Biology subjects

Rezvani, H.-R.

Publications and source records attributed to Rezvani, H.-R..

4 recordsLinked to original sources

bioRxiv2026

SpaceBlocks: an expert-supervised workflow for cohort-level spatial transcriptomics analysis

Spatial transcriptomics (ST) has become a central tool in tissue biology, with multiple technologies addressing the issue from a different angle. Each platform imposes its own raw data format conventions, and few workflows address reproducible, scalable, cohort-level analyses while integrating expert-supervised decisions to strengthen computational and biological provenance. In this work, we present SpaceBlocks, a Snakemake workflow for reproducible cohort-level analysis of single-cell resolution-ST data that prioritizes expert supervision over full automation. SpaceBlocks homogenizes heterogeneous platform outputs into a common data format, whose structure is validated to ensure downstream processing. Comprehensive expert supervision is facilitated through per sample quality control and cell type annotation diagnostic visualizations, after which downstream analyses automatically follow. SpaceBlocks also allows the ingestion of technology-agnostic externally formatted data and provides interoperability with existing tools and technologies. We demonstrate the use of SpaceBlocks through the reanalysis of 37 samples from public Visium HD, Xenium 5K and MERSCOPE datasets. SpaceBlocks exhibited processing scalability across the three platforms. This reanalysis identified previously missed cell types in Visium HD and heterogeneous marker gene expression in MERSCOPE, highlighting the need for expert-supervised annotations. Moreover, SpaceBlocks facilitated the identification of differentially expressed genes associated with previously defined multiple sclerosis (MS) spatial domains in MERSCOPE, and transcriptional differences between healthy and malignant colorectal tissues in Visium HD. Together, these findings establish SpaceBlocks as a flexible and reproducible workflow for expert-supervised spatial transcriptomics analysis across technologies and biological cohorts.

bioinformatics↗

bioRxiv2026

Spatial and Bulk Transcriptomic Profiling Defines the Molecular Evolution of Cutaneous Squamous Cell Carcinoma and Reveals Stage-Specific Biomarkers of Clinical Relevance

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer associated with substantial morbidity and mortality in advanced stages. Despite its well-described stepwise progression from actinic keratosis to invasive disease, robust molecular markers for stage discrimination and clinical decision-making remain limited. We sought to define the transcriptional continuum underlying cSCC progression, identify stage-associated biomarkers, and assess the broader relevance of these programs across human malignancies. Bulk RNA sequencing (HTG EdgeSeq) and spatial transcriptomics (GeoMx) were performed on biopsies from eight patients, each presenting multiple disease stages (healthy skin, premalignant lesion, tumor core, and invasive front) within the same lesion field, enabling within-patient analysis of progression. Spatial transcriptomic analyses identified more than 2,000 differentially expressed genes whose expression varied across disease stages. These genes were organized into 18 coordinated expression programs reflecting progressive biological rewiring during tumor evolution. Proliferation, extracellular matrix remodeling, inflammation, and stress-response pathways were progressively upregulated, whereas epithelial differentiation and metabolic processes, including lipid and amino acid metabolism, were downregulated. Macrophages exhibited distinct metabolic reprogramming, with increased purine metabolism, glycolysis, and pyruvate metabolism across progression. To evaluate the broader clinical relevance of these progression-associated programs, we developed a reproducible Snakemake pipeline to systematically screen 32 solid and hematologic malignancies from The Cancer Genome Atlas (TCGA). A combined cSCC-progression signature was significantly associated with poor overall survival (P < 0.05) in 10 additional cancer types. Finally, we identified 12 stage-informative biomarkers, whose spatially restricted expression patterns were validated using Visium HD. This study provides a spatially resolved and stage-aware transcriptomic map of cSCC progression, identifies coordinated gene programs underlying disease evolution, and defines progression-associated signatures with prognostic relevance across multiple cancers, highlighting their potential translational value.

cancer biology↗

bioRxiv2025

Type I Interferon Signaling Defines a Novel Disease Signature in Xeroderma Pigmentosum C Human Keratinocytes

Xeroderma Pigmentosum C (XPC) is a DNA damage recognition protein central to the global genome nucleotide excision repair (GG-NER) pathway, where it acts as a primary sensor of UV-induced DNA lesions. Loss-of-function mutations in the XPC gene lead to a photosensitive phenotype, with marked accumulation of unrepaired DNA damage and a dramatically elevated risk (10,000-fold) of skin cancer. However, understanding the molecular signaling mechanisms associated with XP-C has been hindered by the lack of reproducible disease models. Here, we overcome this challenge using our genetically engineered human XPC knockout (KO) keratinocytes, the predominant cell type affected by UV radiation. To uncover upstream signaling changes associated with the absence of XPC expression, we quantified protein tyrosine kinase (PTK) activity one-hour post-UVB exposure. XPC KO keratinocytes showed significant dysregulation of PTK activity on [~]100 phosphosites compared to controls. Complementary mass spectrometry (MS)-based quantitative proteomic analysis performed 24 hours post-UVB exposure identified a downstream signature comprising 791 differentially expressed proteins in XPC KO cells irradiated compared to non-irradiated counterparts. An integrative bioinformatic assessment of the kinase activity and proteomic data revealed a significant perturbation in type I interferon signaling via the JAK/STAT pathway in XPC-deficient keratinocytes, which is further exacerbated by UVB exposure. These findings were validated by western blot analysis, establishing a novel disease-associated molecular signature. Given the central role played by JAK/STAT signaling in inflammatory processes, our results implicate this pathway as a key mediator of XP-Cs hypersensitivity, thereby highlighting its potential as a therapeutic target to alleviate the disease pathology.

molecular biology↗

bioRxiv2024

Generation and characterization of CRISPR-Cas9-Mediated XPC Gene Knockout in Human Skin Cells

Xeroderma pigmentosum group C (XPC) is a versatile protein, crucial for sensing DNA damage in the global genome nucleotide excision repair (GG-NER) pathway. This pathway is vital for mammalian cells, acting as their essential approach for repairing DNA lesions stemming from interactions with environmental factors, such as exposure to ultraviolet (UV) radiation from the sun. Loss-of-function mutations in the XPC gene confer a photosensitive phenotype in XP-C patients with the accumulation of unrepaired UV induced DNA damage. This remarkable increase in DNA damage tends to elevate by 10,000-fold the risk of developing melanoma and non-melanoma skin cancers. To date, creating accurate and reproducible models to study human XP-C disease has been an important challenge. To tackle this, we used CRISPR-Cas9 technology in order to knockout XPC gene in various human skin cells (keratinocytes, fibroblasts, and melanocytes). After validation of the XPC knockout in these edited skin cells, we showed that they recapitulate the major phenotypes of XPC mutations: photosensitivity and the impairment of UV induced DNA damage repair. Moreover, these mutated cells demonstrated a reduced proliferative capacity compared to their respective wild-type controls. Finally, to better mimic the disease environment, we built a 3D reconstructed skin using these XPC knockout skin cells. This model exhibited an abnormal behavior, showing an extensive remodeling of its extracellular matrix compared to normal skin. Analyzing the composition of the fibroblasts secretome revealed a significant augmented shift in the inflammatory response following XPC knockout. Our innovative "disease on a dish" approach can provide valuable insights into the molecular mechanisms underlying XP-C disease, paving the way to design novel preventive and therapeutic strategies to alleviate the disease phenotype. Also, given the high risk of skin cancer onset in XP-C disease, our new approach can also serve as a link to draw novel insights towards this elusive field.

genetics↗