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Introduction: While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Methods: Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Results: Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Discussion: Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making. [ABSTRACT FROM AUTHOR]

A study published in Clinical & Translational Medicine examines the connection between mitochondrial dysfunction, immune suppression, and the progression of BRAF V600E-mutated metastatic melanoma. The researchers analyzed proteomic data from 127 melanoma metastasis samples and discovered significant changes in mitochondrial function and immune response in BRAF V600E-mutated tumors. These findings indicate that targeting these adaptive pathways could lead to more effective treatment strategies. The study also emphasizes the important relationship between mitochondrial function and immune response in aggressive melanoma behavior. The article presents the results of a study that aimed to understand the molecular mechanisms underlying mitochondrial translation in melanoma. The researchers conducted bioinformatics analyses and found that high levels of mitochondrial ribosome proteins (MRPs) were associated with increased mitochondrial metabolic activities and compromised immune surveillance, which could facilitate tumor evasion. Conversely, tumors with lower levels of MRPs were enriched for proteins involved in extracellular matrix organization. The study suggests that targeting mitochondrial functions and combining them with immune checkpoint inhibitors could be a potential approach for treating metastatic melanoma. However, the study acknowledges the limitations of its small sample size and the need for further validation and functional studies. [Extracted from the article]

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Background Objective Methods Results Conclusions The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune‐checkpoint‐based therapies still poses a significant problem.Here, we mine large‐scale MM proteogenomic data to identify druggable targets and forecast treatment efficacy and resistance.Leveraging protein profiles from established MM subtypes and molecular structures of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC, and AKT1, across five distinct MM subtypes. These proteins are potential drug targets applicable to one or multiple MM subtypes. Additionally, by integrating proteogenomic profiles obtained from MM subtypes with MM cell line dependency and drug sensitivity data, we identified a total of 162 potentially targetable genes. Lastly, we identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype.Employing these unbiased approaches, we have uncovered compounds targeting ferroptosis demonstrating a striking 30× fold difference in sensitivity among different subtypes.Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy. [ABSTRACT FROM AUTHOR]

Copyright of Revista Saúde is the property of Revista Saude and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Saúde is the property of Revista Saude and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Prostate cancer therapy with surgical or chemical castration with gonadotropin-releasing hormone (GnRH) agonists has been linked to elevated follicle-stimulating hormone (FSH) levels, which may contribute to secondary health disorders, including atherosclerosis and diabetes. Although recent findings suggest a role for FSH beyond the reproductive system, its metabolic impact remains unclear and difficult to disentangle from that of androgens. In this study, we examined the metabolic changes induced by FSH and distinguished them from those caused by testosterone., Methods: Plasma samples from temporarily medically castrated young men (n = 33) treated with FSH and/or testosterone were characterized by proteomics and metabolomics approaches. All subjects received GnRH antagonists. Sixteen men were randomized to recombinant FSH (300 IU 3 times/week) for 5 weeks, while seventeen men served as controls. After 3 weeks, all men received 1000 mg intramuscular testosterone undecanoate. Blood samples were collected at the start, after 3 weeks and after 5 weeks. The proteome and metabolome signatures were characterized in all samples., Results: FSH significantly upregulates key proteins involved in the modulation of inflammatory response and innate immune system (P ≤ 0.03) and dysregulates lipid metabolism, evidenced by downregulation of multiple apolipoproteins (P ≤ 0.04) and increased levels of cholesterol and glycerophospholipids (P ≤ 0.03). In addition, low FSH levels were correlated with a reduction in the active form of vitamin D (P < 0.02). These results highlight the short-term metabolic impacts of FSH in males., Conclusions and Clinical Implications: Our findings underlined the FSH effect on extragonadal systems and its connection to metabolic disorders often seen as secondary effects of prostate cancer treatment.

While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.

The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies still poses a significant problem. Here we mine large scale MM proteogenomic data integrating it with MM cell line dependency screen, and drug sensitivity data to identify druggable targets and forecast treatment efficacy and resistance. Leveraging protein profiles from established MM subtypes and molecular structures of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC and AKT1, across five distinct MM subtypes. These proteins serve as potential drug targets applicable to one or multiple MM subtypes. By analyzing transcriptomic data from 48 publicly accessible melanoma cell lines sourced from Achilles and CRISPR dependency screens, we forecasted 162 potentially targetable genes. We also identified genetic resistance in 260 genes across at least one melanoma subtype. In addition, we employed publicly available compound sensitivity data (Cancer Therapeutics Response Portal, CTRPv2) on the cell lines to assess the correlation of compound effectiveness within each subtype. We have identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype. Remarkably, employing this unbiased approach, we have uncovered compounds targeting ferroptosis, that demonstrate a striking 30x fold difference in sensitivity among different subtypes. This implies that the proteogenomic classification of melanoma has the potential to predict sensitivity to ferroptosis compounds. Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy., Highlights: (1) Proteogenomic subtype classification can define the landscape of genetic dependencies in melanoma (2) Nine proteins from molecular subtypes were identified as potential drug targets for specified MM patients (3) 20 compounds identified that show potential effectiveness in at least one melanoma subtype (4) Proteogenomics can predict specific ferroptosis inducers, HDAC, and RTK Inhibitor sensitivity in melanoma subtypes.