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Debatin NF, Bady E, Mandelkow T, Huang Z, Lurati MCJ, Raedler JB, Müller JH, Vettorazzi E, Plage H, Samtleben H, Klatte T, Hofbauer S, Elezkurtaj S, Furlano K, Weinberger S, Giacomo Bruch P, Horst D, Roßner F, Schallenberg S, Marx AH, Fisch M, Rink M, Slojewski M, Kaczmarek K, Ecke TH, Hallmann S, Koch S, Adamini N, Lennartz M, Minner S, Simon R, Sauter G, Zecha H, Schlomm T, Blessin NC. Prognostic Impact and Spatial Interplay of Immune Cells in Urothelial Cancer. Eur Urol 2024:S0302-2838(24)00065-4. [PMID: 38383257 DOI: 10.1016/j.eururo.2024.01.023] [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: 04/02/2023] [Revised: 12/01/2023] [Accepted: 01/29/2024] [Indexed: 02/23/2024]
Abstract
BACKGROUND Quantity and the spatial relationship of specific immune cell types can provide prognostic information in bladder cancer. OBJECTIVE To characterize the spatial interplay and prognostic role of different immune cell subpopulations in bladder cancer. DESIGN, SETTING, AND PARTICIPANTS A total of 2463 urothelial bladder carcinomas were immunostained with 21 antibodies using BLEACH&STAIN multiplex fluorescence immunohistochemistry in a tissue microarray format and analyzed using a framework of neuronal networks for an image analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Spatial immune parameters were compared with histopathological parameters and overall survival data. RESULTS AND LIMITATIONS The identification of > 300 different immune cell subpopulations and the characterization of their spatial relationship resulted in numerous spatial interaction patterns. Thirty-nine immune parameters showed prognostic significance in univariate analyses, of which 16 were independent from pT, pN, and histological grade in muscle-invasive bladder cancer. Among all these parameters, the strongest association with prolonged overall survival was identified for intraepithelial CD8+ cytotoxic T cells (time-dependent area under receiver operating characteristic curve [AUC]: 0.70), while stromal CD8+ T cells were less relevant (AUC: 0.65). A favorable prognosis of inflamed cancers with high levels of "exhaustion markers" suggests that TIM3, PD-L1, PD-1, and CTLA-4 on immune cells do not hinder antitumoral immune response in tumors rich of tumor infiltrating immune cells. CONCLUSIONS The density of intraepithelial CD8+ T cells was the strongest prognostic feature in muscle-invasive bladder cancer. Given that tumor cell killing by CD8+ cytotoxic T lymphocytes through direct cell-to-cell-contacts represents the "terminal end route" of antitumor immunity, the quantity of "tumor cell adjacent CD8+ T cells" may constitute a surrogate for the efficiency of cancer recognition by the immune system that can be measured straightaway in routine pathology as the CD8 labeling index. PATIENT SUMMARY Quantification of intraepithelial CD8+ T cells, the strongest prognostic feature identified in muscle-invasive bladder cancer, can easily be assessed by brightfield immunohistochemistry and is therefore "ready to use" for routine pathology.
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Affiliation(s)
- Nicolaus F Debatin
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Elena Bady
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tim Mandelkow
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Zhihao Huang
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Magalie C J Lurati
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jonas B Raedler
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; College of Arts and Sciences, Boston University, Boston, MA, USA
| | - Jan H Müller
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Eik Vettorazzi
- Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Henning Plage
- Department of Urology, Charité Berlin, Berlin, Germany
| | - Henrik Samtleben
- Department of Pathology, Academic Hospital Fuerth, Fuerth, Germany
| | - Tobias Klatte
- Department of Urology, Charité Berlin, Berlin, Germany; Department of Urology, Helios Hospital Bad Saarow, Bad Saarow, Germany
| | | | | | - Kira Furlano
- Department of Urology, Charité Berlin, Berlin, Germany
| | | | | | - David Horst
- Institute of Pathology, Charité Berlin, Berlin, Germany
| | | | | | - Andreas H Marx
- Department of Pathology, Academic Hospital Fuerth, Fuerth, Germany
| | - Margit Fisch
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Michael Rink
- Department of Urology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marcin Slojewski
- Department of Urology, University Hospital Stettin, Stettin, Poland
| | | | - Thorsten H Ecke
- Department of Urology, Charité Berlin, Berlin, Germany; Department of Urology, Helios Hospital Bad Saarow, Bad Saarow, Germany
| | - Steffen Hallmann
- Department of Urology, Helios Hospital Bad Saarow, Bad Saarow, Germany
| | - Stefan Koch
- Department of Pathology, Helios Hospital Bad Saarow, Bad Saarow, Germany
| | - Nico Adamini
- Department of Urology, Albertinen Hospital, Hamburg, Germany
| | - Maximilian Lennartz
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Sarah Minner
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ronald Simon
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Guido Sauter
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Henrik Zecha
- Department of Urology, Albertinen Hospital, Hamburg, Germany
| | | | - Niclas C Blessin
- Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
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Hu B, Hounye AH, Wang Z, Qi M, Zhang J. A novel Cuprotosis-related signature predicts the prognosis and selects personal treatments for melanoma based on bioinformatics analysis. Front Oncol 2023; 13:1108128. [PMID: 36824136 PMCID: PMC9941880 DOI: 10.3389/fonc.2023.1108128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 01/18/2023] [Indexed: 02/09/2023] Open
Abstract
Background Melanoma is a common and aggressive cutaneous malignancy characterized by poor prognosis and a high fatality rate. Recently, due to the application of Immune-checkpoint inhibitors (ICI) in melanoma treatment, melanoma patients' prognosis has been tremendously improved. However, the treatment effect varies quite differently from patient to patient. In this study, we aim to construct and validate a Cuproptosis-related risk model to improve outcome prediction of ICIs in melanoma and divide patients into subtypes with different Cuproptosis-related genes. Methods Here, according to differentially expressed genes from four melanoma datasets in GEO (Gene Expression Omnibus), and one in TCGA (The Cancer Genome Atlas) database, a novel signature was developed through LASSO and Cox regression analysis. We used 781 melanoma samples to examine the molecular subtypes associated with Cuproptosis-related genes and studied the related gene mutation and TME cell infiltration. Patients with melanoma can be divided into at least three subtypes based on gene expression profile. Survival pan-cancer analysis was also conducted for melanoma patients. Results The Cuproptosis risk score can predict tumor immunity, subtype, survival, and drug sensitivity for melanoma. And Cuproptosis-associated subtypes can help predict therapeutic outcomes. Conclusion Cuproptosis risk score is a promising potential biomarker in cancer diagnosis, molecular subtypes determination, TME cell infiltration characteristics, and therapy response prediction in melanoma patients.
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Affiliation(s)
- Bingqian Hu
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | | | - Zheng Wang
- School of Computer Science, Hunan First Normal University, Changsha, China,*Correspondence: Zheng Wang, ; Jianglin Zhang, ; Min Qi,
| | - Min Qi
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, China,*Correspondence: Zheng Wang, ; Jianglin Zhang, ; Min Qi,
| | - Jianglin Zhang
- Department of Dermatology, Shenzhen People’s Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, Guangdong, China,Candidate Branch of National Clinical Research Center for Skin Diseases, Shenzhen People’s Hospital, Shenzhen, Guangdong, China,*Correspondence: Zheng Wang, ; Jianglin Zhang, ; Min Qi,
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Georgescu SR, Mitran CI, Mitran MI, Matei C, Constantin C, Neagu M, Tampa M. Apprising Diagnostic and Prognostic Biomarkers in Cutaneous Melanoma—Persistent Updating. J Pers Med 2022; 12:jpm12091506. [PMID: 36143291 PMCID: PMC9505119 DOI: 10.3390/jpm12091506] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/11/2022] [Accepted: 09/11/2022] [Indexed: 12/11/2022] Open
Abstract
The incidence of melanoma, a very aggressive skin cancer, has increased over the past few decades. Although there are well-established clinical, dermoscopic and histopathological criteria, the diagnosis is often performed late, which has important implications on the patient’s clinical outcome. Unfortunately, melanoma is one of the most challenging tumors to diagnose because it is a heterogeneous neoplasm at the clinical, histopathological, and molecular level. The use of reliable biomarkers for the diagnosis and monitoring of disease progression is becoming a standard of care in modern medicine. In this review, we discuss the latest studies, which highlight findings from the genomics, epitranscriptomics, proteomics and metabolomics areas, pointing out different genes, molecules and cells as potential diagnostic and prognostic biomarkers in cutaneous melanoma.
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Affiliation(s)
- Simona Roxana Georgescu
- Department of Dermatology, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Department of Dermatology, “Victor Babes” Clinical Hospital for Infectious Diseases, 030303 Bucharest, Romania
| | - Cristina Iulia Mitran
- Department of Microbiology, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Correspondence: (C.I.M.); (M.I.M.)
| | - Madalina Irina Mitran
- “Cantacuzino” National Medico-Military Institute for Research and Development, 011233 Bucharest, Romania
- Correspondence: (C.I.M.); (M.I.M.)
| | - Clara Matei
- Department of Dermatology, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
| | - Carolina Constantin
- Immunology Department, “Victor Babes” National Institute of Pathology, 050096 Bucharest, Romania
- Colentina Clinical Hospital, 020125 Bucharest, Romania
| | - Monica Neagu
- Immunology Department, “Victor Babes” National Institute of Pathology, 050096 Bucharest, Romania
- Colentina Clinical Hospital, 020125 Bucharest, Romania
- Faculty of Biology, University of Bucharest, 030018 Bucharest, Romania
| | - Mircea Tampa
- Department of Dermatology, “Carol Davila” University of Medicine and Pharmacy, 050474 Bucharest, Romania
- Department of Dermatology, “Victor Babes” Clinical Hospital for Infectious Diseases, 030303 Bucharest, Romania
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Value of a Signature of Immune-Related Genes in Predicting the Prognosis of Melanoma and Its Responses to Immune Checkpoint Blocker Therapies. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:9633416. [PMID: 35770115 PMCID: PMC9236803 DOI: 10.1155/2022/9633416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/24/2022] [Accepted: 05/30/2022] [Indexed: 11/25/2022]
Abstract
Melanoma is becoming increasingly common worldwide, with high rates of transformation into malignancy compared to other skin lesions. The prognosis of patients with melanoma at an advanced stage is highly unsatisfying despite the development of immunotherapy, target therapy, or combinative therapy. The major barrier to exploiting immune checkpoint therapies and achieving the best benefits clinically is resistance that can easily develop if regimens are not selected appropriately. In this study, we investigated the possibility of using immune-related genes to predict patient survival and their responses to immune checkpoint blocker therapies with the expression profiles available at The Cancer Genome Atlas (TCGA) Program plus expression data from the Gene Expression Omnibus (GEO) for validation. A five gene signature that is highly correlated with the local infiltration of cytotoxic lymphocytes in the tumor microenvironment was identified, and a scoring model was developed with stepwise regression after multivariate Cox analyses. The score calculated strongly correlates with Breslow depth, and this model effectively predicts the prognosis of patients with melanoma, whether primary or metastasized. It also depicts the heterogenous immune-related nature of melanoma by revealing different predicted responses to immune checkpoint blocker therapies through its correlation to tumor immune dysfunction and exclusion (TIDE) score.
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