaChina
| | - Ya‐Wen Bin
- Cancer Center, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Si‐Ye Liu
- Department of Diagnostic Radiology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaChina
| | - Jin Liu
- Lung Cancer and Gastrointestinal Unit, Department of Medical Oncology, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of MedicineCentral South UniversityChangshaChina
| | - Liang Zeng
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Hai‐Yan Yang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Chun‐Hua Zhou
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Wen‐Juan Jiang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Li Liu
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Yong‐Chang Zhang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Yi Xiong
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
| | - Zhan Wang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and EngineeringCentral South UniversityChangshaChina
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12
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Kim KY, Lim JU, Kang HS, Kim JS, Kim SK, Kim SJ, Lee SH, Yeo CD. Smoking Status at Time of Diagnosis Affects the Efficacy of Anti-PD-1/L1 Therapy in Patients With Advanced NSCLC. In Vivo 2023; 37:2357-2364. [PMID: 37652510 PMCID: PMC10500490 DOI: 10.21873/invivo.13340] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Revised: 06/08/2023] [Accepted: 06/09/2023] [Indexed: 09/02/2023]
Abstract
BACKGROUND/AIM Programmed death ligand-1 (PD-L1) expression is known to be a predictive biomarker for response to immunotherapy in non-small cell lung cancer (NSCLC). However, PD-L1 is not always a reliable predictive biomarker. In the present study, we aimed to compare responses to immunotherapy according to smoking status in NSCLC patients receiving immunotherapy in second line or further line treatment. PATIENTS AND METHODS The lung cancer registry database of the Catholic Medical Center, Seoul, Republic of Korea was used. Patients were eligible for this study if they were diagnosed with histologically confirmed NSCLC and received immune checkpoint inhibitors (ICIs) as second-line or further line therapy from January 2017 to December 2021. RESULTS Overall, 220 patients with NSCLC treated with ICIs were enrolled. There were 40 never smokers, 73 former smokers, and 107 current smokers. In multivariate analysis, smoking status, pathologic type, and PD-L1 expression were significant factors affecting PFS. Sex, ECOG performance status, pathologic type, and PD-L1 expression were significant factors affecting OS. CONCLUSION Smoking status at diagnosis of lung cancer could be a predictive biomarker for response to ICIs in patients with advanced NSCLC.
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Affiliation(s)
- Kyu Yean Kim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Uijeongbu St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jeong Uk Lim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hye Seon Kang
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Ju Sang Kim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sung Kyoung Kim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Seung Joon Kim
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sang Haak Lee
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Chang Dong Yeo
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
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13
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Zhang H, Wang Y, Wang K, Ding Y, Li X, Zhao S, Jia X, Sun D. Prognostic analysis of lung adenocarcinoma based on cancer-associated fibroblasts genes using scRNA-sequencing. Aging (Albany NY) 2023; 15:6774-6797. [PMID: 37437244 PMCID: PMC10415565 DOI: 10.18632/aging.204838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 06/09/2023] [Indexed: 07/14/2023]
Abstract
Cancer-associated fibroblasts (CAFs) are an important component of the tumor microenvironment (TME). CAFs can promote tumor occurrence and metastasis by promoting cancer cell proliferation, angiogenesis, extracellular matrix (ECM) remodeling, and drug resistance. Nevertheless, how CAFs are related to Lung adenocarcinoma (LUAD) has not yet been revealed, especially since the CAFs-related prediction model has yet to be established. We combined Single-cell RNA-sequencing (scRNA-seq) and Bulk-RNA data to develop a predictive model of 8 CAFs-associated genes. Our model predicted LUAD prognosis and immunotherapy efficacy. TME, mutation landscape and drug sensitivity differences were also systematically analyzed between the LUAD patients of high- and low-risk. Moreover, the model prognostic performance was validated in four independent validation cohorts in the Gene expression omnibus (GEO) and the IMvigor210 immunotherapy cohort.
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Affiliation(s)
- Han Zhang
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Yuhang Wang
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Kai Wang
- Department of Thoracic Surgery, Tianjin Chest Hospital of Tianjin University, Tianjin, China
| | - Yun Ding
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Xin Li
- Department of Thoracic Surgery, Tianjin Chest Hospital of Tianjin University, Tianjin, China
| | - Shuai Zhao
- Department of Thoracic Surgery, Tianjin Chest Hospital of Tianjin University, Tianjin, China
| | - Xiaoteng Jia
- Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
| | - Daqiang Sun
- Department of Thoracic Surgery, Tianjin Chest Hospital of Tianjin University, Tianjin, China
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14
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Wang L, Yang Z, Guo F, Chen Y, Wei J, Dai X, Zhang X. Research progress of biomarkers in the prediction of anti-PD-1/PD-L1 immunotherapeutic efficiency in lung cancer. Front Immunol 2023; 14:1227797. [PMID: 37465684 PMCID: PMC10351040 DOI: 10.3389/fimmu.2023.1227797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 06/13/2023] [Indexed: 07/20/2023] Open
Abstract
Currently, anti-PD-1/PD-L1 immunotherapy using immune checkpoint inhibitors is widely used in the treatment of multiple cancer types including lung cancer, which is a leading cause of cancer death in the world. However, only a limited proportion of lung cancer patients will benefit from anti-PD-1/PD-L1 therapy. Therefore, it is of importance to predict the response to immunotherapy for the precision treatment of patients. Although the expression of PD-L1 and tumor mutation burden (TMB) are commonly used to predict the clinical response of anti-PD-1/PD-L1 therapy, other factors such as tumor-specific genes, dMMR/MSI, and gut microbiome are also promising predictors for immunotherapy in lung cancer. Furthermore, invasive peripheral blood biomarkers including blood DNA-related biomarkers (e.g., ctDNA and bTMB), blood cell-related biomarkers (e.g., immune cells and TCR), and other blood-related biomarkers (e.g., soluble PD-L1 and cytokines) were utilized to predict the immunotherapeutic response. In this review, the current achievements of anti-PD-1/PD-L1 therapy and the potential biomarkers for the prediction of anti-PD-1/PD-L1 immunotherapy in lung cancer treatment were summarized and discussed.
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Affiliation(s)
- Luyao Wang
- Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, First Hospital of Jilin University, Changchun, China
- National-Local Joint Engineering Laboratory of Animal Models for Human Disease, First Hospital of Jilin University, Changchun, China
| | - Zongxing Yang
- Department of Clinical Laboratory, First Hospital of Jilin University, Changchun, China
| | - Fucheng Guo
- Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, First Hospital of Jilin University, Changchun, China
- National-Local Joint Engineering Laboratory of Animal Models for Human Disease, First Hospital of Jilin University, Changchun, China
| | - Yurong Chen
- Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, First Hospital of Jilin University, Changchun, China
- National-Local Joint Engineering Laboratory of Animal Models for Human Disease, First Hospital of Jilin University, Changchun, China
| | - Jiarui Wei
- Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, First Hospital of Jilin University, Changchun, China
- National-Local Joint Engineering Laboratory of Animal Models for Human Disease, First Hospital of Jilin University, Changchun, China
| | - Xiangpeng Dai
- Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, First Hospital of Jilin University, Changchun, China
- National-Local Joint Engineering Laboratory of Animal Models for Human Disease, First Hospital of Jilin University, Changchun, China
| | - Xiaoling Zhang
- Key Laboratory of Organ Regeneration and Transplantation of Ministry of Education, First Hospital of Jilin University, Changchun, China
- National-Local Joint Engineering Laboratory of Animal Models for Human Disease, First Hospital of Jilin University, Changchun, China
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15
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Chen H, Ge M, Zhang F, Xing Y, Yu S, Chen C, Zhang H, Wang X, Gao X, Chen F, Chen P, Zhang D, Zhan Q, Zhu Y. Correlation between immunotherapy biomarker PD-L1 expression and genetic alteration in patients with non-small cell lung cancer. Genomics 2023; 115:110648. [PMID: 37217086 DOI: 10.1016/j.ygeno.2023.110648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 04/19/2023] [Accepted: 05/19/2023] [Indexed: 05/24/2023]
Abstract
Programmed death-ligand 1 (PD-L1) has been widely used in immunotherapy evaluation of patients with non-small cell lung cancer (NSCLC). However, the effect is not particularly ideal, and the association between PD-L1 and genetic alterations requires more exploration. Here, we performed targeted next-generation sequencing and PD-L1 immunohistochemistry (IHC) testing for PD-L1 expression on both tumor cells (TCs) and tumor-infiltrating immune cells (ICs) in 1549 patients. Our studies showed that surgical method of resection was positively correlated with IC+, and a low tumor mutation burden (TMB) was negatively correlated with TC+. Furthermore, we found that EGFR was mutually exclusive with both ALK and STK11. In addition, the features between PD-L1 expression status and genomic alterations were characterized. These results suggest that clinical characteristics and molecular phenotypes are associated with PD-L1 expression signatures, which may provide novel insights for improving the efficiency of immune checkpoint inhibitors (ICIs) in immunotherapy.
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Affiliation(s)
- Hefeng Chen
- Department of Pulmonary and Critical Care Medicine, Huadong Hospital, Fudan University, Shanghai, China
| | - Mengxi Ge
- Department of Oncology, Huashan Hospital, Fudan University, Shanghai, China
| | | | | | | | | | | | | | - Xing Gao
- 3D Medicines Inc., Shanghai, China
| | | | | | | | - Qiong Zhan
- Department of Oncology, Huashan Hospital, Fudan University, Shanghai, China.
| | - Youcai Zhu
- Department of Thoracic Disease Center, Zhejiang Rongjun Hospital, Jiaxing, China.
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Ancel J, Dormoy V, Raby BN, Dalstein V, Durlach A, Dewolf M, Gilles C, Polette M, Deslée G. Soluble biomarkers to predict clinical outcomes in non-small cell lung cancer treated by immune checkpoints inhibitors. Front Immunol 2023; 14:1171649. [PMID: 37283751 PMCID: PMC10239865 DOI: 10.3389/fimmu.2023.1171649] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 05/11/2023] [Indexed: 06/08/2023] Open
Abstract
Lung cancer remains the first cause of cancer-related death despite many therapeutic innovations, including immune checkpoint inhibitors (ICI). ICI are now well used in daily practice at late metastatic stages and locally advanced stages after a chemo-radiation. ICI are also emerging in the peri-operative context. However, all patients do not benefit from ICI and even suffer from additional immune side effects. A current challenge remains to identify patients eligible for ICI and benefiting from these drugs. Currently, the prediction of ICI response is only supported by Programmed death-ligand 1 (PD-L1) tumor expression with perfectible results and limitations inherent to tumor-biopsy specimen analysis. Here, we reviewed alternative markers based on liquid biopsy and focused on the most promising biomarkers to modify clinical practice, including non-tumoral blood cell count such as absolute neutrophil counts, platelet to lymphocyte ratio, neutrophil to lymphocyte ratio, and derived neutrophil to lymphocyte ratio. We also discussed soluble-derived immune checkpoint-related products such as sPD-L1, circulating tumor cells (detection, count, and marker expression), and circulating tumor DNA-related products. Finally, we explored perspectives for liquid biopsies in the immune landscape and discussed how they could be implemented into lung cancer management with a potential biological-driven decision.
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Affiliation(s)
- Julien Ancel
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Respiratory Diseases, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Valérian Dormoy
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
| | - Béatrice Nawrocki Raby
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
| | - Véronique Dalstein
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Biopathology, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Anne Durlach
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Biopathology, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Maxime Dewolf
- Department of Respiratory Diseases, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Christine Gilles
- Laboratory of Tumor and Development Biology, GIGA-Cancer, University of Liège, Liège, Belgium
| | - Myriam Polette
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Biopathology, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
| | - Gaëtan Deslée
- Inserm UMR-S1250, P3Cell, University of Reims Champagne-Ardenne, SFR CAP-SANTE, Reims, France
- Department of Respiratory Diseases, Centre Hospitalier Universitaire de Reims, Hôpital Maison Blanche, Reims, France
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17
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Ouyang Y, Lu W, Wang Y, Wang B, Li F, Li X, Bai Y, Wang Y. Integrated analysis of mRNA and extrachromosomal circular DNA profiles to identify the potential mRNA biomarkers in breast cancer. Gene 2023; 857:147174. [PMID: 36627094 DOI: 10.1016/j.gene.2023.147174] [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: 09/29/2022] [Revised: 12/13/2022] [Accepted: 01/04/2023] [Indexed: 01/08/2023]
Abstract
Extrachromosomal circular DNAs (eccDNAs) have been proved an inseparable relationship with cancer, based on the biological mechanisms of its biogenesis and impact on tumorigenesis, but still lacked of methods to analyze its function on the pathogenesis and progression of breast cancer (BC). The mRNA and eccDNA from BC cell samples (MDA-MB-453 and MCF-12A) were extracted with the removal of rRNA and linear DNA, respectively. High-throughput sequencing and bioinformatics analysis were performed to explore their expression level and molecular characterization of eccDNA. A total number of 161,062 eccDNA ranging from 33 bp to 54229 bp were detected with a median size of 1143 bp, distributed on all chromosomes and enriched on chromosome 20 the most. EccDNAs located in exons, upstream and downstream 2 kb regions were significantly increased compared with background. Analysis of eccDNA-related differentially expressed genes (eccDEGs) showed that FAT2 properly separated the two cells. CTNNB1, CACNA2D2 and CACNA1D were the hub genes with higher degrees in critical modules. All these four genes were significantly differentially expressed between breast invasive carcinoma (BRCA) tissues and normal ones. FAT2 and CTNNB1 correlated with significantly different overall survival (OS) when differentially expressed. The four genes showed a strong correlation with each other significantly and changed between tumor and normal samples. The results showed the potential of FAT2, CTNNB1, CACNA2D2 and CACNA1D as biomarkers with analysis of both DEGs and eccDEGs, which might assist in clinical medical treatment.
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Affiliation(s)
- Yunfei Ouyang
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Wenxiang Lu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Ying Wang
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Bangting Wang
- First Affiliated Hospital of Nanjing Medical University, Nanjing 210096, PR China
| | - Fuyu Li
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Xiaohan Li
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Yunfei Bai
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China.
| | - Yan Wang
- First Affiliated Hospital of Nanjing Medical University, Nanjing 210096, PR China.
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18
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Liu SYM, Chen C, Zhang YK, Zhong WZ, Wu YL, Liu SY, Li Y. Specific TCR profiles predict clinical outcome of adjuvant EGFR-TKIs for resected EGFR-mutant non-small cell lung cancer. Biomark Res 2023; 11:26. [PMID: 36879350 PMCID: PMC9990191 DOI: 10.1186/s40364-023-00470-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: 01/23/2023] [Accepted: 02/26/2023] [Indexed: 03/08/2023] Open
Abstract
BACKGROUND ADJUVANT-CTONG1104 reported a favorable survival outcome from adjuvant gefitinib treatment over chemotherapy in EGFR-mutant non-small cell lung cancer (NSCLC) patients. However, heterogeneous benefit from EGFR-TKIs and chemotherapy demands further biomarker exploration for patient selection. Previously, we identified certain TCR sequences with predictive value for adjuvant therapies from the CTONG1104 trial and found a relationship between the TCR repertoire and genetic variations. It remains unknown which TCR sequences could further enhance the prediction for only adjuvant EGFR-TKI. METHODS In this study, 57 tumor and 12 tumor-adjacent samples, respectively, from gefitinib-treated patients in the CTONG1104 were collected for TCR β gene sequencing. We attempted to constitute a predictive model for prognosis and favorable adjuvant EGFR-TKI outcome for patients with early-stage NSCLC and EGFR mutations. RESULTS The TCR rearrangements demonstrated significant prediction for overall survival (OS). A combined model of high frequent Vβ7-3Jβ2-5 and Vβ24-1Jβ2-1 with lower frequent Vβ5-6Jβ2-7 and Vβ28Jβ2-2 constituted the best value for predicting OS (P < 0.001; Hazard Ratio [HR] = 9.65, 95% confidence interval [CI]: 2.27 to 41.12) or DFS (P = 0.02; HR = 2.61, 95% CI: 1.13 to 6.03). In Cox regression analyses, when multiple clinical data were included, the risk score remained an independent prognostic predictor for OS (P = 0.003; HR = 9.49; 95% CI: 2.21 to 40.92) and DFS (P = 0.015; HR = 3.13; 95% CI: 1.25 to 7.87). CONCLUSIONS In this study, a predictive model was constituted with specific TCR sequences for prognosis prediction and gefitinib benefit in the ADJUVANT-CTONG1104 trial. We provide a potential immune biomarker for EGFR-mutant NSCLC patients who might benefit from an adjuvant EGFR-TKI.
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Affiliation(s)
- Si-Yang Maggie Liu
- Department of Hematology, The First Affiliated Hospital, Jinan University, Guangzhou, 510632, China.,Key Laboratory for Regenerative Medicine of Ministry of Education, Institute of Hematology, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Cunte Chen
- Key Laboratory for Regenerative Medicine of Ministry of Education, Institute of Hematology, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Yi-Kai Zhang
- Department of Hematology, The First Affiliated Hospital, Jinan University, Guangzhou, 510632, China.,Key Laboratory for Regenerative Medicine of Ministry of Education, Institute of Hematology, School of Medicine, Jinan University, Guangzhou, 510632, China
| | - Wen-Zhao Zhong
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Yi-Long Wu
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
| | - Si-Yang Liu
- Guangdong Lung Cancer Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China.
| | - Yangqiu Li
- Department of Hematology, The First Affiliated Hospital, Jinan University, Guangzhou, 510632, China. .,Key Laboratory for Regenerative Medicine of Ministry of Education, Institute of Hematology, School of Medicine, Jinan University, Guangzhou, 510632, China.
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19
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Characterization of Infiltrating Immune Cells and Secretory or Membrane-Associated Proteins in KRAS Lung Adenocarcinoma. J Immunol Res 2023; 2023:4987832. [PMID: 36793588 PMCID: PMC9925262 DOI: 10.1155/2023/4987832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 10/31/2022] [Accepted: 01/16/2023] [Indexed: 02/09/2023] Open
Abstract
Background This study identified the expression and prognosis significance of secretory or membrane-associated proteins in KRAS lung adenocarcinoma (LUAD) and depicted the characteristics between the immune cell infiltration and the expression of these genes. Methods Gene expression data of LUAD samples (n = 563) were accessed from The Cancer Genome Atlas (TCGA). The expression of secretory or membrane-associated proteins was compared among the KRAS-mutant, wild-type, and normal groups, as well as the subgroup of the KRAS-mutant group. We identified the survival-related differentially expressed secretory or membrane-associated proteins and conducted the functional enrichment analysis. Then, the characterization and association between their expression and the 24 immune cell subsets were investigated. We also constructed a scoring model to predict KRAS mutation by LASSO and logistic regression analysis. Results Secretory or membrane-associated genes with differential expression (n = 74) across three groups (137 KRAS LUAD, 368 wild-type LUAD, and 58 normal groups) were identified, and the results of GO and KEGG indicated that they were strongly associated with immune cell infiltrations. Among them, ten genes were significantly related to the survival of patients with KRAS LUAD. The expression of IL37, KIF2, INSR, and AQP3 had the most significant correlations with immune cell infiltration. In addition, eight DEGs from the KRAS subgroups were highly correlated with immune infiltrations, especially TNFSF13B. Using LASSO-logistic regression, a KRAS mutation prediction model based on the 74 differentially expressed secretory or membrane-associated genes was built, and the accuracy was 0.79. Conclusion The research investigated the relationship between the expression of KRAS-related secretory or membrane-associated proteins in LUAD patients with prognostic prediction and immune infiltration characterization. Our study demonstrated that secretory or membrane-associated genes were closely associated with the survival of KRAS LUAD patients and were strongly correlated to immune cell infiltration.
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20
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Sayer MR, Mambetsariev I, Lu KH, Wong CW, Duche A, Beuttler R, Fricke J, Pharoan R, Arvanitis L, Eftekhari Z, Amini A, Koczywas M, Massarelli E, Roosan MR, Salgia R. Predicting survival of NSCLC patients treated with immune checkpoint inhibitors: Impact and timing of immune-related adverse events and prior tyrosine kinase inhibitor therapy. Front Oncol 2023; 13:1064169. [PMID: 36860308 PMCID: PMC9968834 DOI: 10.3389/fonc.2023.1064169] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/30/2023] [Indexed: 02/16/2023] Open
Abstract
Introduction Immune checkpoint inhibitors (ICIs) produce a broad spectrum of immune-related adverse events (irAEs) affecting various organ systems. While ICIs are established as a therapeutic option in non-small cell lung cancer (NSCLC) treatment, most patients receiving ICI relapse. Additionally, the role of ICIs on survival in patients receiving prior targeted tyrosine kinase inhibitor (TKI) therapy has not been well-defined. Objective To investigate the impact of irAEs, the relative time of occurrence, and prior TKI therapy to predict clinical outcomes in NSCLC patients treated with ICIs. Methods A single center retrospective cohort study identified 354 adult patients with NSCLC receiving ICI therapy between 2014 and 2018. Survival analysis utilized overall survival (OS) and real-world progression free survival (rwPFS) outcomes. Model performance matrices for predicting 1-year OS and 6-month rwPFS using linear regression baseline, optimal, and machine learning modeling approaches. Results Patients experiencing an irAE were found to have a significantly longer OS and rwPFS compared to patients who did not (median OS 25.1 vs. 11.1 months; hazard ratio [HR] 0.51, confidence interval [CI] 0.39- 0.68, P-value <0.001, median rwPFS 5.7 months vs. 2.3; HR 0.52, CI 0.41- 0.66, P-value <0.001, respectively). Patients who received TKI therapy before initiation of ICI experienced significantly shorter OS than patients without prior TKI therapy (median OS 7.6 months vs. 18.5 months; P-value < 0.01). After adjusting for other variables, irAEs and prior TKI therapy significantly impacted OS and rwPFS. Lastly, the performances of models implementing logistic regression and machine learning approaches were comparable in predicting 1-year OS and 6-month rwPFS. Conclusion The occurrence of irAEs, the timing of the events, and prior TKI therapy were significant predictors of survival in NSCLC patients on ICI therapy. Therefore, our study supports future prospective studies to investigate the impact of irAEs, and sequence of therapy on the survival of NSCLC patients taking ICIs.
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Affiliation(s)
- Michael R. Sayer
- Department of Pharmacy Practice, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Isa Mambetsariev
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, United States
| | - Kun-Han Lu
- Department of Applied AI and Data Science, City of Hope National Medical Center, Duarte, CA, United States
| | - Chi Wah Wong
- Department of Applied AI and Data Science, City of Hope National Medical Center, Duarte, CA, United States
| | - Ashley Duche
- Department of Pharmacy Practice, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Richard Beuttler
- Department of Pharmacy Practice, Chapman University School of Pharmacy, Irvine, CA, United States
| | - Jeremy Fricke
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, United States
| | - Rebecca Pharoan
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, United States
| | - Leonidas Arvanitis
- Department of Pathology, City of Hope National Medical Center, Duarte, CA, United States
| | - Zahra Eftekhari
- Department of Applied AI and Data Science, City of Hope National Medical Center, Duarte, CA, United States
| | - Arya Amini
- Department of Radiation Oncology, City of Hope National Medical Center, Duarte, CA, United States
| | - Marianna Koczywas
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, United States
| | - Erminia Massarelli
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, United States
| | - Moom Rahman Roosan
- Department of Pharmacy Practice, Chapman University School of Pharmacy, Irvine, CA, United States,*Correspondence: Moom Rahman Roosan, ; Ravi Salgia,
| | - Ravi Salgia
- Department of Medical Oncology and Therapeutics Research, City of Hope National Medical Center, Duarte, CA, United States,*Correspondence: Moom Rahman Roosan, ; Ravi Salgia,
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21
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Goh KY, Cheng TYD, Tham SC, Lim DWT. Circulating Biomarkers for Prediction of Immunotherapy Response in NSCLC. Biomedicines 2023; 11:508. [PMID: 36831044 PMCID: PMC9953588 DOI: 10.3390/biomedicines11020508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/03/2023] [Accepted: 02/08/2023] [Indexed: 02/12/2023] Open
Abstract
Non-small cell lung cancer (NSCLC) constitutes the majority of the lung cancer population and the prognosis is poor. In recent years, immunotherapy has become the standard of care for advanced NSCLC patients as numerous trials demonstrated that immune checkpoint inhibitors (ICI) are more efficacious than conventional chemotherapy. However, only a minority of NSCLC patients benefit from this treatment. Therefore, there is an unmet need for biomarkers that could accurately predict response to immunotherapy. Liquid biopsy allows repeated sampling of blood-based biomarkers in a non-invasive manner for the dynamic monitoring of treatment response. In this review, we summarize the efforts and progress made in the identification of circulating biomarkers that predict immunotherapy benefit for NSCLC patients. We also discuss the challenges with future implementation of circulating biomarkers into clinical practice.
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Affiliation(s)
- Kah Yee Goh
- Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, Singapore 169610, Singapore
| | - Terence You De Cheng
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Proteos, Singapore 138673, Singapore
| | - Su Chin Tham
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Proteos, Singapore 138673, Singapore
| | - Darren Wan-Teck Lim
- Division of Medical Oncology, National Cancer Centre Singapore, 11 Hospital Crescent, Singapore 169610, Singapore
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Proteos, Singapore 138673, Singapore
- Office of Academic and Clinical Development, Duke-NUS Medical School, Singapore 169857, Singapore
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22
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Bironzo P, Pepe F, Russo G, Pisapia P, Gragnano G, Aquino G, Bessi S, Buglioni S, Bartoccini F, Ferrero G, Bresciani MA, Francia di Celle P, Sibona F, Giusti A, Movilia A, Farioli RM, Santoro A, Salemi D, Scarpino S, Galafate D, Tommasi S, Lacalamita R, Seminati D, Sajjadi E, Novello S, Pagni F, Troncone G, Malapelle U. An Italian Multicenter Perspective Harmonization Trial for the Assessment of MET Exon 14 Skipping Mutations in Standard Reference Samples. Diagnostics (Basel) 2023; 13:diagnostics13040629. [PMID: 36832117 PMCID: PMC9955861 DOI: 10.3390/diagnostics13040629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 01/24/2023] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
Lung cancer remains the leading cause of cancer deaths worldwide. International societies have promoted the molecular analysis of MET proto-oncogene, receptor tyrosine kinase (MET) exon 14 skipping for the clinical stratification of non-small cell lung cancer (NSCLC) patients. Different technical approaches are available to detect MET exon 14 skipping in routine practice. Here, the technical performance and reproducibility of testing strategies for MET exon 14 skipping carried out in various centers were evaluated. In this retrospective study, each institution received a set (n = 10) of a customized artificial formalin-fixed paraffin-embedded (FFPE) cell line (Custom METex14 skipping FFPE block) that harbored the MET exon 14 skipping mutation (Seracare Life Sciences, Milford, MA, USA), which was previously validated by the Predictive Molecular Pathology Laboratory at the University of Naples Federico II. Each participating institution managed the reference slides according to their internal routine workflow. MET exon 14 skipping was successfully detected by all participating institutions. Molecular analysis highlighted a median Cq cut off of 29.3 (ranging from 27.1 to 30.7) and 2514 (ranging from 160 to 7526) read counts for real-time polymerase chain reaction (RT-PCR) and NGS-based analyses, respectively. Artificial reference slides were a valid tool to harmonize technical workflows in the evaluation of MET exon 14 skipping molecular alterations in routine practice.
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Affiliation(s)
- Paolo Bironzo
- Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Francesco Pepe
- Department of Public Health, University Federico II of Naples, 80131 Naples, Italy
| | - Gianluca Russo
- Department of Public Health, University Federico II of Naples, 80131 Naples, Italy
| | - Pasquale Pisapia
- Department of Public Health, University Federico II of Naples, 80131 Naples, Italy
| | - Gianluca Gragnano
- Department of Public Health, University Federico II of Naples, 80131 Naples, Italy
| | - Gabriella Aquino
- Department of Pulmonary Oncology, AORN Dei Colli Monaldi, 80131 Naples, Italy
| | - Silvia Bessi
- Departmental Structure of Oncological Molecular Pathology, Oncological Department Azienda USL Toscana Centro, S. Stefano Hospital, 59100 Prato, Italy
| | - Simonetta Buglioni
- Pathology Unit, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy
| | - Federico Bartoccini
- Pathology Unit, IRCCS Regina Elena National Cancer Institute, 00144 Rome, Italy
| | | | | | - Paola Francia di Celle
- Molecular Pathology, AOU Città della Salute e della Scienza di Torino-Presidio Ospedaliero Molinette, 10126 Turin, Italy
| | - Francesca Sibona
- Molecular Pathology, AOU Città della Salute e della Scienza di Torino-Presidio Ospedaliero Molinette, 10126 Turin, Italy
| | - Andrea Giusti
- ASL Toscana Nord Ovest, Pathology Unit, Centro Polispecialistico “Achille Sicari”, 54033 Carrara, Italy
| | - Alessandra Movilia
- Department of Pathology, ASST Ovest Milanese, Ospedale di Legnano, 20025 Legnano, Italy
| | | | - Alessandra Santoro
- Division of Hematology and Bone Marrow Transplantation, Ospedali Riuniti Villa Sofia-Cervello, 90146 Palermo, Italy
| | - Domenico Salemi
- Division of Hematology and Bone Marrow Transplantation, Ospedali Riuniti Villa Sofia-Cervello, 90146 Palermo, Italy
| | - Stefania Scarpino
- Pathology Unit, Department of Clinical and Molecular Medicine, St. Andrea University Hospital, University of Rome La Sapienza, 00189 Rome, Italy
| | - Dino Galafate
- Pathology Unit, Department of Clinical and Molecular Medicine, St. Andrea University Hospital, University of Rome La Sapienza, 00189 Rome, Italy
| | - Stefania Tommasi
- Molecular Genetics Laboratory, IRCCS Istituto Tumori Giovanni Paolo II, 70124 Bari, Italy
| | - Rosanna Lacalamita
- Molecular Genetics Laboratory, IRCCS Istituto Tumori Giovanni Paolo II, 70124 Bari, Italy
| | - Davide Seminati
- Department of Surgery and Translational Medicine, Section of Pathology, Università degli Studi di Mila-no-Bicocca, 20126 Milan, Italy
| | - Elham Sajjadi
- Department of Oncology and Hemato-Oncology, University of Milan, 20136 Milan, Italy
| | - Silvia Novello
- Department of Oncology, S. Luigi Gonzaga Hospital, University of Turin, 10043 Orbassano, Italy
| | - Fabio Pagni
- Department of Surgery and Translational Medicine, Section of Pathology, Università degli Studi di Mila-no-Bicocca, 20126 Milan, Italy
| | - Giancarlo Troncone
- Department of Public Health, University Federico II of Naples, 80131 Naples, Italy
| | - Umberto Malapelle
- Department of Public Health, University Federico II of Naples, 80131 Naples, Italy
- Correspondence:
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23
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Fang Q, Yu J, Li W, Luo J, Deng Q, Chen B, He Y, Zhang J, Zhou C. Prognostic value of inflammatory and nutritional indexes among advanced NSCLC patients receiving PD-1 inhibitor therapy. Clin Exp Pharmacol Physiol 2023; 50:178-190. [PMID: 36419356 PMCID: PMC10107359 DOI: 10.1111/1440-1681.13740] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 11/13/2022] [Accepted: 11/20/2022] [Indexed: 11/25/2022]
Abstract
Though immunotherapy has to some extent improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), only a few patients benefit. Furthermore, immunotherapy efficacy is affected by inflammatory and nutritional status of patients. To investigate whether dynamics of inflammatory and nutritional indexes were associated with prognosis, 223 patients were analysed retrospectively. The inflammatory indexes of interest were neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic immune-inflammation index (SII) while prognostic nutritional index (PNI) and the haemoglobin, albumin, lymphocyte and platelet (HALP) score were considered as nutritional indexes. Patients were divided into high and low groups or into 'increase' and 'decrease' groups based on pre-treatment cut-off values and index dynamics after 6-week follow-up respectively. High pre-treatment PLR (OR = 2.612) and increase in NLR during follow-up (OR = 2.516) were significantly associated with lower objective response rates. Using multivariable analysis, high pre-treatment PLR (HR, 2.319) and increase in SII (HR, 1.731) predicted shorter progression-free survival, while high pre-treatment NLR (HR, 1.635), increase in NLR (HR, 1.663) and PLR (HR, 1.691) and decrease in PNI (HR, 0.611) predicted worse overall survival. The nomogram's C-index in inside validation was 0.718 (95% CI: 0.670-0.766). Our results indicated both nutritional and inflammatory indexes are associated with survival outcomes. Inflammatory indexes were additionally linked to treatment response. Index dynamics are better predictors than baseline values in predicting survival in advanced NSCLC patients receiving PD-1 inhibitor combined with chemotherapy as first-line.
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Affiliation(s)
- Qiyu Fang
- Medical College of Soochow University, Soochow, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Jia Yu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Wei Li
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Jie Luo
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Qinfang Deng
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Bin Chen
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Yayi He
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Jie Zhang
- Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
| | - Caicun Zhou
- Medical College of Soochow University, Soochow, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, Tongji University Medical School Cancer Institute, Tongji University School of Medicine, Shanghai, China
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24
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Peng Y, Li Z, Fu Y, Pan Y, Zeng Y, Liu J, Xiao C, Zhang Y, Su Y, Li G, Wu F. Progress and perspectives of perioperative immunotherapy in non-small cell lung cancer. Front Oncol 2023; 13:1011810. [PMID: 36761954 PMCID: PMC9905802 DOI: 10.3389/fonc.2023.1011810] [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: 08/04/2022] [Accepted: 01/04/2023] [Indexed: 01/27/2023] Open
Abstract
Lung cancer is one of the leading causes of cancer-related death. Lung cancer mortality has decreased over the past decade, which is partly attributed to improved treatments. Curative surgery for patients with early-stage lung cancer is the standard of care, but not all surgical treatments have a good prognosis. Adjuvant and neoadjuvant chemotherapy are used to improve the prognosis of patients with resectable lung cancer. Immunotherapy, an epoch-defining treatment, has improved curative effects, prognosis, and tolerability compared with traditional and ordinary cytotoxic chemotherapy, providing new hope for patients with non-small cell lung cancer (NSCLC). Immunotherapy-related clinical trials have reported encouraging clinical outcomes in their exploration of different types of perioperative immunotherapy, from neoadjuvant immune checkpoint inhibitor (ICI) monotherapy, neoadjuvant immune-combination therapy (chemoimmunotherapy, immunotherapy plus antiangiogenic therapy, immunotherapy plus radiotherapy, or concurrent chemoradiotherapy), adjuvant immunotherapy, and neoadjuvant combined adjuvant immunotherapy. Phase 3 studies such as IMpower 010 and CheckMate 816 reported survival benefits of perioperative immunotherapy for operable patients. This review summarizes up-to-date clinical studies and analyzes the efficiency and feasibility of different neoadjuvant therapies and biomarkers to identify optimal types of perioperative immunotherapy for NSCLC.
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Affiliation(s)
- Yurong Peng
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zhuo Li
- The Ophthalmologic Center of the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yucheng Fu
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yue Pan
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yue Zeng
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Junqi Liu
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Chaoyue Xiao
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yingzhe Zhang
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yahui Su
- XiangYa School of Public Health, Central South University, Changsha, Hunan, China
| | - Guoqing Li
- XiangYa School of Public Health, Central South University, Changsha, Hunan, China
| | - Fang Wu
- Department of Oncology, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China
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Zheng L, Xiong A, Wang S, Xu J, Shen Y, Zhong R, Lu J, Chu T, Zhang W, Li Y, Zheng X, Han B, Zhong H, Nie W, Zhang X. Decreased monocyte-to-lymphocyte ratio was associated with satisfied outcomes of first-line PD-1 inhibitors plus chemotherapy in stage IIIB-IV non-small cell lung cancer. Front Immunol 2023; 14:1094378. [PMID: 36776882 PMCID: PMC9909005 DOI: 10.3389/fimmu.2023.1094378] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 01/11/2023] [Indexed: 01/27/2023] Open
Abstract
Objectives Immune-checkpoint inhibitors (ICIs) combined with chemotherapy are more widely used than monotherapy and have shown better survival in patients with advanced non-small cell lung cancer (NSCLC) without oncogenic driver alterations. The monocyte-to-lymphocyte ratio (MLR) might predict the treatment outcomes of ICI therapy in advanced NSCLC patients but has not yet been investigated. In addition, the cutoff of MLR is controversial. Therefore, the present study aimed to explore the associations between changes in MLR at the initial stage of treatment and clinical outcomes in stage IIIB-IV NSCLC patients receiving first-line PD-1 inhibitor combined with chemotherapy. Methods The present study included 139 stage IIIB-IV NSCLC patients treated with first-line PD-1 inhibitor combined with chemotherapy. The blood results were assessed 10 days before initiation of PD-1 inhibitor-based combination therapy (time point 1, baseline) and before the third cycle of combined therapy (time point 2). Compared to altered MLR, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) in baseline and in time point 2, patients were divided into decreased MLR/NLR/PLR and increased MLR/NLR/PLR groups. The objective response rate (ORR), progression-free survival (PFS), and the association with the changes in blood indicators were analyzed. Results A total of 48 patients were categorized in the decreased MLR group and 91 in the increased MLR group. Patients with decreased MLR had a significantly higher ORR in the univariate (P<0.001) and multivariate (P<0.001) Cox proportional hazards models. On the other hand, decreased MLR was significantly associated with prolonged PFS in the univariate (P=0.007) and multivariate (P=0.016) analyses. Next, 91 patients comprised the decreased NLR group and 48 as the increased NLR group. Patients with decreased NLR exhibited high ORR (P=0.001) and prolonged PFS in univariate analysis (P=0.033). Then, 64 patients comprised the decreased PLR group and 75 the increased PLR group. Decreased PLR was significantly associated with high ORR in univariate (P<0.001) and multivariate (P=0.017) analyses. The subgroup analyses showed that decreased MLR was significantly associated with satisfactory outcomes in patients with all PD-L1 expressions. Conclusion Decreased MLR was associated with high ORR and long PFS and might have a potential predictive value in patients with stage IIIB-IV NSCLC treated with first-line PD-1 inhibitor combined with chemotherapy. In addition, changes in MLR might have predictive value in all PD-L1-expressing populations. Decreased NLR and PLR also showed improved survival, suggesting that changes in NLR and PLR may be complementary to predicting prognosis.
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Affiliation(s)
- Liang Zheng
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Anning Xiong
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Shuyuan Wang
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jianlin Xu
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Yinchen Shen
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Runbo Zhong
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Jun Lu
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Tianqing Chu
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Zhang
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Ying Li
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xiaoxuan Zheng
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Baohui Han
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hua Zhong
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Wei Nie
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Xueyan Zhang
- Department of Pulmonary, Shanghai Chest Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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Perrotta F, Chino V, Allocca V, D’Agnano V, Bortolotto C, Bianco A, Corsico AG, Stella GM. Idiopathic pulmonary fibrosis and lung cancer: targeting the complexity of the pharmacological interconnection. Expert Rev Respir Med 2022; 16:1043-1055. [DOI: 10.1080/17476348.2022.2145948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Fabio Perrotta
- - Department of Translational Medical Sciences, University of Campania “L. Vanvitelli”, 80131, Napoli, Italy
- - U.O.C. Clinica Pneumologica “L. Vanvitelli”, A.O. dei Colli, Ospedale Monaldi, 80131, Napoli, Italy
| | - Vittorio Chino
- - University of Pavia Medical School, 27100 Pavia, Italy
- - Department of Medical Sciences and Infective Diseases, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo Foundation and University of Pavia Medical School, Pavia, Italy
| | - Valentino Allocca
- - Department of Translational Medical Sciences, University of Campania “L. Vanvitelli”, 80131, Napoli, Italy
- - U.O.C. Clinica Pneumologica “L. Vanvitelli”, A.O. dei Colli, Ospedale Monaldi, 80131, Napoli, Italy
| | - Vito D’Agnano
- - Department of Translational Medical Sciences, University of Campania “L. Vanvitelli”, 80131, Napoli, Italy
- - U.O.C. Clinica Pneumologica “L. Vanvitelli”, A.O. dei Colli, Ospedale Monaldi, 80131, Napoli, Italy
| | - Chandra Bortolotto
- - Dept. of Clinical-Surgical, Diagnostic and Paediatric Sciences, University of Pavia Medical School, Pavia, Italy
- - Department of Intensive Medicine, Unit of Radiology, Fondazione IRCCS Policlinico San Matteo, 27100 Pavia, Italy
| | - Andrea Bianco
- - Department of Translational Medical Sciences, University of Campania “L. Vanvitelli”, 80131, Napoli, Italy
- - U.O.C. Clinica Pneumologica “L. Vanvitelli”, A.O. dei Colli, Ospedale Monaldi, 80131, Napoli, Italy
| | - Angelo Guido Corsico
- - Department of Medical Sciences and Infective Diseases, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo Foundation and University of Pavia Medical School, Pavia, Italy
- - Dept. of Internal Medicine and Medical Therapeutics, University of Pavia Medical School, Pavia, Italy
| | - Giulia Maria Stella
- - Department of Medical Sciences and Infective Diseases, Unit of Respiratory Diseases, IRCCS Policlinico San Matteo Foundation and University of Pavia Medical School, Pavia, Italy
- - Dept. of Internal Medicine and Medical Therapeutics, University of Pavia Medical School, Pavia, Italy
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Bożyk A, Nicoś M. The Overview of Perspectives of Clinical Application of Liquid Biopsy in Non-Small-Cell Lung Cancer. Life (Basel) 2022; 12:1640. [PMID: 36295075 PMCID: PMC9604747 DOI: 10.3390/life12101640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/12/2022] [Accepted: 10/17/2022] [Indexed: 01/19/2023] Open
Abstract
The standard diagnostics procedure for non-small-cell lung cancer (NSCLC) requires a pathological evaluation of tissue samples obtained by surgery or biopsy, which are considered invasive sampling procedures. Due to this fact, re-sampling of the primary tumor at the moment of progression is limited and depends on the patient's condition, even if it could reveal a mechanism of resistance to applied therapy. Recently, many studies have indicated that liquid biopsy could be provided for the noninvasive management of NSCLC patients who receive molecularly targeted therapies or immunotherapy. The liquid biopsy of neoplastic patients harbors small fragments of circulating-free DNA (cfDNA) and cell-free RNA (cfRNA) secreted to the circulation from normal cells, as well as a subset of tumor-derived circulating tumor cells (CTCs) or circulating tumor DNA (ctDNA). In NSCLC patients, a longitudinal assessment of genetic alterations in "druggable" genes in liquid biopsy might improve the follow-up of treatment efficacy and allow for the detection of an early progression before it is detectable in computed tomography or a clinical image. However, a liquid biopsy may be used to determine a variety of relevant molecular or genetic information for understanding tumor biology and its evolutionary trajectories. Thus, liquid biopsy is currently associated with greater hope for common diagnostic and clinical applications. In this review, we would like to highlight diagnostic challenges in the application of liquid biopsy into the clinical routine and indicate its implications on the metastatic spread of NSCLC or monitoring of personalized treatment regimens.
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Affiliation(s)
| | - Marcin Nicoś
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-059 Lublin, Poland
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Wu J, Song D, Zhao G, Chen S, Ren H, Zhang B. Cross-talk between necroptosis-related lncRNAs to construct a novel signature and predict the immune landscape of lung adenocarcinoma patients. Front Genet 2022; 13:966896. [PMID: 36186456 PMCID: PMC9519990 DOI: 10.3389/fgene.2022.966896] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 08/30/2022] [Indexed: 11/17/2022] Open
Abstract
Background: As a new style of cell death, necroptosis plays a crucial role in tumor immune microenvironment. LncRNAs have been identified to act as competitive RNAs to influence genes involved in necroptosis. Therefore, we aim to create a signature based on necroptosis-related lncRNAs to predict the prognosis and immune landscape of lung adenocarcinoma (LUAD) patients in this study. Methods: TCGA database was used to acquire RNA sequencing (RNA-Seq) data and clinical information for 59 lung normal samples and 535 lung adenocarcinoma samples. The Pearson correlation analysis, univariate cox regression analysis and least absolute shrinkage and selection operator (LASSO) cox regression were performed to construct the prognostic NRlncRNAs signature. Then we used Kaplan-Meier (K-M) analysis, time-dependent ROC curves, univariate and multivariate cox regression analysis, and nomogram to validate this signature. In addition, GO, KEGG, and GSVA were analyzed to investigate the potential molecular mechanism. Moreover, we analyzed the relationship between our identified signature and immune microenvironment, TMB, and some clinical characteristics. Finally, we detected the expression of the six necroptosis-related lncRNAs in cells and tissues. Results: We constructed a NRlncRNAs signature consisting of six lncRNAs (FRMD6-AS1, LINC01480, FAM83A-AS1, FRMD6-AS1, MED4-AS1, and LINC01415) in LUAD. LUAD patients with high risk scores had lower chance of survival with an AUC of 0.739, 0.709, and 0.733 for 1-year, 3-year, and 5-year respectively. The results based on GO, KEGG, and GSVA enrichment analysis demonstrated that NRlncRNAs signature-related genes were mainly correlated with immune pathways, metabolic-and cell growth-related pathways, cell cycle, and apoptosis. Moreover, the risk score was correlated with the immune status of LUAD patients. Patients with higher risk scores had lower ESTIMATE scores and higher TIDE scores. The risk score was positively correlated with TMB. LINC01415, FRMD6-AS1 and FAM83A-AS1 were significantly overexpressed in lung adenocarcinoma, while the expression levels of MED4-AS1 and LINC01480 were lower in lung adenocarcinoma. Conclusion: Overall, an innovative prognostic signature based on NRlncRNAs was developed for LUAD through comprehensive bioinformatics analysis, which can act as a predictor of immunotherapy and may provide guidance for clinicians.
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Affiliation(s)
- Jie Wu
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Dingli Song
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Guang Zhao
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Sisi Chen
- Department of Oncology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Hong Ren
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Hong Ren, ; Boxiang Zhang,
| | - Boxiang Zhang
- Department of Thoracic Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Hong Ren, ; Boxiang Zhang,
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Li C, Ding Y, Zhang X, Hua K. Integrated in silico analysis of LRP2 mutations to immunotherapy efficacy in pan-cancer cohort. Discov Oncol 2022; 13:65. [PMID: 35834061 PMCID: PMC9283634 DOI: 10.1007/s12672-022-00528-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 07/06/2022] [Indexed: 12/15/2022] Open
Abstract
PURPOSE Immunotherapy has emerged as a novel therapy, while many patients are refractory. Although, several biomarkers have been identified as predictive biomarkers for immunotherapy, such as tumor specific genes, PD-1/PD-L1, tumor mutation burn (TMB), and microsatellite instability (MSI), results remain unsatisfactory. The aim of this study is to evaluate the value of LRP2 mutations in predicating cancer immunotherapy. METHODS We investigated the characteristics of low-density lipoprotein receptor-related protein 2 (LRP2) mutation in the cancer genome atlas (TCGA) and explored the potential association of LRP2 mutations with immunotherapy. Characteristics of LRP2 mutations in 33 cancer types were analyzed using large-scale public data. The association of LRP2 mutations with immune cell infiltration and immunotherapy efficacy was evaluated. Finally, a LPR2 mutation signature (LMS) was developed and validated by TCGA-UCEC and pan-cancer cohorts. Furthermore, we demonstrated the predictive power of LMS score in independent immunotherapy cohorts by performing a meta-analysis. RESULTS Our results revealed that patients with LRP2 mutant had higher TMB and MSI compared with patients without LRP2 mutations. LRP2 mutations were associated with high levels of immune cells infiltration, immune-related genes expression and enrichment of immune related signaling pathways. Importantly, LRP2-mutated patients had a long overall survival (OS) after immunotherapy. In the endometrial cancer (EC) cohort, we found that patients with LRP2 mutations belonged to the POLE and MSI-H type and had a better prognosis. Finally, we developed a LRP2 mutations signature (LMS), that was significantly associated with prognosis in patients receiving immunotherapy. CONCLUSION These results indicated that LRP2 mutations can serve as a biomarker for personalized tumor immunotherapy. Importantly, LMS is a potential predictor of patients' prognosis after immunotherapy.
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Affiliation(s)
- Chunbo Li
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, 419 FangXie Road, Shanghai, 200011, China
| | - Yan Ding
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, 419 FangXie Road, Shanghai, 200011, China
| | - Xuyin Zhang
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, 419 FangXie Road, Shanghai, 200011, China.
| | - Keqin Hua
- Department of Obstetrics and Gynecology, Obstetrics and Gynecology Hospital of Fudan University, 419 FangXie Road, Shanghai, 200011, China.
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30
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Liu J, Zhang Y. Intratumor microbiome in cancer progression: current developments, challenges and future trends. Biomark Res 2022; 10:37. [PMID: 35642013 PMCID: PMC9153132 DOI: 10.1186/s40364-022-00381-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Accepted: 05/01/2022] [Indexed: 11/29/2022] Open
Abstract
Cancer is a complicated disease attributed to multifactorial changes, which causes difficulties with treatment strategies. Various factors have been regarded as the main contributors, and infectious etiological factors have recently attracted interest. Several microbiomes contribute to carcinogenesis, cancer progression, and modulating cancer treatment by inducing cancerous epithelial cells and chronic inflammation. Most of our knowledge on the role of microbiota in tumor oncogenesis and clinical efficiency is associated with the intestinal microbiome. However, compelling evidence has also confirmed the contribution of the intratumor microbiome in cancer. Indeed, the findings of clinical tumor samples, animal models, and studies in vitro have revealed that many intratumor microbiomes promote tumorigenesis and immune evasion. In addition, the intratumor microbiome participates in regulating the immune response and even affects the outcomes of cancer treatment. This review summarizes the interplay between the intratumor microbiota and cancer, focusing on the contribution and mechanism of intratumor microbiota in cancer initiation, progression, and potential applications to cancer therapy.
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Affiliation(s)
- Jinyan Liu
- Biotherapy Center and Cancer Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Yi Zhang
- Biotherapy Center and Cancer Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China. .,State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou, Henan, China.
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