Exploring the role of TIGIT in patients with Small Cell Lung Cancer as a novel predictor of prognosis and immunotherapy response

Cancer Immunology, Immunotherapy (2025) 74:134 https://doi.org/10.1007/s00262-025-03985-6 RESEARCH Exploring the role of TIGIT in patients with Small Cell Lung Cancer as a novel predictor of prognosis and immunotherapy response Li Liu1 · Peng Wu2 · Bingzhi Wang1 · Jiyan Dong1 · Chaoqi Zhang2 · Wenchao Liu1 · Jianming Ying1 Received: 11 September 2024 / Accepted: 17 February 2025 / Published online: 4 March 2025 © The Author(s) 2025 Abstract Background T-cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains (TIGIT) is a novel immune checkpoint playing a crucial role in immunosuppression and immune evasion. This study aims to elucidate the expression patterns, characteristics, and possible mechanisms of TIGIT in small cell lung cancer (SCLC). Methods TIGIT expression was analyzed across various cancers and normal tissues using The Cancer Genome Atlas (TCGA). Transcriptomic data from SCLC patients, sourced from the Gene Expression Omnibus (GEO) and literature, were analyzed to assess TIGIT-related characteristics. Immunohistochemistry (IHC) was used to verify TIGIT expression in post-surgical and advanced SCLC samples, focusing on expression characteristics, prognostic value, and treatment response. Results TIGIT was significantly overexpressed in various tumors, including SCLC (p < 0.05). Higher expression was associated with better overall survival (OS) (p < 0.05). Notably, a significant positive correlation was observed between TIGIT expression and immune-related metagenes, such as HCK, interferon, and LCK (p < 0.05). Immune infiltration analysis revealed a strong positive correlation between TIGIT expression and immune score in multiple cohorts. Additionally, TIGIT expression correlated positively with immune cells, including CD8 T cells, cytotoxic lymphocytes, and B cells (p < 0.05), and multiple immune checkpoints like BTLA, ICOS, and LAG3 (p < 0.05), while it had a significant negative correlation with the TIDE score (p < 0.05). In the validation section, patients with high TIGIT expression showed significantly prolonged disease-free survival (DFS) and OS (p < 0.05), and demonstrated a better response to adjuvant chemotherapy (ACT) and immunotherapy. Conclusion TIGIT serves as a biomarker in SCLC, with its high expression indicating favorable prognosis and treatment response. These effects may be due to TIGIT’s unique immune landscape and its association with other immune checkpoints. Keywords Small cell lung cancer · TIGIT · Prognosis · Immunotherapy · PD-L1/PD-1 · Checkpoint Introduction Lung cancer remains the most prevalent cancer globally and in China, leading in both incidence and mortality [1, 2]. SCLC, a neuroendocrine (NE) tumor originating in the * Jianming Ying 1 Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China 2 Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China bronchial epithelium, accounts for 15% of lung cancer cases and is considered the most aggressive type [3]. While significant advancements have been made in treating non-small cell lung cancer (NSCLC) through moleculartargeted therapies and immunotherapy [4], SCLC treatment has stagnated. Standard chemotherapy and radiotherapy have remained largely unchanged for decades, with limited effectiveness. Most SCLC patients relapse or develop drug resistance after initial treatment, and second-line therapies, such as topotecan, offer poor efficacy (15% ~ 20%) [5]. This underscores the urgent need for new therapeutic strategies. Recent progress in immunotherapy has made it a standard first-line treatment for extensive stage-SCLC (ES-SCLC) [6]. Although data on immunotherapy for limited stageSCLC (LS-SCLC) is lacking, ongoing trials like KEYLYNK-013 are evaluating its potential [7]. Vol.:(0123456789) 134 Page 2 of 15 Currently, there are no formal therapies targeting genes with high mutational rates. Furthermore, the mutation rate of potentially targetable gene loci within the SCLC patient population remains notably low [6, 8, 9]. This highlights the need to identify novel biomarkers to predict survival outcomes and treatment responses, thus optimizing existing therapies. TIGIT, a novel immune checkpoint, is highly expressed in tumor-infiltrating lymphocytes (TILs) including CD8, CD4, regulatory T cells, and natural killer (NK) cells [10, 11]. Studies suggest a correlation between TIGIT expression and factors such as tumor stage, survival rate, and TIL composition in various malignant tumors [12–14]. In NSCLC, high TIGIT levels are linked to worse prognosis [13, 15], but its role in SCLC remains underexplored. Current literature indicates no significant correlation between TIGIT expression and survival in SCLC, necessitating further research [16]. This study analyzed 223 SCLC specimens from three cohorts, including two public datasets and one independent cohort, to evaluate TIGIT’s impact on prognosis, immune characteristics, clinicopathological features, and responses to chemotherapy and immunotherapy. Materials and methods Publicly available mRNA datasets We collected the pan-cancer dataset from the cancer genomics browser of the University of California Santa Cruz (UCSC) Xena (https://xenabrowser.net/datapages/). This dataset includes RNA-seq data from 18,102 tumor and normal tissue samples across 33 cancer types. The RNA-seq data were uniformly processed using the Toil pipeline, with the formula log2(tpm + 1) applied for analysis. The dataset was utilized for pan-cancer analysis of TIGIT mRNA expression, excluding SCLC. Additionally, two datasets from the GEO database (http://www.ncbi.nlm.nih.gov/ geo), GSE60052 (47 LS-SCLC and 7 normal controls) and GSE149507 (18 paired samples), were analyzed to assess TIGIT mRNA expression differences between SCLC and normal tissues. Further detailed analysis incorporated 68 LS-SCLC samples from the Nature cohort [8]. Supplementary Table 1 provides additional details. Patient cohorts and tissue sampling The National Cancer Centre (NCC) cohort included 108 formalin-fixed paraffin-embedded (FFPE) SCLC samples collected at the National Cancer Centre of China from January 2017 to August 2021. Clinical features were derived from the medical record system, and pathological specifics were extracted from pathology reports and confirmed by Cancer Immunology, Immunotherapy (2025) 74:134 two pathologists (LL and JD) according to the 2021 WHO classification of lung tumors [17]. The 8th edition of the TNM classification was used to determine the stage and prognosis [18]. All patients had primary tumors and had not received preoperative radiotherapy, chemotherapy or any other tumor-related treatments. Addition (...truncated)