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Cai S, Yang G, Hu M, Li C, Yang L, Zhang W, Sun J, Sun F, Xing L, Sun X. Spatial cell interplay networks of regulatory T cells predict recurrence in patients with operable non-small cell lung cancer. Cancer Immunol Immunother 2024; 73:189. [PMID: 39093404 PMCID: PMC11297009 DOI: 10.1007/s00262-024-03762-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: 11/05/2023] [Accepted: 06/13/2024] [Indexed: 08/04/2024]
Abstract
BACKGROUND The interplay between regulatory T cells (Tregs) and neighboring cells, which is pivotal for anti-tumor immunity and closely linked to patient prognosis, remains to be fully elucidated. METHODS Tissue microarrays of 261 operable NSCLC patients were stained by multiplex immunofluorescence (mIF) assay, and the interaction between Tregs and neighboring cells in the tumor microenvironment (TME) was evaluated. Employing various machine learning algorithms, we developed a spatial immune signature to predict the prognosis of NSCLC patients. Additionally, we explored the interplay between programmed death-1/programmed death ligand-1 (PD-1/PD-L1) interactions and their relationship with Tregs. RESULTS Survival analysis indicated that the interplay between Tregs and neighboring cells in the invasive margin (IM) and tumor center was associated with recurrence in NSCLC patients. We integrated the intersection of the three algorithms to identify four crucial spatial immune features [P(CD8+Treg to CK) in IM, P(CD8+Treg to CD4) in IM, N(CD4+Treg to CK) in IM, N(CD4+Tcon to CK) in IM] and employed these characteristics to establish SIS, an independent prognosticator of recurrence in NSCLC patients [HR = 2.34, 95% CI (1.53, 3.58), P < 0.001]. Furthermore, analysis of cell interactions demonstrated that a higher number of Tregs contributed to higher PD-L1+ cells surrounded by PD-1+ cells (P < 0.001) with shorter distances (P = 0.004). CONCLUSION We dissected the cell interplay network within the TME, uncovering the spatial architecture and intricate interactions between Tregs and neighboring cells, along with their impact on the prognosis of NSCLC patients.
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Affiliation(s)
- Siqi Cai
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Guanqun Yang
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Mengyu Hu
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Chaozhuo Li
- School of Clinical Medicine, Weifang Medical University, Weifang, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Liying Yang
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Wei Zhang
- Shandong Cancer Hospital and Institute and Shandong Academy of Medical Science, Jinan, Shandong, China
| | - Jujie Sun
- Department of Pathology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Science, Jinan, Shandong, China
| | - Fenghao Sun
- Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No.440, Jiyan Road, Huaiyin District, Jinan, 250117, Shandong, China
| | - Ligang Xing
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, and Shandong Academy of Medical Sciences, Jinan, Shandong, China
| | - Xiaorong Sun
- Shandong University Cancer Center, Shandong University, Jinan, Shandong, China.
- Department of Nuclear Medicine, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No.440, Jiyan Road, Huaiyin District, Jinan, 250117, Shandong, China.
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Wang Y, Ye J, Zhou K, Chen N, Huang G, Feng G, Zhang G, Gou X. Radiomics Features on Enhanced Computed Tomography Predict FOXP3 Expression and Clinical Prognosis in Patients with Head and Neck Squamous Cell Carcinoma. JOURNAL OF IMAGING INFORMATICS IN MEDICINE 2024; 37:1323-1335. [PMID: 38376584 PMCID: PMC11300763 DOI: 10.1007/s10278-023-00910-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/13/2023] [Accepted: 08/23/2023] [Indexed: 02/21/2024]
Abstract
Forkhead box P3 (FOXP3) has been identified as a novel molecular marker in various types of cancer. The present study assessed the expression of FOXP3 in patients with head and neck squamous cell carcinoma (HNSCC) and its potential as a clinical prognostic indicator, and developed a radiomics model based on enhanced computed tomography (CT) imaging. Data from 483 patients with HNSCC were downloaded from the Cancer Genome Atlas for FOXP3 prognostic analysis and enhanced CT images from 139 patients included in the Cancer Imaging Archives, which were subjected to the maximum relevance and minimum redundancy and recursive feature elimination algorithms for radiomics feature extraction and processing. Logistic regression was used to build a model for predicting FOXP3 expression. A prognostic scoring system for radiomics score (RS), FOXP3, and patient clinicopathological factors was established to predict patient survival. The area under the receiver operating characteristic (ROC) curve (AUC) and calibration curve and decision curve analysis (DCA) were used to evaluate model performance. Furthermore, the relationship between FOXP3 and the immune microenvironment, as well as the association between RS and immune checkpoint-related genes, was analyzed. Results of analysis revealed that patients with HNSCC and high FOXP3 mRNA expression exhibited better overall survival. Immune infiltration analysis revealed that FOXP3 had a positive correlation with CD4 + and CD8 + T cells and other immune cells. The 8 best radiomics features were selected to construct the radiomics model. In the FOXP3 expression prediction model, the AUC values were 0.707 and 0.702 for the training and validation sets, respectively. Additionally, the calibration curve and DCA demonstrated the positive diagnostic utility of the model. RS was correlated with immune checkpoint-related genes such as ICOS, CTLA4, and PDCD1. A predictive nomogram was established, the AUCs were 0.87, 0.787, and 0.801 at 12, 24, and 36 months, respectively, and DCA demonstrated the high clinical applicability of the nomogram. The enhanced CT radiomics model can predict expression of FOXP3 and prognosis in patients with HNSCC. As such, FOXP3 may be used as a novel prognostic marker to improve individualized clinical diagnosis and treatment decisions.
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Affiliation(s)
- Yi Wang
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Juan Ye
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Kai Zhou
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Nian Chen
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Gang Huang
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Guangyong Feng
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China
| | - Guihai Zhang
- Department of Oncology, Zhuhai People's Hospital (Zhuhai Clinical Medical College of Jinan University), Zhuhai, Guangdong, China.
| | - Xiaoxia Gou
- Department of Head and Neck Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China.
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Huang Z, Xie T, Xie W, Chen Z, Wen Z, Yang L. Research trends in lung cancer and the tumor microenvironment: a bibliometric analysis of studies published from 2014 to 2023. Front Oncol 2024; 14:1428018. [PMID: 39144829 PMCID: PMC11322073 DOI: 10.3389/fonc.2024.1428018] [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: 05/05/2024] [Accepted: 07/16/2024] [Indexed: 08/16/2024] Open
Abstract
Background Lung cancer (LC) is one of the most common malignant tumors in the world and the leading cause of cancer-related deaths, which seriously threatens human life and health as well as brings a heavy burden to the society. In recent years, the tumor microenvironment (TME) has become an emerging research field and hotspot affecting tumor pathogenesis and therapeutic approaches. However, to date, there has been no bibliometric analysis of lung cancer and the tumor microenvironment from 2014 to 2023.This study aims to comprehensively summarize the current situation and development trends in the field from a bibliometric perspective. Methods The publications about lung cancer and the tumor microenvironment from 2014 to 2023 were extracted from the Web of Science Core Collection (WoSCC). The Microsoft Excel, Origin, R-bibliometrix, CiteSpace, and VOSviewer software are comprehensively used to scientifically analyze the data. Results Totally, 763 publications were identified in this study. A rapid increase in the number of publications was observed after 2018. More than 400 organizations published these publications in 36 countries or regions. China and the United States have significant influence in this field. Zhou, CC and Frontiers in Immunology are the most productive authors and journals respectively. Besides, the most frequently cited references were those on lung cancer pathogenesis, clinical trials, and treatment modalities. It suggests that novel lung cancer treatment models mainly based on the TME components, such as cancer-associated fibroblasts (CAFs) may lead to future research trends. Conclusions The field of lung cancer and the tumor microenvironment research is still in the beginning stages. Gene expression, molecular pathways, therapeutic modalities, and novel detection technologies in this field have been widely studied by researchers. This is the first bibliometric study to comprehensively summarize the research trend and development regarding lung cancer and tumor microenvironment over the last decade. The result of our research provides the updated perspective for scholars to understand the key information and cutting-edge hotspots in this field, as well as to identify future research directions.
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Affiliation(s)
- Zhilan Huang
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Tingyi Xie
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Wei Xie
- Department of Respiratory Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Zhuni Chen
- Department of Respiratory Medicine, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Zhiyuan Wen
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
| | - Lin Yang
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, Guangdong, China
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Fu X, Ma W, Zuo Q, Qi Y, Zhang S, Zhao Y. Application of machine learning for high-throughput tumor marker screening. Life Sci 2024; 348:122634. [PMID: 38685558 DOI: 10.1016/j.lfs.2024.122634] [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: 01/16/2024] [Revised: 03/26/2024] [Accepted: 04/10/2024] [Indexed: 05/02/2024]
Abstract
High-throughput sequencing and multiomics technologies have allowed increasing numbers of biomarkers to be mined and used for disease diagnosis, risk stratification, efficacy assessment, and prognosis prediction. However, the large number and complexity of tumor markers make screening them a substantial challenge. Machine learning (ML) offers new and effective ways to solve the screening problem. ML goes beyond mere data processing and is instrumental in recognizing intricate patterns within data. ML also has a crucial role in modeling dynamic changes associated with diseases. Used together, ML techniques have been included in automatic pipelines for tumor marker screening, thereby enhancing the efficiency and accuracy of the screening process. In this review, we discuss the general processes and common ML algorithms, and highlight recent applications of ML in tumor marker screening of genomic, transcriptomic, proteomic, and metabolomic data of patients with various types of cancers. Finally, the challenges and future prospects of the application of ML in tumor therapy are discussed.
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Affiliation(s)
- Xingxing Fu
- Key Laboratory of Biotechnology and Bioresources Utilization of Ministry of Education, Dalian Minzu University, Dalian 116600, China
| | - Wanting Ma
- Key Laboratory of Biotechnology and Bioresources Utilization of Ministry of Education, Dalian Minzu University, Dalian 116600, China
| | - Qi Zuo
- Key Laboratory of Biotechnology and Bioresources Utilization of Ministry of Education, Dalian Minzu University, Dalian 116600, China
| | - Yanfei Qi
- Centenary Institute, The University of Sydney, Sydney, NSW 2050, Australia
| | - Shubiao Zhang
- Key Laboratory of Biotechnology and Bioresources Utilization of Ministry of Education, Dalian Minzu University, Dalian 116600, China.
| | - Yinan Zhao
- Key Laboratory of Biotechnology and Bioresources Utilization of Ministry of Education, Dalian Minzu University, Dalian 116600, China
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Ziółkowska-Suchanek I, Żurawek M. FOXP3: A Player of Immunogenetic Architecture in Lung Cancer. Genes (Basel) 2024; 15:493. [PMID: 38674427 PMCID: PMC11050689 DOI: 10.3390/genes15040493] [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: 03/13/2024] [Revised: 04/05/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
The transcription factor forkhead box protein 3 (FOXP3) is considered to be a prominent component of the immune system expressed in regulatory T cells (Tregs). Tregs are immunosuppressive cells that regulate immune homeostasis and self-tolerance. FOXP3 was originally thought to be a Tregs-specific molecule, but recent studies have pinpointed that FOXP3 is expressed in a diversity of benign tumors and carcinomas. The vast majority of the data have shown that FOXP3 is correlated with an unfavorable prognosis, although there are some reports indicating the opposite function of this molecule. Here, we review recent progress in understanding the FOXP3 role in the immunogenetic architecture of lung cancer, which is the leading cause of cancer-related death. We discuss the prognostic significance of tumor FOXP3 expression, tumor-infiltrating FOXP3-lymphocytes, tumor FOXP3 in tumor microenvironments and the potential of FOXP3-targeted therapy.
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Lorenzi M, Resi MV, Bonanno L, Frega S, Dal Maso A, Ferro A, Guarneri V, Pasello G. Tissue and circulating biomarkers of benefit to immunotherapy in extensive-stage small cell lung cancer patients. Front Immunol 2024; 15:1308109. [PMID: 38348046 PMCID: PMC10859471 DOI: 10.3389/fimmu.2024.1308109] [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: 10/05/2023] [Accepted: 01/12/2024] [Indexed: 02/15/2024] Open
Abstract
Extensive stage-Small-Cell Lung Cancer (ES-SCLC) is an aggressive cancer with dismal prognosis. The addition of immune-checkpoint inhibitors (ICIs) to platinum-based chemotherapy have been consistently demonstrated to improve outcomes and survival, becoming the new standard in first - line treatment of ES-SCLC patients. However, despite positive results reported in the pivotal trials, longer benefit appears evident only for a selected group of patients. Several predictive biomarkers have been studied so far but the prospective identification of patients more likely to experience better outcome seems to be challenging in SCLC. Indeed, classical immune predictive biomarkers as PD-L1 and tumor mutational burden (TMB) seem not to correlate with outcomes. Recently, a new molecular classification of SCLC based on differential expression of genes associated with specific clinical behaviors and therapeutic vulnerability have been presented suggesting a new field to be investigated. Despite the achievements, these studies focused mainly on inter-tumoral heterogeneity, limiting the exploration of intra-tumoral heterogeneity and cell to cell interactions. New analysis methods are ongoing in order to explore subtypes plasticity. Analysis on single biopsies cannot catch the whole genomic profile and dynamic change of disease over time and during treatment. Moreover, the availability of tissue for translational research is limited due to the low proportion of patients undergoing surgery. In this context, liquid biopsy is a promising tool to detect reliable predictive biomarkers. Here, we reviewed the current available data on predictive role of tissue and liquid biomarkers in ES-SCLC patients receiving ICIs. We assessed latest results in terms of predictive and prognostic value of gene expression profiling in SCLC. Finally, we explored the role of liquid biopsy as a tool to monitor SCLC patients over time.
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Affiliation(s)
- Martina Lorenzi
- Department of Medical Oncology, Santa Chiara Hospital, Trento, Italy
| | - Maria Vittoria Resi
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
- Department of Surgery, Oncology, and Gastroenterology, University of Padova, Padova, Italy
| | - Laura Bonanno
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
| | - Stefano Frega
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
| | - Alessandro Dal Maso
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
| | - Alessandra Ferro
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
| | - Valentina Guarneri
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
- Department of Surgery, Oncology, and Gastroenterology, University of Padova, Padova, Italy
| | - Giulia Pasello
- Division of Medical Oncology 2, Veneto Institute of Oncology - IRCCS, Padova, Italy
- Department of Surgery, Oncology, and Gastroenterology, University of Padova, Padova, Italy
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Lei Y, Cao P, Zheng X, Wei J, Cheng M, Liu M. Perspectives for immunotherapy of EBV-associated GLELC: A relatively "hot" tumor microenvironment. Cancer Med 2023; 12:19838-19849. [PMID: 37732493 PMCID: PMC10587976 DOI: 10.1002/cam4.6555] [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: 07/21/2022] [Revised: 09/01/2023] [Accepted: 09/08/2023] [Indexed: 09/22/2023] Open
Abstract
BACKGROUND Epstein-Barr virus (EBV)-associated gastric lymphoepithelioma-like carcinoma (EBVaGLELC) represents a small number of gastric cancer (GC), and research on tumor microenvironment (TME) and treatment strategy are still lacking. AIMS Here, we aim to elucidate the immune features of this rare disease and further help to develop more effective treatment options. MATERIALS & METHODS A retrospective analysis was conducted between 2019 to 2022 in West China Hospital to reveal the immunological characteristics of EBV-positive GLELC. The difference of immune cell subset and tumor vascular structure between gastric denocarcinoma (GAC) and EBVaGLELC will be pointed out. DISCUSSION 13 patients with GELEC and 8 patients with GAC were retrospectively studied. The heterogeneity of the immune cell profile was then confirmed through multiplexed immunofluorescence staining (mIF), which revealed a higher proportion of CD3+ T cells, CD8+ T cells, and Treg cells in the EBV-associated GLELC group. Such a distinct TME may provide therapeutic advantages, and patients with this rare subtype of GC could be good candidates for immune checkpoint inhibitors (ICIs). Angiogenesis in EBV-positive GLELC may be less intense than that in gastric adenocarcinoma (GAC), a feature that might decrease their susceptibility to antiangiogenic therapy. Furthermore, we reported a 52-year-old male with advanced EBV-positive GLELC who showed a favorable response to the combined therapy with . A repeat evaluation showed sustained partial response (PR), and the progression-free survival (PFS) was more than 34 months until now. CONCLUSION Compared with GAC, EBVaGLELC revealed higher T cell infiltration and less intense of angiogenesis. It displays relatively "hot" TME that may provide the rationality to treat with immunotherapy in EBV-related GLELC.
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Affiliation(s)
- Yanna Lei
- Department of Gastric Cancer Center, West China HospitalSichuan UniversityChengduSichuanChina
- Department of Abdominal Oncology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Peng Cao
- Department of Abdominal Oncology, West China HospitalSichuan UniversityChengduSichuanChina
- Department of Colorectal Cancer Center, West China HospitalSichuan UniversityChengduSichuanChina
| | - Xiufeng Zheng
- Department of Gastric Cancer Center, West China HospitalSichuan UniversityChengduSichuanChina
- Department of Abdominal Oncology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Jing Wei
- Department of Gastric Cancer Center, West China HospitalSichuan UniversityChengduSichuanChina
- Department of Abdominal Oncology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Mo Cheng
- Department of Gastric Cancer Center, West China HospitalSichuan UniversityChengduSichuanChina
- Department of Abdominal Oncology, West China HospitalSichuan UniversityChengduSichuanChina
| | - Ming Liu
- Department of Gastric Cancer Center, West China HospitalSichuan UniversityChengduSichuanChina
- Department of Abdominal Oncology, West China HospitalSichuan UniversityChengduSichuanChina
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Zhang D, Lu B, Liang B, Li B, Wang Z, Gu M, Jia W, Pan Y. Interpretable deep learning survival predictive tool for small cell lung cancer. Front Oncol 2023; 13:1162181. [PMID: 37213271 PMCID: PMC10196231 DOI: 10.3389/fonc.2023.1162181] [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: 02/09/2023] [Accepted: 04/24/2023] [Indexed: 05/23/2023] Open
Abstract
Background Small cell lung cancer (SCLC) is an aggressive and almost universally lethal neoplasm. There is no accurate predictive method for its prognosis. Artificial intelligence deep learning may bring new hope. Methods By searching the Surveillance, Epidemiology, and End Results database (SEER), 21,093 patients' clinical data were eventually included. Data were then divided into two groups (train dataset/test dataset). The train dataset (diagnosed in 2010-2014, N = 17,296) was utilized to conduct a deep learning survival model, validated by itself and the test dataset (diagnosed in 2015, N = 3,797) in parallel. According to clinical experience, age, sex, tumor site, T, N, M stage (7th American Joint Committee on Cancer TNM stage), tumor size, surgery, chemotherapy, radiotherapy, and history of malignancy were chosen as predictive clinical features. The C-index was the main indicator to evaluate model performance. Results The predictive model had a 0.7181 C-index (95% confidence intervals, CIs, 0.7174-0.7187) in the train dataset and a 0.7208 C-index (95% CIs, 0.7202-0.7215) in the test dataset. These indicated that it had a reliable predictive value on OS for SCLC, so it was then packaged as a Windows software which is free for doctors, researchers, and patients to use. Conclusion The interpretable deep learning survival predictive tool for small cell lung cancer developed by this study had a reliable predictive value on their overall survival. More biomarkers may help improve the prognostic predictive performance of small cell lung cancer.
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Affiliation(s)
- Dongrui Zhang
- Department of Respiratory and Critical Care Medicine, Tianjin Chest Hospital, Tianjin, China
| | - Baohua Lu
- Department of Oncology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Bowen Liang
- Department of Traditional Chinese Medicine, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Bo Li
- Department of Traditional Chinese Medicine, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Ziyu Wang
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Meng Gu
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
| | - Wei Jia
- Department of Respiratory and Critical Care Medicine, Tianjin Chest Hospital, Tianjin, China
- *Correspondence: Yuanming Pan, ; Wei Jia,
| | - Yuanming Pan
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, China
- *Correspondence: Yuanming Pan, ; Wei Jia,
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Ferroptosis, necroptosis, and pyroptosis in the tumor microenvironment: Perspectives for immunotherapy of SCLC. Semin Cancer Biol 2022; 86:273-285. [PMID: 35288298 DOI: 10.1016/j.semcancer.2022.03.009] [Citation(s) in RCA: 112] [Impact Index Per Article: 56.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 03/07/2022] [Accepted: 03/09/2022] [Indexed: 01/27/2023]
Abstract
Small cell lung cancer (SCLC) is an aggressive form of lung cancer characterized by dismal prognosis. Although SCLC may initially respond well to platinum-based chemotherapy, it ultimately relapses and is almost universally resistant to this treatment. Immune checkpoint inhibitors (ICIs) have been approved as the first- and third-line therapeutic regimens for extensive-stage or relapsed SCLC, respectively. Despite this, only a minority of patients with SCLC respond to ICIs partly due to a lack of tumor-infiltrating lymphocytes (TILs). Transforming the immune "cold" tumors into "hot" tumors that are more likely to respond to ICIs is the main challenge for SCLC therapy. Ferroptosis, necroptosis, and pyroptosis represent the newly discovered immunogenic cell death (ICD) forms. Promoting ICD may alter the tumor microenvironment (TME) and the influx of TILs, and combination of their inducers and ICIs plays a synergistical role in enhancing antitumor effects. Nevertheless, the combination of the above two modalities has not been systematically discussed in SCLC therapy. In the present review, we summarize the roles of distinct ICD mechanisms on antitumor immunity and recent advances of ferroptosis-, necroptosis- and pyroptosis-inducing agents, and present perspectives on these cell death mechanisms in immunotherapy of SCLC.
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Zheng D, Xia K, Wei Z, Wei Z, Guo W. Identification of a novel gene signature with regard to ferroptosis, prognosis prediction, and immune microenvironment in osteosarcoma. Front Genet 2022; 13:944978. [PMID: 36330451 PMCID: PMC9623102 DOI: 10.3389/fgene.2022.944978] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 09/26/2022] [Indexed: 11/23/2022] Open
Abstract
Ferroptosis is a novel form of non-apoptotic cell death that mainly results from the iron-dependent lethal accumulation of lipid peroxidation products. Here, we defined differentially expressed genes between control and RSL3-treated osteosarcoma cells as ferroptosis-associated genes (FAGs). These FAGs were then subjected to weighted gene correlation network analysis (WGCNA), and we found that the turquoise module, containing 71 FAGs, was markedly related to the patient’s vital status. After that, FAGs in the turquoise module were utilized to construct a prognostic multigene (COL5A2, HOXB4, and UNC5B) signature for risk stratification in osteosarcoma. Validation in internal and external cohorts indicated the accuracy and clinical applicability of this signature in predicting the prognosis of patients with osteosarcoma. Univariate and multivariate Cox regression analyses suggested that the signature-derived risk score is an independent indicator of patient prognosis. Immunological analysis indicated that significant variations in stromal and ESTIMATE scores, as well as tumor purity, were found when the high- and low-risk groups were compared. Regarding immune cell infiltration, the proportion of activated CD4 memory T cells was significantly lower in the high-risk group than that in the low-risk group. The ssGSEA results suggested that CD8+ T, Tfh, and Th1 cell scores were consistently lower in the high-risk group than those in the low-risk group. In terms of immune-related activities, the high-risk group had considerably lower scores for promoting inflammation, T-cell co-inhibition, and T-cell co-stimulation than the low-risk group, indicating the differential immunological state of the high- and low-risk groups. Of the three FAGs included in the signature, the expression of COL5A2, HOXB4, and UNC5B was higher in the high-risk groups, and the expression of COL5A2 and UNC5B was negatively associated with patient prognosis. Additionally, the mRNA levels of COL5A2 and HOXB4 were lower and those of UNC5B were higher in RSL3-treated cells than in control cells. In all, we systematically analyzed the transcriptional changes of osteosarcoma cells induced by RSL3 and constructed a novel three-gene signature with regard to ferroptosis, prognosis prediction, and immune microenvironment. We also identified COL5A2, HOXB4, and UNC5B as potential therapeutic targets and important regulators of ferroptosis in osteosarcoma.
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Yin X, Liao H, Yun H, Lin N, Li S, Xiang Y, Ma X. Artificial intelligence-based prediction of clinical outcome in immunotherapy and targeted therapy of lung cancer. Semin Cancer Biol 2022; 86:146-159. [PMID: 35963564 DOI: 10.1016/j.semcancer.2022.08.002] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 08/06/2022] [Accepted: 08/08/2022] [Indexed: 11/26/2022]
Abstract
Lung cancer accounts for the main proportion of malignancy-related deaths and most patients are diagnosed at an advanced stage. Immunotherapy and targeted therapy have great advances in application in clinics to treat lung cancer patients, yet the efficacy is unstable. The response rate of these therapies varies among patients. Some biomarkers have been proposed to predict the outcomes of immunotherapy and targeted therapy, including programmed cell death-ligand 1 (PD-L1) expression and oncogene mutations. Nevertheless, the detection tests are invasive, time-consuming, and have high demands on tumor tissue. The predictive performance of conventional biomarkers is also unsatisfactory. Therefore, novel biomarkers are needed to effectively predict the outcomes of immunotherapy and targeted therapy. The application of artificial intelligence (AI) can be a possible solution, as it has several advantages. AI can help identify features that are unable to be used by humans and perform repetitive tasks. By combining AI methods with radiomics, pathology, genomics, transcriptomics, proteomics, and clinical data, the integrated model has shown predictive value in immunotherapy and targeted therapy, which significantly improves the precision treatment of lung cancer patients. Herein, we reviewed the application of AI in predicting the outcomes of immunotherapy and targeted therapy in lung cancer patients, and discussed the challenges and future directions in this field.
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Affiliation(s)
- Xiaomeng Yin
- Division of Biotherapy, Cancer Center, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China
| | - Hu Liao
- Department of Thoracic Surgery, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China
| | - Hong Yun
- Division of Biotherapy, Cancer Center, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China
| | - Nan Lin
- Division of Biotherapy, Cancer Center, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China
| | - Shen Li
- West China School of Medicine, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China
| | - Yu Xiang
- Division of Biotherapy, Cancer Center, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China
| | - Xuelei Ma
- Division of Biotherapy, Cancer Center, West China Hospital and State Key Laboratory of Biotherapy, Sichuan University, No. 37 GuoXue Alley, Chengdu 610041, China.
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12
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The Immunological Contribution of a Novel Metabolism-Related Signature to the Prognosis and Anti-Tumor Immunity in Cervical Cancer. Cancers (Basel) 2022; 14:cancers14102399. [PMID: 35626004 PMCID: PMC9139200 DOI: 10.3390/cancers14102399] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 02/04/2023] Open
Abstract
Cervical cancer is the most frequently diagnosed malignancy in the female reproductive system. Conventional stratification of patients based on clinicopathological characters has gradually been outpaced by a molecular profiling strategy. Our study aimed to identify a reliable metabolism-related predictive signature for the prognosis and anti-tumor immunity in cervical cancer. In this study, we extracted five metabolism-related hub genes, including ALOX12B, CA9, FAR2, F5 and TDO2, for the establishment of the risk score model. The Kaplan-Meier curve suggested that patients with a high-risk score apparently had a worse prognosis in the cervical cancer training cohort (TCGA, n = 304, p < 0.0001), validation cohort (GSE44001, n = 300, p = 0.0059) and pan-cancer cohorts (including nine TCGA tumors). Using a gene set enrichment analysis (GSEA), we observed that the model was correlated with various immune-regulation-related pathways. Furthermore, pan-cancer cohorts and immunohistochemical analysis showed that the infiltration of tumor infiltrating lymphocytes (TILs) was lower in the high-score group. Additionally, the model could also predict the prognosis of patients with cervical cancer based on the expression of immune checkpoints (ICPs) in both the discovery and validation cohorts. Our study established and validated a metabolism-related prognostic model, which might improve the accuracy of predicting the clinical outcome of patients with cervical cancer and provide guidance for personalized treatment.
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13
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Tang Y, Hu Y, Niu Y, Sun L, Guo L. CCL5 as a Prognostic Marker for Survival and an Indicator for Immune Checkpoint Therapies in Small Cell Lung Cancer. Front Med (Lausanne) 2022; 9:834725. [PMID: 35252266 PMCID: PMC8891515 DOI: 10.3389/fmed.2022.834725] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 01/20/2022] [Indexed: 11/13/2022] Open
Abstract
The standard treatment for small cell lung cancer (SCLC) has not changed in decades. Recently, important advances have been made in immunotherapy. However, analysis of these trials suggests that only a small proportion of patients benefit from immune checkpoint blockade (ICB). Identifying these patients is a clinical challenge. In this study, we applied the ESTIMATE calculation to calculate immune scores in 159 cases of SCLC from two published cohorts. COX regression analysis was used to analyze the differentially expressed genes (DEGs) with high and low immune score. We found that CCL5 expression was positively correlated with survival in SCLC patients. In addition, we verified the effect of CCL5 on survival and response to treatment in another cohort that received immunotherapy. Meanwhile, Gene set enrichment analysis (GSEA) showed that genes with high expression of CCL5 were mainly enriched in immune-related activities. The result of Tumor Immune Dysfunction and Exclusion (TIDE) demonstrated that CCL5 was a potential biomarker to predict response to ICB for SCLC, which is correspondent with the result in verified cohort. These results suggest that CCL5 may be the reason for TME to maintain its immune dominance, making it a favorable factor for ICB. Therefore, CCL5 levels may help to outline the prognosis of patients with SCLC.
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Affiliation(s)
- Yichun Tang
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yueyang Hu
- Department of Hepatobiliary Surgery, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Yuchun Niu
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Lei Sun
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Linlang Guo
- Department of Pathology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
- *Correspondence: Linlang Guo
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14
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Plaja A, Moran T, Carcereny E, Saigi M, Hernández A, Cucurull M, Domènech M. Small-Cell Lung Cancer Long-Term Survivor Patients: How to Find a Needle in a Haystack? Int J Mol Sci 2021; 22:ijms222413508. [PMID: 34948300 PMCID: PMC8707503 DOI: 10.3390/ijms222413508] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Revised: 12/09/2021] [Accepted: 12/13/2021] [Indexed: 12/28/2022] Open
Abstract
Small-cell lung cancer (SCLC) is an aggressive malignancy characterized by a rapid progression and a high resistance to treatments. Unlike other solid tumors, there has been a scarce improvement in emerging treatments and survival during the last years. A better understanding of SCLC biology has allowed for the establishment of a molecular classification based on four transcription factors, and certain therapeutic vulnerabilities have been proposed. The universal inactivation of TP53 and RB1, along with the absence of mutations in known targetable oncogenes, has hampered the development of targeted therapies. On the other hand, the immunosuppressive microenvironment makes the success of immune checkpoint inhibitors (ICIs), which have achieved a modest improvement in overall survival in patients with extensive disease, difficult. Currently, atezolizumab or durvalumab, in combination with platinum–etoposide chemotherapy, is the standard of care in first-line setting. However, the magnitude of the benefit is scarce and no predictive biomarkers of response have yet been established. In this review, we describe SCLC biology and molecular classification, examine the SCLC tumor microenvironment and the challenges of predictive biomarkers of response to new treatments, and, finally, assess clinical and molecular characteristics of long-term survivor patients in order to identify possible prognostic factors and treatment vulnerabilities.
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15
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Chen P, Wang H, Zhao L, Guo H, Zhang L, Zhang W, Sun C, Zhao S, Li W, Zhu J, Yu J, Wu C, He Y. Immune Checkpoints OX40 and OX40L in Small-Cell Lung Cancer: Predict Prognosis and Modulate Immune Microenvironment. Front Oncol 2021; 11:713853. [PMID: 34900670 PMCID: PMC8652148 DOI: 10.3389/fonc.2021.713853] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 08/04/2021] [Indexed: 12/24/2022] Open
Abstract
Background OX40 and OX40 ligand (OX40L), as essential immune checkpoint (IC) modulators, are highly correlated with cancer immunity regulation as well as tumor microenvironment (TME). Immunotherapy showed outstanding advantages in small-cell lung cancer (SCLC) therapy. However, functions and clinical significance of OX40 and OX40L in SCLC were not clear yet. Materials and Methods SCLC samples of 143 patients were collected for immunohistochemistry (IHC) or whole-exome sequencing (WES). We comprehensively explored the expression and mutation of OX40/OX40L in SCLC, and systematically linked OX40/OX40L with TME. Results The expression of OX40/OX40L on tumor cells and tumor-infiltrating lymphocytes (TILs) was found in the IHC cohort and verified in other cohorts with SCLC tissues and cell lines. The results showed co-expression patterns among OX40/OX40L, other ICs, and T-cell markers. The WES data suggested that OX40/OX40L mutation is rare in SCLC (<5%). Patients with positive OX40 protein expression on TILs showed substantially higher recurrence-free survival than those with negative expression (p=0.009). The external dataset also indicated that high OX40/OX40L expression was correlated with better prognosis [overall survival: OX40, p<0.001; OX40L, p=0.019]. Importantly, activation of immunity and high infiltration of CD4(+) and CD8(+) T cells were observed in the high OX40/OX40L expression group. Conclusions Collectively, this work highlighted the significance of OX40 and OX40L in prognosis and TME cell infiltration characterization of SCLC. Evaluating the OX40/OX40L-expression levels of individual patients with SCLC might contribute to guiding more precise therapy.
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Affiliation(s)
- Peixin Chen
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Hao Wang
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Lishu Zhao
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Haoyue Guo
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Liping Zhang
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Wei Zhang
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Chenglong Sun
- School of Medicine, Tongji University, Shanghai, China.,Anhui No. 2 Provincial People's Hospital, Hefei, China
| | - Sha Zhao
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wei Li
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Jun Zhu
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Jia Yu
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Chunyan Wu
- Department of Pathology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Yayi He
- School of Medicine, Tongji University, Shanghai, China.,Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China
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16
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Sun H, Dai J, Zhao L, Zhu J, Wang H, Chen P, Lu H, Chen Q, Zhang Z. Lymphocyte activation gene-3 is associated with programmed death-ligand 1 and programmed cell death protein 1 in small cell lung cancer. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1468. [PMID: 34734020 PMCID: PMC8506769 DOI: 10.21037/atm-21-4481] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 09/10/2021] [Indexed: 12/12/2022]
Abstract
Background In recent years, immunotherapy has achieved notable success in cancer treatment. Indeed, the novel immune checkpoint lymphocyte activation gene-3 (LAG3) has shown promising therapeutic efficacy in non-small cell lung cancer. However, it is unclear about the role of LAG3 in immunotherapy and survival in small cell lung cancer (SCLC). Methods The expression of LAG3 in SCLC was evaluated in four public datasets. The association of LAG3 with programmed death-ligand 1 (PD-L1), programmed cell death protein 1 (PD-1), and overall survival (OS) was investigated. The LAG3-related biological processes and pathways were identified by functional analyses. Results LAG3 expression was detected in SCLC tumor tissues. In the cBioPortal dataset with 81 clinical SCLC samples, LAG3 expression was markedly associated with PD-1 and PD-L1 expression (both P<0.050). In addition, Patients with high LAG3 expression had a trend toward a better OS (P=0.073). A similar survival trend was also observed in the GSE60052 dataset. Significantly, LAG3 expression was related to immune-related biological processes, such as immune response, antigen processing and presentation, and T cell co-stimulation (all P<0.001). Conclusions This study demonstrated that LAG3 is an important immune checkpoint that is closely associated with PD-1/PD-L1. LAG3 may be a promising novel immunotherapy target for SCLC.
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Affiliation(s)
- Hui Sun
- Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.,School of Medicine, Tongji University, Shanghai, China
| | - Jiawei Dai
- SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Lishu Zhao
- Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.,School of Medicine, Tongji University, Shanghai, China
| | - Jun Zhu
- Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.,School of Medicine, Tongji University, Shanghai, China
| | - Hao Wang
- Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.,School of Medicine, Tongji University, Shanghai, China
| | - Peixin Chen
- Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.,School of Medicine, Tongji University, Shanghai, China
| | - Hui Lu
- SJTU-Yale Joint Center for Biostatistics and Data Science, Department of Bioinformatics and Biostatistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China
| | - Qiankun Chen
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Zhemin Zhang
- Department of Medical Oncology, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.,School of Medicine, Tongji University, Shanghai, China
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17
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What Are the Biomarkers for Immunotherapy in SCLC? Int J Mol Sci 2021; 22:ijms222011123. [PMID: 34681779 PMCID: PMC8538776 DOI: 10.3390/ijms222011123] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 10/12/2021] [Accepted: 10/12/2021] [Indexed: 12/15/2022] Open
Abstract
Small-cell lung cancer (SCLC) is an aggressive malignancy that exhibits a rapid doubling time, a high growth fraction, and the early development of widespread metastases. The addition of immune checkpoint inhibitors to first-line chemotherapy represents the first significant improvement of systemic therapy in several decades. However, in contrast to its effects on non-SCLC, the advantageous effects of immunotherapy addition are modest in SCLC. In particular, only a small number of SCLC patients benefit from immune checkpoint inhibitors. Additionally, biomarkers selection is lacking for SCLC, with clinical trials largely focusing on unselected populations. Here, we review the data concerning the major biomarkers for immunotherapy, namely, programmed death ligand 1 expression and tumour mutational burden. Furthermore, we explore other potential biomarkers, including the role of the immune microenvironment in SCLC, the role of genetic alterations, and the potential links between neurological paraneoplastic syndromes, serum anti-neuronal nuclear antibodies, and outcomes in SCLC patients treated with immunotherapy.
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