Biology subjects

Cosenza Contreras, M.

Publications and source records attributed to Cosenza Contreras, M..

2 recordsLinked to original sources

bioRxiv2024

Proteomic profiling of IDH-wildtype Glioblastoma Tissue and Serum uncovers prognostic Subtypes and Marker Candidates

BackgroundIDH-wildtype glioblastoma (GBM) is the most prevalent primary brain cancer with a 5-year survival rate below 10%. Despite combined treatment through extensive resection and radiochemotherapy, nine out of ten patients develop recurrences. The lack of targeted treatment options and reliable diagnostic markers for recurrent tumors remain major challenges. Methods & AimsIn this study, we present the proteomic characterization of tissue and serum from 55 initial GBM tumors and five matching recurrences, which we investigated for proteomic tumor subtypes and proteomic signatures associated with recurrence. ResultsPrimary tumors revealed four distinct subgroups through hierarchical clustering: a neuronal cluster with elevated mature neuron markers, an innate immunity cluster with increased protease expression, a mixed cluster, and a stem-cell cluster. Neurodevelopmental and inflammatory processes were identified as key factors influencing clustering, with proteolytic activity increasing relative to the degree of inflammation. An analysis comprising proteins with lower coverage confirmed and expanded this pattern. Patients in the neuronal cluster exhibited significantly longer survival compared to those in the stem-cell cluster. In a patient-matched differential expression analysis, five recurrent tumors displayed significantly altered protein expression compared to their primary counterparts, emphasizing the proteomic plasticity of recurrent tumors. Investigation of serum proteomes before and after surgery, using a depletion-based protocol, revealed highly patient-specific and stable proteome compositions, despite a notable increase in inflammation markers post-surgery. However, the levels of circulating proteolytic products matched to the proteolytic activity within the tissue and one fragment of proteolysis activated receptor 2 (PAR2) consistently dropped in abundance after removal of inflamed tumors. ConclusionOverall, we describe a large proteomic GBM cohort. We identified distinct tumor subgroups, molecular patterns of recurrence, and matching proteomic patterns in the bloodstream, which may improve risk prediction for recurrent GBM.

cancer biology↗

bioRxiv2024

Proteomic Characterization of Intrahepatic Cholangiocarcinoma Identifies Distinct Subgroups and Proteins Associated with Time-To-Recurrence

Background & AimsIntrahepatic cholangiocarcinoma (ICC) is a poorly understood cancer with dismal survival and high recurrence rates. ICCs are often detected in advanced stages. Surgical resection is the most important first-line treatment but limited to non-advanced cases, whereas chemotherapy provides only a moderate benefit. The proteome biology of ICC has only been scarcely studied and the prognostic value of initial ICCs proteomic features for the time-to-recurrence (TTR) remains unclear. MethodsWe dissected formalin-fixed, paraffin-embedded samples from 80 tumor- and 77 matching adjacent non-malignant (TANM) tissues. All samples were measured via liquid-chromatography mass-spectrometry (LC-MS/MS) in data independent acquisition mode (DIA). ResultsTumor- and TANM tissue showed strongly different biologies and DNA-repair, translation, and matrisomal processes were upregulated in ICC. In a hierarchical clustering analysis, we determined two proteomic subgroups of ICC, which showed significantly diverging TTRs. Cluster 1, which is associated with a beneficial prognosis, was enriched for matrisomal processes and proteolytic processing, while cluster 2 showed increased RNA and protein turnover. In a second, independent Cox proportional hazards model analysis, we identified individual proteins whose expression correlates with TTR distribution. Proteins with a positive hazard ratio were mainly involved in carbon/glucose metabolism and protein turnover. Conversely, proteins associated with a low hazard ratio were mostly linked to the extracellular matrix. Additional proteome profiling of patient-derived xenograft tumor models of ICC successfully distinguished tumor and stromal proteins and provided insights into cell-matrix interactions. ConclusionsWe successfully determine the proteome biology of ICC and present two proteome clusters in ICC patients with significantly different TTR rates and distinct biological motifs. A xenograft model confirmed the importance of tumor-stroma interactions for this cancer.

cancer biology↗