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Zhao X, Cui H, Zhou M, Ren X, Li Z, Liu P, Zhao D, Lin S, Kang H. A novel glycogene-related signature for prognostic prediction and immune microenvironment assessment in kidney renal clear cell carcinoma. Ann Med 2025; 57:2495762. [PMID: 40329678 PMCID: PMC12064129 DOI: 10.1080/07853890.2025.2495762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2024] [Revised: 03/25/2025] [Accepted: 03/28/2025] [Indexed: 05/08/2025] Open
Abstract
BACKGROUND Kidney Renal Clear Cell Carcinoma (KIRC) is a prevalent urinary malignancies worldwide. Glycosylation is a key post-translational modification that is essential in cancer progression. However, its relationship with prognosis, tumour microenvironment (TME), and treatment response in KIRC remains unclear. METHOD Expression profiles and clinical data were retrieved from The Cancer Genome Atlas and Gene Expression Omnibus databases. Consensus clustering, Cox regression, and LASSO regression analyses were conducted to develop an optimal glycogene-related signature. The prognostic relevance of this molecular signature was rigorously analyzed, along with its connections to tumour microenvironment (TME), tumour mutation burden, immune checkpoint activity, cancer-immunity cycle regulation, immunomodulatory gene expression patterns, and therapeutic response profiles. Validation was performed using real-world clinical specimens, quantitative PCR (qPCR), and immunohistochemistry (IHC), supported by cohort analyses from the Human Protein Atlas (HPA) database. RESULTS A glycogene-associated prognostic scoring system was established to categorize patients into risk-stratified subgroups. Patients in the high-risk cohort exhibited significantly poorer survival outcomes (p < 0.001). By incorporating clinicopathological variables into this framework, we established a predictive nomogram demonstrating strong calibration and a concordance index (C-index) of 0.78. The high-risk subgroup displayed elevated immune infiltration scores (p < 0.001), upregulated expression of immune checkpoint-related genes (p < 0.05), and an increased frequency of somatic mutations (p = 0.043). The risk score positively correlated with cancer-immunity cycle activation and immunotherapy-related signals. The high-risk groups also showed associations with T cell exhaustion, immune-activating genes, chemokines, and receptors. Drug sensitivity analysis revealed that low-risk patients were more sensitive to sorafenib, pazopanib, and erlotinib, whereas high-risk individuals responded better to temsirolimus (p < 0.01). qPCR and IHC analyses consistently revealed distinct expression patterns of MX2 and other key genes across the risk groups, further corroborated by the HPA findings. CONCLUSION This glycogene-based signature provides a robust tool for predicting prognosis, TME characteristics, and therapeutic responses in KIRC, offering potential clinical utility in patient management.
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Affiliation(s)
- Xuyan Zhao
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Hanxiao Cui
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Mingjing Zhou
- Department of Neurosurgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Xueting Ren
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Zihao Li
- Department of Urology, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Peinan Liu
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Danni Zhao
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Shuai Lin
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
| | - Huafeng Kang
- The Comprehensive Breast Care Center, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, Shaanxi, China
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Wu Z, Zhang J, Li L, Wang Z, Yang C. Biomarkers in metastatic castration-resistant prostate cancer for efficiency of immune checkpoint inhibitors. Ann Med 2025; 57:2426755. [PMID: 39895499 PMCID: PMC11792157 DOI: 10.1080/07853890.2024.2426755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2023] [Revised: 03/29/2024] [Accepted: 09/05/2024] [Indexed: 02/04/2025] Open
Abstract
Almost all patients with prostate cancer progress to metastatic castration-resistant prostate cancer (mCRPC) despite initial responses. In cases where traditional first-line treatments prove ineffective, the potential of immune checkpoint blockade (ICB) therapy emerges as a promising approach for managing mCRPC. However, while immune checkpoint inhibitor monotherapy or combination therapy targeting cytotoxic T lymphocyte antigen 4 (CTLA-4) and/or programmed cell death-1 (PD-1)/PD-1 ligand 1 (PD-L1) axis has been regarded as the standard therapy in many solid tumours, mCRPC as 'cold' tumours are considered to be relatively resistant to ICB treatment. Encouragingly, recent evidence suggests that ICB therapy may be particularly beneficial in specific subgroups of patients with high PD-L1 tumour expression, high tumour mutational burden or high tumour microsatellite instability/mismatch repair deficiency. Better understanding of these predictive biomarkers could screen which patients are most likely to benefit. This review article examines biomarkers for screening patients potentially effective in immune checkpoint inhibitor therapy.
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Affiliation(s)
- Zixi Wu
- Department of Urology, Tongji Hospital Affiliated Tongji Medical College of Huazhong University of Science and Technology (HUST), Wuhan, China
- Huangshi Hubei Medical Group of Maternal and Child Health Hospital, Hubei, China
| | - Junbiao Zhang
- Department of Urology, Tongji Hospital Affiliated Tongji Medical College of Huazhong University of Science and Technology (HUST), Wuhan, China
- Huangshi Hubei Medical Group of Maternal and Child Health Hospital, Hubei, China
| | - Le Li
- Department of Urology, Tongji Hospital Affiliated Tongji Medical College of Huazhong University of Science and Technology (HUST), Wuhan, China
- Huangshi Hubei Medical Group of Maternal and Child Health Hospital, Hubei, China
| | - Zhihua Wang
- Department of Urology, Tongji Hospital Affiliated Tongji Medical College of Huazhong University of Science and Technology (HUST), Wuhan, China
- Huangshi Hubei Medical Group of Maternal and Child Health Hospital, Hubei, China
| | - Chunguang Yang
- Department of Urology, Tongji Hospital Affiliated Tongji Medical College of Huazhong University of Science and Technology (HUST), Wuhan, China
- Huangshi Hubei Medical Group of Maternal and Child Health Hospital, Hubei, China
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Ye D, Zhang Z, Yao Y, Pan B, Wu H, Zhang X, Wang X, Tang N. Neurogranin facilitates maintaining the immunosuppressive state of hepatocellular carcinoma by promoting TGF-β1 secretion. Int J Biol Macromol 2025; 311:143716. [PMID: 40316076 DOI: 10.1016/j.ijbiomac.2025.143716] [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: 01/25/2025] [Revised: 04/27/2025] [Accepted: 04/29/2025] [Indexed: 05/04/2025]
Abstract
Immunotherapy has revolutionized cancer treatment, but its effectiveness is limited due to the complexity of the tumor immune microenvironment. Identifying reliable biomarkers that can predict immunotherapy response is essential for enhancing treatment strategies. This study evaluated the potential of Neurogranin (NRGN) as a biomarker for prognosis and immunotherapy response across multiple cancers. Through pan-cancer bioinformatics analyses, coupled with in vitro and in vivo experiments, we explored NRGN's differential expression across various cancer types and its role in the immune microenvironment. Our approach involved database mining, immune genomic feature correlation analyses, and functional validation through NRGN knockdown and overexpression studies. The results revealed differential NRGN expression across cancers, particularly hepatocellular carcinoma (HCC), where elevated levels correlated with immune evasion, poor prognosis, and upregulation of checkpoint genes like TGFB1. NRGN modulated T cell activity and macrophage polarization by regulating the TGF-β pathway through interaction with TCF4 and promoting its nuclear localization, driving tumor progression. Targeting TGF-β with anti-TGF-β and anti-PD-1 antibodies additively inhibited HCC in an Nrgn-dependent manner in mice. These findings indicate that NRGN may serve as a promising immunotherapeutic target, as its overexpression predicts poor prognosis and immune evasion, thereby offering insights for improving immunotherapy and developing new treatments.
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Affiliation(s)
- Dongjie Ye
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Zhu Zhang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yuxin Yao
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Banglun Pan
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Hao Wu
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xinyu Zhang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiaoqian Wang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Cancer Center of Fujian Medical University, Fujian Medical University Union Hospital, Fuzhou, China
| | - Nanhong Tang
- Department of Hepatobiliary Surgery and Fujian Institute of Hepatobiliary Surgery, Fujian Medical University Union Hospital, Fuzhou, China; Cancer Center of Fujian Medical University, Fujian Medical University Union Hospital, Fuzhou, China; Key Laboratory of Clinical Laboratory Technology for Precision Medicine (Fujian Medical University), Fujian Province University, Fuzhou, China; Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, Fuzhou, China.
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Gou M, Zhang H, Qian N, Zhang Y, Sun Z, Li G, Wang Z, Dai G. Deep learning radiomics analysis for prediction of survival in patients with unresectable gastric cancer receiving immunotherapy. Eur J Radiol Open 2025; 14:100626. [PMID: 39807092 PMCID: PMC11728962 DOI: 10.1016/j.ejro.2024.100626] [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: 10/28/2024] [Revised: 12/03/2024] [Accepted: 12/14/2024] [Indexed: 01/16/2025] Open
Abstract
Objective Immunotherapy has become an option for the first-line therapy of advanced gastric cancer (GC), with improved survival. Our study aimed to investigate unresectable GC from an imaging perspective combined with clinicopathological variables to identify patients who were most likely to benefit from immunotherapy. Method Patients with unresectable GC who were consecutively treated with immunotherapy at two different medical centers of Chinese PLA General Hospital were included and divided into the training and validation cohorts, respectively. A deep learning neural network, using a multimodal ensemble approach based on CT imaging data before immunotherapy, was trained in the training cohort to predict survival, and an internal validation cohort was constructed to select the optimal ensemble model. Data from another cohort were used for external validation. The area under the receiver operating characteristic curve was analyzed to evaluate performance in predicting survival. Detailed clinicopathological data and peripheral blood prior to immunotherapy were collected for each patient. Univariate and multivariable logistic regression analysis of imaging models and clinicopathological variables was also applied to identify the independent predictors of survival. A nomogram based on multivariable logistic regression was constructed. Result A total of 79 GC patients in the training cohort and 97 patients in the external validation cohort were enrolled in this study. A multi-model ensemble approach was applied to train a model to predict the 1-year survival of GC patients. Compared to individual models, the ensemble model showed improvement in performance metrics in both the internal and external validation cohorts. There was a significant difference in overall survival (OS) among patients with different imaging models based on the optimum cutoff score of 0.5 (HR = 0.20, 95 % CI: 0.10-0.37, P < 0.001). Multivariate Cox regression analysis revealed that the imaging models, PD-L1 expression, and lung immune prognostic index were independent prognostic factors for OS. We combined these variables and built a nomogram. The calibration curves showed that the C-index of the nomogram was 0.85 and 0.78 in the training and validation cohorts. Conclusion The deep learning model in combination with several clinical factors showed predictive value for survival in patients with unresectable GC receiving immunotherapy.
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Affiliation(s)
- Miaomiao Gou
- Department of Medical Oncology, The Fifth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, PR China
| | - Hongtao Zhang
- Department of Medical Oncology, The Fifth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, PR China
| | - Niansong Qian
- Department of Thoracic Oncology, The Eighth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, PR China
| | - Yong Zhang
- Department of Medical Oncology, The Second Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, PR China
| | - Zeyu Sun
- R&D Center, Keya Medical Technology Co., Ltd, Beijing, PR China
| | - Guang Li
- R&D Center, Keya Medical Technology Co., Ltd, Beijing, PR China
| | - Zhikuan Wang
- Department of Medical Oncology, The Fifth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, PR China
| | - Guanghai Dai
- Department of Medical Oncology, The Fifth Medical Center, Chinese People’s Liberation Army General Hospital, Beijing, PR China
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Ding Y, Ye Z, Ding B, Feng S, Zhang Y, Shen Y. Identification of CXCL13 as a Promising Biomarker for Immune Checkpoint Blockade Therapy and PARP Inhibitor Therapy in Ovarian Cancer. Mol Biotechnol 2025; 67:2428-2442. [PMID: 38856873 DOI: 10.1007/s12033-024-01207-5] [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: 02/13/2024] [Accepted: 05/27/2024] [Indexed: 06/11/2024]
Abstract
Ovarian cancer has poor response rates to immune checkpoint blockade (ICB) therapy, despite the use of genomic sequencing to identify molecular targets. Homologous recombination deficiency (HRD) is a conventional indicator of genomic instability (GI) and has been used as a marker for targeted therapies. Indicators reflecting HRD status have shown potential in predicting the efficacy of ICB treatment. Public databases, including TCGA, ICGC, and GEO, were used to obtain data. HRD scores, neoantigen load, and TMB were obtained from the TCGA cohort. Candidate biomarkers were validated in multiple databases, such as the Imvigor210 immunotherapy cohort and the open-source single-cell sequencing database. Immunohistochemistry was performed to further validate the results in independent cohorts. CXCL10, CXCL11, and CXCL13 were found to be significantly upregulated in HRD tumors and exhibited prognostic value. A comprehensive analysis of the tumor immune microenvironment (TIME) revealed that CXCL13 expression positively correlated with neoantigen load and immune cell infiltration. In addition, single-cell sequencing data and clinical trial results supported the utility of CXCL13 as a biomarker for ICB therapy. Not only does CXCL13 serve as a biomarker reflecting HRD status, but it also introduces a potentially novel perspective on prognostic biomarkers for ICB in ovarian cancer.
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Affiliation(s)
- Yue Ding
- Department of Obstetrics and Gynaecology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, China
| | - Zheng Ye
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 210096, China
| | - Bo Ding
- Department of Obstetrics and Gynaecology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, China
| | - Songwei Feng
- Department of Obstetrics and Gynaecology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, China
| | - Yang Zhang
- Department of Obstetrics and Gynecology, First People's Hospital of Lianyungang, No. 6 East Zhenhua Road, Haizhou, Lianyungang, China.
| | - Yang Shen
- Department of Obstetrics and Gynaecology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, 210009, China.
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Ran R, Chen X, Yang J, Xu B. Immunotherapy in breast cancer: current landscape and emerging trends. Exp Hematol Oncol 2025; 14:77. [PMID: 40405250 PMCID: PMC12096519 DOI: 10.1186/s40164-025-00667-y] [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: 03/04/2025] [Accepted: 05/08/2025] [Indexed: 05/24/2025] Open
Abstract
Breast cancer remains one of the most prevalent malignancies worldwide, underscoring an urgent need for innovative therapeutic strategies. Immunotherapy has emerged as a transformative frontier in this context. In triple-negative breast cancer (TNBC), the combination of immunotherapy based on PD-1/PD-L1 immune checkpoint inhibitors (ICIs) with chemotherapy has proven efficacious in both early and advanced clinical trials. These encouraging results have led to the approval of ICIs for TNBC, opening up new therapeutic avenues for challenging-to-treat patient populations. Furthermore, a multitude of ongoing trials are actively investigating the efficacy of immunotherapy-based combinations, including ICIs in conjunction with chemotherapy, targeted therapy and radiation therapy, as well as other novel strategies such as bispecific antibodies, CAR-T cells and cancer vaccines across all breast cancer subtypes, including HR-positive/HER2-negative and HER2-positive disease. This review provides a comprehensive overview of current immunotherapeutic approaches in breast cancer, highlighting pivotal findings from recent clinical trials and the potential impact of these advancements on patient outcomes.
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Affiliation(s)
- Ran Ran
- Cancer Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xi Chen
- Cancer Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jin Yang
- Cancer Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| | - Binghe Xu
- Cancer Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
- National Cancer Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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7
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Cen S, Li Y, Xiong X, Ma Z, Wang Y, Gao X. Comprehensive analysis Neddylation-related genes identified UBB as a prognostic biomarker for clear cell renal cell carcinoma. Discov Oncol 2025; 16:859. [PMID: 40402349 PMCID: PMC12098231 DOI: 10.1007/s12672-025-02547-7] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2024] [Accepted: 05/02/2025] [Indexed: 05/23/2025] Open
Abstract
Neddylation, as a type of post-translational modification, plays a key role in cancer development. However, the biological characteristics and clinical prognosis value of Neddylation-related genes (NRGs) signatures in clear cell renal cell carcinoma (ccRCC) remain undetermined. Here, we identified two subtypes of NRGs in ccRCC based on TCGA data and constructed a NRGs risk signature (NRGS). Survival analysis, ROC curves, and nomograms showed that NRGS was an important predictor of prognosis in patients with clear cell renal cell carcinoma. We further revealed important correlations between NRGS and clinicopathological features, gene mutations, drug sensitivity, and immune cell infiltration. High NRGS indicates a poorer prognosis for kidney cancer, but higher remission rates with immunotherapy. Drug sensitivity also varies across risk groups. UBB was identified as a hub gene for NRGS and was downregulated in ccRCC, which is associated with poor prognosis. In conclusion, this study provides strategies for predicting prognosis and individualizing treatment for ccRCC.
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Affiliation(s)
- Shengren Cen
- Guangdong Provincial Key Laboratory of Urological Diseases, Guangzhou Institute of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Yingpeng Li
- Guangdong Provincial Key Laboratory of Urological Diseases, Guangzhou Institute of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Xinhao Xiong
- Guangdong Provincial Key Laboratory of Urological Diseases, Guangzhou Institute of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Zihong Ma
- Guangdong Provincial Key Laboratory of Urological Diseases, Guangzhou Institute of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Yongsheng Wang
- Guangdong Provincial Key Laboratory of Urological Diseases, Guangzhou Institute of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China
| | - Xingcheng Gao
- Guangdong Provincial Key Laboratory of Urological Diseases, Guangzhou Institute of Urology, Department of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510230, Guangdong, China.
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Ziogas DC, Foteinou D, Theocharopoulos C, Martinos A, Petsiou DP, Anastasopoulou A, Gogas H. State-of-the-art in Metastatic Uveal Melanoma Treatment: A 2025 Update : How to treat Metastatic Uveal Melanoma in 2025. Curr Oncol Rep 2025:10.1007/s11912-025-01684-0. [PMID: 40380030 DOI: 10.1007/s11912-025-01684-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/28/2025] [Indexed: 05/19/2025]
Abstract
PURPOSE OF REVIEW Uveal melanoma (UM) is the most common intraocular malignancy in adults, representing a rare but aggressive melanoma subtype with a distinct molecular landscape, unique metastatic behavior and limited therapeutic options in the metastatic setting. This review provides an in-depth analysis of the latest evidence on the evolving treatment landscape of metastatic UM. RECENT FINDINGS For liver-only metastatic disease, locoregional therapies provide significant benefit compared to systemic therapies. The recent approval of tebentafusp-tebn, a bispecific gp100 peptide-HLA-directed CD3 T-cell engager, marks a pivotal advancement for HLA-A*02:01-positive patients with unresectable/metastatic UM, demonstrating a clinically significant survival benefit. Several clinical studies are currently active, examining emerging locoregional and systemic treatments for metastatic UM, with promising early data. Despite effective local disease control through radiotherapy and enucleation, approximately 50% of patients develop metastatic disease, predominantly in the liver, with a median survival of less than one year. The approval of tebentafusp represents a landmark achievement in UM treatment, while promising experimental combinations have demonstrated clinical utility in late phase clinical trials, offering hope for further improvement in patient survival.
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Affiliation(s)
- Dimitrios C Ziogas
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece.
| | - Dimitra Foteinou
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Charalampos Theocharopoulos
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Anastasios Martinos
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Dioni-Pinelopi Petsiou
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Amalia Anastasopoulou
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - Helen Gogas
- First Department of Medicine, School of Medicine, National and Kapodistrian University of Athens, Athens, Greece
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Nagano Y, Takahashi M, Sumi T, Yokoo K, Ishikawa T, Honjo O, Kudo S, Kondo S, Tanaka Y, Shioya M, Hashimoto M, Otsuka M, Sudo Y, Yanagi M, Yabe H, Nishikiori H, Yamazoe M, Asai Y, Fukataki Y, Hinotsu S, Chiba H. Efficacy of nivolumab + ipilimumab ± chemotherapy versus pembrolizumab + chemotherapy in patients with PD-L1-negative non-small cell lung cancer (START001 PART-B): a multicenter retrospective observational study. Jpn J Clin Oncol 2025:hyaf073. [PMID: 40333938 DOI: 10.1093/jjco/hyaf073] [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: 01/24/2025] [Accepted: 04/17/2025] [Indexed: 05/09/2025] Open
Abstract
BACKGROUND Programmed death ligand 1 (PD-L1) serves as a crucial biomarker for predicting the efficacy of immune checkpoint inhibitors in patients with non-small cell lung cancer (NSCLC). This study aimed to identify the most suitable first-line treatment regimen for patients with PD-L1 expression <1% (PD-L1-negative) NSCLC by comparing nivolumab plus ipilimumab (NI), NI combined with chemotherapy (NICT), and pembrolizumab and chemotherapy (PCT). METHODS We analyzed data from 141 patients with PD-L1-negative NSCLC treated with NI, NICT, or PCT at 14 Japanese institutions between December 2020 and November 2022. Propensity score analysis was employed to minimize selection bias, and Kaplan-Meier analysis and Cox proportional hazards regression were used to evaluate progression-free survival (PFS) and overall survival (OS). RESULTS Neither NI nor NICT demonstrated superior PFS or OS than PCT. Subgroup analyses revealed no significant differences between treatment groups across age, histological subtypes, or clinical features. Results from propensity score matching and inverse probability of treatment weighting were consistent with those observed in the overall cohort. Moreover, safety profiles showed that PCT was associated with the lowest rates of treatment discontinuation and immune-related adverse events requiring systemic corticosteroid therapy. CONCLUSIONS In patients with PD-L1-negative NSCLC, the efficacy of NI and NICT was not superior to that of PCT. Thus, we concluded that PCT could be a favorable treatment option for this patient population.
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Affiliation(s)
- Yutaro Nagano
- Department of Respiratory Medicine, Otaru General Hospital, 1-1-1 Wakamatsu, Otaru, Hokkaido 047-0017, Japan
- Department of Respiratory Medicine, Hakodate Municipal Hospital, 1-10-1 Minato-cho, Hakodate, Hokkaido 041-0821, Japan
| | - Mamoru Takahashi
- Department of Respiratory Medicine and Allergology, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkaido 060-8543, Japan
| | - Toshiyuki Sumi
- Department of Respiratory Medicine, Hakodate Goryoukaku Hospital, 38-3 Goryokaku-cho, Hakodate, Hokkaido 041-8611, Japan
| | - Keiki Yokoo
- Department of Respiratory Medicine, Teine Keijinkai Hospital, 1-40 Maeda 1-jo 12-chome, Teine-ku, Sapporo, Hokkaido 006-0811, Japan
| | - Tatsuru Ishikawa
- Department of Respiratory Medicine and Allergology, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkaido 060-8543, Japan
| | - Osamu Honjo
- Department of Respiratory Medicine, Sapporo Minami-Sanjo Hospital, 4-2 Minami 3-jo Nishi 6-chome, Chuo-ku, Sapporo, Hokkaido 060-0063, Japan
| | - Sayaka Kudo
- Department of Respiratory Medicine, Kushiro City General Hospital, 1-12 Shunkodai, Kushiro, Hokkaido 085-0822, Japan
| | - Shun Kondo
- Department of Respiratory Medicine, Steel Memorial Muroran Hospital, 45 Chiribetsu-cho 1-chome, Muroran, Hokkaido 050-0076, Japan
| | - Yusuke Tanaka
- Department of Respiratory Medicine and Allergology, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkaido 060-8543, Japan
- Department of Respiratory Medicine, 3-8 Kita 4-jo Nishi 7-chome, Chuo-ku, Tonan Hospital, Sapporo, Hokkaido 060-0004, Japan
| | - Makoto Shioya
- Department of Respiratory Medicine, Otaru General Hospital, 1-1-1 Wakamatsu, Otaru, Hokkaido 047-0017, Japan
| | - Midori Hashimoto
- Department of Respiratory Medicine, NTT-East Corporation Sapporo Medical Center, Minami 1-jo Nishi 15-chome, Chuo-ku, Sapporo, Hokkaido 060-0062, Japan
| | - Mitsuo Otsuka
- Department of Respiratory Medicine, Hokkaido P.W.F.A.C Sapporo-Kosei Hospital, 5 Kita 3-jo Higashi 8-chome, Chuo-ku, Sapporo, Hokkaido 060-0033, Japan
| | - Yuta Sudo
- Department of Respiratory Medicine, Japanese Red Cross Asahikawa Hospital, 1-1 Akebono 1-jo 1-chome, Asahikawa, Hokkaido 070-0061, Japan
| | - Masahiro Yanagi
- Department of Respiratory Medicine, Muroran City General Hospital, 8-1 Yamate-cho 3-chome, Muroran, Hokkaido 051-0012, Japan
| | - Hayato Yabe
- Department of Respiratory Medicine, Japan Community Healthcare Organization Sapporo Hokushin Hospital, 2-1 Atsubetsu Chuo 2-jo 6-chome, Atsubetsu-ku, Sapporo, Hokkaido 004-8618, Japan
| | - Hirotaka Nishikiori
- Department of Respiratory Medicine and Allergology, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkaido 060-8543, Japan
| | - Masami Yamazoe
- Department of Respiratory Medicine, Hakodate Municipal Hospital, 1-10-1 Minato-cho, Hakodate, Hokkaido 041-0821, Japan
| | - Yuichiro Asai
- Department of Respiratory Medicine, 3-8 Kita 4-jo Nishi 7-chome, Chuo-ku, Tonan Hospital, Sapporo, Hokkaido 060-0004, Japan
| | - Yasuko Fukataki
- Department of Biostatics and Data Management, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkadio 060-8543, Japan
| | - Shiro Hinotsu
- Department of Biostatics and Data Management, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkadio 060-8543, Japan
| | - Hirofumi Chiba
- Department of Respiratory Medicine and Allergology, Sapporo Medical University School of Medicine, 291 Minami 1-jo Nishi 16-chome, Chuo-ku, Sapporo, Hokkaido 060-8543, Japan
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10
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Koh GCC, Nanda AS, Rinaldi G, Boushaki S, Degasperi A, Badja C, Pregnall AM, Zhao SJ, Chmelova L, Black D, Heskin L, Dias J, Young J, Memari Y, Shooter S, Czarnecki J, Brown MA, Davies HR, Zou X, Nik-Zainal S. A redefined InDel taxonomy provides insights into mutational signatures. Nat Genet 2025; 57:1132-1141. [PMID: 40210680 DOI: 10.1038/s41588-025-02152-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 03/04/2025] [Indexed: 04/12/2025]
Abstract
Despite their deleterious effects, small insertions and deletions (InDels) have received far less attention than substitutions. Here we generated isogenic CRISPR-edited human cellular models of postreplicative repair dysfunction (PRRd), including individual and combined gene edits of DNA mismatch repair (MMR) and replicative polymerases (Pol ε and Pol δ). Unique, diverse InDel mutational footprints were revealed. However, the prevailing InDel classification framework was unable to discriminate these InDel signatures from background mutagenesis and from each other. To address this, we developed an alternative InDel classification system that considers flanking sequences and informative motifs (for example, longer homopolymers), enabling unambiguous InDel classification into 89 subtypes. Through focused characterization of seven tumor types from the 100,000 Genomes Project, we uncovered 37 InDel signatures; 27 were new. In addition to unveiling previously hidden biological insights, we also developed PRRDetect-a highly specific classifier of PRRd status in tumors, with potential implications for immunotherapies.
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Affiliation(s)
- Gene Ching Chiek Koh
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
- School of Medical and Life Sciences, Sunway University, Sunway City, Malaysia
| | - Arjun Scott Nanda
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Giuseppe Rinaldi
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Soraya Boushaki
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Andrea Degasperi
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Cherif Badja
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Andrew Marcel Pregnall
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Salome Jingchen Zhao
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Lucia Chmelova
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Daniella Black
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Laura Heskin
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - João Dias
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Jamie Young
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Yasin Memari
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Scott Shooter
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Jan Czarnecki
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Matthew Arthur Brown
- Genomics England, Queen Mary University of London, Dawson Hall, Charterhouse Square, London, UK
| | - Helen Ruth Davies
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Xueqing Zou
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Serena Nik-Zainal
- Department of Genomic Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK.
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11
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Thomas QD, Vendrell JA, Khellaf L, Cavaillon S, Quantin X, Solassol J, Cabello‐Aguilar S. Artificial intelligence-driven microsatellite instability profiling reveals distinctive genetic features in patients with lung cancer. Cancer 2025; 131:e35882. [PMID: 40297960 PMCID: PMC12038786 DOI: 10.1002/cncr.35882] [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: 09/10/2024] [Revised: 02/10/2025] [Accepted: 03/24/2025] [Indexed: 04/30/2025]
Abstract
BACKGROUND Microsatellite instability (MSI) has emerged as a predictive biomarker for immunotherapy response in various cancers, but its role in non-small cell lung cancer (NSCLC) is not fully understood. METHODS The authors used the bioinformatics tool MIAmS to assess microsatellite status from next-generation sequencing (NGS) data using a tailored microsatellite score. Immunohistochemistry (IHC) assays were also performed to evaluate the correspondence between MSI and deficient mismatch repair (dMMR) status. A retrospective analysis of 1547 lung cancer patients was conducted, focusing on those with an MSI phenotype. Clinical characteristics, co-occurring molecular alterations, tumor mutation burden (TMB), and homologous recombination deficiency (HRD) status were evaluated in this subset. RESULTS Of the 1547 patients analyzed, eight (0.52%) were identified as having MSI through MIAmS, with six (0.39%) of these cases also being dMMR on IHC. All patients with dMMR had an MS score ≥2 and a history of smoking. Most patients showed loss of MLH1 and PMS2 staining on IHC. No correlation was found between MSI status and programmed death-ligand 1 expression, although all MSI patients exhibited high TMB, averaging 21.4 ± 5.6 mutations per megabase. DISCUSSION MSI/dMMR in lung cancer is exceedingly rare, affecting less than 1% of cases. NGS-based analysis combined with bioinformatics tools provides a robust method to identify MSI/dMMR patients, potentially guiding immunotherapy decisions. This comprehensive approach integrates molecular genotyping and MSI detection, offering personalized treatment options for lung cancer patients. NGS-based MSI testing is emerging as the preferred method for detecting microsatellite instability in various tumor types, including rare cancers.
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Affiliation(s)
- Quentin Dominique Thomas
- Department of Medical OncologyInstitute du Cancer de MontpellierMontpellier UniversityMontpellierFrance
- Oncogenic Pathways in Lung CancerMontpellier Cancer Research InstituteUniversity of MontpellierMontpellierFrance
| | - Julie Adèle Vendrell
- Solid Tumor LaboratoryDepartment of Pathology and OncobiologyMontpellier University Hospital MontpellierArnaud de Villeneuve HospitalMontpellierFrance
| | - Lakhdar Khellaf
- Department of PathologyInstitute du Cancer de MontpellierMontpellier UniversityMontpellierFrance
| | - Sarah Cavaillon
- Department of Medical OncologyInstitute du Cancer de MontpellierMontpellier UniversityMontpellierFrance
| | - Xavier Quantin
- Department of Medical OncologyInstitute du Cancer de MontpellierMontpellier UniversityMontpellierFrance
- Oncogenic Pathways in Lung CancerMontpellier Cancer Research InstituteUniversity of MontpellierMontpellierFrance
| | - Jérôme Solassol
- Solid Tumor LaboratoryDepartment of Pathology and OncobiologyMontpellier University Hospital MontpellierArnaud de Villeneuve HospitalMontpellierFrance
| | - Simon Cabello‐Aguilar
- Solid Tumor LaboratoryDepartment of Pathology and OncobiologyMontpellier University Hospital MontpellierArnaud de Villeneuve HospitalMontpellierFrance
- Montpellier BioInformatics for Clinical DiagnosisMolecular Medicine and Genomics PlatformMontpellier University Hospital MontpellierMontpellierFrance
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12
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Srivastava R. Advancing precision oncology with AI-powered genomic analysis. Front Pharmacol 2025; 16:1591696. [PMID: 40371349 PMCID: PMC12075946 DOI: 10.3389/fphar.2025.1591696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2025] [Accepted: 04/21/2025] [Indexed: 05/16/2025] Open
Abstract
Multiomics data integration approaches offer a comprehensive functional understanding of biological systems, with significant applications in disease therapeutics. However, the quantitative integration of multiomics data presents a complex challenge, requiring highly specialized computational methods. By providing deep insights into disease-associated molecular mechanisms, multiomics facilitates precision medicine by accounting for individual omics profiles, enabling early disease detection and prevention, aiding biomarker discovery for diagnosis, prognosis, and treatment monitoring, and identifying molecular targets for innovative drug development or the repurposing of existing therapies. AI-driven bioinformatics plays a crucial role in multiomics by computing scores to prioritize available drugs, assisting clinicians in selecting optimal treatments. This review will explain the potential of AI and multiomics data integration for disease understanding and therapeutics. It highlight the challenges in quantitative integration of diverse omics data and clinical workflows involving AI in cancer genomics, addressing the ethical and privacy concerns related to AI-driven applications in oncology. The scope of this text is broad yet focused, providing readers with a comprehensive overview of how AI-powered bioinformatics and integrative multiomics approaches are transforming precision oncology. Understanding bioinformatics in Genomics, it explore the integrative multiomics strategies for drug selection, genome profiling and tumor clonality analysis with clinical application of drug prioritization tools, addressing the technical, ethical, and practical hurdles in deploying AI-driven genomics tools.
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13
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Martín-Arana J, Gimeno-Valiente F, Henriksen TV, García-Micó B, Martínez-Castedo B, Gambardella V, Martínez-Ciarpaglini C, Palomar B, Huerta M, Camblor DG, García Bartolomé M, Carbonell-Asins JA, Frydendahl A, Gotchalck KA, Fleitas T, Tébar-Martínez R, Moro D, Pla V, Pérez-Santiago L, Martín-Arévalo J, Casado D, García-Botello S, Espí A, Roselló S, Roda D, Andersen CL, Cervantes A, Tarazona N. Whole-exome tumor-agnostic ctDNA analysis enhances minimal residual disease detection and reveals relapse mechanisms in localized colon cancer. NATURE CANCER 2025:10.1038/s43018-025-00960-z. [PMID: 40301653 DOI: 10.1038/s43018-025-00960-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2024] [Accepted: 03/25/2025] [Indexed: 05/01/2025]
Abstract
In stage 2-3 colon cancer (CC), postsurgery circulating tumor DNA (ctDNA) assessment is crucial for guiding adjuvant chemotherapy (ACT) decisions. While existing assays detect ctDNA and help identify high-risk persons with CC for recurrence, their limited sensitivity after surgery poses challenges in deciding on ACT. Additionally, a substantial portion of persons with CC fail to clear ctDNA after ACT, leading to recurrence. In this study, we performed whole-exome sequencing (WES) of ctDNA at different time points in participants with relapsed CC in two independent cohorts, alongside transcriptomic and proteomic analyses of metastases, to enhance comprehension of progression mechanisms. A plasma WES-based tumor-agnostic assay demonstrated higher sensitivity in detecting minimal residual disease (MRD) compared to current assays. Immune evasion appears to be the primary driver of progression in the localized CC setting, indicating the potential efficacy of immunotherapy for microsatellite stability in persons with CC. Organoid modeling further supports the promising potential of targeted therapy in eradicating MRD, surpassing conventional treatments.
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Affiliation(s)
- Jorge Martín-Arana
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Francisco Gimeno-Valiente
- Cancer Evolution and Genome Instability Laboratory, University College London Cancer Institute, London, UK
| | - Tenna Vesterman Henriksen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Blanca García-Micó
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Belén Martínez-Castedo
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Valentina Gambardella
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
| | - Carolina Martínez-Ciarpaglini
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
- Department of Pathology, INCLIVA Biomedical Research Institute, Valencia, Spain
| | - Brenda Palomar
- Department of Pathology, INCLIVA Biomedical Research Institute, Valencia, Spain
| | - Marisol Huerta
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Daniel G Camblor
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Miguel García Bartolomé
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
| | | | - Amanda Frydendahl
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | | | - Tania Fleitas
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Roberto Tébar-Martínez
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
| | - David Moro
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - Vicente Pla
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - Leticia Pérez-Santiago
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - José Martín-Arévalo
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - David Casado
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - Stephanie García-Botello
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - Alejandro Espí
- Colorectal Surgery Unit, Department of General and Digestive Surgery, INCLIVA Biomedical Research Institute, Hospital Clínico Universitario, Valencia, Spain
- Department of Surgery, University of Valencia, Valencia, Spain
| | - Susana Roselló
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Desamparados Roda
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain
| | - Claus Lindbjerg Andersen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark.
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
| | - Andrés Cervantes
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain.
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain.
| | - Noelia Tarazona
- Department of Medical Oncology, INCLIVA Biomedical Research Institute, University of Valencia, Valencia, Spain.
- Instituto de Salud Carlos III, CIBERONC, Madrid, Spain.
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14
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Oya Y, Tanaka I. Latest Advances in Perioperative care for Resectable Non-small lung cancer. Respir Investig 2025; 63:532-541. [PMID: 40288221 DOI: 10.1016/j.resinv.2025.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2024] [Revised: 02/10/2025] [Accepted: 04/01/2025] [Indexed: 04/29/2025]
Abstract
Resectable non-small cell lung cancer (NSCLC) has a relatively poor prognosis owing to the risk of developing local or distant metastatic recurrence, even at stage I. To overcome the high recurrence rate, perioperative therapies have been rapidly developed through the combination of existing cytotoxic chemotherapies with immune checkpoint inhibitors (ICIs) and molecular targeted therapies. These new therapeutic strategies have significantly improved the prognosis of patients with stage II-III NSCLC and have been approved for clinical use. However, new challenges have emerged in the selection of the optimal perioperative treatment in clinical practice. First, it is currently difficult to determine which perioperative treatment is superior, preoperative or postoperative. Additionally, since surgery alone is curative in some patients, the addition of anticancer agents such as ICIs raises concerns regarding toxicity, as serious side effects during preoperative treatment may lead to an inability to perform the surgery itself. Moreover, because various perioperative treatments are still being developed, treatment options for perioperative care are expected to increase soon. To summarize the increasingly complex perioperative treatment of resectable NSCLC, this review provides a comprehensive summary of the clinical efficacies of current perioperative therapies and future directions based on basic background, patient selection, ongoing trials, and enhancing immunotherapy.
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Affiliation(s)
- Yuko Oya
- Department of Respiratory Medicine & Clinical Allergy, Fujita Health University, Dengakugakubo, Kutsukake-cho, Toyoake, 470-1192, Japan.
| | - Ichidai Tanaka
- Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, 65, Tsurumai-cho, Showa-ku, Nagoya, 466-8550, Japan.
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15
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Chiu DKC, Zhang X, Cheng BYL, Liu Q, Hayashi K, Yu B, Lee R, Zhang C, An X, Rajadas J, Reticker-Flynn NE, Rankin EB, Engleman EG. Tumor-derived erythropoietin acts as an immunosuppressive switch in cancer immunity. Science 2025; 388:eadr3026. [PMID: 40273234 DOI: 10.1126/science.adr3026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2024] [Revised: 12/20/2024] [Accepted: 03/05/2025] [Indexed: 04/26/2025]
Abstract
Successful cancer immunotherapy requires a patient to mount an effective immune response against tumors; however, many cancers evade the body's immune system. To investigate the basis for treatment failure, we examined spontaneous mouse models of hepatocellular carcinoma (HCC) with either an inflamed T cell-rich or a noninflamed T cell-deprived tumor microenvironment (TME). Our studies reveal that erythropoietin (EPO) secreted by tumor cells determines tumor immunotype. Tumor-derived EPO autonomously generates a noninflamed TME by interacting with its cognate receptor EPOR on tumor-associated macrophages (TAMs). EPO signaling prompts TAMs to become immunoregulatory through NRF2-mediated heme depletion. Removing either tumor-derived EPO or EPOR on TAMs leads to an inflamed TME and tumor regression independent of genotype, owing to augmented antitumor T cell immunity. Thus, the EPO/EPOR axis functions as an immunosuppressive switch for antitumor immunity.
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Affiliation(s)
| | - Xiangyue Zhang
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Bowie Yik-Ling Cheng
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, CA, USA
| | - Qiang Liu
- Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute, Department of Medicine, Stanford University, Stanford, CA, USA
| | | | - Bo Yu
- ImmunEdge Inc., Mountain View, CA, USA
| | - Ryan Lee
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Catherine Zhang
- Department of Pathology, Stanford University, Stanford, CA, USA
| | - Xiuli An
- Laboratory of Membrane Biology, New York Blood Center, New York, NY, USA
| | - Jayakumar Rajadas
- Advanced Drug Delivery and Regenerative Biomaterials Laboratory, Cardiovascular Institute, Department of Medicine, Stanford University, Stanford, CA, USA
| | | | - Erinn B Rankin
- Department of Radiation Oncology, Stanford University, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University, Palo Alto, CA, USA
| | - Edgar G Engleman
- Department of Pathology, Stanford University, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University, Palo Alto, CA, USA
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16
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Xu P, Hong C, Liu L, Xiao L. PD-1/PD-L1 blockade therapy in hepatocellular carcinoma: Current status and potential biomarkers. Biochim Biophys Acta Rev Cancer 2025; 1880:189334. [PMID: 40280499 DOI: 10.1016/j.bbcan.2025.189334] [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: 09/21/2024] [Revised: 04/21/2025] [Accepted: 04/21/2025] [Indexed: 04/29/2025]
Abstract
Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death and the sixth most prevalent cancer worldwide. However, most patients with HCC are at an advanced stage at the time of clinical diagnosis, making surgery impossible. In the past, targeted therapeutic drugs such as sorafenib and lenvatinib were the main treatments. With recent breakthroughs in medicine, immunotherapy, particularly immune checkpoint inhibitors (ICIs), has garnered interest and has been extensively studied for clinical treatment. In addition to single-agent therapies, combination regimens involving ICIs have also been developed. Despite this progress, not all patients with HCC benefit from immunotherapy. Therefore, to improve the treatment response rates, it is crucial to identify patients with HCC who are suitable for immunotherapy. The exploration and validation of markers to predict the outcomes of immunotherapeutic treatments in patients with HCC are of clinical importance. In this article, we provide a comprehensive review of research progress in immunotherapy, particularly ICIs and combination therapies, for HCC. Furthermore, we summarize the clinical indicators and tumor markers discovered in recent years to forecast immunotherapy outcomes in patients with HCC. We also outline predictive markers for the occurrence of immune-related adverse events in patients with HCC receiving immunotherapy and discuss future research directions in the immunotherapeutic treatment landscape.
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Affiliation(s)
- Peishuang Xu
- Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Chang Hong
- Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Li Liu
- Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
| | - Lushan Xiao
- Department of Health Management, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China; Guangdong Provincial Key Laboratory of Viral Hepatitis Research, Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
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17
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Lin KT, Muneer G, Huang PR, Chen CS, Chen YJ. Mass Spectrometry-Based Proteomics for Next-Generation Precision Oncology. MASS SPECTROMETRY REVIEWS 2025. [PMID: 40269546 DOI: 10.1002/mas.21932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Revised: 03/29/2025] [Accepted: 04/01/2025] [Indexed: 04/25/2025]
Abstract
Cancer is the leading cause of death worldwide characterized by patient heterogeneity and complex tumor microenvironment. While the genomics-based testing has transformed modern medicine, the challenge of diverse clinical outcomes highlights unmet needs for precision oncology. As functional molecules regulating cellular processes, proteins hold great promise as biomarkers and drug targets. Mass spectrometry (MS)-based clinical proteomics has illuminated the molecular features of cancers and facilitated discovery of biomarkers or therapeutic targets, paving the way for innovative strategies that enhance the precision of personalized treatment. In this article, we introduced the tools and current achievements of MS-based proteomics, choice of discovery and targeted MS from discovery to validation phases, profiling sensitivity from bulk samples to single-cell level and tissue to liquid biopsy specimens, current regulatory landscape of MS-based protein laboratory-developed tests (LDTs). The challenges, success and future perspectives in translating research MS assay into clinical applications are also discussed. With well-designed validation studies to demonstrate clinical benefits and meet the regulatory requirements for both analytical and clinical performance, the future of MS-based assays is promising with numerous opportunities to improve cancer diagnosis, treatment, and monitoring.
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Affiliation(s)
- Kuen-Tyng Lin
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
| | - Gul Muneer
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
| | | | - Ciao-Syuan Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
| | - Yu-Ju Chen
- Institute of Chemistry, Academia Sinica, Taipei, Taiwan
- Department of Chemistry, National Taiwan University, Taipei, Taiwan
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18
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Kordowitzki P, Lange B, Elias KM, Haigis MC, Mechsner S, Braicu IE, Sehouli J. Transforming treatment paradigms: Focus on personalized medicine for high-grade serous ovarian cancer. CA Cancer J Clin 2025. [PMID: 40252048 DOI: 10.3322/caac.70008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2025] [Revised: 02/20/2025] [Accepted: 02/26/2025] [Indexed: 04/21/2025] Open
Abstract
High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of ovarian cancer, accounting for approximately 70% of all ovarian cancer cases and contributing significantly to the high mortality rates associated with this disease. Because of the asymptomatic nature of early stage disease, most patients are diagnosed at advanced stages when the cancer has already spread into the abdominal cavity, requiring complex and intensive surgical and chemotherapeutic interventions followed by maintenance therapies. Although a minority of cases are associated with well defined genetic syndromes, specific risk factors and a clear etiology in many cases remain elusive. HGSOC tumors are characterized by a high frequency of somatic gene copy number alterations, often associated with defects in homologous recombination repair of DNA. All attempts to introduce an effective screening for HGSOC to date have been unsuccessful. This review elucidates the complexities surrounding HGSOC and encompasses its etiology, epidemiology, classification, pathogenesis, and the current array of treatment strategies. Understanding molecular underpinnings is crucial for the development of targeted therapies and personalized multimodal treatment approaches in centralized therapeutic structures. This review also examines the importance of the tumor microenvironment. In addition, the authors' objective is to underscore the critical importance of placing the patient's perspective and diversity at the forefront of therapeutic strategies, thereby fostering a genuinely participatory decision-making process and ultimately improving patient quality of life.
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Affiliation(s)
- Pawel Kordowitzki
- Department of Preclinical and Basic Sciences, Nicolaus Copernicus University, Torun, Poland
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, USA
- Department of Gynecology, Center of Oncological Surgery, European Competence Center for Ovarian Cancer, Charité-University Medicine Berlin, Berlin, Germany
| | - Britta Lange
- Institute for Cultural Studies, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Kevin M Elias
- Section of Gynecologic Oncology, Obstetrics and Gynecology Institute, Taussig Cancer Institute, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Marcia C Haigis
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts, USA
| | - Sylvia Mechsner
- Department of Gynecology, Center of Oncological Surgery, European Competence Center for Ovarian Cancer, Charité-University Medicine Berlin, Berlin, Germany
| | - Ioana Elena Braicu
- Department of Gynecology, Center of Oncological Surgery, European Competence Center for Ovarian Cancer, Charité-University Medicine Berlin, Berlin, Germany
| | - Jalid Sehouli
- Department of Gynecology, Center of Oncological Surgery, European Competence Center for Ovarian Cancer, Charité-University Medicine Berlin, Berlin, Germany
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19
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Cao R, Jiao P, Zhang S, Li J, Liu Q. Predicting the Efficacy of Immune Checkpoint Inhibitors in Esophageal Cancer: Changes in Peripheral Blood Lymphocyte Subsets Before and After Immunotherapy. Cancer Manag Res 2025; 17:815-825. [PMID: 40256769 PMCID: PMC12009565 DOI: 10.2147/cmar.s503171] [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: 11/12/2024] [Accepted: 04/04/2025] [Indexed: 04/22/2025] Open
Abstract
Background Immunotherapy has demonstrated potential in the treatment of esophageal cancer (EC); however, the overall response rate (ORR) remains below 30% among EC patients. Herein, the use of peripheral blood lymphocyte subsets as biomarkers was explored to evaluate the efficacy of immunotherapy in this patient population. Methods Sixty-three patients were enrolled. The patients were diagnosed with EC and treated with immune checkpoint inhibitors (ICIs) at The Fourth Hospital of Hebei Medical University from December 2019 to June 2023. Kaplan-Meier (KM) survival curves were used to reflect differences in survival benefit. The prognostic factors of survival were investigated using the Cox proportional hazards regression model for both univariate and multivariate analyses. Two-tailed P values were reported and statistical significance was defined as P < 0.05. Results The results of univariate and multifactorial Cox regression analysis for progression-free survival (PFS) revealed that only CD8+ T lymphocytes demonstrated a significant association with PFS (P = 0.034, P = 0.020). Additionally, the multifactorial Cox regression analysis results for overall survival (OS) revealed a significant association between natural killer (NK) cells and OS (P=0.049). Further, a systematic analysis was conducted on the CD8+ T cell biomarker. The KM survival curves indicated that the group with low CD8+ T cell levels experienced a significantly greater PFS benefit compared to the high CD8+ T cell group (P = 0.030). Conclusion The present study reveals that the reduction of both CD8+ T lymphocytes and NK cells in peripheral blood lymphocyte subsets after immunotherapy can serve as superior predictors for the effectiveness of ICIs in patients diagnosed with EC.
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Affiliation(s)
- Ruijie Cao
- Department of Immunology and Rheumatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, People’s Republic of China
| | - Pengqing Jiao
- Department of Immunology and Rheumatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, People’s Republic of China
| | - Shasha Zhang
- Department of Immunology and Rheumatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, People’s Republic of China
| | - Jiasong Li
- Department of Immunology and Rheumatology, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, People’s Republic of China
| | - Qingyi Liu
- Department of Cardiothoracic Surgery, The Fourth Hospital of Hebei Medical University, Shijiazhuang, 050011, People’s Republic of China
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20
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Philips S, Lu P, Fausel C, Wagner T, Jiang G, Shen F, Cantor E, Tran M, Roland LM, Schneider BP. Association of heightened host and tumor immunity with prolonged duration of response to checkpoint inhibition across solid tumors. Sci Rep 2025; 15:13195. [PMID: 40240402 PMCID: PMC12003766 DOI: 10.1038/s41598-025-96925-4] [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: 09/19/2024] [Accepted: 04/01/2025] [Indexed: 04/18/2025] Open
Abstract
Cancer immunotherapy is a beneficial therapy for many cancer types, but predictive pan-tumor biomarkers for clinical benefit are suboptimal. Our study, employing DNA and RNA based analysis, investigated the role of predicted neoantigens in the benefits of immunotherapy within a cohort of 88 patients of European descent with advanced solid tumors. Patients who had a prolonged (> 12 months) duration of immunotherapy exhibited heightened immune responses, characterized by increased levels of predicted neoantigens with strong HLA binding potential, elevated cytotoxic marker levels, and enhanced T cell activity. Furthermore, our analysis revealed associations between prolonged duration of therapy and rare variants, notably within the EPHA8 gene. These variants, exclusive to patients with a prolonged (> 12 months) duration of immunotherapy, suggest potential implications for immunotherapy response. In addition, the evolutionary conservation of these variants across vertebrate species underscores their functional importance in tumor biology and ultimately, treatment outcomes. Despite limitations in sample size and patient homogeneity, our findings emphasize the potential utility of understanding the molecular and immunological mechanisms underlying immunotherapy responses to further refine personalized treatment strategies.
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Affiliation(s)
- Santosh Philips
- Division of Hematology and Oncology, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Pei Lu
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Chris Fausel
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Thomas Wagner
- College of Pharmacy and Health Sciences, Butler University, Indianapolis, IN, USA
| | - Guanglong Jiang
- Division of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Fei Shen
- Division of Hematology and Oncology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Erica Cantor
- Division of Hematology and Oncology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Mya Tran
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Lauren M Roland
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA
| | - Bryan P Schneider
- Division of Hematology and Oncology, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, USA.
- Division of Hematology/Oncology, Department of Medicine, Indiana University, 535 Barnhill Drive, RT 473, Indianapolis, IN, 46202, USA.
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21
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Wei W, Li H, Tian S, Zhang C, Liu J, Tao W, Cai T, Dong Y, Wang C, Lu D, Ai Y, Zhang W, Wang H, Liu K, Fan Y, Gao Y, Huang Q, Ma X, Wang B, Zhang X, Huang Y. Asparagine drives immune evasion in bladder cancer via RIG-I stability and type I IFN signaling. J Clin Invest 2025; 135:e186648. [PMID: 39964752 PMCID: PMC11996873 DOI: 10.1172/jci186648] [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: 09/03/2024] [Accepted: 02/07/2025] [Indexed: 02/20/2025] Open
Abstract
Tumor cells often employ many ways to restrain type I IFN signaling to evade immune surveillance. However, whether cellular amino acid metabolism regulates this process remains unclear, and its effects on antitumor immunity are relatively unexplored. Here, we found that asparagine inhibited IFN-I signaling and promoted immune escape in bladder cancer. Depletion of asparagine synthetase (ASNS) strongly limited in vivo tumor growth in a CD8+ T cell-dependent manner and boosted immunotherapy efficacy. Moreover, clinically approved L-asparaginase (ASNase),synergized with anti-PD-1 therapy in suppressing tumor growth. Mechanistically, asparagine can directly bind to RIG-I and facilitate CBL-mediated RIG-I degradation, thereby suppressing IFN signaling and antitumor immune responses. Clinically, tumors with higher ASNS expression show decreased responsiveness to immune checkpoint inhibitor therapy. Together, our findings uncover asparagine as a natural metabolite to modulate RIG-I-mediated IFN-I signaling, providing the basis for developing the combinatorial use of ASNase and anti-PD-1 for bladder cancer.
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Affiliation(s)
- Wenjie Wei
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Hongzhao Li
- Department of Urology, The Third Medical Center and
| | - Shuo Tian
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Chi Zhang
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Junxiao Liu
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Wen Tao
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Tianwei Cai
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Yuhao Dong
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Chuang Wang
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Dingyi Lu
- State Key Laboratory of Proteomics, Institute of Basic Medical Sciences, National Center of Biomedical Analysis, Beijing, China
| | - Yakun Ai
- Department of Pathology, The Third Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Wanlin Zhang
- Department of Pathology, The Third Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Hanfeng Wang
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
- Medical School of PLA, Beijing, China
| | - Kan Liu
- Department of Urology, The Third Medical Center and
| | - Yang Fan
- Department of Urology, The Third Medical Center and
| | - Yu Gao
- Department of Urology, The Third Medical Center and
| | - Qingbo Huang
- Department of Urology, The Third Medical Center and
| | - Xin Ma
- Department of Urology, The Third Medical Center and
| | - Baojun Wang
- Department of Urology, The Third Medical Center and
| | - Xu Zhang
- Department of Urology, The Third Medical Center and
| | - Yan Huang
- Department of Urology, The Third Medical Center and
- Department of Urology Laboratory, Chinese PLA General Hospital, Beijing, China
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22
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Li H, Chang Y, Jin T, Zhang M. Progress of PD-1/PD-L1 immune checkpoint inhibitors in the treatment of triple-negative breast cancer. Cancer Cell Int 2025; 25:139. [PMID: 40211301 PMCID: PMC11987362 DOI: 10.1186/s12935-025-03769-z] [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: 10/05/2024] [Accepted: 03/28/2025] [Indexed: 04/13/2025] Open
Abstract
Triple-negative breast cancer (TNBC) is a highly heterogeneous cancer with substantial recurrence potential. Currently, surgery and chemotherapy are the main treatments for this disease. However, chemotherapy is often limited by several factors, including low bioavailability, significant systemic toxicity, inadequate targeting, and multidrug resistance. Immune checkpoint inhibitors (ICIs), including those targeting programmed death protein-1 (PD-1) and its ligand (PD-L1), have been proven effective in the treatment of various tumours. In particular, in the treatment of TNBC with PD-1/PD-L1 inhibitors, both monotherapy and combination chemotherapy, as well as targeted drugs and other therapeutic strategies, have broad therapeutic prospects. In addition, these inhibitors can participate in the tumour immune microenvironment (TIME) through blocking PD-1/PD-L1 binding, which can improve immune efficacy. This article provides an overview of the use of PD-1/PD-L1 inhibitors in the treatment of TNBC and the progress of multiple therapeutic studies. To increase the survival of TNBC patients, relevant biomarkers for predicting the efficacy of PD-1/PD-L1 inhibitor therapy have been explored to identify new strategies for the treatment of TNBC.
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Affiliation(s)
- Hongshu Li
- Department of Pathology and Cancer Research Center, Yanbian University Medical College, Gong Yuan Road No. 977, Yanji, 133002, P. R. China
- Key Laboratory of the Science and Technology Department of Jilin Province, Yanji, P. R. China
| | - Ying Chang
- Department of Pathology and Cancer Research Center, Yanbian University Medical College, Gong Yuan Road No. 977, Yanji, 133002, P. R. China
- Key Laboratory of the Science and Technology Department of Jilin Province, Yanji, P. R. China
| | - Tiefeng Jin
- Department of Pathology and Cancer Research Center, Yanbian University Medical College, Gong Yuan Road No. 977, Yanji, 133002, P. R. China.
- Key Laboratory of the Science and Technology Department of Jilin Province, Yanji, P. R. China.
| | - Meihua Zhang
- Department of Ultrasound Medicine, Yanbian University Hospital, Yanji, 133000, P. R. China.
- Department of Pathology and Cancer Research Center, Yanbian University Medical College, Gong Yuan Road No. 977, Yanji, 133002, P. R. China.
- Key Laboratory of the Science and Technology Department of Jilin Province, Yanji, P. R. China.
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23
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Casalegno Garduño R, Spitschak A, Pannek T, Pützer BM. CD8+ T Cell Subsets as Biomarkers for Predicting Checkpoint Therapy Outcomes in Cancer Immunotherapy. Biomedicines 2025; 13:930. [PMID: 40299510 PMCID: PMC12025007 DOI: 10.3390/biomedicines13040930] [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: 02/27/2025] [Revised: 04/01/2025] [Accepted: 04/04/2025] [Indexed: 04/30/2025] Open
Abstract
The advent of immune checkpoint blockade (ICB) has transformed cancer immunotherapy, enabling remarkable long-term outcomes and improved survival, particularly with ICB combination treatments. However, clinical benefits remain confined to a subset of patients, and life-threatening immune-related adverse effects pose a significant challenge. This limited efficacy is attributed to cancer heterogeneity, which is mediated by ligand-receptor interactions, exosomes, secreted factors, and key transcription factors. Oncogenic regulators like E2F1 and MYC drive metastatic tumor environments and intertwine with immunoregulatory pathways, impairing T cell function and reducing immunotherapy effectiveness. To address these challenges, FDA-approved biomarkers, such as tumor mutational burden (TMB) and programmed cell death-ligand 1 (PD-L1) expression, help to identify patients most likely to benefit from ICB. Yet, current biomarkers have limitations, making treatment decisions difficult. Recently, T cells-the primary target of ICB-have emerged as promising biomarkers. This review explores the relationship between cancer drivers and immune response, and emphasizes the role of CD8+ T cells in predicting and monitoring ICB efficacy. Tumor-infiltrating CD8+ T cells correlate with positive clinical outcomes in many cancers, yet obtaining tumor tissue remains complex, limiting its practical use. Conversely, circulating T cell subsets are more accessible and have shown promise as predictive biomarkers. Specifically, memory and progenitor exhausted T cells are associated with favorable immunotherapy responses, while terminally exhausted T cells negatively correlate with ICB efficacy. Ultimately, combining biomarkers enhances predictive accuracy, as demonstrated by integrating TMB/PD-L1 expression with CD8+ T cell frequency. Computational models incorporating cancer and immune signatures could further refine patient stratification, advancing personalized immunotherapy.
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Affiliation(s)
- Rosaely Casalegno Garduño
- Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, 18057 Rostock, Germany; (R.C.G.); (A.S.); (T.P.)
| | - Alf Spitschak
- Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, 18057 Rostock, Germany; (R.C.G.); (A.S.); (T.P.)
| | - Tim Pannek
- Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, 18057 Rostock, Germany; (R.C.G.); (A.S.); (T.P.)
| | - Brigitte M. Pützer
- Institute of Experimental Gene Therapy and Cancer Research, Rostock University Medical Center, 18057 Rostock, Germany; (R.C.G.); (A.S.); (T.P.)
- Department Life, Light & Matter, University of Rostock, 18059 Rostock, Germany
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24
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Gong JR, Lee J, Han Y, Cho KH. DDX54 downregulation enhances anti-PD1 therapy in immune-desert lung tumors with high tumor mutational burden. Proc Natl Acad Sci U S A 2025; 122:e2412310122. [PMID: 40172969 PMCID: PMC12002276 DOI: 10.1073/pnas.2412310122] [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: 06/19/2024] [Accepted: 02/25/2025] [Indexed: 04/04/2025] Open
Abstract
High tumor mutational burden (TMB-H) is a predictive biomarker for the responsiveness of cancer to immune checkpoint inhibitor (ICI) therapy that indicates whether immune cells can sufficiently recognize cancer cells as nonself. However, about 30% of all cancers from The Cancer Genome Atlas (TCGA) are classified as immune-desert tumors lacking T cell infiltration despite TMB-H. Since the underlying mechanism of these immune-desert tumors has yet to be unraveled, there is a pressing need to transform such immune-desert tumors into immune-inflamed tumors and thereby enhance their responsiveness to anti-PD1 therapy. Here, we present a systems framework for identifying immuno-oncotargets, based on analysis of gene regulatory networks, and validating the effect of these targets in transforming immune-desert into immune-inflamed tumors. In particular, we identify DEAD-box helicases 54 (DDX54) as a master regulator of immune escape in immune-desert lung cancer with TMB-H and show that knockdown of DDX54 can increase immune cell infiltration and lead to improved sensitivity to anti-PD1 therapy.
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Affiliation(s)
- Jeong-Ryeol Gong
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon34141, Republic of Korea
| | - Jungeun Lee
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon34141, Republic of Korea
| | - Younghyun Han
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon34141, Republic of Korea
| | - Kwang-Hyun Cho
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon34141, Republic of Korea
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25
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Braganca Xavier C, Guardia GDA, Alves JPB, Lopes CDH, Awni BM, Campos EF, Jardim DL, Galante PAF. Identifying predictors of overall survival among patients with TMB-low metastatic cancer treated with immune checkpoint inhibitors. Oncologist 2025; 30:oyaf078. [PMID: 40285678 PMCID: PMC12032576 DOI: 10.1093/oncolo/oyaf078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2024] [Accepted: 03/25/2025] [Indexed: 04/29/2025] Open
Abstract
BACKGROUND Immune checkpoint inhibitors (ICIs) have significantly advanced cancer therapy, yet their efficacy in tumors with low tumor mutational burden (TMB) remains suboptimal. In this study, we aimed to elucidate the impact of somatic mutations on overall survival (OS) in TMB-low patients treated with ICIs and to explore the potential for personalized treatment selection through machine learning. METHODS We conducted a comprehensive analysis of 1172 TMB-low (TMB < 10 mutations per megabase) patients with cancer receiving ICIs, examining the association between specific gene mutations and OS. Additionally, we developed a decision tree model (DTM) to predict OS based on clinical features and tumor mutational profiles. RESULTS Our findings reveal that mutations in DAXX, HLA-A, H3C2, IGF1R, CTNNB1, SMARCA4, KMT2D, and TP53 are significantly associated with poorer survival outcomes in the multivariate analysis. Remarkably, for renal cell carcinoma (RCC) patients, VHL mutations predicted improved OS following ICI even when adjusted for age, sex, and microsatellite instability (MSI) status in both multivariate analysis and the DTM model. CONCLUSIONS These results reinforce the prevailing notion that TMB alone does not predict ICI response, highlighting the critical role of individual gene mutations in TMB-low tumors under ICI therapy. Furthermore, our study demonstrates the promise of machine learning models in optimizing ICI treatment decisions, paving the way for more precise and effective therapeutic strategies in this patient population.
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Affiliation(s)
- Camila Braganca Xavier
- MD Anderson Cancer Center, Houston, TX, 77030, United States
- Hospital Sírio-Libanês, São Paulo, SP, 01308-050, Brazil
| | | | | | | | - Beatriz M Awni
- Hospital Sírio-Libanês, São Paulo, SP, 01308-050, Brazil
| | | | - Denis L Jardim
- Hospital Sírio-Libanês, São Paulo, SP, 01308-050, Brazil
- Oncoclínicas&CO - Medica Scientia Innovation Research (MedSir), São Paulo, SP, 04538-132, Brazil
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26
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Zhang Y, Gou M. Combined Chemotherapy-Immunotherapy for Advanced Biliary Tract Cancer (BTC): A Clinical, Genomic, and Biomarker Analysis. J Gastrointest Cancer 2025; 56:90. [PMID: 40167580 DOI: 10.1007/s12029-025-01215-x] [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] [Accepted: 03/25/2025] [Indexed: 04/02/2025]
Abstract
BACKGROUND Biliary tract cancer (BTC) represents a heterogeneous disease spectrum associated with an unfavorable prognosis. A combination of immunotherapy and chemotherapy has become a new standard strategy for advanced BTC. However, understanding the association between genomic alterations and outcomes of immunotherapy in BTC is crucial for further improving clinical benefits. METHOD Patients with metastatic BTC were included in this study retrospectively, who received PD-1/PD-L1 (ICI) antibodies combined with chemotherapy. The primary endpoint was progression-free survival (PFS), and the secondary endpoints included overall response rate (ORR) and disease control rate (DCR). Additionally, we conducted exploratory analysis of genomic alterations and biomarkers. RESULTS Ninety-one patients were enrolled in this study. The patients were divided into two groups: albumin paclitaxel + S1 (AS) + PD-1 (n = 56) group and GC + ICI (n = 35) group. There were no significant differences in terms of PFS, ORR, and DCR between the two groups. Regarding biomarker analysis, 44 patients had positive PD-L1 expression, with a mPFS of 4.8 months and an ORR of 15.9%. Surprisingly, 29 patients had negative PD-L1 expression, with a mPFS of 9.9 months and an ORR of 27.6%. The average tumor mutational burden (TMB) was 4.5 mutations per megabase (mut/MB) for patients with microsatellite-stable (MSS) tumors. There was no significant difference in PFS between patients with TMB high and low (cutoff = 4.5 mut/MB). Genomic analysis revealed TP53 (n = 13, 43.3%), KRAS (n = 8, 26.7%), NTRK1/2/3 (n = 8, 26.7%), isocitrate dehydrogenase (IDH) 1/2 (n = 6, 20.0%), PIK3CA (n = 6, 20.0%), BRCA2 (n = 5, 16.7%), MDM2/4 (n = 5, 16.7%), and BRAF (n = 4, 13.3%) as the most common gene alterations. MDM2/4 mutations were associated with shorter survival (p < 0.05). CONCLUSION GC plus immunotherapy is still the standard of care for late stage BTC. PD-L1 expression and TMB were not good predictors for selecting patients who would benefit more from immunotherapy plus chemotherapy.
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Affiliation(s)
- Yong Zhang
- Medical Oncology Department, The Second Medical Center and National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Miaomiao Gou
- Medical Oncology Department, The Fifth Medical Center, Chinese PLA General Hospital, Beijing, China.
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27
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Zheng M. High tumor mutation burden mitigates the negative impact of chemotherapy history on immune checkpoint blockade therapy. Semin Oncol 2025; 52:152334. [PMID: 40081267 DOI: 10.1053/j.seminoncol.2025.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2024] [Revised: 01/24/2025] [Accepted: 01/27/2025] [Indexed: 03/15/2025]
Abstract
Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small-cell lung cancer (NSCLC) accounting for the majority of cases. Immune checkpoint inhibitor (ICI) therapy, particularly with PD-1 inhibitors like nivolumab, has become a critical treatment option for advanced NSCLC. ICI therapy has revolutionized treatment, but prior chemotherapy may diminish ICI treatment efficacy. Tumor mutation burden (TMB) has emerged as a crucial predictor of ICI response, yet its interaction with chemotherapy history in ICI therapy is not fully understood. In this study, I investigate the impact of chemotherapy history on ICI treatment outcomes, focusing on TMB as a potential mitigating factor. Analyzing data from 512 patients with advanced NSCLC treated with PD-1/PD-L1 or CTLA-4 inhibitors, this sudy found that prior chemotherapy significantly reduced objective response rates (ORR) to ICI therapy, particularly in patients with low TMB (<15 mut/Mb). However, in patients with high TMB (≥15 mut/Mb), the negative impact of chemotherapy history on ICI treatment efficacy is minimal, suggesting that high TMB mitigates chemotherapy-induced resistance to ICI therapy. Furthermore, while chemotherapy history is associated with worse overall survival (OS) and progression-free survival (PFS) following ICI therapy in low-TMB patients, no such association is observed in high-TMB patients. These findings highlight the importance of TMB as a predictive biomarker, emphasizing the need for optimal treatment sequencing and personalized therapeutic strategies to overcome chemotherapy-induced immune resistance and maximize ICI treatment efficacy. These results suggest that ICI therapy may be more beneficial as a first-line treatment, particularly for patients with low TMB.
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Affiliation(s)
- Ming Zheng
- Beijing Institute of Basic Medical Sciences, 27 Taiping Road, Beijing 100850, China; Academy of Military Medical Sciences, 27 Taiping Road, Beijing 100850, China.
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28
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Luo P, Li Z, He H, Tang Y, Zeng L, Luo L, Ouyang L, Wen M, Li Y, Jiang Y. Exploring the impact of RPN1 on tumorigenesis and immune response in cancer. FASEB J 2025; 39:e70345. [PMID: 40079196 DOI: 10.1096/fj.202401088r] [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: 05/15/2024] [Revised: 12/26/2024] [Accepted: 01/15/2025] [Indexed: 03/14/2025]
Abstract
The ribophorin family, including RPN1, has been associated with tumor progression, but its specific role in pan-cancer dynamics remains unclear. Using data from TCGA, GTEx, and Ualcan databases, we investigated the relationship of RPN1 with prognosis, genomic alterations, and epigenetic modifications across various cancers. Differential analysis revealed elevated RPN1 expression in multiple cancer types, indicating a potential prognostic value. Amplification was the predominant mutation type of RPN1 in pan-cancer, with notable correlations with DNA methylation and copy number variation. Gene set variation analysis identified RPN1's involvement in cancer development, immunity, and metabolism. Additionally, RPN1 expression correlated with the tumor microenvironment, immune response factors, and response to anti-tumor therapies. Functional validation in triple-negative breast cancer, glioblastoma, and bladder cancer cell lines demonstrated the role of RPN1 in tumor cell proliferation and migration. Our findings highlight RPN1 as a potential biomarker for cancer diagnosis and treatment response in pan-cancer therapy.
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Affiliation(s)
- Pengfei Luo
- Department of Oncology, The Central Hospital of Yongzhou, Yongzhou, Hunan, China
| | - Zhimin Li
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Haodong He
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Yuanbin Tang
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Lijun Zeng
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Lunqi Luo
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Lianjie Ouyang
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Meiling Wen
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Yuehua Li
- Department of Oncology, the First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan, China
| | - Yongjun Jiang
- Department of Oncology, The Central Hospital of Yongzhou, Yongzhou, Hunan, China
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Imyanitov EN, Preobrazhenskaya EV, Mitiushkina NV. Overview on biomarkers for immune oncology drugs. EXPLORATION OF TARGETED ANTI-TUMOR THERAPY 2025; 6:1002298. [PMID: 40135049 PMCID: PMC11933888 DOI: 10.37349/etat.2025.1002298] [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: 01/20/2025] [Accepted: 02/24/2025] [Indexed: 03/27/2025] Open
Abstract
Although immune checkpoint inhibitors (ICIs) are widely used in clinical oncology, less than half of treated cancer patients derive benefit from this therapy. Both tumor- and host-related variables are implicated in response to ICIs. The predictive value of PD-L1 expression is confined only to several cancer types, so this molecule is not an agnostic biomarker. Highly elevated tumor mutation burden (TMB) caused either by excessive carcinogenic exposure or by a deficiency in DNA repair is a reliable indicator for ICI efficacy, as exemplified by tumors with high-level microsatellite instability (MSI-H). Other potentially relevant tumor-related characteristics include gene expression signatures, pattern of tumor infiltration by immune cells, and, perhaps, some immune-response modifying somatic mutations. Host-related factors have not yet been comprehensively considered in relevant clinical trials. Microbiome composition, markers of systemic inflammation [e.g., neutrophil-to-lymphocyte ratio (NLR)], and human leucocyte antigen (HLA) diversity may influence the efficacy of ICIs. Studies on ICI biomarkers are likely to reveal modifiable tumor or host characteristics, which can be utilized to direct the antitumor immune defense. Examples of the latter approach include tumor priming to immune therapy by cytotoxic drugs and elevation of ICI efficacy by microbiome modification.
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Affiliation(s)
- Evgeny N. Imyanitov
- Department of Tumor Growth Biology, N.N. Petrov Institute of Oncology, 197758 St.-Petersburg, Russia
- Department of Medical Genetics, St.-Petersburg State Pediatric Medical University, 194100 St.-Petersburg, Russia
| | - Elena V. Preobrazhenskaya
- Department of Tumor Growth Biology, N.N. Petrov Institute of Oncology, 197758 St.-Petersburg, Russia
- Department of Medical Genetics, St.-Petersburg State Pediatric Medical University, 194100 St.-Petersburg, Russia
| | - Natalia V. Mitiushkina
- Department of Tumor Growth Biology, N.N. Petrov Institute of Oncology, 197758 St.-Petersburg, Russia
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Azad AD, Zhang JJ, Emerick KS, Shalhout SZ, Kaufman HL, Miller DM, Lee NG, Yoon MK, Freitag SK, Stagner AM, Wolkow N. Immunotherapy for Advanced Conjunctival Squamous Cell Carcinoma: Treatment Failures. Ophthalmic Plast Reconstr Surg 2025:00002341-990000000-00591. [PMID: 40081357 DOI: 10.1097/iop.0000000000002935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2025]
Abstract
PURPOSE To review the treatment response of advanced conjunctival squamous cell carcinoma (SCC) to systemic immune checkpoint inhibitor (ICI) therapy at a single institution. METHODS A retrospective review of patients treated at a single institution from 2015 to 2024 was conducted to identify those with advanced conjunctival SCC who had been treated with ICI therapy. Advanced disease included patients with orbital invasion of tumors, unresectable disease, or metastatic disease. Computed tomography imaging and tumor mutational burden data were evaluated for all patients. RESULTS Five patients with advanced conjunctival SCC were treated with ICIs. All patients had the American Joint Committee on Cancer stage cT3N0M0. All patients had best corrected visual acuity in the affected eye of 20/30 or better at presentation. All patients progressed while on ICIs, with 3 ultimately requiring exenteration at a median time of 6 months from initial diagnosis. One patient had progressive metastatic disease, and one had direct intracranial extension. All patients had low tumor mutational burden. CONCLUSIONS Unlike prior reports demonstrating complete treatment response while on ICI therapy in patients with advanced conjunctival SCC, the current study demonstrates that 5 of 5 patients had disease progression while on ICI therapy. All patients also had low tumor mutational burden. Tumor mutational burden may be important in predicting disease response to ICI in patients with conjunctival SCC; however, given the small number of patients with conjunctival SCC treated with ICI to date, more data are needed to understand the role of ICIs in conjunctival SCC.
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Affiliation(s)
- Amee D Azad
- Ophthalmic Plastic Surgery Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Jia Jia Zhang
- Ophthalmic Plastic Surgery Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Kevin S Emerick
- Department of Otolaryngology-Head and Neck Surgery, Mike Toth Cancer Center, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Sophia Z Shalhout
- Department of Otolaryngology-Head and Neck Surgery, Mike Toth Cancer Center, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Howard L Kaufman
- Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - David M Miller
- Division of Hematology/Oncology Mass General Hospital, Department of Medicine, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Nahyoung G Lee
- Ophthalmic Plastic Surgery Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Michael K Yoon
- Ophthalmic Plastic Surgery Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Suzanne K Freitag
- Ophthalmic Plastic Surgery Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Anna M Stagner
- Department of Ophthalmology, David G. Cogan Laboratory of Ophthalmic Pathology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
| | - Natalie Wolkow
- Ophthalmic Plastic Surgery Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
- Department of Ophthalmology, David G. Cogan Laboratory of Ophthalmic Pathology, Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts, U.S.A
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Jafari P, Forrest M, Segal J, Wang P, Tjota MY. Pan-Cancer Molecular Biomarkers: Practical Considerations for the Surgical Pathologist. Mod Pathol 2025; 38:100752. [PMID: 40058460 DOI: 10.1016/j.modpat.2025.100752] [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: 09/12/2024] [Revised: 02/25/2025] [Accepted: 02/26/2025] [Indexed: 03/29/2025]
Abstract
Traditional anatomic pathologic classification of cancer is based on tissue of origin and morphologic and immunohistochemical characterization of the malignant cells. With the technological improvements of massively parallel or next-generation sequencing, oncogenic drivers that are shared across different tumor types are increasingly being identified and used as pan-cancer biomarkers. This approach is reflected in the growing list of Food and Drug Administration-approved tumor-agnostic therapies, including pembrolizumab in the setting of microsatellite instability and high tumor mutational burden, larotrectinib and entrectinib for solid tumors with NTRK fusions, and combined dabrafenib-trametinib for BRAF V600E-mutated neoplasms. Several other biomarkers are currently under investigation, including fibroblast growth factor receptor (FGFR), RET, and ROS1 fusions; ERBB2 amplification; and mutations in the AKT1/2/3, NF1, RAS pathway and (mitogen-activated protein kinase (MAPK) pathway. As molecular assays are increasingly incorporated into routine tumor workup, the emergence of additional pan-cancer biomarkers is likely to be a matter more of "when" than "if." In this review, we first explore some of the conceptual and technical considerations at the intersection of surgical and molecular pathology, followed by a brief overview of both established and emerging molecular pan-cancer biomarkers and their diagnostic and clinical applications.
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Affiliation(s)
- Pari Jafari
- Department of Pathology, The University of Chicago, Chicago, Illinois
| | - Megan Forrest
- Department of Pathology, The University of Chicago, Chicago, Illinois
| | - Jeremy Segal
- Department of Pathology, The University of Chicago, Chicago, Illinois
| | - Peng Wang
- Department of Pathology, The University of Chicago, Chicago, Illinois
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Dong YM, Bao GQ. Characterization of SUSD3 as a novel prognostic biomarker and therapeutic target for breast cancer. Clin Transl Oncol 2025; 27:935-949. [PMID: 39107655 DOI: 10.1007/s12094-024-03641-y] [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: 06/04/2024] [Accepted: 07/24/2024] [Indexed: 01/03/2025]
Abstract
BACKGROUND Breast cancer (BC) remains a significant global health challenge, contributing substantially to cancer-related deaths worldwide. Its prevalence and associated death rates remain alarmingly high, highlighting the persistent public health burden. The objective of this study was to systematically examine the involvement of SUSD3 (Sushi Domain-Containing 3) in BC, highlighting its crucial role in the pathogenesis and progression of this disease. METHODS BC-related gene microarray data, along with corresponding clinicopathological information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Leveraging TIMER and HPA databases, we conducted comparative analyses to evaluate SUSD3 expression in BC. We then analyzed the association between SUSD3 and clinical traits, as well as the prognostic value of SUSD3. SUSD3-related differential expression genes (DEGs) were sent for analysis utilizing GO, KEGG, and GSEA. We utilized SUSD3 mRNA expression to assess immune cells' scores in BC tissues calculated by single-sample enrichment analyses based on "CIBERSORT" R package. Drug sensitivity analysis was used to screen potential drugs sensitive to SUSD3. R software was used for statistical analyses and graphical representation of the data. RESULTS Our findings confirmed a significant upregulation of SUSD3 expression in BC, which correlated with a favorable prognosis. Clinical correlation analysis further emphasized the strong association between SUSD3 expression and key clinical parameters like estrogen receptor (ER) status, progesterone receptor (PR) status, stage, and T classification in breast cancer. Univariate and multivariate Cox regression analyses showed that SUSD3 could be used as an independent prognostic factor for BC. Differentially expressed genes (DEGs) co-expressed with SUSD3 were significantly associated with various biological processes, such as the cell cycle, DNA replication, p53 signaling pathway, cancer-related pathways, and Wnt signaling pathway, as indicated by gene set enrichment analysis (GSEA). Furthermore, our analysis demonstrated that SUSD3 generally exhibited negative associations with immune modulators. Drug sensitivity analysis revealed positive correlations between SUSD3 and the efficacy of Fulvestrant, Raloxifene, and Fluphenazine. CONCLUSION The research emphasizes the significance of SUSD3 as a potential marker for BC, providing insights into the underlying molecular mechanisms implicated in tumorigenesis. SUSD3 holds promise in helping the classification of breast cancer pathological groups, predicting prognosis, and facilitating targeted therapy.
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Affiliation(s)
- Yan-Ming Dong
- Department of General Surgery, The Second Affiliated Hospital of Air Force Medical University, No. 356 of Xinsi Road, Baqiao District, Xi'an, 710038, Shaanxi, China
| | - Guo-Qiang Bao
- Department of General Surgery, The Second Affiliated Hospital of Air Force Medical University, No. 356 of Xinsi Road, Baqiao District, Xi'an, 710038, Shaanxi, China.
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Wei G, Wang Y, Liu R, Liu L. An integrated machine learning framework for developing and validating a prognostic risk model of gastric cancer based on endoplasmic reticulum stress-associated genes. Biochem Biophys Rep 2025; 41:101891. [PMID: 39698734 PMCID: PMC11653156 DOI: 10.1016/j.bbrep.2024.101891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 11/06/2024] [Accepted: 11/30/2024] [Indexed: 12/20/2024] Open
Abstract
Background Gastric cancer (GC), a prevalent and deadly malignancy, demonstrates poor survival outcomes. Evidence has emerged indicating that disruptions in endoplasmic reticulum homeostasis are significantly implicated in the onset and progression of various oncological conditions. This study was designed to construct a prognostic model based on genes related to endoplasmic reticulum stress(ERS) to predict survival outcomes in patients with GC. Methods Expression profiling data for GC samples were extracted and analyzed from TCGA-STAD, revealing 214 genes related to endoplasmic reticulum stress that show differential expression when compared with normal gastric tissue. Building on these insights, a prognostic model was formulated using data from TCGA-STAD and validated through subsequent analyses of GEO datasets. The tumor immune dysfunction and exclusion(TIDE) algorithm was applied to determine the susceptibility of individuals in high- and low-risk categories to immunotherapy. The presence of immune and stromal cells within the tumor microenvironment was assessed with the aid of the ESTIMATE algorithm. Sensitivity variations to prevalent anticancer drugs between the risk groups were evaluated using the Genomics of Drug Sensitivity in Cancer(GDSC) database, and prospective therapeutic agents were confirmed through molecular docking techniques. Results Thirty-one endoplasmic reticulum stress (ERS)-related differentially expressed genes (DEGs) crucial for prognosis in GC were pinpointed. These DEGs were then used to construct a prognostic model and were considered as independent prognostic factors for GC patients. This risk model proved to have a good predictive performance for estimating the overall survival of these patients. The patients placed into the high-risk group showed worse results and lower sensitivity to immunotherapy. Moreover, five specific targeted therapy drugs, namely BMS-754807, Dasatinib, JQ1, AZD8055 and SB505124, produced better results in the treatment of the high-risk group of patients. Conclusions A new molecular prognostic model associated with ERS was established and validated for GC and showed relatively good discriminative and predictive ability. This model greatly expands the collection of weapons in the armoury of prognostic analysis in GC.
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Affiliation(s)
- Gang Wei
- Emergency Department, The XIJING 986 Hospital of Air Force Medical University, Xi'an, Shaanxi, China
| | - Yan Wang
- Department of Clinical Laboratory, The Second Affiliated Hospital of Air Force Medical University, Xi'an, Shaanxi, China
| | - Ru Liu
- Emergency Department, The XIJING 986 Hospital of Air Force Medical University, Xi'an, Shaanxi, China
| | - Lei Liu
- Emergency Department, The XIJING 986 Hospital of Air Force Medical University, Xi'an, Shaanxi, China
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Chang TG, Spathis A, Schäffer AA, Gavrielatou N, Kuo F, Jia D, Mukherjee S, Sievers C, Economopoulou P, Anastasiou M, Moutafi M, Pal LR, Vos J, Lee AS, Lam S, Zhao K, Jiang P, Allen CT, Foukas P, Gomatou G, Altan-Bonnet G, Morris LGT, Psyrri A, Ruppin E. Tumor and blood B-cell abundance outperforms established immune checkpoint blockade response prediction signatures in head and neck cancer. Ann Oncol 2025; 36:309-320. [PMID: 39551185 PMCID: PMC11845298 DOI: 10.1016/j.annonc.2024.11.008] [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: 07/19/2024] [Revised: 11/04/2024] [Accepted: 11/08/2024] [Indexed: 11/19/2024] Open
Abstract
BACKGROUND Immunotherapy has improved the outcomes for some patients with head and neck squamous-cell carcinoma (HNSCC). However, the low and variable response rates observed highlight the need for robust response biomarkers to select patients for treatment. PATIENTS AND METHODS We assembled and analyzed a large HNSCC dataset, encompassing 11 clinical cohorts including 1232 patient samples, spanning a variety of disease subtypes and immune checkpoint blockade (ICB) treatment types, tissue sources, data modalities, and timing of measurements. We conducted a comprehensive evaluation of the predictive power of various cell types, traditional biomarkers, and emerging predictors in both blood and tumor tissues of HNSCC patients. RESULTS Tumor B-cell infiltration emerged as a strong and robust predictor of both patient survival and ICB response. It outperformed all other established biomarkers of response to ICB, including the tertiary lymphoid structure signature and numerous T-cell-based signatures. B-cell infiltration was associated with a 'hot' antitumor microenvironment that promotes tumor eradication. Furthermore, B-cell levels in peripheral blood mononuclear cells (PBMCs) correlated strongly with tumor B-cell levels and demonstrated high predictive value for ICB response, with high odds ratios (≥7.8) in two independent clinical cohorts. CONCLUSION B-cell abundance, whether assessed in PBMCs or tumor tissues, is one of the strongest predictors of ICB response in HNSCC. For translation to patient care, measuring B-cell abundance in PBMCs via cytometry offers a practical and accessible tool for clinical decision making.
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Affiliation(s)
- T-G Chang
- Cancer Data Science Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA
| | - A Spathis
- Department of Pathology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - A A Schäffer
- Cancer Data Science Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA
| | - N Gavrielatou
- Internal Medicine/Section of Department of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - F Kuo
- Department of Surgery and Cancer Immunogenomics Research Program, Memorial Sloan Kettering Cancer Center, New York, USA
| | - D Jia
- Immunodynamics Group, Laboratory of Integrative Cancer Immunology, CCR, NCI, Bethesda, USA
| | - S Mukherjee
- Cancer Data Science Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA
| | - C Sievers
- Surgical Oncology Program, CCR, NCI, NIH, Bethesda, USA
| | - P Economopoulou
- Internal Medicine/Section of Department of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - M Anastasiou
- Internal Medicine/Section of Department of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - M Moutafi
- Internal Medicine/Section of Department of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - L R Pal
- Cancer Data Science Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA
| | - J Vos
- Department of Surgery and Cancer Immunogenomics Research Program, Memorial Sloan Kettering Cancer Center, New York, USA
| | - A S Lee
- Department of Surgery and Cancer Immunogenomics Research Program, Memorial Sloan Kettering Cancer Center, New York, USA
| | - S Lam
- Department of Surgery and Cancer Immunogenomics Research Program, Memorial Sloan Kettering Cancer Center, New York, USA
| | - K Zhao
- Department of Surgery and Cancer Immunogenomics Research Program, Memorial Sloan Kettering Cancer Center, New York, USA
| | - P Jiang
- Cancer Data Science Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA
| | - C T Allen
- Surgical Oncology Program, CCR, NCI, NIH, Bethesda, USA; Center for Immune-Oncology, CCR, NCI, NIH, Bethesda, USA
| | - P Foukas
- Department of Pathology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - G Gomatou
- Internal Medicine/Section of Department of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece
| | - G Altan-Bonnet
- Immunodynamics Group, Laboratory of Integrative Cancer Immunology, CCR, NCI, Bethesda, USA
| | - L G T Morris
- Department of Surgery and Cancer Immunogenomics Research Program, Memorial Sloan Kettering Cancer Center, New York, USA.
| | - A Psyrri
- Internal Medicine/Section of Department of Medical Oncology, Attikon University Hospital, National Kapodistrian University of Athens, Athens, Greece.
| | - E Ruppin
- Cancer Data Science Laboratory, Center for Cancer Research (CCR), National Cancer Institute (NCI), National Institutes of Health (NIH), Bethesda, USA.
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Mosalem O, Tan W, Bryce AH, Dronca RS, Childs DS, Pagliaro LC, Orme JJ, Kase AM. A real-world experience of pembrolizumab monotherapy in microsatellite instability-high and/or tumor mutation burden-high metastatic castration-resistant prostate cancer: outcome analysis. Prostate Cancer Prostatic Dis 2025; 28:138-144. [PMID: 38341460 DOI: 10.1038/s41391-024-00799-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Revised: 01/18/2024] [Accepted: 01/23/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND The efficacy of pembrolizumab monotherapy in metastatic castration-resistant prostate cancer patients (mCRPC) when stratified by MSI-H and/or TMB-H is poorly defined. Additionally, outcomes based on sequencing source (i.e., tissue or liquid biopsy) have not been well described. We sought to assess outcomes of pembrolizumab monotherapy in patients with mCRPC and compare efficacy based on MSI-H and/or TMB-H when identified by tissue or liquid biopsy. METHODS A retrospective analysis was performed of mCRPC patients treated at Mayo Clinic with pembrolizumab monotherapy between 2018 and 2023. Objective response rates (ORR), median progression-free survival (mPFS), and overall survival (mOS), were determined by RECIST v1.1 criteria. RESULTS Twenty-two patients with mCRPC received pembrolizumab monotherapy for at least 3 cycles for a MSI-H or TMB-H indication. All patients had next generation sequencing (NGS) performed via tissue (n = 11) or liquid (n = 10) biopsy source. The ORR was 50% (27.3% complete response and 22.7% had partial response). The mPFS for TMB 10-14.9 mut/Mb (n = 4), TMB 15-24.9 mut/Mb (n = 6), and TMB ≥ 25 mut/Mb (n = 10) was 2.1, not reached (NR), and NR, respectively (p = 0.0003). The mOS for these same groups was 5.1 months, 20.5 months, and not reached, respectively. Among patients with TMB-H without co-occurring MSI-H or CDK12 (n = 6), none experienced a response and only one patient had stable disease compared to patients with MSI-H (n = 12) for whom the ORR was 75%. Immunotherapy responsive alterations such as ATRX and PTCH1 mutations were frequently noticed among patients who had complete response (CR). CONCLUSIONS Our hypothesis-generating study suggests that MSI-H drives the efficacy of pembrolizumab in mCRPC with better survival outcomes as TMB increases. Clinicians should consider alternative treatment strategies for advanced prostate cancer when TMB-H is present without co-occurring MSI-H or CDK12.
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Affiliation(s)
- Osama Mosalem
- Division of Hematology and Oncology, Department of Internal Medicine, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Winston Tan
- Division of Hematology and Oncology, Department of Internal Medicine, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Alan H Bryce
- Division of Hematology and Oncology, Department of Internal Medicine, Mayo Clinic, Phoenix, AZ, 85054, USA
| | - Roxana S Dronca
- Division of Hematology and Oncology, Department of Internal Medicine, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Daniel S Childs
- Department of Medical Oncology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Lance C Pagliaro
- Department of Medical Oncology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Jacob J Orme
- Department of Medical Oncology, Mayo Clinic, Rochester, MN, 55902, USA
| | - Adam M Kase
- Division of Hematology and Oncology, Department of Internal Medicine, Mayo Clinic, Jacksonville, FL, 32224, USA.
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Hua Y, Wang A, Xie C, Agrafiotis AC, Zhang P, Li B. Clinical-genomic nomogram for predicting sensitivity to second-line immunotherapy for advanced non-small cell lung cancer. Transl Lung Cancer Res 2025; 14:526-537. [PMID: 40114939 PMCID: PMC11921187 DOI: 10.21037/tlcr-2024-1249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2024] [Accepted: 02/18/2025] [Indexed: 03/22/2025]
Abstract
Background The introduction of immune checkpoint inhibitors (ICIs) has significantly improved the outcomes of patients with advanced non-small cell lung cancer (NSCLC). However, ICIs only benefit a subset of patients. The study aimed to identify genomic biomarkers and construct models to predict the response to second-line ICI therapy. Methods We retrospectively collected clinical data and genetic testing results from patients with NSCLC treated with second-line ICI at a single medical center between August 2018 and June 2021. We reanalyzed the raw sequence data of clinical genetic testing and defined the common detection region among the different testing panels. Immunotherapy sensitivity was evaluated using the immune-based Response Evaluation Criteria in Solid Tumors. Results We included 102 patients as a training cohort and 46 as a test cohort. In the training cohort, we examined the relationship between ICI response and the mutation status of 343 genes. Mutations in the EGFR gene were significantly more common in the resistant group than in the sensitive group (41.0% vs. 20.6%; P=0.04), while mutations in the EP300 gene were associated with greater sensitivity to ICIs (39.7% vs. 15.4%; P=0.01). A nomogram was built based on clinical variables, genomic data, and programmed death-ligand 1 (PD-L1) expression. The total nomogram points were significantly higher in the sensitive group than in the resistance group in both cohorts, and the areas under the receiver operating characteristic curve were 0.780 in the training cohort and 0.720 in the test cohort. The higher nomogram points also indicated better progression-free survival. Conclusions Based on real-world clinical settings, the clinical genomic nomogram, which involved limited input variables that were economical and easy to obtain, demonstrated a good ability to predict the response to second-line ICI treatment in advanced NSCLC.
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Affiliation(s)
- Ying Hua
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
- Department of Radiation Oncology, Tianjin Medical University, Tianjin, China
- Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Ai Wang
- Department of Oncology, Heze Hospital of Traditional Chinese Medicine, Heze, China
| | - Chao Xie
- Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Apostolos C Agrafiotis
- Department of Thoracic Surgery, Saint-Pierre University Hospital, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Pinlang Zhang
- Department of Medical Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Baosheng Li
- Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China
- Department of Radiation Oncology, Tianjin Medical University, Tianjin, China
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
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Shi R, Sun J, Zhou Z, Shi M, Wang X, Gao Z, Zhao T, Li M, Shu Y. Integration of multiple machine learning approaches develops a gene mutation-based classifier for accurate immunotherapy outcomes. NPJ Precis Oncol 2025; 9:54. [PMID: 40011681 DOI: 10.1038/s41698-025-00842-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Accepted: 02/17/2025] [Indexed: 02/28/2025] Open
Abstract
In addition to traditional biomarkers like PD-(L)1 expression and tumor mutation burden (TMB), more reliable methods for predicting immune checkpoint blockade (ICB) response in cancer patients are urgently needed. This study utilized multiple machine learning approaches on nonsynonymous mutations to identify key mutations that are most significantly correlated to ICB response. We proposed a classifier, Gene mutation-based Predictive Signature (GPS), to categorize patients based on their predicted response and clinical outcomes post-ICB therapy. GPS outperformed conventional predictors when validated in independent cohorts. Multi-omics analysis and multiplex immunohistochemistry (mIHC) revealed insights into tumor immunogenicity, immune responses, and the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) across different GPS groups. Finally, we validated distinct responses of different GPS samples to ICB in an ex-vivo tumor organoid-PBMC co-culture model. Overall, our findings highlight a simple, robust classifier for accurate ICB response prediction, which could reduce costs, shorten testing times, and facilitate clinical implementation.
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Affiliation(s)
- Run Shi
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Jing Sun
- Department of Endocrinology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- The First Clinical Medical College of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zhaokai Zhou
- Department of Urology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Meiqi Shi
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China
| | - Xin Wang
- Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China
| | - Zhaojia Gao
- Department of Thoracic Surgery, The Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University, Changzhou, China
| | - Tianyu Zhao
- Institute and Clinic for Occupational, Social and Environmental Medicine, LMU University Hospital Munich, Munich, Germany
| | - Minglun Li
- Department of Radiation Oncology, Lueneburg Municipal Hospital, Lueneburg, Germany
| | - Yongqian Shu
- Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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Kuras M, Betancourt LH, Hong R, Szadai L, Rodriguez J, Horvatovich P, Pla I, Eriksson J, Szeitz B, Deszcz B, Welinder C, Sugihara Y, Ekedahl H, Baldetorp B, Ingvar C, Lundgren L, Lindberg H, Oskolas H, Horvath Z, Rezeli M, Gil J, Appelqvist R, Kemény LV, Malm J, Sanchez A, Szasz AM, Pawłowski K, Wieslander E, Fenyö D, Nemeth IB, Marko-Varga G. Proteogenomic Profiling of Treatment-Naïve Metastatic Malignant Melanoma. Cancers (Basel) 2025; 17:832. [PMID: 40075679 PMCID: PMC11899103 DOI: 10.3390/cancers17050832] [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: 01/24/2025] [Accepted: 02/12/2025] [Indexed: 03/14/2025] Open
Abstract
BACKGROUND Melanoma is a highly heterogeneous disease, and a deeper molecular classification is essential for improving patient stratification and treatment approaches. Here, we describe the histopathology-driven proteogenomic landscape of 142 treatment-naïve metastatic melanoma samples to uncover molecular subtypes and clinically relevant biomarkers. METHODS We performed an integrative proteogenomic analysis to identify proteomic subtypes, assess the impact of BRAF V600 mutations, and study the molecular profiles and cellular composition of the tumor microenvironment. Clinical and histopathological data were used to support findings related to tissue morphology, disease progression, and patient outcomes. RESULTS Our analysis revealed five distinct proteomic subtypes that integrate immune and stromal microenvironment components and correlate with clinical and histopathological parameters. We demonstrated that BRAF V600-mutated melanomas exhibit biological heterogeneity, where an oncogene-induced senescence-like phenotype is associated with improved survival. This led to a proposed mortality risk-based stratification that may contribute to more personalized treatment strategies. Furthermore, tumor microenvironment composition strongly correlated with disease progression and patient outcomes, highlighting a histopathological connective tissue-to-tumor ratio assessment as a potential decision-making tool. We identified a melanoma-associated SAAV signature linked to extracellular matrix remodeling and SAAV-derived neoantigens as potential targets for anti-tumor immune responses. CONCLUSIONS This study provides a comprehensive stratification of metastatic melanoma, integrating proteogenomic insights with histopathological features. The findings may aid in the development of tailored diagnostic and therapeutic strategies, improving patient management and outcomes.
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Affiliation(s)
- Magdalena Kuras
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Lazaro Hiram Betancourt
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, 221 00 Lund, Sweden; (C.W.); (B.B.); (L.L.); (H.O.)
| | - Runyu Hong
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; (R.H.); (D.F.)
- Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Leticia Szadai
- Department of Dermatology and Allergology, University of Szeged, 6720 Szeged, Hungary; (L.S.); (I.B.N.)
| | - Jimmy Rodriguez
- Department of Biochemistry and Biophysics, Karolinska Institute, 171 77 Stockholm, Sweden;
| | - Peter Horvatovich
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
- Department of Analytical Biochemistry, Faculty of Science and Engineering, University of Groningen, 9712 CP Groningen, The Netherlands
| | - Indira Pla
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Jonatan Eriksson
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Beáta Szeitz
- Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, 1085 Budapest, Hungary
| | - Bartłomiej Deszcz
- Department of Biochemistry and Microbiology, Warsaw University of Life Sciences, 02-787 Warsaw, Poland;
| | - Charlotte Welinder
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, 221 00 Lund, Sweden; (C.W.); (B.B.); (L.L.); (H.O.)
| | - Yutaka Sugihara
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Henrik Ekedahl
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, 221 00 Lund, Sweden; (C.W.); (B.B.); (L.L.); (H.O.)
- SUS University Hospital Lund, 222 42 Lund, Sweden;
| | - Bo Baldetorp
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, 221 00 Lund, Sweden; (C.W.); (B.B.); (L.L.); (H.O.)
| | - Christian Ingvar
- SUS University Hospital Lund, 222 42 Lund, Sweden;
- Department of Surgery, Clinical Sciences, Lund University, SUS, 221 00 Lund, Sweden
| | - Lotta Lundgren
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, 221 00 Lund, Sweden; (C.W.); (B.B.); (L.L.); (H.O.)
- SUS University Hospital Lund, 222 42 Lund, Sweden;
| | - Henrik Lindberg
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Henriett Oskolas
- Department of Clinical Sciences Lund, Division of Oncology, Lund University, 221 00 Lund, Sweden; (C.W.); (B.B.); (L.L.); (H.O.)
| | - Zsolt Horvath
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Melinda Rezeli
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Jeovanis Gil
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
| | - Roger Appelqvist
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
| | - Lajos V. Kemény
- HCEMM-SU Translational Dermatology Research Group, Semmelweis University, 1085 Budapest, Hungary;
- Department of Dermatology, Venereology and Dermatooncology, Faculty of Medicine, Semmelweis University, 1085 Budapest, Hungary
- Department of Physiology, Faculty of Medicine, Semmelweis University, 1085 Budapest, Hungary
- MTA-SE Lendület “Momentum” Dermatology Research Group, Hungarian Academy of Sciences and Semmelweis University, 1085 Budapest, Hungary
| | - Johan Malm
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
| | - Aniel Sanchez
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
| | | | - Krzysztof Pawłowski
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
- Department of Biochemistry and Microbiology, Warsaw University of Life Sciences, 02-787 Warsaw, Poland;
- Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elisabet Wieslander
- Department of Translational Medicine, Lund University, Skåne University Hospital Malmö, 214 28 Malmö, Sweden; (M.K.); (J.G.); (J.M.); (A.S.); (K.P.)
| | - David Fenyö
- Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY 10016, USA; (R.H.); (D.F.)
- Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY 10016, USA
| | - Istvan Balazs Nemeth
- Department of Dermatology and Allergology, University of Szeged, 6720 Szeged, Hungary; (L.S.); (I.B.N.)
| | - György Marko-Varga
- Department of Biomedical Engineering, Lund University, 221 00 Lund, Sweden; (P.H.); (I.P.); (J.E.); (Y.S.); (H.L.); (M.R.); (R.A.); (G.M.-V.)
- Chemical Genomics Global Research Lab, Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 03722, Republic of Korea
- 1st Department of Surgery, Tokyo Medical University, Tokyo 160-8402, Japan
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Eklund EA, Svensson J, Näslund LS, Yhr M, Sayin SI, Wiel C, Akyürek LM, Torstensson P, Sayin VI, Hallqvist A, Raghavan S, Rohlin A. Comprehensive genetic variant analysis reveals combination of KRAS and LRP1B as a predictive biomarker of response to immunotherapy in patients with non-small cell lung cancer. J Exp Clin Cancer Res 2025; 44:75. [PMID: 40011914 PMCID: PMC11866712 DOI: 10.1186/s13046-025-03342-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2024] [Accepted: 02/20/2025] [Indexed: 02/28/2025] Open
Abstract
BACKGROUND In non-small cell lung cancer (NSCLC), the rapid advancement of predictive genetic testing of tumors by identifying specific pathogenic driver variants has significantly improved treatment guidance. However, immune checkpoint blockade (ICB) is typically administered to patients with tumors in the absence of such driver variants. Since only about 30% of patients will respond to ICB treatment, identifying novel genetic biomarkers of clinical response is crucial and will improve treatment decisions. This prospective clinical study aims to combine molecular biology, advanced bioinformatics and clinical data on response to treatment with ICB from a prospective cohort of NSCLC patients to identify single or combination of genetic variants in the tumor that can serve as predictive biomarkers of clinical response. METHODS In this prospective bi-center clinical study, we performed next-generation sequencing (NGS) of 597 cancer-associated genes in a prospective cohort of 49 patients as the final cohort analyzed, with stage III or IV NSCLC, followed by establishment of an in-house developed bioinformatics-based molecular classification method that integrates, interprets and evaluates data from multiple databases and variant prediction tools. Overall survival (OS) and progression-free survival (PFS) were analyzed for selected candidate genes and variants identified using our novel methodology including molecular tools, databases and clinical information. RESULTS Our novel molecular interpretation and classification method identified high impact variants in frequently altered genes KRAS, LRP1B, and TP53. Analysis of these genes as single predictive biomarkers in ICB-treated patients revealed that the presence of likely pathogenic variants and variants of unclear significance in LRP1B was associated with improved OS (p = 0.041). Importantly, further analysis of variant combinations in the tumor showed that co-occurrence of KRAS and LRP1B variants significantly improved OS (p = 0.003) and merged PFS (p = 0.008). Notably, the triple combination of variants in KRAS, LRP1B, and TP53 positively impacted both OS (p = 0.026) and merged PFS (p = 0.003). CONCLUSIONS This study suggests that combination of the LRP1B and KRAS variants identified through our novel molecular classification scheme leads to better outcomes following ICB treatment in NSCLC. The addition of TP53 improves the outcome even further. To our knowledge, this is the first report indicating that harboring a combination of KRAS, LRP1B, and TP53 variants can significantly enhance the response to ICB, suggesting a novel predictive biomarker combination for NSCLC patients.
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Affiliation(s)
- Ella A Eklund
- Sahlgrenska Center for Cancer Research, Department of Surgery, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Johanna Svensson
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Laboratory Medicine, Institute for Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Louise Stauber Näslund
- Department of Clinical Pathology, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Maria Yhr
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Laboratory Medicine, Institute for Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sama I Sayin
- Sahlgrenska Center for Cancer Research, Department of Surgery, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Clotilde Wiel
- Sahlgrenska Center for Cancer Research, Department of Surgery, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
| | - Levent M Akyürek
- Department of Clinical Pathology, Institute for Biomedicine, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Per Torstensson
- Department of Pulmonary Medicine, Skaraborg Hospital, Skövde, Sweden
| | - Volkan I Sayin
- Sahlgrenska Center for Cancer Research, Department of Surgery, Institute of Clinical Sciences, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Andreas Hallqvist
- Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Oncology, Institute for Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sukanya Raghavan
- Department of Microbiology and Immunology, Sahlgrenska Center for Cancer Research, Institute for Biomedicine, University of Gothenburg, Gothenburg, Sweden
- Department of Clinical Immunology and Transfusion Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Anna Rohlin
- Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg, Sweden.
- Department of Laboratory Medicine, Institute for Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
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Tang WW, Battistone B, Bauer KM, Weis AM, Barba C, Fadlullah MZH, Ghazaryan A, Tran VB, Lee SH, Agir ZB, Nelson MC, Victor ES, Thibeaux A, Hernandez C, Tantalla J, Tan AC, Rao D, Williams M, Drummond MJ, Beswick EJ, Round JL, Ekiz HA, Voth WP, O'Connell RM. A microRNA-regulated transcriptional state defines intratumoral CD8 + T cells that respond to immunotherapy. Cell Rep 2025; 44:115301. [PMID: 39951377 PMCID: PMC11924119 DOI: 10.1016/j.celrep.2025.115301] [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: 08/04/2024] [Revised: 11/24/2024] [Accepted: 01/22/2025] [Indexed: 02/16/2025] Open
Abstract
The rising incidence of advanced-stage colorectal cancer (CRC) and poor survival outcomes necessitate new and effective therapies. Immune checkpoint inhibitors (ICIs), specifically anti-PD-1 therapy, show promise, yet clinical determinants of a positive response are suboptimal. Here, we identify microRNA-155 (miR-155) as necessary for CD8+ T cell-infiltrated tumors through an unbiased in vivo CRISPR-Cas9 screen identifying functional tumor antigen-specific CD8+ T cell-expressed microRNAs. T cell miR-155 is required for anti-PD-1 responses and for a vital intratumor CD8+ T cell differentiation cascade by repressing Ship-1, inhibiting Tcf-1 and stemness, and subsequently enhancing Cxcr6 expression, anti-tumor immunity, and effector functions. Based on an underlying miR-155-dependent CD8+ T cell transcriptional profile, we identify a gene signature that predicts ICI responses across 12 diverse cancers. Together, our findings support a model whereby miR-155 serves as a central regulator of CD8+ T cell-dependent cancer immunity and ICI responses that may be leveraged for future therapeutics.
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Affiliation(s)
- William W Tang
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Ben Battistone
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Kaylyn M Bauer
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Allison M Weis
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Cindy Barba
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Muhammad Zaki Hidayatullah Fadlullah
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Arevik Ghazaryan
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Van B Tran
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Soh-Hyun Lee
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Z Busra Agir
- Department of Molecular Biology and Genetics, İzmir Institute of Technology, İzmir, Turkey
| | - Morgan C Nelson
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Emmanuel Stephen Victor
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Amber Thibeaux
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Colton Hernandez
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Jacob Tantalla
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Aik C Tan
- Department of Oncological Sciences, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Dinesh Rao
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Matthew Williams
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Micah J Drummond
- Department of Physical Therapy and Athletic Training, University of Utah, Salt Lake City, UT 84108, USA
| | - Ellen J Beswick
- Division of Digestive Disease and Nutrition, Department of Internal Medicine, University of Kentucky, Lexington, KY 40508, USA
| | - June L Round
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - H Atakan Ekiz
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Department of Molecular Biology and Genetics, İzmir Institute of Technology, İzmir, Turkey; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Warren P Voth
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
| | - Ryan M O'Connell
- Department of Pathology, Division of Microbiology and Immunology, University of Utah, Salt Lake City, UT 84112, USA; Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Lv D, Lan B, Guo Q, Yi Z, Qian H, Guan Y, Peng X, Chen T, Ma F. Exploration of the clonal evolution and construction of the tumor clonal evolution rate as a prognostic indicator in metastatic breast cancer. BMC Med 2025; 23:122. [PMID: 40001125 PMCID: PMC11863457 DOI: 10.1186/s12916-025-03959-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Accepted: 02/18/2025] [Indexed: 02/27/2025] Open
Abstract
BACKGROUND Tumor heterogeneity and clonal evolution are related to the treatment resistance and disease progression in metastatic breast cancer (MBC). However, the process of clonal evolution and their relationship to prognosis remain unclear. This study aimed to elucidate the evolution of MBC through circulating tumor DNA (ctDNA) analysis and to develop a novel indicator for predicting treatment efficacy and prognosis. METHODS This multicenter retrospective study enrolled MBC patients who underwent next-generation sequencing between April 2016 and October 2022. The clonal evolution of tumors was inferred using PyClone and CITUP software. RESULTS The study included 406 MBC patients. A cohort of 139 patients from the National Cancer Center served as the training cohort, while 267 patients from other centers comprised the validation cohort. In the training cohort, clonal analysis revealed that most MBCs exhibited branched clonal evolution, while a minority showed linear evolution. The branched evolution pattern was associated with slower disease progression (HR, 0.53; 95% CI, 0.32-0.87; P = 0.012). We introduced tumor clonal evolution rate (TER) as a novel concept to reflect the speed of clonal evolution. Survival analysis demonstrated that compared to the TER-high group, patients in the TER-low group had better progression-free survival (PFS) (HR, 0.62; 95% CI, 0.40-0.96; P = 0.033) and overall survival (OS) (HR, 0.45; 95% CI, 0.24-0.85; P = 0.013). Similarly, in the validation cohort, although the median OS was not reached, patients in the TER-low group had better prognosis compared to those in the TER-high group (HR, 0.41; 95% CI, 0.21-0.83; P < 0.001). CONCLUSIONS Patients with branched evolution have better treatment efficacy than those with linear evolution. The TER shows potential as a biomarker for treatment efficacy and prognosis, providing new evidence that ctDNA is a valuable molecular indicator for predicting treatment outcomes in metastatic breast cancer.
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Affiliation(s)
- Dan Lv
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Bo Lan
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Qihan Guo
- Department of Computer Science and Technology & Institute of Artificial Intelligence & BNRist, Tsinghua University, Beijing, 100084, China
| | - Zongbi Yi
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Haili Qian
- State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Yanfang Guan
- Geneplus-Beijing Institute, Beijing, 102206, China
| | - Xuenan Peng
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China
| | - Ting Chen
- Department of Computer Science and Technology & Institute of Artificial Intelligence & BNRist, Tsinghua University, Beijing, 100084, China.
| | - Fei Ma
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
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Zheng M. Clinical metric of tumor mutational burden depicts colorectal cancer patients at the extremes. Clin Transl Oncol 2025:10.1007/s12094-025-03873-6. [PMID: 39984774 DOI: 10.1007/s12094-025-03873-6] [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: 11/14/2024] [Accepted: 02/08/2025] [Indexed: 02/23/2025]
Abstract
PURPOSE Rare cases of colorectal cancer patients with exceptionally good or poor prognosis often remain overlooked, limiting insights into prognostic factors and underlying mechanisms. METHODS This study developed an analytical framework to investigate cancer patients at the extremes using tumor mutational burden (TMB). By analyzing data from 1277 colorectal cancer patients who did not receive immunotherapy, this analysis assessed how patient survival varies with a broad range of TMB levels. RESULTS Among patients with TMB ≤ 10 mutations per megabase (mut/Mb), increasing TMB was associated with worse survival outcomes. In contrast, patients with TMB > 10 mut/Mb showed increasingly improved survival. Notably, a small subgroup (3.83%) with TMB > 60 mut/Mb had significantly better survival outcomes. CONCLUSIONS These findings highlight TMB's dual role in colorectal cancer progression. This study suggests that atypical patients can coexist within the same "disease continuum" with typical patients, under the universal context unified by a shared cancer hallmark. TMB provides a useful biomarker for identifying these extremes, offering a clinical metric to better predict patient outcomes and personalize treatment strategies.
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Affiliation(s)
- Ming Zheng
- Beijing Institute of Basic Medical Sciences, 27 Taiping Road, Beijing, 100850, China.
- Academy of Military Medical Sciences, 27 Taiping Road, Beijing, 100850, China.
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43
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Boll LM, Vázquez Montes de Oca S, Camarena ME, Castelo R, Bellmunt J, Perera-Bel J, Albà MM. Predicting immunotherapy response of advanced bladder cancer through a meta-analysis of six independent cohorts. Nat Commun 2025; 16:1213. [PMID: 39979258 PMCID: PMC11842772 DOI: 10.1038/s41467-025-56462-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Accepted: 01/14/2025] [Indexed: 02/22/2025] Open
Abstract
Advanced bladder cancer patients show very variable responses to immune checkpoint inhibitors (ICIs) and effective strategies to predict response are still lacking. Here we integrate mutation and gene expression data from 707 advanced bladder cancer patients treated with anti-PD-1/anti-PD-L1 to build highly accurate predictive models. We find that, in addition to tumor mutational burden (TMB), enrichment in the APOBEC mutational signature, and the abundance of pro-inflammatory macrophages, are major factors associated with the response. Paradoxically, patients with high immune infiltration do not show an overall better response. We show that this can be explained by the activation of immune suppressive mechanisms in a large portion of these patients. In the case of non-immune-infiltrated cancer subtypes, we uncover specific variables likely to be involved in the response. Our findings provide information for advancing precision medicine in patients with advanced bladder cancer treated with immunotherapy.
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Affiliation(s)
| | | | | | - Robert Castelo
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Joaquim Bellmunt
- Hospital del Mar Research Institute (HMRIB), Barcelona, Spain.
- Dana Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
| | | | - M Mar Albà
- Hospital del Mar Research Institute (HMRIB), Barcelona, Spain.
- Catalan Institute for Research and Advanced Studies (ICREA), Barcelona, Spain.
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Yang P, He S, Fan L, Ye L, Weng H. Risk factors for immunoresistance in advanced non-small cell lung cancer and the advantages of targeted therapy in improving prognosis. Am J Cancer Res 2025; 15:573-586. [PMID: 40084370 PMCID: PMC11897627 DOI: 10.62347/fgay1920] [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: 10/17/2024] [Accepted: 01/17/2025] [Indexed: 03/16/2025] Open
Abstract
OBJECTIVES The advent of immunotherapy has transformed the therapeutic landscape for advanced non-small cell lung cancer (NSCLC); nonetheless, the emergence of resistance to immunotherapy poses a considerable obstacle. Our research sought to identify factors contributing to immunotherapy resistance and to assess the effectiveness of subsequent treatments in patients with advanced NSCLC who have been exposed to immune checkpoint inhibitors (ICIs). METHODS This retrospective study analyzed data from 232 individuals with advanced NSCLC who were treated with ICIs during January 2020 to December 2023. Based on their response to ICIs, these patients were classified into two groups: immunoresistance group (IM group) and non-immunoresistance group (NIM group). Data collected included demographics, clinical parameters, cytokine profiles, tumor mutational burden (TMB), PD-L1 expression, overall survival (OS), progression-free survival (PFS), and adverse events. The association between risk factors and immunoresistance were assessed, and second-line treatment outcomes were evaluated. RESULTS Key risk factors for immunoresistance included lower TMB, higher levels of interleukin-10 (IL-10), and PD-L1 expression ≥ 50%. TMB was inversely correlated with immunoresistance (rho = -0.838, P < 0.001). In multivariate analysis, IL-10 remained a significant risk factor (OR = 33.654, P = 0.021), whereas TMB was protective (OR = 0.786, P < 0.001). Second-line targeted therapy significantly improved OS (8.72 ± 2.02 months) and PFS (5.37 ± 2.15 months) compared to chemotherapy (OS: 7.93 ± 2.13 months; PFS: 4.86 ± 1.68 months) (P < 0.05). The targeted therapy group experienced distinct side effects, notably increased hypertension and hand-foot syndrome, while chemotherapy group had higher rates of fatigue (P < 0.05). CONCLUSION Immunoresistance in advanced NSCLC is influenced by IL-10, TMB, and PD-L1 expression. Targeted therapies offer superior outcomes than chemotherapy, though side effect management remains crucial.
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Affiliation(s)
- Ping Yang
- Department of Respiratory and Critical Care Medicine, The People’s Hospital Affiliated to Fujian University of Traditional Chinese MedicineFuzhou 350000, Fujian, China
| | - Shangxiang He
- Department of Medical Oncology, Shanghai GoBroad Cancer Hospital, China Pharmaceutical UniversityShanghai 200100, China
| | - Linyin Fan
- Department of Radiology, Zhejiang Cancer HospitalHangzhou 310022, Zhejiang, China
| | - Ling Ye
- Department of Respiratory and Critical Care Medicine, The People’s Hospital Affiliated to Fujian University of Traditional Chinese MedicineFuzhou 350000, Fujian, China
| | - Heng Weng
- Department of Respiratory and Critical Care Medicine, The People’s Hospital Affiliated to Fujian University of Traditional Chinese MedicineFuzhou 350000, Fujian, China
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Xu K, Han D, Fan Z, Li Y, Liu S, Liao Y, Zhou H, Wu Q, Li S. B-cell signatures characterize the immune landscape and predict LUAD prognosis via the integration of scRNA-seq and bulk RNA-seq. Sci Rep 2025; 15:5453. [PMID: 39953119 PMCID: PMC11828960 DOI: 10.1038/s41598-025-89213-8] [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: 08/22/2024] [Accepted: 02/04/2025] [Indexed: 02/17/2025] Open
Abstract
Lung adenocarcinoma (LUAD) is the most common type of lung cancer, accounting for approximately 35-40% of lung cancers, and the overall survival time of patients with LUAD is still very poor. B cells are important effector cells of adaptive immunity, and B-cell infiltration increases in various tumors. The role of B cells in LUAD is still largely unknown. Therefore, it is particularly important to clarify the role of B cells in LUAD. GSE164983, GSE50081, GSE37745 and GSE30219 were obtained from the GEO database. The TCGA-LUAD dataset was obtained from the TCGA database. UMAP was used to perform clustering descending and subgroup identification on single-cell RNA-sequencing (scRNA-seq) data to obtain B-cell markers. The TCGA cohort was used to obtain differentially expressed genes (DEGs). B-cell-related differentially expressed genes (BRGs) were identified through the intersection of B-cell markers and DEGs. The LASSO method was used to identify characteristic genes of BRGs and construct a prognostic risk model. LUAD patients were divided into high-risk and low-risk groups based on risk scores, and the immune landscape of the two groups was evaluated. We also analyzed the differences in clinical characteristics, mutations, immunotherapy, and drug sensitivity between the two groups. Thirty BRGs were obtained, and 6 characteristic genes were identified. Based on the characteristic genes, a prognostic risk model was constructed. According to the prognostic risk model, LUAD patients were divided into two groups: high-risk group and low-risk group. Patients in the high-risk group had worse outcomes and shorter survival times. Low-risk patients had better survival, while patients with high TNM stage accounted for a greater proportion of patients in the high-risk group. In addition, high-risk patients had a greater probability of mutation and worse immunotherapy response. Finally, we found different susceptibility profiles between the high-risk and low-risk groups. The prognostic risk model built based on the BRGs had good predictive performance, providing a new perspective on the prognosis and immunotherapy of LUAD patients and a new reference for LUAD research.
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Affiliation(s)
- Kexin Xu
- Faculty of Chinese Medicine, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China
| | - Di Han
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China
| | - Zhengyuan Fan
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China
| | - Ya Li
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China
| | - Suxiao Liu
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China
| | - Yixi Liao
- Faculty of Chinese Medicine, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China
| | - Hua Zhou
- Chinese Medicine Guangdong Laboratory (Hengqin Laboratory), Guangdong-Macao ln-Depth Cooperation Zone in Hengqin, 519000, Hengqin, P.R. China.
- State Key Laboratory of Traditional Chinese Medicine Syndrome, The Second Affiliated Hospital of Guangzhou, Guangdong Provincial Hospital of Chinese Medicine, Guangdong Provincial Academy of Chinese Medical Sciences, University of Chinese Medicine, Guangzhou, 510006, P.R. China.
| | - Qibiao Wu
- Faculty of Chinese Medicine, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, 999078, China.
- Chinese Medicine Guangdong Laboratory (Hengqin Laboratory), Guangdong-Macao ln-Depth Cooperation Zone in Hengqin, 519000, Hengqin, P.R. China.
| | - Suyun Li
- Department of Respiratory and Critical Care Medicine, Chinese Medicine Pharmacology (Respiratory) Laboratory, the First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, 450046, Henan Province, China.
- Collaborative Innovation Center for Chinese Medicine and Respiratory Diseases Co-constructed by Henan, Province & Education Ministry of P. R. China, Zhengzhou, 450046, Henan Province, China.
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Acha-Sagredo A, Andrei P, Clayton K, Taggart E, Antoniotti C, Woodman CA, Afrache H, Fourny C, Armero M, Moinudeen HK, Green M, Bhardwaj N, Mikolajczak A, Rodriguez-Lopez M, Crawford M, Connick E, Lim S, Hobson P, Linares J, Ignatova E, Pelka D, Smyth EC, Diamantis N, Sosnowska D, Carullo M, Ciraci P, Bergamo F, Intini R, Nye E, Barral P, Mishto M, Arnold JN, Lonardi S, Cremolini C, Fontana E, Rodriguez-Justo M, Ciccarelli FD. A constitutive interferon-high immunophenotype defines response to immunotherapy in colorectal cancer. Cancer Cell 2025; 43:292-307.e7. [PMID: 39824178 DOI: 10.1016/j.ccell.2024.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 10/21/2024] [Accepted: 12/19/2024] [Indexed: 01/20/2025]
Abstract
Fewer than 50% of metastatic deficient mismatch repair (dMMR) colorectal cancer (CRC) patients respond to immune checkpoint inhibition (ICI). Identifying and expanding this patient population remains a pressing clinical need. Here, we report that an interferon-high immunophenotype locally enriched in cytotoxic lymphocytes and antigen-presenting macrophages is required for response. This immunophenotype is not exclusive to dMMR CRCs but comprises a subset of MMR proficient (pMMR) CRCs. Single-cell spatial analysis and in vitro cell co-cultures indicate that interferon-producing cytotoxic T cells induce overexpression of antigen presentation in adjacent macrophages and tumor cells, including MHC class II invariant chain CD74. dMMR CRCs expressing high levels of CD74 respond to ICI and a subset of CD74 high pMMR CRC patients show better progression free survival when treated with ICI. Therefore, CD74 abundance can identify the constitutive interferon-high immunophenotype determining clinical benefit in CRC, independently of tumor mutational burden or MMR status.
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Affiliation(s)
- Amelia Acha-Sagredo
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK; Centre for Cancer Evolution, Bart's Cancer Institute, Queen Mary University London, London EC1M 6AU, UK
| | - Pietro Andrei
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK; Centre for Cancer Evolution, Bart's Cancer Institute, Queen Mary University London, London EC1M 6AU, UK
| | - Kalum Clayton
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK; Centre for Cancer Evolution, Bart's Cancer Institute, Queen Mary University London, London EC1M 6AU, UK
| | - Emma Taggart
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK; Centre for Cancer Evolution, Bart's Cancer Institute, Queen Mary University London, London EC1M 6AU, UK
| | - Carlotta Antoniotti
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Chloé A Woodman
- School of Cancer and Pharmaceutical Sciences, King's College London, London SE1 1UL, UK
| | - Hassnae Afrache
- Centre for Inflammation Biology and Cancer Immunology, King's College London, London SE1 1UL, UK; Molecular Immunology Laboratory, Francis Crick Institute, London NW1 1AT, UK
| | - Constance Fourny
- Centre for Inflammation Biology and Cancer Immunology, King's College London, London SE1 1UL, UK; Molecular Immunology Laboratory, Francis Crick Institute, London NW1 1AT, UK
| | - Maria Armero
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK; Centre for Cancer Evolution, Bart's Cancer Institute, Queen Mary University London, London EC1M 6AU, UK
| | - Hafsa Kaja Moinudeen
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Mary Green
- Experimental Histopathology, The Francis Crick Institute, London NW1 1AT, UK
| | - Nisha Bhardwaj
- Experimental Histopathology, The Francis Crick Institute, London NW1 1AT, UK
| | - Anna Mikolajczak
- Experimental Histopathology, The Francis Crick Institute, London NW1 1AT, UK
| | | | - Marg Crawford
- Advanced Sequencing Facility, The Francis Crick Institute, London NW1 1AT, UK
| | - Emma Connick
- Advanced Sequencing Facility, The Francis Crick Institute, London NW1 1AT, UK
| | - Steven Lim
- Flow Cytometry Facility, The Francis Crick Institute, London NW1 1AT, UK
| | - Philip Hobson
- Flow Cytometry Facility, The Francis Crick Institute, London NW1 1AT, UK
| | - Josep Linares
- Department of Histopathology, University College London Cancer Institute, London, UK
| | | | - Diana Pelka
- Drug Development Unit, Sarah Cannon Research Institute UK, London, UK
| | - Elizabeth C Smyth
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford OX3 7LE, UK
| | - Nikolaos Diamantis
- Department of Medical Oncology, Royal Free London NHS Foundation Trust, London WC1E 6BT, UK
| | - Dominika Sosnowska
- School of Cancer and Pharmaceutical Sciences, King's College London, London SE1 1UL, UK
| | - Martina Carullo
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Paolo Ciraci
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Francesca Bergamo
- Oncology Unit 1, Department of Oncology Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Rossana Intini
- Oncology Unit 1, Department of Oncology Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Emma Nye
- Experimental Histopathology, The Francis Crick Institute, London NW1 1AT, UK
| | - Patricia Barral
- Centre for Inflammation Biology and Cancer Immunology, King's College London, London SE1 1UL, UK; Immune Responses to Lipids Laboratory, The Francis Crick Institute, London NW1 1AT, UK
| | - Michele Mishto
- Centre for Inflammation Biology and Cancer Immunology, King's College London, London SE1 1UL, UK; Molecular Immunology Laboratory, Francis Crick Institute, London NW1 1AT, UK
| | - James N Arnold
- School of Cancer and Pharmaceutical Sciences, King's College London, London SE1 1UL, UK
| | - Sara Lonardi
- Oncology Unit 1, Department of Oncology Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Chiara Cremolini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Elisa Fontana
- Drug Development Unit, Sarah Cannon Research Institute UK, London, UK
| | | | - Francesca D Ciccarelli
- Cancer Systems Biology Laboratory, The Francis Crick Institute, London NW1 1AT, UK; Centre for Cancer Evolution, Bart's Cancer Institute, Queen Mary University London, London EC1M 6AU, UK.
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Gandara DR, Agarwal N, Gupta S, Klempner SJ, Andrews MC, Mahipal A, Subbiah V, Eskander RN, Carbone DP, Riess JW, Sammons S, Snider J, Bouzit L, Cho-Phan C, Price M, Li G, Quintanilha JCF, Huang RSP, Ross JS, Fabrizio D, Oxnard GR, Graf RP. Tumor mutational burden and survival on immune checkpoint inhibition in >8000 patients across 24 cancer types. J Immunother Cancer 2025; 13:e010311. [PMID: 39915003 PMCID: PMC11815411 DOI: 10.1136/jitc-2024-010311] [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: 08/08/2024] [Accepted: 11/26/2024] [Indexed: 02/14/2025] Open
Abstract
BACKGROUND There is uncertainty around clinical applicability of tumor mutational burden (TMB) across cancer types, in part because of inconsistency between TMB measurements from different platforms. The KEYNOTE 158 trial supported United States Food and Drug Administration (FDA) approval of the Foundation Medicine test (FoundationOneCDx) at TMB≥10 mut/Mb as a companion diagnostic (CDx) for single-agent pembrolizumab in second+line. Using a large real-world dataset with validated survival endpoint data, we evaluated clinical validity of TMB measurement by the test in over 8000 patients across 24 cancer types who received single-agent immune checkpoint inhibitor (ICI). METHODS Patients with advanced-stage cancers from 24 cancer types treated with single-agent anti-PD(L)1 therapy in standard-of-care settings were included. Deidentified data from electronic health records from approximately 280 cancer treatment facilities were captured into a clinico-genomic database. This study used the TMB algorithm from the FDA-approved test supporting solid tumor CDx and composite mortality variable validated against the national death index: real-world overall survival (rwOS). Following a prespecified analysis plan, rwOS by TMB level was assessed using Cox PH models adjusted for Eastern Cooperative Oncology Group performance status, prior treatment, microsatellite instability, sex, age, opioid rx pretherapy, and socioeconomic assessment. RESULTS 8440 patients met inclusion criteria. Adjusting for aforementioned factors, increasing TMB was significantly associated with rwOS across tumor types; HRs (95% CIs) relative to TMB<5: TMB 5 to <10: 0.95 (0.89 to 1.02), TMB 10 to <20: 0.79 (0.73 to 0.85), TMB≥20: 0.52 (0.47 to 0.58). For individual cancer types with prespecified statistical power, adjusted rwOS comparing TMB≥10 vs TMB<10 significantly favored TMB≥10 in 9 of 10 cancer types. In microsatellite stable subcohorts (except colorectal cancer), TMB≥10 remained associated with enriched ICI benefit. Exploratory assessments of patients receiving ICI+chemotherapy (n=4369) observed more favorable rwOS only in TMB≥20. CONCLUSIONS Across >8000 patients treated with single-agent ICI, and within individual cancer types with sufficient power, elevated TMB based on the FDA-approved CDx was associated with more favorable rwOS compared with similar patients with lower TMB levels. This biomarker deserves further clinical investigation to potentially guide the use of immunotherapy in expanded clinical contexts.
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Affiliation(s)
- David R Gandara
- Department of Medicine, Cancer Ctr So./Division of Hematologic & Oncology, UC Davis, Sacramento, California, USA
| | - Neeraj Agarwal
- Department of Medical Oncology, University of Utah Health Huntsman Cancer Institute, Salt Lake City, Utah, USA
| | - Shilpa Gupta
- Department of Hematology and Oncology, Cleveland Clinic Taussig Cancer Center, Cleveland, Ohio, USA
| | - Samuel J Klempner
- Massachusetts General Hospital Cancer Center, Boston, Massachusetts, USA
| | - Miles C Andrews
- Department of Medicine, Monash University Central Clinical School, Melbourne, Victoria, Australia
| | - Amit Mahipal
- Lake Health University Hospitals Seidman Cancer Center, Cleveland, Ohio, USA
| | - Vivek Subbiah
- Sarah Cannon Research Institute, Nashville, Tennessee, USA
| | - Ramez N Eskander
- Department of Obstetrics, Gynecology and Reproductive Sciences, UC San Diego Health Moores Cancer Center, La Jolla, California, USA
| | - David P Carbone
- The Ohio State University Medical Center, Columbus, Ohio, USA
| | - Jonathan W Riess
- UC Davis Comprehensive Cancer Center, Sacramento, California, USA
| | - Sarah Sammons
- Breast Oncology Program, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | | | | | | | - Megan Price
- Flatiron Health Inc, New York, New York, USA
| | - Gerald Li
- Foundation Medicine Inc, Boston, Massachusetts, USA
| | | | | | | | | | | | - Ryon P Graf
- Foundation Medicine Inc, San Diego, California, USA
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Liu Y, Tao H, Jia S, Wang H, Guo L, Hu Z, Zhang W, Liu F. Prognostic value and immune landscapes of disulfidptosis‑related lncRNAs in bladder cancer. Mol Clin Oncol 2025; 22:19. [PMID: 39776943 PMCID: PMC11706340 DOI: 10.3892/mco.2024.2814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2024] [Accepted: 11/11/2024] [Indexed: 01/11/2025] Open
Abstract
Disulfidptosis, which was recently identified, has shown promise as a potential cancer treatment. Nonetheless, the precise role of long non-coding RNAs (lncRNAs) in this phenomenon is currently unclear. To elucidate their significance in bladder cancer (BLCA), a signature of disulfidptosis-related lncRNAs (DRlncRNAs) was developed and their potential prognostic significance was explored. BLCA sample data were sourced from The Cancer Genome Atlas. A predictive signature comprising DRlncRNAs was formulated and subsequently validated. The combination of this signature with clinical characteristics facilitated the development of a nomogram with practical clinical utility. Additionally, enrichment analysis was conducted, the tumor microenvironment (TME) was assessed, the tumor mutational burden (TMB) was analyzed, and drug sensitivity was explored. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to quantify lncRNA expression. The results revealed an eight-gene signature based on DRlncRNAs was established, and the predictive accuracy of the nomogram that incorporated the risk score [area under the curve (AUC)=0.733] outperformed the nomogram without it (AUC=0.703). High-risk groups were associated with pathways such as WNT signaling, focal adhesion and cell cycle pathways. The TME study revealed that high-risk patients had increased immune infiltration, whereas the TMB and tumor immune dysfunction and exclusion scores in low-risk patients indicated a potentially robust immune response. Drug sensitivity analysis identified appropriate antitumor drugs for each group. RT-qPCR experiments validated significant differences in DRlncRNAs expression between normal and BLCA cell lines. In conclusion, the prognostic risk signature, which includes the eight identified DRlncRNAs, demonstrates promise for predicting prognosis of patients with BLCA and guiding the selection of suitable immunotherapy and chemotherapy strategies.
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Affiliation(s)
- Yijiang Liu
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
- Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Huijing Tao
- Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
- Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Shengjun Jia
- Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
- Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Haozheng Wang
- Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
- Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Long Guo
- Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Zhuozheng Hu
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Wenxiong Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
| | - Fei Liu
- Department of Urology Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi 330006, P.R. China
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Zhang L, Shi J, Zhu MH, Huang Y, Lu Q, Sun P, Chen HZ, Lai X, Fang C. Liposomes-enabled cancer chemoimmunotherapy. Biomaterials 2025; 313:122801. [PMID: 39236630 DOI: 10.1016/j.biomaterials.2024.122801] [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: 04/27/2024] [Revised: 08/05/2024] [Accepted: 09/01/2024] [Indexed: 09/07/2024]
Abstract
Chemoimmunotherapy is an emerging paradigm in the clinic for treating several malignant diseases, such as non-small cell lung cancer, breast cancer, and large B-cell lymphoma. However, the efficacy of this strategy is still restricted by serious adverse events and a high therapeutic termination rate, presumably due to the lack of tumor-targeted distribution of both chemotherapeutic and immunotherapeutic agents. Targeted drug delivery has the potential to address this issue. Among the most promising nanocarriers in clinical translation, liposomes have drawn great attention in cancer chemoimmunotherapy in recent years. Liposomes-enabled cancer chemoimmunotherapy has made significant progress in clinics, with impressive therapeutic outcomes. This review summarizes the latest preclinical and clinical progress in liposome-enabled cancer chemoimmunotherapy and discusses the challenges and future directions of this field.
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Affiliation(s)
- Lele Zhang
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jiangpei Shi
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Mao-Hua Zhu
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yanhu Huang
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Qin Lu
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Peng Sun
- Department of General Surgery, Tongren Hospital, SJTU-SM, Shanghai, 200336, China
| | - Hong-Zhuan Chen
- Shanghai Frontiers Science Center of TCM Chemical Biology, Institute of Interdisciplinary Integrative Biomedical Research, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China
| | - Xing Lai
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Chao Fang
- Hongqiao International Institute of Medicine, Tongren Hospital and State Key Laboratory of Systems Medicine for Cancer, Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China; Key Laboratory of Basic Pharmacology of Ministry of Education & Joint International Research Laboratory of Ethnomedicine of Ministry of Education, Zunyi Medical University, Zunyi, 563003, China.
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Rakaee M, Tafavvoghi M, Ricciuti B, Alessi JV, Cortellini A, Citarella F, Nibid L, Perrone G, Adib E, Fulgenzi CAM, Hidalgo Filho CM, Di Federico A, Jabar F, Hashemi S, Houda I, Richardsen E, Rasmussen Busund LT, Donnem T, Bahce I, Pinato DJ, Helland Å, Sholl LM, Awad MM, Kwiatkowski DJ. Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer. JAMA Oncol 2025; 11:109-118. [PMID: 39724105 PMCID: PMC11843371 DOI: 10.1001/jamaoncol.2024.5356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2024] [Accepted: 08/23/2024] [Indexed: 12/28/2024]
Abstract
Importance Only a small fraction of patients with advanced non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment. For optimal personalized NSCLC care, it is imperative to identify patients who are most likely to benefit from immunotherapy. Objective To develop a supervised deep learning-based ICI response prediction method; evaluate its performance alongside other known predictive biomarkers; and assess its association with clinical outcomes in patients with advanced NSCLC. Design, Setting, and Participants This multicenter cohort study developed and independently validated a deep learning-based response stratification model for predicting ICI treatment outcome in patients with advanced NSCLC from whole slide hematoxylin and eosin-stained images. Images for model development and validation were obtained from 1 participating center in the US and 3 in the European Union (EU) from August 2014 to December 2022. Data analyses were performed from September 2022 to May 2024. Exposure Monotherapy with ICIs. Main Outcomes and Measures Model performance measured by clinical end points and objective response rate (ORR) differentiation power vs other predictive biomarkers, ie, programmed death-ligand 1 (PD-L1), tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs). Results A total of 295 581 image tiles from 958 patients (mean [SD] age, 66.0 [10.6] years; 456 [48%] females and 502 [52%] males) treated with ICI for NSCLC were included in the analysis. The US-based development cohort consisted of 614 patients with median (IQR) follow-up time of 54.5 (38.2-68.1) months, and the EU-based validation cohort, 344 patients with 43.3 (27.4-53.9) months of follow-up. The ORR to ICI was 26% in the developmental cohort and 28% in the validation cohort. The deep learning model's area under the receiver operating characteristic curve (AUC) for ORR was 0.75 (95% CI, 0.64-0.85) in the internal test set and 0.66 (95% CI, 0.60-0.72) in the validation cohort. In a multivariable analysis, the deep learning model's score was an independent predictor of ICI response in the validation cohort for both progression-free (hazard ratio, 0.56; 95% CI, 0.42-0.76; P < .001) and overall survival (hazard ratio, 0.53; 95% CI, 0.39-0.73; P < .001). The tuned deep learning model achieved a higher AUC than TMB, TILs, and PD-L1 in the internal set; in the validation cohort, it was superior to TILs and comparable with PD-L1 (AUC, 0.67; 95% CI, 0.60-0.74), with a 10-percentage point improvement in specificity. In the validation cohort, combining the deep learning model with PD-L1 scores achieved an AUC of 0.70 (95% CI, 0.63-0.76), outperforming either marker alone, with a response rate of 51% compared to 41% for PD-L1 (≥50%) alone. Conclusions and Relevance The findings of this cohort study demonstrate a strong and independent deep learning-based feature associated with ICI response in patients with NSCLC across various cohorts. Clinical use of this deep learning model could refine treatment precision and better identify patients who are likely to benefit from ICI for treatment of advanced NSCLC.
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Affiliation(s)
- Mehrdad Rakaee
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Cancer Genetics, Oslo University Hospital, Oslo, Norway
- Department of Clinical Pathology, University Hospital of North Norway, Tromsø, Norway
- Department of Medical Biology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Masoud Tafavvoghi
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Biagio Ricciuti
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Joao V. Alessi
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Alessio Cortellini
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
- Medical Oncology Operative Research Unit, Fondazione Policlinico Campus Bio-Medico, Rome, Italy
- Research Unit of Medical Oncology, Department of Medicine and Surgery, Universitá Campus Bio-Medico, Rome, Italy
| | - Fabrizio Citarella
- Medical Oncology Operative Research Unit, Fondazione Policlinico Campus Bio-Medico, Rome, Italy
- Research Unit of Medical Oncology, Department of Medicine and Surgery, Universitá Campus Bio-Medico, Rome, Italy
| | - Lorenzo Nibid
- Research Unit of Anatomical Pathology, Department of Medicine and Surgery, Università Campus Bio-Medico, Rome, Italy
- Anatomical Pathology Operative Research Unit, Fondazione Policlinico Università Campus Bio-Medico, Rome, Italy
| | - Giuseppe Perrone
- Research Unit of Anatomical Pathology, Department of Medicine and Surgery, Università Campus Bio-Medico, Rome, Italy
- Anatomical Pathology Operative Research Unit, Fondazione Policlinico Università Campus Bio-Medico, Rome, Italy
| | - Elio Adib
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | | | - Cassio Murilo Hidalgo Filho
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Alessandro Di Federico
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Falah Jabar
- Department of Clinical Pathology, University Hospital of North Norway, Tromsø, Norway
| | - Sayed Hashemi
- Department of Pulmonary Medicine, Cancer Center Amsterdam, VU Medical Center, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Ilias Houda
- Department of Pulmonary Medicine, Cancer Center Amsterdam, VU Medical Center, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Elin Richardsen
- Department of Clinical Pathology, University Hospital of North Norway, Tromsø, Norway
| | - Lill-Tove Rasmussen Busund
- Department of Clinical Pathology, University Hospital of North Norway, Tromsø, Norway
- Department of Medical Biology, UiT The Arctic University of Norway, Tromsø, Norway
| | - Tom Donnem
- Department of Clinical Medicine, UiT The Arctic University of Norway, Tromsø, Norway
- Department of Oncology, University Hospital of North Norway, Tromsø, Norway
| | - Idris Bahce
- Department of Pulmonary Medicine, Cancer Center Amsterdam, VU Medical Center, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - David J. Pinato
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
- Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy
| | - Åslaug Helland
- Department of Cancer Genetics, Oslo University Hospital, Oslo, Norway
- Division of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lynette M. Sholl
- Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Mark M. Awad
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - David J. Kwiatkowski
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
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