bioRxiv Science⌕ Search

Biology subjects

Dragomir, M. P.

Publications and source records attributed to Dragomir, M. P..

2 recordsLinked to original sources

Deep spatial proteomics of ovarian cancer precursor lesions delineates early disease changes and cell-of-origin signatures

High-grade serous ovarian cancer (HGSOC) is a devastating disease that is frequently detected at an incurable stage. Advances in ultrasensitive mass spectrometry-based spatial proteomics have provided a unique opportunity to uncover early molecular events in tumorigenesis and common dysregulated pathways with high therapeutic potential. Here, we present a comprehensive proteomic analysis of serous tubal intraepithelial carcinoma (STIC), the HGSOC precursor lesion, covering more than 10,000 proteins. We found that STICs and concurrent invasive carcinomas were indistinguishable at the global proteomic level, revealing a similar level of molecular heterogeneity. Using cell-type resolved tissue proteomics, we revealed strong cell-of-origin signatures preserved in STICs and invasive tumors and identified early dysregulated pathways of therapeutic relevance, such as an onco-metabolic increase in cholesterol biosynthesis. Finally, we uncovered substantial remodeling of the co-evolving tumor microenvironment, affecting approximately one-third of the stromal proteome, and derived a common signature associated with progressive immunosuppression and extracellular matrix restructuring. In summary, our study highlights the power of spatially resolved quantitative proteomics to dissect the molecular underpinnings of early carcinogenesis and provides a rich proteomic resource for future biomarker and drug target research in ovarian cancer.

systems biology↗

A quantitative tumor-wide analysis of morphological heterogeneity of colorectal adenocarcinoma

Morphologic heterogeneity of colorectal adenocarcinoma (CRC) is poorly understood. Previously, we identified morphological patterns associated with CRC molecular subtypes, and showed that these patterns have distinct molecular motifs (Budinska et al., 2023). Here, we evaluated the heterogeneity of these patterns across CRC. Three pathologists evaluated dominant, secondary, and tertiary morphology on four different tissue blocks per tumor in a pilot set of 22 CRCs (n=88). An artificial intelligence (AI) image analysis tool was trained using the pathologist-rated tumors to assess the morphologic heterogeneity on an expanded set of 161 CRCs (644 images). Heterogeneity was expressed as a combination of morphology patterns (morphotypes) across slides and normalized Shannons index (NSI). All pathologists agreed that the majority of tumors had 2-3 different dominant morphotypes, and that the complex tubular (CT) morphotype was the most common. AI analysis confirmed these observations in the full set. CT morphotype combined with all other dominant morphotypes within a tumor. Desmoplastic (DE) morphotype was rarely dominant and rarely combined with other dominant morphotypes. Mucinous (MU) was most often combined with solid/trabecular (TB) and papillary (PP). Most tumors showed medium or high NSI, but without clinical consequence. The proportion of DE morphotype was associated with higher T-stage, N-stage, metastasis, AJCC-stage, and shorter relapse-free survival, and MU morphotype was associated with higher grade, right side, microsatellite instability, and shorter overall survival. In conclusion, we observed high intratumoral morphological heterogeneity of CRC, and that not heterogeneity per se, but the proportion of certain morphotypes showed associations with clinical outcome. This has implications for molecular profiling of CRC.

cancer biology↗