Clear cell renal cell carcinoma (ccRCC) is the third most common and most malignant urological cancer, with a 5-year survival rate of 10% for patients with advanced tumors. Here, we identified 10,160 unique proteins by in-depth quantitative proteomics, of which 955 proteins were significantly regulated between tumor and normal adjacent tissues. We verified four putatively secreted biomarker candidates, namely, PLOD2, FERMT3, SPARC, and SIRPα, as highly expressed proteins that are not affected by intratumor and intertumor heterogeneity. Moreover, SPARC displayed a significant increase in urine samples of patients with ccRCC, making it a promising marker for the detection of the disease in body fluids. Furthermore, based on molecular expression profiles, we propose a biomarker panel for the robust classification of ccRCC tumors into two main clusters, which significantly differed in patient outcome with an almost three times higher risk of death for cluster 1 tumors compared with cluster 2 tumors. Moreover, among the most significant clustering proteins, 13 were targets of repurposed inhibitory FDA-approved drugs. Our rigorous proteomics approach identified promising diagnostic and tumor-discriminative biomarker candidates which can serve as therapeutic targets for the treatment of ccRCC. Implications: Our in-depth quantitative proteomics analysis of ccRCC tissues identifies the putatively secreted protein SPARC as a promising urine biomarker and reveals two molecular tumor phenotypes.

Purpose Coronavirus disease 2019 (COVID‐19) continues to threaten public health globally. Severe acute respiratory coronavirus type 2 (SARS‐CoV‐2) infection‐dependent alterations in the host cell signaling network may unveil potential target proteins and pathways for therapeutic strategies. In this study, we aim to define early severity biomarkers and monitor altered pathways in the course of SARS‐CoV‐2 infection. Experimental Design We systematically analyzed plasma proteomes of COVID‐19 patients from Turkey by using mass spectrometry. Different severity grades (moderate, severe, and critical) and periods of disease (early, inflammatory, and recovery) are monitored. Significant alterations in protein expressions are used to reconstruct the COVID‐19 associated network that was further extended to connect viral and host proteins. Results Across all COVID‐19 patients, 111 differentially expressed proteins were found, of which 28 proteins were unique to our study mainly enriching in immunoglobulin production. By monitoring different severity grades and periods of disease, CLEC3B, MST1, and ITIH2 were identified as potential early predictors of COVID‐19 severity. Most importantly, we extended the COVID‐19 associated network with viral proteins and showed the connectedness of viral proteins with human proteins. The most connected viral protein ORF8, which has a role in immune evasion, targets many host proteins tightly connected to the deregulated human plasma proteins. Conclusions and Clinical Relevance Plasma proteomes from critical patients are intrinsically clustered in a distinct group than severe and moderate patients. Importantly, we did not recover any grouping based on the infection period, suggesting their distinct proteome even in the recovery phase. The new potential early severity markers can be further studied for their value in the clinics to monitor COVID‐19 prognosis. Beyond the list of plasma proteins, our disease‐associated network unravels altered pathways, and the possible therapeutic targets in SARS‐CoV‐2 infection by connecting human and viral proteins. Follow‐up studies on the disease associated network that we propose here will be useful to determine molecular details of viral perturbation and to address how the infection affects human physiology.

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Clear cell Renal Cell Carcinoma (ccRCC) is the third most common and most malignant urological cancer, with a 5-year survival rate of 10% for patients with advanced tumors. Here, we identified 10,160 unique proteins by in-depth quantitative proteomics, of which 955 proteins were significantly regulated between tumor and normal adjacent tissues. We verified 4 putatively secreted biomarker candidates, namely PLOD2, FERMT3, SPARC and SIRPα, as highly expressed proteins that are not affected by intra- and inter-tumor heterogeneity. Moreover, SPARC displayed a significant increase in urine samples of ccRCC patients, making it a promising marker for clinical screening assays. Furthermore, based on molecular expression profiles, we propose a biomarker panel for the robust classification of ccRCC tumors into two main clusters, which significantly differed in patient outcome with an almost three times higher risk of death for cluster 1 tumors compared to cluster 2 tumors. Moreover, among the most significant clustering proteins, 13 were targets of repurposed inhibitory FDA-approved drugs. Our rigorous proteomics approach identified promising diagnostic and tumor-discriminative biomarker candidates which can serve as therapeutic targets for the treatment of ccRCC.

Supplementary Data from Quantitative Proteomics Identifies Secreted Diagnostic Biomarkers as well as Tumor-Dependent Prognostic Targets for Clear Cell Renal Cell Carcinoma