Genomic Landscape Alterations in Primary Tumor and Matched Lymph Node Metastasis in Hormone-Naïve Prostate Cancer Patients

Russo, Giorgio Ivan; Bonacci, Paolo Giuseppe; Bivona, Dalida Angela; Privitera, Grete Francesca; Broggi, Giuseppe; Caltabiano, Rosario; Vella, Jessica; Giudice, Arturo Lo; Asmundo, Maria Giovanna; Cimino, Sebastiano; Morgia, Giuseppe; Stefani, Stefania; Musso, Nicolò

doi:10.3390/cancers14174212

Cited by 3 publications

(1 citation statement)

References 31 publications

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“…CD8A (38), FCGR3A (39) and PTPRC (40) are identi ed as candidate biomarkers in various cancers or important molecule in PCa patients with bone metastases. Recent studies have indicated that HRAS alterations in patients with PCa lymph node metastasis demonstrated worse overall survival and disease free survival (41). Further studies are still needed to determine how these hub genes contribute to PCa bone metastases.…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Guo

Wan

et al. 2023

Preprint

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Background Immunotherapy has become a revolutionary treatment for cancer and brought new vitality to tumor immunity. Still, using either immunotherapy alone is unlikely to significantly change the outcome of prostate cancer (PCa), especially metastatic PCa. Bone metastases are the most prevalent metastatic site for advanced PCa. Therefore, finding new immunotherapy targets in PCa patients with bone metastasis is urgently needed. Methods We conducted an elaborative bioinformatics study of immune related genes (IRGs) and tumor-infiltrating immune cells (TIICs) in PCa bone metastases. The TCGA-PRAD and cBioPortal databases were integrated to obtain RNA-sequencing data and clinical prognostic information. Univariate and multivariate Cox regression analyses were conducted to construct an overall survival (OS) prediction model. GSE32269 in the GEO database was analyzed to acquire differentially expressed IRGs. A total of 209 differentially expressed IRGs were identified, of which 159 were down-regulated and 50 were up-regulated. Subsequently, the PPI network was established by Cytoscape for identifying hub genes and biological network. The OS prediction model was established by employing six IRGs (MAVS, HSP90AA1, FCGR3A, CTSB, FCER1G, and CD4). The CIBERSORT algorithm was adopted to assess the proportion of TIICs in each group. Furthermore, Transwell, MTT, and wound healing assays were employed to determine the effect of MAVS on PCa cells. Results High-risk patients had worse OS compared to the low-risk patients in the training and validation cohorts. Meanwhile, clinically practical nomograms were generated using these identified IRGs to predict the 3- and 5-year survival rates of patients. The infiltration percentages of some TIICs were closely linked to the risk score of the OS prediction model. Naïve B cells, M1 and M2 macrophages, and CD4 memory resting T cells were related to the OS. FCGR3A was closely correlated with some TIICs. In vitro experiments verified that up-regulation of MAVS suppressed the proliferation and metastatic abilities of PCa cells. Conclusions Our work presented a thorough interpretation of TIICs and IRGs for illustrating and discovering new potential immune checkpoints in bone metastases of PCa. Additionally, we developed a trustworthy OS risk score model that may serve as a prognostic biomarker and potential immune checkpoints for immunotherapy.

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Section: Discussionmentioning

confidence: 99%

Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Guo

Wan

et al. 2023

Preprint

View full text Add to dashboard Cite

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Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Guo

Fan

et al. 2023

Aging

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Is There a Role of Warburg Effect in Prostate Cancer Aggressiveness? Analysis of Expression of Enzymes of Lipidic Metabolism by Immunohistochemistry in Prostate Cancer Patients (DIAMOND Study)

Russo

Asmundo

Giudice

et al. 2023

Cancers

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Prostate Cancer (PCa) is still ranked as the first cancer in the male population and evidences have suggested an alteration of glycemic and lipidic metabolism that are related to its progression and prognosis. The aim of the study is to investigate associations between enzymes’ expression, especially involved in the lipidic pathway, and PCa aggressiveness. We retrospectively analyzed data from 390 patients with PCa or benign prostatic hyperplasia (BPH) at the Department of Urology, University of Catania. Immunohistochemical slides were evaluated for the expression of proteins related to glucose and lipidic metabolism. A total of 286 were affected by PCa while 104 by BPH. We demonstrated that ATP-lyase (odds ratio [OR]: 1.71; p < 0.01), fatty acid synthase (OR: 4.82; p < 0.01), carnitine palmitoyl transferase-1a (OR: 2.27; p < 0.05) were associated with androgen receptor (AR) expression. We found that steaoryl Co-A desaturase expression in PCa patients with total cholesterol ≥ 200 mg/dL was independently associated with ISUP ≥4 (OR: 4.22; p = 0.049). We found that CPT-1a+ was associated with biochemical recurrence (hazard ratio: 1.94; p = 0.03]). Our results support the evidence that the manipulation of lipidic metabolism could serve in the future to contrast PCa progression.

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Genomic Landscape Alterations in Primary Tumor and Matched Lymph Node Metastasis in Hormone-Naïve Prostate Cancer Patients

Cited by 3 publications

References 31 publications

Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Is There a Role of Warburg Effect in Prostate Cancer Aggressiveness? Analysis of Expression of Enzymes of Lipidic Metabolism by Immunohistochemistry in Prostate Cancer Patients (DIAMOND Study)

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