Biology subjects

Jandus, C.

Publications and source records attributed to Jandus, C..

4 recordsLinked to original sources

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↗

bioRxiv2025

Targeting CXCR4-expressing TAMs in muscle-invasive bladder cancer to enhance tumor control after immunotherapy

Bladder cancer (BC) is a prevalent malignancy with poor prognosis in advanced stages. While immune checkpoint blockade has revolutionized immunotherapy, its efficacy remains limited for most advanced BC patients. The detailed characterization of BCs tumor microenvironment (TME) is a prerequisite to understand these mechanisms of resistance and to develop new therapeutic strategies. In this study, we used a genetically engineered BC mouse model resistant to anti-PD1 treatment, and BC patient samples, to investigate the evolution of tumor-associated macrophages (TAMs) during BC progression. We identified a subset of pro-tumor TAMs expressing CXCR4, predominantly found in advanced stages of BC-bearing mice and in half of muscle-invasive BC patients from the studied cohort. Interestingly, CXCR4+ TAM-rich regions were associated with CD8 T cell-excluded areas in both mice and patients. Administration of a small molecule CXCR4 inhibitor significantly reduced the number of pro-tumor TAMs within the tumor and markedly prolonged mouse survival. Incorporating this inhibitor into a tri-immunotherapy regimen further enhanced survival, highlighting the potential of targeting multiple pathways to strongly enhance anti-tumor effects and offering new hope for improving immunotherapy in advanced BC.

immunology↗

bioRxiv2023

Robust estimation of cancer and immune cell-type proportions from bulk tumor ATAC-Seq data.

Assay for Transposase-Accessible Chromatin sequencing (ATAC-Seq) is a widely used technique to explore gene regulatory mechanisms. For most ATAC-Seq data from healthy and diseased tissues such as tumors, chromatin accessibility measurement represents a mixed signal from multiple cell types. In this work, we derive reliable chromatin accessibility marker peaks and reference profiles for most non-malignant cell types frequently observed in the micro-environment of human tumors. We then integrate these data into the EPIC deconvolution framework (Racle et al., 2017) to quantify cell-type heterogeneity in bulk ATAC-Seq data. Our EPIC-ATAC tool accurately predicts non-malignant and malignant cell fractions in tumor samples. When applied to a human breast cancer cohort, EPIC-ATAC accurately infers the immune contexture of the main breast cancer subtypes.

bioinformatics↗

bioRxiv2019

Deep motif deconvolution of HLA-II peptidomes for robust class II epitope predictions

CD4 T cells are key for priming and regulating immune recognition of infected and cancer cells, but predictions of class II epitopes have limited accuracy. We combined unbiased Mass Spectrometry-based HLA-II peptidomics with a novel motif deconvolution algorithm to profile and analyze a total of 99265 unique HLA-II ligands. Our work demonstrates substantial improvement in the definition of HLA-II binding motifs and enhanced accuracy in class II epitope predictions.

immunology↗