1
|
Zhang W, Wang S. Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma. Melanoma Res 2024; 34:215-224. [PMID: 38364052 DOI: 10.1097/cmr.0000000000000957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2024]
Abstract
Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a tumor. ITH was involved in the cancer progression, aggressiveness, therapy resistance and cancer recurrence. Integrative machine learning procedure including 10 methods was conducted to develop an ITH-related signature (IRS) in The Cancer Genome Atlas (TCGA), GSE54467, GSE59455 and GSE65904 cohort. Several scores, including tumor immune dysfunction and exclusion (TIDE) score, tumor mutation burden (TMB) score and immunophenoscore (IPS), were used to evaluate the role of IRS in predicting immunotherapy benefits. Two immunotherapy datasets (GSE91061 and GSE78220) were utilized to the role of IRS in predicting immunotherapy benefits of skin cutaneous melanoma (SKCM) patients. The optimal prognostic IRS constructed by Lasso method acted as an independent risk factor and had a stable and powerful performance in predicting the overall survival rate in SKCM, with the area under the curve of 2-, 3- and 4-year receiver operating characteristic curve being 0.722, 0.722 and 0.737 in TCGA cohort. We also constructed a nomogram and the actual 1-, 3- and 5-year survival times were highly consistent with the predicted survival times. SKCM patients with low IRS scores had a lower TIDE score, lower immune escape score and higher TMB score, higher PD1&CTLA4 IPS. Moreover, SKCM patients with low IRS scores had a lower gene sets score involved in DNA repair, angiogenesis, glycolysis, hypoxia, IL2-STAT5 signaling, MTORC1 signaling, NOTCH signaling and P53 pathway. The current study constructed a novel IRS in SKCM using 10 machine learning methods. This IRS acted as an indicator for predicting the prognosis and immunotherapy benefits of SKCM patients.
Collapse
Affiliation(s)
- Wei Zhang
- Department of Emergency, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shuai Wang
- Department of Burn Plastic Surgery, The First Affiliated Hospital of Wannan Medical College, Wuhu, China
| |
Collapse
|
2
|
Sun J, Wang M, Kan Z. Diagnostic and prognostic risk factors analysis for distant metastasis in melanoma: a population-based study. Eur J Cancer Prev 2024:00008469-990000000-00125. [PMID: 38251671 DOI: 10.1097/cej.0000000000000871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
BACKGROUND We aimed to develop tools that could predict the occurrence of distant metastases in melanoma and its prognosis based on clinical and pathological characteristics. MATERIALS AND METHODS We obtained data from the Surveillance, Epidemiology, and End Results (SEER) database of melanoma patients diagnosed between 2010 and 2019. Logistic analyses were performed to identify independent risk factors associated with distant metastasis. Additionally, multivariate Cox analyses were conducted to determine independent prognostic factors for patients with distant metastasis. Two nomograms were established and evaluated with the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Furthermore, we performed a retrospective analysis of melanoma with distant metastasis from our institute between March 2018 and June 2022. RESULTS Of the total 19 396 melanoma patients, 352 (1.8%) had distant metastases at the time of diagnosis. The following clinical and pathological characteristics were identified as independent risk factors for distant metastasis in melanoma: N stage, tumor size, ulceration, mitosis, primary tumor site, and pathological subtype. Furthermore, tumor size, pathological subtype, and radiotherapy were identified as independent prognostic factors. The results of the training and validation cohorts' ROC curves, calibration, DCA, and Kaplan-Meier survival curves demonstrate the effectiveness of the two nomograms. The retrospective study results from our center supported the results from the SEER database. CONCLUSION The clinical and pathological characteristics of melanoma can predict a patient's risk of metastasis and prognosis, and the two nomograms are expected to be effective tools to guide therapy decisions.
Collapse
Affiliation(s)
- Junwei Sun
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing
- Department of Neurosurgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
| | - Mingyu Wang
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Zhisheng Kan
- Department of Neurosurgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
| |
Collapse
|
3
|
Roccuzzo G, Bongiovanni E, Tonella L, Pala V, Marchisio S, Ricci A, Senetta R, Bertero L, Ribero S, Berrino E, Marchiò C, Sapino A, Quaglino P, Cassoni P. Emerging prognostic biomarkers in advanced cutaneous melanoma: a literature update. Expert Rev Mol Diagn 2024; 24:49-66. [PMID: 38334382 DOI: 10.1080/14737159.2024.2314574] [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: 08/05/2023] [Accepted: 02/01/2024] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Over the past two years, the scientific community has witnessed an exponential growth in research focused on identifying prognostic biomarkers for melanoma, both in pre-clinical and clinical settings. This surge in studies reflects the need of developing effective prognostic indicators in the field of melanoma. AREAS COVERED The aim of this work is to review the scientific literature on the most recent findings on the development or validation of prognostic biomarkers in melanoma, in the attempt of providing both clinicians and researchers with an updated broad synopsis of prognostic biomarkers in cutaneous melanoma. EXPERT OPINION While the field of prognostic biomarkers in melanoma appears promising, there are several complexities and limitations to address. The interdependence of clinical, histological, and molecular features requires accurate classification of different biomarker families. Correlation does not imply causation, and adjustments for confounding factors are often overlooked. In this scenario, large-scale studies based on high-quality clinical trial data can provide more reliable evidence. It is essential to avoid oversimplification by focusing on a single biomarker, as the interactions among multiple factors contribute to define the disease course and patient's outcome. Furthermore, implementing well-supported evidence in real-life settings can help advance prognostic biomarker research in melanoma.
Collapse
Affiliation(s)
- Gabriele Roccuzzo
- Department of Medical Sciences, Section of Dermatology, University of Turin, Turin, Italy
| | - Eleonora Bongiovanni
- Department of Medical Sciences, Section of Dermatology, University of Turin, Turin, Italy
| | - Luca Tonella
- Department of Medical Sciences, Section of Dermatology, University of Turin, Turin, Italy
| | - Valentina Pala
- Department of Medical Sciences, Section of Dermatology, University of Turin, Turin, Italy
| | - Sara Marchisio
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Alessia Ricci
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Rebecca Senetta
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Luca Bertero
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Simone Ribero
- Department of Medical Sciences, Section of Dermatology, University of Turin, Turin, Italy
| | - Enrico Berrino
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Caterina Marchiò
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Anna Sapino
- Candiolo Cancer Institute, FPO-IRCCS, Candiolo, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Pietro Quaglino
- Department of Medical Sciences, Section of Dermatology, University of Turin, Turin, Italy
| | - Paola Cassoni
- Pathology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| |
Collapse
|
4
|
Song B, Wang K, Peng Y, Zhu Y, Cui Z, Chen L, Yu Z, Song B. Combined signature of G protein-coupled receptors and tumor microenvironment provides a prognostic and therapeutic biomarker for skin cutaneous melanoma. J Cancer Res Clin Oncol 2023; 149:18135-18160. [PMID: 38006451 DOI: 10.1007/s00432-023-05486-4] [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: 08/24/2023] [Accepted: 10/19/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND G protein-coupled receptors (GPCRs) have been shown to have an important role in tumor development and metastasis, and abnormal expression of GPCRs is significantly associated with poor prognosis of tumor patients. In this study, we analyzed the GPCRs-related gene (GPRGs) and tumor microenvironment (TME) in skin cutaneous melanoma (SKCM) to construct a prognostic model to help SKCM patients obtain accurate clinical treatment strategies. METHODS SKCM expression data and clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differential expression analysis, LASSO algorithm, and univariate and multivariate cox regression analysis were used to screen prognosis-related genes (GPR19, GPR146, S1PR2, PTH1R, ADGRE5, CXCR3, GPR143, and OR2I1P) and multiple prognosis-good immune cells; the data set was analyzed according to above results and build up a GPR-TME classifier. The model was further subjected to immune infiltration, functional enrichment, tumor mutational load, immunotherapy prediction, and scRNA-seq data analysis. Finally, cellular experiments were conducted to validate the functionality of the key gene GPR19 in the model. RESULTS The findings indicate that high expression of GPRGs is associated with a poor prognosis in patients with SKCM, highlighting the significant role of GPRGs and the tumor microenvironment (TME) in SKCM development. Notably, the group characterized by low GPR expression and a high TME exhibited the most favorable prognosis and immunotherapeutic efficacy. Furthermore, cellular assays demonstrated that knockdown of GPR19 significantly reduced the proliferation, migration, and invasive capabilities of melanoma cells in A375 and A2058 cell lines. CONCLUSION This study provides novel insights for the prognosis evaluation and treatment of melanoma, along with the identification of a new biomarker, GPR19.
Collapse
Affiliation(s)
- Binyu Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Kai Wang
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Yixuan Peng
- School of Basic Medicine, The Fourth Military Medical University, 169 Changle West Road, Xi'an, 710032, China
| | - Yuhan Zhu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Zhiwei Cui
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China
| | - Lin Chen
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China.
| | - Zhou Yu
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China.
| | - Baoqiang Song
- Department of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, 127 Changle West Road, Xi'an, 710032, Shaanxi Province, China.
| |
Collapse
|
5
|
Chen J, Yu N, Ou S, Wang X, Li H, Zhu H. Integrated analysis reveals SMARCD1 is a potential biomarker and therapeutic target in skin cutaneous melanoma. J Cancer Res Clin Oncol 2023; 149:11619-11634. [PMID: 37401939 DOI: 10.1007/s00432-023-05064-8] [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: 06/07/2023] [Accepted: 06/29/2023] [Indexed: 07/05/2023]
Abstract
OBJECTIVE SMARCD1 is a part of the SWI/SNF chromatin remodeling complex family, which consists of transcription factors that are implicated in various types of cancer. Examining SMARCD1 expression in human cancers can provide valuable insights into the development and progression of skin cutaneous melanoma (SKCM). METHODS Our study comprehensively examined the association between SMARCD1 expression and numerous factors, including prognosis, tumor microenvironment (TME), immune infiltration, tumor mutational burden (TMB), and microsatellite instability (MSI) in SKCM. Then we utilized immunohistochemical staining to measure the SMARCD1 expression in both SKCM tissues and normal skin tissues. Furthermore, we conducted in vitro experimentation to evaluate the effects of SMARCD1 knockdown on SKCM cells. RESULTS We found that aberrant expression of SMARCD1 across 16 cancers was strongly correlated with overall survival (OS) and progression-free survival (PFS). In addition, our research revealed that SMARCD1 expression is associated with multiple factors in different types of cancer, including immune infiltration, TME, immune-related genes, MSI, TMB, and sensitivity to anti-cancer drugs. SMARCD1 is likely involved in various SKCM signaling pathways and biological processes. Additionally, our research revealed that an SMARCD1-based risk factor model accurately predicted OS in SKCM patients. Furthermore, the downregulation of SMARCD1 expression demonstrated a significant inhibition of SKCM cell proliferation and migration, as well as an increase in apoptosis and cell cycle arrest. CONCLUSION We conclude that SMARCD1 is a promising diagnostic, prognostic, and therapeutic biomarker for SKCM, and its expression has significant clinical implications for the development of novel treatment strategies.
Collapse
Affiliation(s)
- Jiaoquan Chen
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, Guangdong, China
| | - Nanji Yu
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, Guangdong, China
| | - Shanshan Ou
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, Guangdong, China
| | - Xue Wang
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, Guangdong, China
| | - Huaping Li
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, Guangdong, China
| | - Huilan Zhu
- Department of Dermatology, Guangzhou Institute of Dermatology, Guangzhou, 510095, Guangdong, China.
| |
Collapse
|
6
|
Cui Z, Liang Z, Song B, Zhu Y, Chen G, Gu Y, Liang B, Ma J, Song B. Machine learning-based signature of necrosis-associated lncRNAs for prognostic and immunotherapy response prediction in cutaneous melanoma and tumor immune landscape characterization. Front Endocrinol (Lausanne) 2023; 14:1180732. [PMID: 37229449 PMCID: PMC10203625 DOI: 10.3389/fendo.2023.1180732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 04/03/2023] [Indexed: 05/27/2023] Open
Abstract
Background Cutaneous melanoma (CM) is one of the malignant tumors with a relative high lethality. Necroptosis is a novel programmed cell death that participates in anti-tumor immunity and tumor prognosis. Necroptosis has been found to play an important role in tumors like CM. However, the necroptosis-associated lncRNAs' potential prognostic value in CM has not been identified. Methods The RNA sequencing data collected from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx) was utilized to identify differentially expressed genes in CM. By using the univariate Cox regression analysis and machine learning LASSO algorithm, a prognostic risk model had been built depending on 5 necroptosis-associated lncRNAs and was verified by internal validation. The performance of this prognostic model was assessed by the receiver operating characteristic curves. A nomogram was constructed and verified by calibration. Furthermore, we also performed sub-group K-M analysis to explore the 5 lncRNAs' expression in different clinical stages. Function enrichment had been analyzed by GSEA and ssGSEA. In addition, qRT-PCR was performed to verify the five lncRNAs' expression level in CM cell line (A2058 and A375) and normal keratinocyte cell line (HaCaT). Results We constructed a prognostic model based on five necroptosis-associated lncRNAs (AC245041.1, LINC00665, AC018553.1, LINC01871, and AC107464.3) and divided patients into high-risk group and low-risk group depending on risk scores. A predictive nomogram had been built to be a prognostic indicator to clinical factors. Functional enrichment analysis showed that immune functions had more relationship and immune checkpoints were more activated in low-risk group than that in high-risk group. Thus, the low-risk group would have a more sensitive response to immunotherapy. Conclusion This risk score signature could be used to divide CM patients into low- and high-risk groups, and facilitate treatment strategy decision making that immunotherapy is more suitable for those in low-risk group, providing a new sight for CM prognostic evaluation.
Collapse
Affiliation(s)
- Zhiwei Cui
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Zhen Liang
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Binyu Song
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Yuhan Zhu
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Guo Chen
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Yanan Gu
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Baoyan Liang
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Jungang Ma
- Department of Cancer Center, Daping Hospital, Army Medical University, Chongqing, China
| | - Baoqiang Song
- Department of Plastic and Reconstructive Surgery, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| |
Collapse
|
7
|
Xiong K, Wang Z, Hounye AH, Peng L, Zhang J, Qi M. Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients. Apoptosis 2023; 28:840-859. [PMID: 36964478 DOI: 10.1007/s10495-023-01831-7] [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] [Accepted: 03/10/2023] [Indexed: 03/26/2023]
Abstract
Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.
Collapse
Affiliation(s)
- Kaifen Xiong
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China
| | - Zheng Wang
- School of Computer Science, Hunan First Normal University, Changsha, 410205, China
| | | | - Li Peng
- School of Computer Science, Hunan First Normal University, Changsha, 410205, China.
| | - 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, 518020, Guangdong, China.
- Candidate Branch of National Clinical Research Center for Skin Diseases, Shenzhen, 518020, Guangdong, China.
- Department of Geriatrics, Shenzhen People's Hospital(The Second Clinical Medical College, Jinan UniversityThe First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, Guangdong, China.
| | - Min Qi
- Department of Plastic Surgery, Xiangya Hospital, Central South University, Changsha, 410008, China.
| |
Collapse
|