Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts.

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.

Identifying Ferroptosis Inducers, HDAC, and RTK Inhibitor Sensitivity in Melanoma Subtypes through Unbiased Drug Target Prediction.

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.

Bicarbonate defective CFTR variants increase risk for chronic pancreatitis: A meta-analysis.

INTRODUCTION: Cystic fibrosis transmembrane conductance regulator (CFTR) plays a central role in pancreatic ductal fluid secretion by mediating Cl- and HCO3- ion transport across the apical membrane. Severe CFTR mutations that diminish chloride conductance cause cystic fibrosis (CF) if both alleles are affected, whereas heterozygous carrier status increases risk for chronic pancreatitis (CP). It has been proposed that a subset of CFTR variants characterized by a selective bicarbonate conductance defect (CFTRBD) may be associated with CP but not CF. However, a rigorous genetic analysis of the presumed association has been lacking. AIMS: To investigate the role of heterozygous CFTRBD variants in CP by meta-analysis of published case-control studies. MATERIALS AND METHODS: A systematic search was conducted in the MEDLINE, Embase, Scopus, and CENTRAL databases for published studies that reported the CFTRBD variants p.R74Q, p.R75Q, p.R117H, p.R170H, p.L967S, p.L997F, p.D1152H, p.S1235R, and p.D1270N in CP patients and controls. RESULTS: Twenty-two studies were eligible for quantitative synthesis. Combined analysis of the 9 CFTRBD variants indicated enrichment in CP patients versus controls (OR = 2.31, 95% CI = 1.17-4.56). Individual analysis of CFTRBD variants revealed no association of p.R75Q with CP (OR = 1.12, 95% CI = 0.89-1.40), whereas variants p.R117H and p.L967S were significantly overrepresented in cases relative to controls (OR = 3.16, 95% CI = 1.94-5.14, and OR = 3.88, 95% CI = 1.32-11.47, respectively). The remaining 6 low-frequency variants gave inconclusive results when analyzed individually, however, their pooled analysis indicated association with CP (OR = 2.08, 95% CI = 1.38-3.13). CONCLUSION: Heterozygous CFTRBD variants, with the exception of p.R75Q, increase CP risk about 2-4-fold.

Deep Proteomic Analysis on Biobanked Paraffine-Archived Melanoma with Prognostic/Predictive Biomarker Read-Out.

The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort's heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient's response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments.

The human melanoma proteome atlas-Defining the molecular pathology.

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in-depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.