Biology subjects

Musulen, E.

Publications and source records attributed to Musulen, E..

4 recordsLinked to original sources

bioRxiv2024

Discovery and evaluation of novel biomarkers reveal dasatinib as a potential treatment for a specific subtype of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) represents the most heterogeneous and aggressive subtype of breast carcinomas, characterized by the absence of clinical biomarkers (ER, PR, and HER2) and the lack of targeted therapies. In this regard, several clinical trials have consistently failed to effectively stratify patients and identify specific treatments that elicit substantial responses. This study aims to pinpoint biomarkers expressed exclusively in the basal mammary epithelial compartment, facilitating a refined subclassification of this breast cancer subtype. Using computational analyses of single-cell RNA sequencing data, we have identified a list of genes associated with basal identity (BC-markers). Histological validation in 137 human samples has enabled us to categorize TNBC patients into BC-positive and BC-negative TNBC subtypes. Significantly, the presence of these markers correlates with a poorer prognosis in TNBC patients. Functional analyses have revealed a pivotal role for TAGLN in cell migration, likely influencing tumor aggressiveness. Further, we discovered that BC-marker expression is associated with the mesenchymal phenotype and increased sensitivity to the tyrosine kinase inhibitor dasatinib, particularly in BC-positive TNBC, suggesting novel therapeutic avenues. In our study, TAGLN emerged as a potential predictive biomarker for dasatinib responsiveness, offering new directions for personalized therapy for TNBC patients.

cancer biology↗

bioRxiv2024

Spatial transcriptomics unveils the in situ cellular and molecular hallmarks of the lung in fatal COVID-19

Severe Coronavirus disease 2019 (COVID-19) induces heterogeneous and progressive diffuse alveolar damage (DAD) highly disrupting lung tissue architecture and homeostasis, hampering disease management leading to fatal outcomes. Characterizing DAD pathophysiology across disease progression is of ultimate importance to better understand the molecular and cellular features driving different DAD patterns and to optimize treatment strategies. To contextualize the interplay between cell types and assess their distribution, spatial transcriptomics (ST) techniques have emerged, allowing unprecedented resolution to investigate spatial architecture of tissues. To this end, post-mortem lung tissue provides valuable insights into cellular composition and their spatial relationships at the time of death. Here, we have leveraged VisumST technology in post-mortem COVID-19 induced acute and proliferative DAD lungs including control samples with normal morphological appearance, to unravel the immunopathological mechanisms underlying DAD, providing novel insights into cellular and molecular communication events driving DAD progression in fatal COVID-19. We report a progressive loss of endothelial cell types, pneumocytes type I and natural killer cells coupled with a continuous increase of myeloid and stromal cells, mostly peribronchial fibroblasts, over disease progression. Spatial organization analysis identified variable cellular compartments, ranging from major compartments defined by cell type lineages in control lungs to increased and more specific compartmentalization including immune-specific clusters across DAD spectrum. Importantly, spatially informed ligand-receptor interaction (LRI) analysis revealed an intercellular communication signature defining COVID-19 induced DAD lungs. Transcription factor (TF) activity enrichment analysis identified TGF-B pathway as DAD driver, highlighting SMAD3 and SMAD7 TFs activity role during lung fibrosis. Integration of deregulated LRIs and TFs activity allowed us to propose a downstream intracellular signaling pathway in peribronchial fibroblasts, suggesting potential novel therapeutic targets. Finally, spatio-temporal trajectories analysis provided insights into the alveolar epithelium regeneration program, characterizing markers of pneumocytes type II differentiation towards pneumocytes type I. In conclusion, we provide a spatial characterization of lung tissue architecture upon COVID-19 induced DAD progression, identifying molecular and cellular hallmarks that may help optimize treatment and patient management.

pathology↗

bioRxiv2024

Comparison of spatial transcriptomics technologies across six cancer types

Spatial biology experiments integrate the molecular and histological landscape of tissues to provide a previously inaccessible view of tissue biology, unlocking the architecture of complex multicellular tissues. Within spatial biology, spatial transcriptomics platforms are among the most advanced, allowing researchers to characterize the expression of thousands of genes across space. These new technologies are transforming our understanding of how cells are organized in space and communicate with each other to determine emergent phenotypes. This is particularly important in cancer research, as tumor evolution is shaped not only by the genetic properties of cancer cells but also by how they interact with the tumor microenvironment and their spatial organization. While many platforms can generate spatial transcriptomics profiles, it is still unclear in which context each platform better suits the needs of its users. Here we compare the results obtained using 5 different spatial transcriptomics (VISIUM, VISIUM CytAssist, VisiumHD, Xenium, and CosMx) and one spatial proteomics (VISIUM CytAssist) platforms across serial sections of 6 FFPE samples from primary human tumors covering some of the most common forms of the disease (lung, breast, colorectal, bladder, lymphoma and ovary). We observed that the VISIUM platform with CytAssist chemistry yielded superior data quality than manual VISIUM. On the other hand, Xenium consistently produced more reliable results for in situ platforms, with better gene clustering and fewer false positives than CosMx. Importantly, these platform-based variations didnt significantly affect cell type identification. VisiumHD offers the best options of both worlds, with subcellular resolution and whole-transcriptome coverage, albeit with some limitations that need to be accounted for in downstream analyses. Finally, by comparing VISIUM protein profiles with the spatial transcriptomics data from all four platforms on each sample, we identified several genes with mismatched RNA and protein expression patterns, highlighting the importance of multi-omics profiling to reveal the true biology of human tumors.

genomics↗

bioRxiv2022

Charting the Spatial Landscape of Cancer Hallmarks

Tumors are complex ecosystems with dozens of interacting cell types. The concept of Cancer Hallmarks distills this complexity into a set of underlying principles that govern tumor growth. Here, we exploit this abstraction to explore the physical distribution of Cancer Hallmarks across 63 primary untreated tumors from 10 cancer types using spatial transcriptomics. We show that Hallmark activity is spatially organized-with 7 out of 13 Hallmarks consistently more active in cancer cells than within the non-cancerous tumor microenvironment (TME). The opposite is true for the remaining six Hallmarks. Additionally, we discovered that genomic distance between tumor subclones correlates with differences in Cancer Hallmark activity, even leading to clone-Hallmark specialization in some cases. Finally, we demonstrate interdependent relationships between Cancer Hallmarks at the junctions of TME and cancer compartments. In conclusion, including the spatial dimension, particularly through the lens of Cancer Hallmarks, can improve our understanding of tumor ecology. SignificanceWe explored Cancer Hallmarks in 63 primary untreated tumors from 10 cancer types using spatial transcriptomics. This study unveiled spatial patterns in Hallmark activity, with some being more active in cancer cells and others in the non-cancerous tumor environment. Genomic distance impacted Hallmark activity, and we identified interdependencies at the TME-cancer junctions, improving our understanding of tumor ecology.

cancer biology↗