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Brown LK, Kanagasabai T, Li G, Celada SI, Rumph JT, Adunyah SE, Stewart LV, Chen Z. Co-targeting SKP2 and KDM5B inhibits prostate cancer progression by abrogating AKT signaling with induction of senescence and apoptosis. Prostate 2024; 84:877-887. [PMID: 38605532 DOI: 10.1002/pros.24706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 03/08/2024] [Accepted: 03/29/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND Prostate cancer (PCa) is the second-leading cause of cancer mortalities in the United States and is the most commonly diagnosed malignancy in men. While androgen deprivation therapy (ADT) is the first-line treatment option to initial responses, most PCa patients invariably develop castration-resistant PCa (CRPC). Therefore, novel and effective treatment strategies are needed. The goal of this study was to evaluate the anticancer effects of the combination of two small molecule inhibitors, SZL-P1-41 (SKP2 inhibitor) and PBIT (KDM5B inhibitor), on PCa suppression and to delineate the underlying molecular mechanisms. METHODS Human CRPC cell lines, C4-2B and PC3 cells, were treated with small molecular inhibitors alone or in combination, to assess effects on cell proliferation, migration, senescence, and apoptosis. RESULTS SKP2 and KDM5B showed an inverse regulation at the translational level in PCa cells. Cells deficient in SKP2 showed an increase in KDM5B protein level, compared to that in cells expressing SKP2. By contrast, cells deficient in KDM5B showed an increase in SKP2 protein level, compared to that in cells with KDM5B intact. The stability of SKP2 protein was prolonged in KDM5B depleted cells as measured by cycloheximide chase assay. Cells deficient in KDM5B were more vulnerable to SKP2 inhibition, showing a twofold greater reduction in proliferation compared to cells with KDM5B intact (p < 0.05). More importantly, combined inhibition of KDM5B and SKP2 significantly decreased proliferation and migration of PCa cells as compared to untreated controls (p < 0.005). Mechanistically, combined inhibition of KDM5B and SKP2 in PCa cells abrogated AKT activation, resulting in an induction of both cellular senescence and apoptosis, which was measured via Western blot analysis and senescence-associated β-galactosidase (SA-β-Gal) staining. CONCLUSIONS Combined inhibition of KDM5B and SKP2 was more effective at inhibiting proliferation and migration of CRPC cells, and this regimen would be an ideal therapeutic approach of controlling CRPC malignancy.
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Affiliation(s)
- LaKendria K Brown
- Department of Biomedical Sciences, School of Graduate Studies, Meharry Medical College, Nashville, Tennessee, USA
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Thanigaivelan Kanagasabai
- Department of Biomedical Sciences, School of Graduate Studies, Meharry Medical College, Nashville, Tennessee, USA
| | - Guoliang Li
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Sherly I Celada
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Jelonia T Rumph
- Department of Biomedical Sciences, School of Graduate Studies, Meharry Medical College, Nashville, Tennessee, USA
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
- Department of Microbiology, Immunology and Physiology, Meharry Medical College, Nashville, Tennessee, USA
| | - Samuel E Adunyah
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - LaMonica V Stewart
- Department of Biomedical Sciences, School of Graduate Studies, Meharry Medical College, Nashville, Tennessee, USA
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
| | - Zhenbang Chen
- Department of Biochemistry, Cancer Biology, Neuroscience and Pharmacology, Meharry Medical College, Nashville, Tennessee, USA
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Yu X, Feng B, Wu J, Li M. A novel anoikis-related gene signature can predict the prognosis of hepatocarcinoma patients. Transl Cancer Res 2024; 13:1834-1847. [PMID: 38737687 PMCID: PMC11082671 DOI: 10.21037/tcr-23-2096] [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: 11/13/2023] [Accepted: 02/20/2024] [Indexed: 05/14/2024]
Abstract
Background Hepatocellular carcinoma (HCC) is a major health problem with more than 850,000 cases per year worldwide. This cancer is now the third leading cause of cancer-related deaths worldwide, and the number is rising. Cancer cells develop anoikis resistance which is a vital step during cancer progression and metastatic colonization. However, there is not much research that specifically addresses the role of anoikis in HCC, especially in terms of prognosis. Methods This study obtained gene expression data and clinical information from 371 HCC patients through The Cancer Genome Atlas (TCGA) Program and The Gene Expression Omnibus (GEO) databases. A total of 516 anoikis-related genes (ANRGs) were retrieved from GeneCard database and Harmonizome portal. Differential expression analysis identified 219 differentially expressed genes (DEGs), and univariate Cox regression analysis was utilized to select 99 ANRGs associated with the prognosis of HCC patients. A risk scoring model with seven genes was established using the least absolute shrinkage and selection operator (LASSO) regression model, and internal validation of the model was performed. Results The identified 99 ANRGs are closely associated with the prognosis of HCC patients. The risk scoring model based on seven characteristic genes demonstrates excellent predictive performance, further validated by receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. The study reveals significant differences in immune cell infiltration, gene expression, and survival status among different risk groups. Conclusions The prognosis of HCC patients can be predicted using a unique prognostic model built on ANRGs in HCC.
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Affiliation(s)
- Xiaohan Yu
- General Surgery Department, Dandong Central Hospital, China Medical University, Dandong, China
| | - Bo Feng
- General Surgery Department, Dandong Central Hospital, China Medical University, Dandong, China
| | - Jinge Wu
- General Surgery Department, Dandong Central Hospital, China Medical University, Dandong, China
| | - Meng Li
- General Surgery Department, Dandong Central Hospital, China Medical University, Dandong, China
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Li J, Zhou K, Wu M, Zhang R, Jin X, Qiao H, Li J, Cao X, Zhang S, Dong G. The Characteristics of Transcription Factors Regulating T Cell Exhaustion Were Analyzed to Predict the Prognosis and Therapeutic Effect in Patients with HCC. Int J Gen Med 2023; 16:5597-5619. [PMID: 38045905 PMCID: PMC10693252 DOI: 10.2147/ijgm.s435620] [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: 09/30/2023] [Accepted: 11/08/2023] [Indexed: 12/05/2023] Open
Abstract
Purpose Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related deaths, posing a significant threat to people in diverse regions. T-cell exhaustion (Tex) can hinder the efficacy of immunotherapy in patients with HCC, and the transcription factors that regulate Tex in HCC have not yet been fully elucidated. Patients and Methods We used the single sample gene set enrichment analysis (ssGSEA) method to define the transcription factor pathway that regulates Tex and employed LASSO regression analysis to establish Tex related genes (TEXRS). To predict differences in immunotherapy efficacy between the two groups, we used the immunophenotype score and submap algorithm. RT-qPCR was used to detect the expression levels of the model genes in 21 pairs of HCC tissues. Finally, we assessed the cell communication strength and identified ligand receptors using the "CellChat" R package. Results Nine Tex transcription factors were identified as regulators of the HCC immune microenvironment, with Tex scores affecting patient survival. Patients with a high Tex Risk Score (TEXRS) had significantly worse overall survival compared to patients with low TEXRS. After adjusting for confounding factors, TEXRS remained an independent prognostic factor. Importantly, TEXRS performed well in multiple independent external validation cohorts. Various algorithms have shown that patients in the low-TEXRS group might benefit more from immunotherapy. Finally, RT-qPCR analysis of 21 HCC samples showed that C7, CD5L, and SDS were significantly downregulated in HCC tissues, consistent with the bioinformatics analysis results. Conclusion TEXRS proved to be a valuable predictor of immunotherapy and transcatheter arterial chemoembolization efficacy in patients with HCC. This holds promise for enhancing the prognosis and treatment outcomes of patients with HCC.
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Affiliation(s)
- Jingbo Li
- Department of Anesthesiology Research Institute, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Kun Zhou
- Department of Clinical Laboratory, Beidahuang Industry Group General Hospital, Harbin, People’s Republic of China
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Meng Wu
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Rongzheng Zhang
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Xi Jin
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Han Qiao
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Jiaqi Li
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Xinyang Cao
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Shuyun Zhang
- Scientific Research Center, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
| | - Guanglu Dong
- Department of Tumor Radiotherapy, The Second Affiliated Hospital of Harbin Medical University, Harbin, People’s Republic of China
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