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Zhu L, Qin J. Predictive biomarkers for immunotherapy response in extensive-stage SCLC. J Cancer Res Clin Oncol 2024; 150:22. [PMID: 38245636 PMCID: PMC10799815 DOI: 10.1007/s00432-023-05544-x] [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: 10/09/2023] [Accepted: 12/13/2023] [Indexed: 01/22/2024]
Abstract
BACKGROUND Small cell lung cancer (SCLC) accounts for about 13-15% of all lung cancers, and about 70% of SCLC patients have developed extensive-stage small cell lung cancer (ES-SCLC) at the time of diagnosis because of its highgrade malignancy, easy invasion, and metastasis. In recent years, immunotherapy combined with chemotherapy has become the standard first-line treatment for ES-SCLC. However, SCLC is a relatively immune-cold lung cancer subtype with a limited number of beneficiaries and a short benefit period. Therefore, the use of biomarkers to identify populations with significant benefits from immunotherapy will help improve the efficacy and survival benefits of immunotherapy. However, predictive biomarkers suitable for clinical practice have not been established in the field of SCLC. PURPOSE In order to find the predictive biomarkers of immunotherapy for ES-SCLC, we summarized the research progress of traditional biomarkers, such as programmed cell death ligand 1 (PD-L1) and tumor mutation burden (TMB), and summarizes the research of potential biomarkers associated with prognosis, such as molecular subtypes, special gene expression, expression of major histocompatibility complex (MHC) I and II classes, tumor immune microenvironment (TIME), and circulating tumor DNA (ctDNA) .We aim to provide new insights on biomarkers. CONCLUSION The exploration of biomarkers for immunotherapy of SCLC is still very difficult, and it is clear that conventional predictive biomarkers are not suitable for SCLC. At present, the molecular subtypes defined from transcription factors may have some guiding significance, which still needs to be confirmed by prospective clinical studies. In addition, the ctDNA positivity rate of SCLC is higher than that of other tumor types, which can also solve the dilemma of the difficulty of obtaining specimens of SCLC tissues. And the dynamic change of ctDNA also has great potential to predict the curative effect of SCLC, which is worth further clinical exploration.
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Affiliation(s)
- Lin Zhu
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China
| | - Jing Qin
- Department of Thoracic Medical Oncology, Zhejiang Cancer Hospital, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, 310022, Zhejiang, China.
- Zhejiang Key Laboratory of Diagnosis and Treatment Technology on Thoracic Oncology (Lung and Esophagus), Zhejiang Cancer Hospital, Hangzhou, 310022, People's Republic of China.
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Liu Q, Zhang J, Guo C, Wang M, Wang C, Yan Y, Sun L, Wang D, Zhang L, Yu H, Hou L, Wu C, Zhu Y, Jiang G, Zhu H, Zhou Y, Fang S, Zhang T, Hu L, Li J, Liu Y, Zhang H, Zhang B, Ding L, Robles AI, Rodriguez H, Gao D, Ji H, Zhou H, Zhang P. Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies. Cell 2024; 187:184-203.e28. [PMID: 38181741 DOI: 10.1016/j.cell.2023.12.004] [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: 12/19/2022] [Revised: 09/25/2023] [Accepted: 12/01/2023] [Indexed: 01/07/2024]
Abstract
We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.
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Affiliation(s)
- Qian Liu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China; Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Jing Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Chenchen Guo
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mengcheng Wang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chenfei Wang
- Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Department of Orthopedics, Tongji Hospital, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China; Frontier Science Center for Stem Cells, School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Yilv Yan
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Liangdong Sun
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Di Wang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Lele Zhang
- Central Laboratory, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Huansha Yu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Likun Hou
- Department of Pathology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Chunyan Wu
- Department of Pathology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Yuming Zhu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Gening Jiang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China
| | - Hongwen Zhu
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Yanting Zhou
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Shanhua Fang
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Tengfei Zhang
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liang Hu
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China
| | - Junqiang Li
- D1 Medical Technology, Shanghai 201800, China
| | - Yansheng Liu
- Cancer Biology Institute, Yale University School of Medicine, West Haven, CT 06516, USA
| | - Hui Zhang
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Bing Zhang
- Lester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Li Ding
- Department of Medicine, McDonnell Genome Institute, Washington University, St. Louis, MO 63108, USA
| | - Ana I Robles
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA
| | - Henry Rodriguez
- Office of Cancer Clinical Proteomics Research, National Cancer Institute, National Institutes of Health, Rockville, MD 20850, USA
| | - Daming Gao
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
| | - Hongbin Ji
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China; Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China; School of Life Science and Technology, Shanghai Tech University, Shanghai 200120, China.
| | - Hu Zhou
- Department of Analytical Chemistry, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China; University of Chinese Academy of Sciences, Beijing 100049, China; School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China.
| | - Peng Zhang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai 200433, China.
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Lin X, Zong C, Zhang Z, Fang W, Xu P. Progresses in biomarkers for cancer immunotherapy. MedComm (Beijing) 2023; 4:e387. [PMID: 37799808 PMCID: PMC10547938 DOI: 10.1002/mco2.387] [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: 04/07/2023] [Revised: 09/02/2023] [Accepted: 09/08/2023] [Indexed: 10/07/2023] Open
Abstract
Currently, checkpoint inhibitor-based immunotherapy has emerged as prevailing treatment modality for diverse cancers. However, immunotherapy as a first-line therapy has not consistently yielded durable responses. Moreover, the risk of immune-related adverse events increases with combination regimens. Thus, the development of predictive biomarkers is needed to optimize individuals benefit, minimize risk of toxicities, and guide combination approaches. The greatest focus has been on tumor programmed cell death-ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational burden (TMB). However, there remains a subject of debate due to thresholds variability and significant heterogeneity. Major unmet challenges in immunotherapy are the discovery and validation of predictive biomarkers. Here, we show the status of tumor PD-L1, MSI, TMB, and emerging data on novel biomarker strategies with oncogenic signaling and epigenetic regulation. Considering the exploration of peripheral and intestinal immunity has served as noninvasive alternative in predicting immunotherapy, this review also summarizes current data in systemic immunity, encompassing solute PD-L1 and TMB, circulating tumor DNA and infiltrating lymphocytes, routine emerging inflammatory markers and cytokines, as well as gut microbiota. This review provides up-to-date information on the evolving field of currently available biomarkers in predicting immunotherapy. Future exploration of novel biomarkers is warranted.
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Affiliation(s)
- Xuwen Lin
- Department of Pulmonary and Critical Care MedicinePeking University Shenzhen HospitalShenzhenGuangdong ProvinceChina
- Department of Internal MedicineShantou University Medical CollegeShantouGuangdong ProvinceChina
| | - Chenyu Zong
- Department of Pulmonary and Critical Care MedicinePeking University Shenzhen HospitalShenzhenGuangdong ProvinceChina
- Department of Internal MedicineZunyi Medical UniversityZunyiGuizhou ProvinceChina
| | - Zhihan Zhang
- Department of Pulmonary and Critical Care MedicinePeking University Shenzhen HospitalShenzhenGuangdong ProvinceChina
| | - Weiyi Fang
- Cancer Research InstituteSchool of Basic Medical ScienceSouthern Medical UniversityGuangzhouGuangdong ProvinceChina
- Cancer CenterIntegrated Hospital of Traditional Chinese MedicineSouthern Medical UniversityGuangzhouGuangdong ProvinceChina
| | - Ping Xu
- Department of Pulmonary and Critical Care MedicinePeking University Shenzhen HospitalShenzhenGuangdong ProvinceChina
- Department of Internal MedicineZunyi Medical UniversityZunyiGuizhou ProvinceChina
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Su Y, Lu C, Zheng S, Zou H, Shen L, Yu J, Weng Q, Wang Z, Chen M, Zhang R, Ji J, Wang M. Precise prediction of the sensitivity of platinum chemotherapy in SCLC: Establishing and verifying the feasibility of a CT-based radiomics nomogram. Front Oncol 2023; 13:1006172. [PMID: 37007144 PMCID: PMC10061075 DOI: 10.3389/fonc.2023.1006172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 03/06/2023] [Indexed: 03/18/2023] Open
Abstract
ObjectivesTo develop and validate a CT-based radiomics nomogram that can provide individualized pretreatment prediction of the response to platinum treatment in small cell lung cancer (SCLC).MaterialsA total of 134 SCLC patients who were treated with platinum as a first-line therapy were eligible for this study, including 51 patients with platinum resistance (PR) and 83 patients with platinum sensitivity (PS). The variance threshold, SelectKBest, and least absolute shrinkage and selection operator (LASSO) were applied for feature selection and model construction. The selected texture features were calculated to obtain the radiomics score (Rad-score), and the predictive nomogram model was composed of the Rad-score and the clinical features selected by multivariate analysis. Receiver operating characteristic (ROC) curves, calibration curves, and decision curves were used to assess the performance of the nomogram.ResultsThe Rad-score was calculated using 10 radiomic features, and the resulting radiomics signature demonstrated good discrimination in both the training set (area under the curve [AUC], 0.727; 95% confidence interval [CI], 0.627–0.809) and the validation set (AUC, 0.723; 95% CI, 0.562–0.799). To improve diagnostic effectiveness, the Rad-score created a novel prediction nomogram by combining CA125 and CA72-4. The radiomics nomogram showed good calibration and discrimination in the training set (AUC, 0.900; 95% CI, 0.844-0.947) and the validation set (AUC, 0.838; 95% CI, 0.534-0.735). The radiomics nomogram proved to be clinically beneficial based on decision curve analysis.ConclusionWe developed and validated a radiomics nomogram model for predicting the response to platinum in SCLC patients. The outcomes of this model can provide useful suggestions for the development of tailored and customized second-line chemotherapy regimens.
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Affiliation(s)
- Yanping Su
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Department of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, Institute of Aging, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Key Laboratory of Alzheimer’s Disease of Zhejiang, Wenzhou, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Chenying Lu
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Shenfei Zheng
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Hao Zou
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Lin Shen
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Junchao Yu
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Qiaoyou Weng
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Zufei Wang
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Minjiang Chen
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
| | - Ran Zhang
- AI Research Department, Huiying Medical Technology Co., Ltd, Beijing, China
| | - Jiansong Ji
- Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Institute of Imaging Diagnosis and Minimally Invasive Intervention Research, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, China
- Clinical College of The Affiliated Central Hospital, School of Medicine, Lishui University, Lishui, Zhejiang, China
- *Correspondence: Meihao Wang, ; Jiansong Ji,
| | - Meihao Wang
- Department of Radiology, Key Laboratory of Intelligent Medical Imaging of Wenzhou, Institute of Aging, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Key Laboratory of Alzheimer’s Disease of Zhejiang, Wenzhou, Zhejiang, China
- *Correspondence: Meihao Wang, ; Jiansong Ji,
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