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Sajjad F, Jalal A, Jalal A, Gul Z, Mubeen H, Rizvi SZ, Un-Nisa EA, Asghar A, Butool F. Multi-omic analysis of dysregulated pathways in triple negative breast cancer. Asia Pac J Clin Oncol 2024. [PMID: 38899578 DOI: 10.1111/ajco.14095] [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: 02/01/2024] [Revised: 04/18/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024]
Abstract
The aggressive characteristics of triple-negative breast cancer (TNBC) and the absence of targeted medicines make TNBC a challenging clinical case. The molecular landscape of TNBC has been well-understood thanks to recent developments in multi-omic analysis, which have also revealed dysregulated pathways and possible treatment targets. This review summarizes the utilization of multi-omic approaches in elucidating TNBC's complex biology and therapeutic avenues. Dysregulated pathways including cell cycle progression, immunological modulation, and DNA damage response have been uncovered in TNBC by multi-omic investigations that integrate genomes, transcriptomics, proteomics, and metabolomics data. Methods like this pave the door for the discovery of new therapeutic targets, such as the EGFR, PARP, and mTOR pathways, which in turn direct the creation of more precise treatments. Recent developments in TNBC treatment strategies, including immunotherapy, PARP inhibitors, and antibody-drug conjugates, show promise in clinical trials. Emerging biomarkers like MUC1, YB-1, and immune-related markers offer insights into personalized treatment approaches and prognosis prediction. Despite the strengths of multi-omic analysis in offering a more comprehensive view and personalized treatment strategies, challenges exist. Large sample sizes and ensuring high-quality data remain crucial for reliable findings. Multi-omic analysis has revolutionized TNBC research, shedding light on dysregulated pathways, potential targets, and emerging biomarkers. Continued research efforts are imperative to translate these insights into improved outcomes for TNBC patients.
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Affiliation(s)
- Fatima Sajjad
- School of Interdisciplinary Engineering and Sciences, National University of Sciences and Technology (NUST), Islamabad, Pakistan
| | - Ahmer Jalal
- Faculty of Sciences and Technology, University of Central Punjab, Lahore, Pakistan
| | - Amir Jalal
- Department of Biochemistry, Sahara Medical College, Narowal, Pakistan
| | - Zulekha Gul
- Environmental and Biological Science, Nanjing University of Science and Technology, Nanjing, China
| | - Hira Mubeen
- Faculty of Sciences and Technology, University of Central Punjab, Lahore, Pakistan
| | - Seemal Zahra Rizvi
- Faculty of Sciences and Technology, University of Central Punjab, Lahore, Pakistan
| | - Ex Alim Un-Nisa
- Food and Biotechnology Research Centre, Pakistan Council of Scientific and Industrial Research, Lahore, Pakistan
| | - Andleeb Asghar
- Institute of Pharmaceutical Sciences, University of Veterinary and Animal Sciences Lahore, Lahore, Pakistan
| | - Farah Butool
- Institute of Pharmacy, Faculty of Pharmaceutical and Allied Health Sciences, Lahore College for Women University Lahore, Lahore, Pakistan
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Laisné M, Rodgers B, Benlamara S, Wicinski J, Nicolas A, Djerroudi L, Gupta N, Ferry L, Kirsh O, Daher D, Philippe C, Okada Y, Charafe-Jauffret E, Cristofari G, Meseure D, Vincent-Salomon A, Ginestier C, Defossez PA. A novel bioinformatic approach reveals cooperation between Cancer/Testis genes in basal-like breast tumors. Oncogene 2024; 43:1369-1385. [PMID: 38467851 PMCID: PMC11065691 DOI: 10.1038/s41388-024-03002-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 02/22/2024] [Accepted: 03/01/2024] [Indexed: 03/13/2024]
Abstract
Breast cancer is the most prevalent type of cancer in women worldwide. Within breast tumors, the basal-like subtype has the worst prognosis, prompting the need for new tools to understand, detect, and treat these tumors. Certain germline-restricted genes show aberrant expression in tumors and are known as Cancer/Testis genes; their misexpression has diagnostic and therapeutic applications. Here we designed a new bioinformatic approach to examine Cancer/Testis gene misexpression in breast tumors. We identify several new markers in Luminal and HER-2 positive tumors, some of which predict response to chemotherapy. We then use machine learning to identify the two Cancer/Testis genes most associated with basal-like breast tumors: HORMAD1 and CT83. We show that these genes are expressed by tumor cells and not by the microenvironment, and that they are not expressed by normal breast progenitors; in other words, their activation occurs de novo. We find these genes are epigenetically repressed by DNA methylation, and that their activation upon DNA demethylation is irreversible, providing a memory of past epigenetic disturbances. Simultaneous expression of both genes in breast cells in vitro has a synergistic effect that increases stemness and activates a transcriptional profile also observed in double-positive tumors. Therefore, we reveal a functional cooperation between Cancer/Testis genes in basal breast tumors; these findings have consequences for the understanding, diagnosis, and therapy of the breast tumors with the worst outcomes.
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Affiliation(s)
- Marthe Laisné
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | - Brianna Rodgers
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | - Sarah Benlamara
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | - Julien Wicinski
- CRCM, Inserm, CNRS, Institut Paoli-Calmettes, Aix-Marseille University, Epithelial Stem Cells and Cancer Laboratory, Equipe Labellisée LIGUE Contre le Cancer, Marseille, France
| | - André Nicolas
- Platform of Experimental Pathology, Department of Diagnostic and Theranostic Medicine, Institut Curie-Hospital, 75005, Paris, France
| | - Lounes Djerroudi
- Department of Pathology, Institut Curie, 26 Rue d'Ulm, 75005, Paris, France
| | - Nikhil Gupta
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | - Laure Ferry
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | - Olivier Kirsh
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | - Diana Daher
- Université Paris Cité, CNRS, Epigenetics and Cell Fate, F-75013, Paris, France
| | | | - Yuki Okada
- Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, Japan
| | - Emmanuelle Charafe-Jauffret
- CRCM, Inserm, CNRS, Institut Paoli-Calmettes, Aix-Marseille University, Epithelial Stem Cells and Cancer Laboratory, Equipe Labellisée LIGUE Contre le Cancer, Marseille, France
| | | | - Didier Meseure
- Platform of Experimental Pathology, Department of Diagnostic and Theranostic Medicine, Institut Curie-Hospital, 75005, Paris, France
| | | | - Christophe Ginestier
- CRCM, Inserm, CNRS, Institut Paoli-Calmettes, Aix-Marseille University, Epithelial Stem Cells and Cancer Laboratory, Equipe Labellisée LIGUE Contre le Cancer, Marseille, France
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3
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Cao T, Huang M, Huang X, Tang T. Research and experimental verification on the mechanisms of cellular senescence in triple-negative breast cancer. PeerJ 2024; 12:e16935. [PMID: 38435998 PMCID: PMC10909353 DOI: 10.7717/peerj.16935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 01/22/2024] [Indexed: 03/05/2024] Open
Abstract
Background Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with high heterogeneity, poor prognosis, and a low 10-year survival rate of less than 50%. Although cellular senescence displays extensive effects on cancer, the comprehensions of cellular senescence-related characteristics in TNBC patients remains obscure. Method Single-cell RNA sequencing (scRNA-seq) data were analyzed by Seurat package. Scores for cellular senescence-related pathways were computed by single-sample gene set enrichment analysis (ssGSEA). Subsequently, unsupervised consensus clustering was performed for molecular cluster identification. Immune scores of patients in The Cancer Genome Atlas (TCGA) dataset and associated immune cell scores were calculated using Estimation of STromal and Immune cells in MAlignantTumours using Expression data (ESTIMATE) and Microenvironment Cell Populations-counter (MCP-counter), Tumor Immune Estimation Resource (TIMER) and Estimating the Proportion of Immune and Cancer cells (EPIC) methods, respectively. Immunotherapy scores were assessed using TIDE. Furthermore, feature genes were identified by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses; these were used to construct a risk model. Additionally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and transwell assay were conducted for in vitro validation of hub genes. Result TNBC was classified into three subtypes based on cellular senescence-related pathways as clusters 1, 2, and 3. Specifically, cluster 1 showed the best prognosis, followed by cluster 2 and cluster 3. The levels of gene expression in cluster 2 were the lowest, whereas these were the highest in cluster 3. Moreover, clusters 1 and 3 showed a high degree of immune infiltration. TIDE scores were higher for cluster 3, suggesting that immune escape was more likely in patients with the cluster 3 subtype who were less likely to benefit from immunotherapy. Next, the TNBC risk model was constructed and validated. RT-qPCR revealed that prognostic risk genes (MMP28, ACP5 and KRT6A) were up-regulated while protective genes (CT83) were down-regulated in TNBC cell lines, validating the results of the bioinformatics analysis. Meanwhile, cellular experiments revealed that ACP5 could promote the migration and invasion abilities in two TNBC cell lines. Finally, we evaluated the validity of prognostic models for assessing TME characteristics and TNBC chemotherapy response. Conclusion In conclusion, these findings help to assess the efficacy of targeted therapies in patients with different molecular subtypes, have practical applications for subtype-specific treatment of TNBC patients, and provide information on prognostic factors, as well as guidance for the revelation of the molecular mechanisms by which senescence-associated genes influence TNBC progression.
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Affiliation(s)
- Tengfei Cao
- Department of Breast Surgery, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Mengjie Huang
- Department of Breast Surgery, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xinyue Huang
- Department of Breast Surgery, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Tian Tang
- Department of Pathology, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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Gul S, Pang J, Yuan H, Chen Y, Yu Q, Wang H, Tang W. Stemness signature and targeted therapeutic drugs identification for Triple Negative Breast Cancer. Sci Data 2023; 10:815. [PMID: 37985782 PMCID: PMC10662149 DOI: 10.1038/s41597-023-02709-8] [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: 06/13/2023] [Accepted: 10/31/2023] [Indexed: 11/22/2023] Open
Abstract
Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and carries the worst prognosis, characterized by the lack of progesterone, estrogen, and HER2 gene expression. This study aimed to analyze cancer stemness-related gene signature to determine patients' risk stratification and prognosis feature with TNBC. Here one-class logistic regression (OCLR) algorithm was applied to compute the stemness index of TNBC patients. Cox and LASSO regression analysis was performed on stemness-index related genes to establish 16 genes-based prognostic signature, and their predictive performance was verified in TCGA and METABERIC merged data cohort. We diagnosed the expression level of prognostic genes signature in the tumor immune microenvironment, analyzed the TNBC scRNA-seq GSE176078 dataset, and further validated the expression level of prognostic genes using the HPA database. Finally, the small molecular compounds targeted at the anti-tumor effect of predictive genes were screened by molecular docking; this novel stemness-based prognostic genes signature study could facilitate the prognosis of patients with TNBC and thus provide a feasible therapeutic target for TNBC.
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Affiliation(s)
- Samina Gul
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China
| | - Jianyu Pang
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China
| | - Hongjun Yuan
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China
| | - Yongzhi Chen
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China
| | - Qian Yu
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China
| | - Hui Wang
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China
| | - Wenru Tang
- Laboratory of Molecular Genetics of Aging & Tumor, Medical School, Kunming University of Science and Technology, 727 jingming south road, Kunming city, Yunnan province, 650500, China.
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Xiao J, Huang F, Li L, Zhang L, Xie L, Liu B. Expression of four cancer-testis antigens in TNBC indicating potential universal immunotherapeutic targets. J Cancer Res Clin Oncol 2023; 149:15003-15011. [PMID: 37610673 PMCID: PMC10602960 DOI: 10.1007/s00432-023-05274-0] [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: 07/18/2023] [Accepted: 08/10/2023] [Indexed: 08/24/2023]
Abstract
OBJECTIVE Immunotherapy is an attractive treatment for breast cancer. Cancer-testis antigens (CTAs) are potential targets for immunotherapy for their restricted expression. Here, we investigate the expression of CTAs in breast cancer and their value for prognosis. So as to hunt for a potential panel of CTAs for universal immunotherapeutic targets. MATERIAL AND METHODS A total of 137 breast cancer tissue specimens including 51 triple-negative breast cancer (TNBC) were assessed for MAGE-A4, MAGEA1, NY-ESO-1, KK-LC-1 and PRAME expression by immunohistochemistry. The expression of PD-L1 and TILs was also calculated and correlated with the five CTAs. Clinical data were collected to evaluate the CTA's value for prognosis. Data from the K-M plotter were used as a validation cohort. RESULTS The expression of MAGE-A4, NY-ESO-1 and KK-LC-1 in TNBC was significantly higher than in non-TNBC (P = 0.012, P = 0.005, P < 0.001 respectively). 76.47% of TNBC expressed at least one of the five CTAs. Patients with positive expression of either MAGE-A4 or PRAME had a significantly extended disease-free survival (DFS). Data from the Kaplan-Meier plotter confirm our findings. CONCLUSIONS MAGE-A4, NY-ESO-1, PRAME and KK-LC-1 are overexpressed in breast cancer, especially in TNBC. Positive expression of MAGE-A4 or PARME may be associated with prolonged DFS. A panel of CTAs is attractive universal targets for immunotherapy.
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Affiliation(s)
- Jie Xiao
- Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Fengli Huang
- Department of Oncology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, 210008, China
| | - Lin Li
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210008, China
| | - Lianru Zhang
- Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China
| | - Li Xie
- Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
| | - Baorui Liu
- Department of Oncology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
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6
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Ochoa S, Hernández-Lemus E. Molecular mechanisms of multi-omic regulation in breast cancer. Front Oncol 2023; 13:1148861. [PMID: 37564937 PMCID: PMC10411627 DOI: 10.3389/fonc.2023.1148861] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 07/05/2023] [Indexed: 08/12/2023] Open
Abstract
Breast cancer is a complex disease that is influenced by the concurrent influence of multiple genetic and environmental factors. Recent advances in genomics and other high throughput biomolecular techniques (-omics) have provided numerous insights into the molecular mechanisms underlying breast cancer development and progression. A number of these mechanisms involve multiple layers of regulation. In this review, we summarize the current knowledge on the role of multiple omics in the regulation of breast cancer, including the effects of DNA methylation, non-coding RNA, and other epigenomic changes. We comment on how integrating such diverse mechanisms is envisioned as key to a more comprehensive understanding of breast carcinogenesis and cancer biology with relevance to prognostics, diagnostics and therapeutics. We also discuss the potential clinical implications of these findings and highlight areas for future research. Overall, our understanding of the molecular mechanisms of multi-omic regulation in breast cancer is rapidly increasing and has the potential to inform the development of novel therapeutic approaches for this disease.
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Affiliation(s)
- Soledad Ochoa
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
- Department of Obstetrics and Gynecology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Enrique Hernández-Lemus
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
- Center for Complexity Sciences, Universidad Nacional Autónoma de México, Mexico City, Mexico
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Norberg SM, Hinrichs CS. Engineered T cell therapy for viral and non-viral epithelial cancers. Cancer Cell 2023; 41:58-69. [PMID: 36400016 PMCID: PMC9839504 DOI: 10.1016/j.ccell.2022.10.016] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/13/2022] [Accepted: 10/17/2022] [Indexed: 11/18/2022]
Abstract
Engineered T cell therapy has shown remarkable efficacy in hematologic malignancies and has the potential for application to common epithelial cancers. Diverse T cell therapy strategies including adoptive transfer of tumor-infiltrating lymphocytes, chimeric antigen receptor (CAR)-T cells, and T cell receptor (TCR)-T cells have been studied in clinical trials. Recent research has established treatment of human papillomavirus (HPV)-associated cancers with TCR-T cells as a model for proof-of-principle studies in epithelial cancers. These studies and others have provided critical insight into mechanisms of tumor regression, therapeutic targets, treatment safety, treatment design, and barriers to curative cell therapies for common types of cancer. This perspective will review and consolidate understanding gained from clinical trials to treat viral and non-viral epithelial cancers with cell and gene therapy and will examine how past experience may guide future strategy in treatment and biomarker discovery.
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Affiliation(s)
- Scott M Norberg
- National Cancer Institute, Center for Immuno-Oncology, Bethesda, MD 20892, USA
| | - Christian S Hinrichs
- Rutgers Cancer Institute of New Jersey, Duncan and Nancy MacMillan Cancer Immunology and Metabolism Center of Excellence, New Brunswick, NJ 08901, USA.
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Tanvir I, Hassan A, Albeladi F. DNA Methylation and Epigenetic Events Underlying Renal Cell Carcinomas. Cureus 2022; 14:e30743. [DOI: 10.7759/cureus.30743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/26/2022] [Indexed: 11/05/2022] Open
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Kang Y, Gan Y, Jiang Y, You J, Huang C, Chen Q, Xu X, Chen F, Chen L. Cancer-testis antigen KK-LC-1 is a potential biomarker associated with immune cell infiltration in lung adenocarcinoma. BMC Cancer 2022; 22:834. [PMID: 35907786 PMCID: PMC9339200 DOI: 10.1186/s12885-022-09930-5] [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: 04/12/2022] [Accepted: 07/25/2022] [Indexed: 11/25/2022] Open
Abstract
Background Cancer-testis antigens (CTAs) have emerged as potential clinical biomarkers targeting immunotherapy. KK-LC-1 is a member of CTAs, which has been demonstrated in a variety of tumors tissues and been found to elicit immune responses in cancer patients. However, the expression level and immune infiltration role of KK-LC-1 in lung adenocarcinoma (LUAD) remains to be elucidated. Methods In this study, the mRNA expression and overall survival rate of KK-LC-1 were evaluated by the TIMER and TCGA database in LUAD tissues and KK-LC-1 expression was further validated by clinical serum samples using quantitative RT-PCR. The relationship of KK-LC-1 with clinicopathologic parameters was analyzed. ROC curve result showed that miR-1825 was able to distinguish preoperative breast cancer patients from healthy people and postoperative patients. Then, the ROC curves were used to examine the ability of KK-LC-1 to distinguish preoperative LUAD patients from healthy and postoperative patients. The correlation between KK-LC-1 and infiltrating immune cells and immune marker sets was investigated via TIMER, TISIDB database, and CIBERSORT algorithm. The Kaplan-Meier plotter was used to further evaluate the prognostic value based on the expression levels of KK-LC-1 in related immune cells. Results The results showed that KK-LC-1 was significantly over-expressed in LUAD, and high levels of expression of KK-LC-1 were also closely correlated with poor overall survival. We also found that KK-LC-1 associated with TMN stage, NSE and CEA. The ROC curve result showed that KK-LC-1 was able to distinguish preoperative LUAD cancer patients from healthy people and postoperative patients. Moreover, KK-LC-1 had a larger AUC with higher diagnostic sensitivity and specificity than CEA. Based on the TIMER, TISIDB database, and CIBERSORT algorithm, the expression of KK-LC-1 was negatively correlated with CD4+ T cell, Macrophage, and Dendritic Cell in LUAD. Moreover, Based on the TIMER database, KK-LC-1 expression had a remarkable correlation with the type markers of Monocyte, TAM, M1 Macrophage, and M2 Macrophage. Furthermore, KK-LC-1 expression influenced the prognosis of LUAD patients by directly affecting immune cell infiltration by the Kaplan-Meier plotter analysis. Conclusions In conclusion, KK-LC-1 may serve as a promising diagnostic and prognostic biomarker in LUAD and correlate with immune infiltration and prognosis.
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Affiliation(s)
- Yanli Kang
- Department of Clinical Laboratory, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Yuhan Gan
- Department of Clinical Laboratory, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Yingfeng Jiang
- Department of Clinical Laboratory, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Jianbin You
- Department of Clinical Laboratory, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Chen Huang
- Department of Thoracic Surgery, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Qianshun Chen
- Department of Thoracic Surgery, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Xunyu Xu
- Department of Clinical Laboratory, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China
| | - Falin Chen
- Department of Thoracic Surgery, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China.
| | - Liangyuan Chen
- Department of Clinical Laboratory, Fujian Provincial hospital, Shengli Clinical Medical College of Fujian Medical University, No.134, East street, Gulou District, Fuzhou, 350001, China.
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Thalor A, Kumar Joon H, Singh G, Roy S, Gupta D. Machine learning assisted analysis of breast cancer gene expression profiles reveals novel potential prognostic biomarkers for triple-negative breast cancer. Comput Struct Biotechnol J 2022; 20:1618-1631. [PMID: 35465161 PMCID: PMC9014315 DOI: 10.1016/j.csbj.2022.03.019] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 03/19/2022] [Accepted: 03/21/2022] [Indexed: 12/12/2022] Open
Abstract
Tumor heterogeneity and the unclear metastasis mechanisms are the leading cause for the unavailability of effective targeted therapy for Triple-negative breast cancer (TNBC), a breast cancer (BrCa) subtype characterized by high mortality and high frequency of distant metastasis cases. The identification of prognostic biomarker can improve prognosis and personalized treatment regimes. Herein, we collected gene expression datasets representing TNBC and Non-TNBC BrCa. From the complete dataset, a subset reflecting solely known cancer driver genes was also constructed. Recursive Feature Elimination (RFE) was employed to identify top 20, 25, 30, 35, 40, 45, and 50 gene signatures that differentiate TNBC from the other BrCa subtypes. Five machine learning algorithms were employed on these selected features and on the basis of model performance evaluation, it was found that for the complete and driver dataset, XGBoost performs the best for a subset of 25 and 20 genes, respectively. Out of these 45 genes from the two datasets, 34 genes were found to be differentially regulated. The Kaplan-Meier (KM) analysis for Distant Metastasis Free Survival (DMFS) of these 34 differentially regulated genes revealed four genes, out of which two are novel that could be potential prognostic genes (POU2AF1 and S100B). Finally, interactome and pathway enrichment analyses were carried out to investigate the functional role of the identified potential prognostic genes in TNBC. These genes are associated with MAPK, PI3-AkT, Wnt, TGF-β, and other signal transduction pathways, pivotal in metastasis cascade. These gene signatures can provide novel molecular-level insights into metastasis.
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Affiliation(s)
- Anamika Thalor
- Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Hemant Kumar Joon
- Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India
- Regional Centre for Biotechnology, Faridabad 121001, Haryana, India
| | - Gagandeep Singh
- Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Shikha Roy
- Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Dinesh Gupta
- Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi 110067, India
- Corresponding author at: Translational Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, India.
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11
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Ouban A. Filamin-A expression in triple-negative breast cancer and its clinical significance. BIOTECHNOL BIOTEC EQ 2021. [DOI: 10.1080/13102818.2021.1985611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Abderrahman Ouban
- Department of Pathology, College of Medicine, Alfaisal University, Riyadh, Kingdom of Saudi Arabia
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