Biology subjects

Schraml, P.

Publications and source records attributed to Schraml, P..

6 recordsLinked to original sources

bioRxiv2026

Decoding the Plasma Proteomic Landscape of Clear Cell Renal Cell Carcinoma Reveals Diagnostic and Prognostic Liquid Biopsy Biomarkers

Clear cell renal cell carcinoma (ccRCC) remains the most lethal urological malignancy, with high metastatic rates, both at initial diagnosis and during disease progression, contributing to poor survival outcomes. Current diagnostic and prognostic approaches rely primarily on histopathology, limiting early detection of localized disease and relevant intervention for metastatic patients. Here, we performed the most extensive to-date mass spectrometry-based discovery profiling of longitudinal plasma samples collected across multiple clinical follow-up points spanning up to five years post-diagnosis., to characterize the circulating plasma proteome and identify biomarkers for localized and metastatic disease. Network analysis identified protein modules enriched in pathways involved in matrix remodeling and metabolic deregulation, perpetuating the ccRCC phenotype. A five-protein signature, comprising PRL, THBS1, ANGPT1, IGFBP1, and SRGN, demonstrated high diagnostic performance for localized ccRCC. Notably, PRL appeared as a promising stand-alone biomarker (AUC = 0.812), with independent validation confirming its utility as a diagnostic biomarker. Importantly, a six-protein signature (AMBP, C1S, C2, IGFBP3, RASGRP2, TFRC) stringently distinguished metastatic from high-grade non-metastatic ccRCC cases. Further validation of these signatures could inform clinical decision-making, enabling early detection of metastasis and minimal residual disease and real-time longitudinal monitoring for ccRCC patients. Statement of SignificanceThis study presents the most comprehensive longitudinal plasma proteomic dataset for ccRCC to date, defining robust circulating protein biomarker signatures for both localized and metastatic disease, and establishing a proteomic landscape for minimally invasive, real-time monitoring and improved clinical management of ccRCC patients. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/742031v1_ufig1.gif" ALT="Figure 1000"> View larger version (35K): org.highwire.dtl.DTLVardef@196d9eorg.highwire.dtl.DTLVardef@16bbee5org.highwire.dtl.DTLVardef@c1c1a1org.highwire.dtl.DTLVardef@8f62a7_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2023

Multi-resolution deep learning characterizestertiary lymphoid structures in solid tumors

Tertiary lymphoid structures (TLSs) are dense accumulations of lym-phocytes in inflamed peripheral tissues, including cancer, and are associated with improved survival and response to immunotherapy in various solid tumors. Histological TLS quantification has been pro-posed as a novel predictive and prognostic biomarker, but lack of standardized methods of TLS characterization hampers assessment of TLS densities across different patients, diseases, and clinical centers. We introduce a novel approach based on HookNet-TLS, a multi-resolution deep learning model, for automated and unbiased TLS quantification and identification of germinal centers in routine hema-toxylin and eosin stained digital pathology slides. We developed a HookNet-TLS model using n=1019 manually annotated TCGA slides from clear cell renal cell carcinoma, muscle-invasive blad-der cancer, and lung squamous cell carcinoma. We show that HookNet-TLS automates TLS quantification with a human-level performance and demonstrates prognostic associations similar to visual assessment. We made HookNet-TLS publicly available to aid the adoption of objective TLS assessment in routine pathology.

pathology↗

bioRxiv2022

Pro-apoptotic and anti-invasive properties underscore the tumor suppressing impact of myoglobin on subset of human breast cancer cells

Expression of myoglobin (MB), well known as the oxygen storage and transport protein of myocytes, is a novel hallmark of the luminal subtype in breast cancer patients and correlates with better prognosis. The mechanisms by which MB impacts mammary tumorigenesis are hitherto unclear. We aimed to unravel this role, by using CRISPR/Cas9 technology to generate MB-deficient clones of MCF7 and SKBR3 breast cancer cell lines and subsequently characterize them by transcriptomics plus molecular and functional analyses. As main findings, loss of MB, at normoxia, upregulated the expression of cell cyclins and increased cell survival while it prevented apoptosis in MCF7 cells. Also, MB-deficient cells were less sensitive to doxorubicin but not ionizing radiation. Under hypoxia, loss of MB enhanced partial epithelial to mesenchymal transition, thus augmenting the migratory and invasive cell behavior. Notably, in human invasive mammary ductal carcinoma tissues, MB and apoptotic marker levels were positively correlated. In addition, MB protein expression in invasive ductal carcinomas was associated with a positive prognostic value, independent of the known tumor suppressor p53. In conclusion, we provide multiple lines of evidence that endogenous MB in cancer cells by itself exerts novel tumor-suppressive roles through which it can reduce cancer malignancy.

cancer biology↗

bioRxiv2021

A statistical test for clonal exclusivity in tumour evolution

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Pairs of mutations that are overrepresented in a clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical test, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our test for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 6 clonally exclusive and 2 clonally co-occurring gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

cancer biology↗

bioRxiv2020

Highly multiplexed molecular and cellular mapping of breast cancer tissue in three dimensions using mass tomography.

A holistic understanding of tissue and organ structures and their functions requires the detection of molecular constituents in their original three-dimensional (3D) context. Imaging mass cytometry (IMC) makes possible the detection of up to 40 antigens and specific nucleic acids simultaneously using metal-tagged antibodies or nucleic acid probes, respectively, but has so far been restricted to two-dimensional imaging. To enable use of IMC for 3D tissue analyses, we developed mass tomography, which combines quasi deformation-free serial sectioning with novel computational methods. We utilized mass tomography to analyze a breast cancer sample. The resulting 3D representation reveals spatial and cellular heterogeneity, preferential cell-to-cell interactions, detailed tissue-architecture motifs, and the unique microenvironment of a micro-invasion, where micro-metastases clonality is examined, showing that cells arising from the same invasive area, displaying very distinct phenotypes, are all able to produce initial invasive lesions. Mass tomography will provide invaluable insights into the tissue microenvironment, cellular neighborhoods, and tissue organization.

cell biology↗

bioRxiv2018

Intra-tumor heterogeneity and clonal exclusivity in renal cell carcinoma

Intra-tumour heterogeneity is the molecular hallmark of renal cancer, and the molecular tumour composition determines the treatment outcome of renal cancer patients. In renal cancer tumourigenesis, in general, different tumour clones evolve over time. We analysed intra-tumour heterogeneity and subclonal mutation patterns in 178 tumour samples obtained from 89 clear cell renal cell carcinoma patients. In an initial discovery phase, whole-exome and transcriptome sequencing data from paired tumour biopsies from 16 ccRCC patients were used to design a gene panel for follow-up analysis. In this second phase, 826 selected genes were targeted at deep coverage in an extended cohort of 89 patients for a detailed analysis of tumour heterogeneity. On average, we found 22 mutations per patient. Pairwise comparison of the two biopsies from the same tumour revealed that on average 62% of the mutations in a patient were detected in one of the two samples. In addition to commonly mutated genes (VHL, PBRM1, SETD2 and BAP1), frequent subclonal mutations with low variant allele frequency (<10%) were observed in TP53 and in mucin coding genes MUC6, MUC16, and MUC3A. Of the 89 ccRCC tumours, 87 (~98%) harboured private mutations, occurring in only one of the paired tumour samples. Clonally exclusive pathway pairs were identified using the WES data set from 16 ccRCC patients. Our findings imply that shared and private mutations significantly contribute to the complexity of differential gene expression and pathway interaction, and might explain clonal evolution of different molecular renal cancer subgroups. Multi-regional sequencing is central for the identification of subclones within ccRCC.

cancer biology↗