Biology subjects

Jeanneret, F.

Publications and source records attributed to Jeanneret, F..

5 recordsLinked to original sources

bioRxiv2026

Human decellularized extracellular matrix from adipose tissue is a permissive microenvironment for pancreatic organoids generation

In vitro reconstruction of human tissue microenvironments that integrate native biochemical and biomechanical cues is essential for disease modelling, regenerative medicine, and personalized therapeutic approaches. However, most currently available engineered matrices fail to recapitulate the complexity and tissue specificity of the human extracellular matrix (ECM). To address this limitation, we developed a novel hydrogel derived from decellularized human adipose tissue (atdECM) designed to support three-dimensional culture of human cells. The decellularization and delipidation processes were first validated, and the biochemical composition and biomechanical properties of atdECM were comprehensively characterized. Human pancreatic organoids were then cultured within atdECM hydrogel, and their structural organization and transcriptional profiles were analyzed and compared with those obtained in Matrigel, the current gold-standard matrix for organoid culture. Proteomic and cytokine analyses demonstrated efficient decellularization while preserving collagen-rich ECM architecture and a diverse repertoire of soluble bioactive factors. AtdECM exhibited physiological stiffness and retained tissue-specific extracellular cues. Pancreatic organoids cultured in atdECM displayed morphological similarities with those grown in Matrigel but exhibited transcriptional profiles more consistent with physiological epithelial homeostasis, with reduced activation of inflammatory and stress-related pathways. Altogether, these findings indicate that atdECM provides a human-derived, tissue-relevant, and permissive microenvironment for human organoid generation. This platform represents a promising alternative to Matrigel for studying human tissue biology and for developing physiologically relevant in vitro models.

bioengineering↗

bioRxiv2024

DNA methylation is a key determinant of response to targeted and immune checkpoint therapies in metastatic renal cell carcinoma

The response to targeted therapies and immune checkpoint inhibitors for patients suffering from metastatic clear cell renal cell carcinoma (ccRCC) is heterogeneous and currently not predictable in clinic. In this work, a comprehensive integrated study of 700 ccRCCs profiled by DNA methylation and RNA sequencing showed that the hyper-methylated tumors exhibited a worse prognosis, a higher fraction of cycling tumor cells and a lower activity of homeobox transcription factors. To translate the use of DNA methylation information into a clinical setting, we developed a simple model accurately predicting the ccRCC methylation subtypes (AUC-ROCs of 0.91) from two gene expression ratios (IGF2BP3/PCCA, TNNT1/TMEM88). In addition, these methylation subtypes were significantly associated with the therapeutic outcome of patients to anti-PD-1, mTOR inhibitor or tyrosine kinase inhibitor therapies. Overall, our framework for predicting the ccRCC DNA methylation subtypes from targeted gene expression data is easy to translate in clinic and contributes to better personalization of ccRCC therapies.

bioinformatics↗

bioRxiv2023

Microenvironment of metastatic site reveals key predictors of PD-1 blockade response in renal cell carcinoma

Immune checkpoint blockade (ICB) therapies have improved the overall survival (OS) of many patients with advanced cancers. However, the response rate to ICB varies widely among patients, exposing non-responders to potentially severe immune-related adverse events. The discovery of new biomarkers to identify patients responding to ICB is now a critical need in the clinic. We therefore investigated the tumor microenvironment (TME) of advanced clear cell renal cell carcinoma (ccRCC) samples from primary and metastatic sites to identify molecular and cellular markers of response to ICB. We revealed a significant discrepancy in treatment response between subgroups based on cell fractions inferred from metastatic sites. One of the subgroups was enriched in non-responders and harbored a lower fraction of CD8+ T cells and plasma cells, as well as a decreased expression of immunoglobulin genes. In addition, we developed the Tumor-Immunity Differential (TID) score which combines features from tumor cells and the TME to accurately predict response to anti-PD-1 immunotherapy (AUC-ROC=0.88, log-rank tests for PFS P < 0.0001, OS P = 0.01). Finally, we also defined TID-related genes (YWHAE, CXCR6 and BTF3), among which YWHAE was validated as a robust predictive marker of ICB response in independent cohorts of pre- or on-treatment biopsies of melanoma and lung cancers. Overall, these results provide a rationale to further explore variations in the cell composition of metastatic sites, and underlying gene signatures, to predict patient response to ICB treatments. One Sentence SummaryTumor microenvironment balance of metastasis and associated genes are key predictors of immunotherapy patient response in kidney cancer.

bioinformatics↗

bioRxiv2022

AB668, a novel highly selective protein kinase CK2 inhibitor with a distinct anti-tumor mechanism as compared to CX-4945 and SGC-CK2-1

Although the involvement of protein kinase CK2 in cancer is well-documented, there is a need for selective CK2 inhibitors suitable for investigating CK2 specific roles in cancer-related biological pathways and further explore its therapeutic potential. Here we have discovered AB668, a new bivalent inhibitor that binds both at the ATP site and an allosteric D pocket unique to CK2. The molecule inhibits CK2 activity with an outstanding selectivity over other kinases. Using caspase activation assay, live-cell imaging and transcriptomic analysis, we have compared the effects of this bivalent inhibitor to the non-selective ATP-competitive inhibitor CX-4945 that reached clinic and to the selective ATP-competitive SGC-CK2-1 molecule. Our results show that in contrast to CX-4945 or SGC-CK2-1, AB668 has a distinct mechanism of action regarding its anti-cancer activity, inducing apoptotic cell death and stimulating distinct biological pathways in several cancer cell lines while sparing healthy cells. Our data suggest that targeting a cryptic CK2 D pocket validates an allosteric approach to targeting CK2 and provides a starting point for creating drug-like CK2 inhibitors for aggressive cancers.

biochemistry↗

bioRxiv2021

Towards an integrative multi-omics workflow

The advent of high-throughput techniques has greatly enhanced biological discovery. Last years, analysis of multi-omics data has taken the front seat to improve physiological understanding. Handling functional enrichment results from various biological data raises practical questions. We propose an integrative workflow to better interpret biological process insights in a multi-omics approach applied to breast cancer data from The Cancer Genome Atlas (TCGA) related to Invasive Ductal Carcinoma (IDC) and Invasive Lobular Carcinoma (ILC). Pathway enrichment by Over Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA) has been conducted with both features information from differential expression analysis or selected features from multi-block sPLS-DA methods. Then, comprehensive comparisons of enrichment results have been carried out by looking at classical enrichment analysis, probabilities pooling by Stouffers Z scores method and pathways clustering in biological themes. Our work shows that ORA enrichment with selected sPLS-DA features and pathways probabilities pooling by Stouffers method lead to enrichment maps highly associated to physiological knowledge of IDC or ILC phenotypes, better than ORA and GSEA with differential expression driven features.

bioinformatics↗