Biology subjects

Gueguen, P.

Publications and source records attributed to Gueguen, P..

5 recordsLinked to original sources

bioRxiv2026

Keto-gluconeogenic metabolic axis mirrors renal homeostasis and post-injury response in spatial transcriptomics

Metabolic disturbance is a key feature in acute kidney injury (AKI) and chronic kidney disease (CKD). The kidney highly depends on fatty acid metabolism; how renal cells rewire metabolism upon AKI and CKD transition remained unclear. Here, we combine spatial transcriptomics with biochemical analyses to characterize metabolic changes and intercellular interactions during AKI to CKD transition. Using aristolochic acid model of CKD, we spatio-temporally correlated changes in structure and function with metabolic profile during AKI to CKD transition. Surprisingly, keto-gluconeogenic metabolic axis was highly enriched in healthy kidney and paralleled injury phase transitions. Intercellular interaction analysis associated a subtype of macrophage with the drift to chronicity. Online scRNAseq datasets analysis confirmed altered keto-gluconeogenic metabolic pathways in ischemia-reperfusion injured mouse kidneys and AKI and CKD human kidney biopsies compared to healthy controls. This study identifies a metabolic axis transcriptionally mirroring renal homeostasis and injury responses, and tubulo-interstitial interactions that can be targeted to mitigate AKI to CKD transition.

pathology↗

bioRxiv2026

p63 and PITX1 sustain a pre-invasive malignant keratinocyte population in squamous cell carcinoma precursors

BackgroundCutaneous squamous cell carcinoma (cSCC) is among the most common human cancers, yet the cellular identity and molecular programs of its preinvasive precursor, actinic keratosis (AK), remains poorly defined. MethodsWe applied CITE-seq to patient-matched AK, UV-exposed normal skin, and non-UV-exposed normal skin (n=5 patients, 12 biopsies) and performed spatial whole-transcriptome profiling in an independent cohort (n=4) to map pre-invasive keratinocyte states at single-cell resolution. ResultsWe identify AK-specific keratinocytes (ASK), a discrete population localized to the dysplastic basal epidermis and characterized by UV-associated mutational signatures (SBS7b), high mutational burden, and recurrent copy number alterations including 9p loss and 8q gain. ASK occupies a basal-like undifferentiated state sustained by a {Delta}Np63/PITX1 regulatory module that attenuates Notch/HES1-driven differentiation and activates glycolytic metabolism. Comparison with published cSCC data reveals that ASK share core tumor-propagating gene networks with tumor-specific keratinocytes (TSK), including IGFBP6, IGFBP2, and ITGA6, but lack invasion effectors MMP1, MMP10, and PTHLH. Functional experiments identify IGFBP6 as a pro-proliferative factor in AK-derived keratinocytes. The AK microenvironment shows expansion of inflammatory basal keratinocytes, barrier disruption, and early immunosuppressive T cell remodeling. ConclusionsThese findings define the molecular identity of a pre-invasive malignant keratinocyte population governed by p63/PITX1 and distinguish early oncogenic programs shared with invasive cSCC from later-acquired invasion effectors, identifying candidate targets for prevention or treatment of squamous cell carcinoma.

cancer biology↗

bioRxiv2026

KLRG1 identifies circulating cytotoxic CD4 T cells with selective anti-tumor function in human cancer

Given the critical role of CD4 T cells in anti-tumor immunity, strategies to harness these cells for cancer immunotherapy are gaining increasing interest. Historically overshadowed by CD8 T cells, cytotoxic CD4 T cells can directly kill MHC class II-expressing tumor cells. However, the defining molecular signature and the mechanisms underlying their cytolytic activity remain poorly understood, particularly in cancer patients. Here, using ex vivo single-cell transcriptomic and spatial analyses of CD4 T cells from paired blood and tumor samples of melanoma patients, we identified Killer Cell Lectin-Like Receptor G1 (KLRG1) as a defining surface marker of cytotoxic CD4 T cells. The CD4+ KLRG1+ T cell subset was notably enriched among circulating cells compared with tumor-infiltrating populations, which were instead enriched in T follicular helper (Tfh) states. Functionally, KLRG1+ CD4 T cells expressed elevated levels of cytotoxic genes and exhibited superior tumor-killing capacity compared with their KLRG1- counterparts. We demonstrated that their cytotoxicity is granulysin-dependent, as confirmed by CRISPR/Cas9-mediated gene deletion. Mechanistically, CD4 T cells spared MHC class II+ cells lacking the KLRG1 ligands CD324 and CD325, such as professional antigen-presenting cells (APCs), indicating that cytotoxicity was selectively directed towards tumor cells while preserving immune cells. Finally, by investigating how the tumor microenvironment may impair CD4 T cell cytotoxicity, we showed that tumor-derived factors, including interleukin-6 (IL-6), are key drivers promoting the transition of cytotoxic CD4 T cells toward a Tfh phenotype. In summary, our findings define KLRG1 as a defining cell surface marker of cytotoxic CD4 T cells in cancer patients, as well as a key regulator that protects MHC class II+ APCs. Moreover, targeting the IL-6 signalling pathway may enhance CD4 T cell anti-tumor cytotoxicity, offering new avenues for cancer immunotherapy.

immunology↗

bioRxiv2023

Semi-supervised integration of single-cell transcriptomics data

Single-cell sequencing technologies offer unprecedented opportunities to characterize the complexity of biological samples with high resolution. At the same time, variations in sample processing and experimental protocols introduce technical variability - or "batch effects" - in the molecular readouts, hindering comparative analyses across samples and individuals. Although batch effect correction methods are routinely applied in single-cell omics analyses, data integration often leads to overcorrection, resulting in the loss of true biological variability. In this study, we present STACAS v2, a semi-supervised scRNA-seq data integration method that leverages prior knowledge in the form of cell type annotations to preserve biological variance. Through an open and reproducible benchmarking pipeline, we show that semi-supervised STACAS outperforms popular unsupervised methods such as Harmony, FastMNN, Seurat v4, scVI, and Scanorama, as well as supervised methods such as scANVI and scGen. Notably, STACAS is robust to incomplete and imprecise cell type annotations, which are commonly encountered in real-life integration tasks. Highlighting its scalability, we successfully applied semi-supervised STACAS to construct a high-resolution map of tumor-infiltrating CD8 T cells encompassing over 500,000 cells from 265 individuals. Based on our findings, we argue that the incorporation of prior cell type information should be a common practice in single-cell data integration, and we provide a flexible framework for semi-supervised batch effect correction. STACAS seamlessly integrates with Seurat pipelines and can be run with one command: Run.STACAS(seurat.list, cell.labels).

bioinformatics↗

bioRxiv2020

Contribution of resident and circulating precursors to tumor-infiltrating CD8+ T cell populations in non-small cell lung cancer patients

Tumor-infiltrating lymphocytes (TILs) in general, and CD8+ TILs in particular, represent a favorable prognostic factor in non-small cell lung cancer (NSCLC). The tissue origin, regenerative capacities, and differentiation pathways of TIL subpopulations, however, remain poorly understood. Using a combination of single cell RNA and T cell receptor (TCR) sequencing, we investigate the functional organization of TIL populations in primary NSCLC. We identify two CD8+ TIL subpopulations expressing memory-like gene modules: one is also present in blood (circulating precursors) and the other one in juxta-tumor tissue (tissue resident precursors). In tumors, these two precursor populations converge through a unique transitional state into terminally differentiated cells, often referred to as dysfunctional or exhausted. Differentiation is associated with TCR expansion, and transition from precursor to late differentiated states correlates with intratumor T cell cycling. These results provide a coherent working model for TIL origin, filiation and functional organization in primary NSCLC.

immunology↗