Biology subjects

Chiche, L.

Publications and source records attributed to Chiche, L..

5 recordsLinked to original sources

bioRxiv2022

TREM1+ regulatory myeloid cells expand in steatohepatitis-HCC and associate with poor prognosis and therapeutic resistance to anti-PD-1 blockade

Hepatocellular carcinoma (HCC) is an inflammation-associated cancer arising from viral and non-viral etiologies. Immune checkpoint blockade primarily benefits patients with viral HCC. Expansion of suppressive myeloid cells is a hallmark of chronic inflammation and cancer, but their heterogeneity in HCC is not fully resolved and might underlie immunotherapy resistance in the steatohepatitis setting. Here, we present a high resolution atlas of hepatic innate immune cells from patients with HCC that unravels a steatohepatitis contexture characterized by the emergence of high entropy myeloid cell states and myeloid-biased NK cell differentiation. We identify a discrete population of tumor-infiltrating myeloid cells, predominant in the steatohepatitis setting, that expresses a variety of myeloid lineage-affiliated genes, including granulocyte, macrophage and dendritic cell features, and can be identified in HCC tumors based on selective dual expression of TREM1 and CD163. Functional characterization reveals that TREM1+ CD163+ myeloid cells highly express TGF{beta} and IL-13RA, localize to HCC fibrotic lesions, and potently suppress T cell effector functions ex vivo, a function further potentiated by TREM1 engagement. We refer to this population as TREM1+ CD163+ regulatory myeloid cells (TREM1+CD163+ Mreg). Deconvolution analyses in large cohorts of patients with HCC and other solid tumors reveals that the density of TREM1+ CD163+ Mreg increases in advanced stages, associates with poor prognosis, and therapeutic resistance to PD-1 blockade. Our data support myeloid subset-targeted immunotherapies to treat HCC and identify TREM1 as a therapeutic target. HIGHLIGHTSO_LIAtlas of hepatic innate immune cells (100,000 transcriptomes) from patients with HCC C_LIO_LICore signatures to identify, discriminate and localize innate lymphoid and myeloid cells C_LIO_LIA population of TREM1+CD163+ myeloid cells, referred to as TREM1+CD163+ Mreg, expands in steatohepatitis HCC C_LIO_LITREM1+CD163+ Mreg express granulocyte- and macrophage/dendritic cell-lineage genes C_LIO_LITREM1+CD163+ Mreg potently suppress T cell effector functions, which is potentiated by TREM1 engagement by cognate ligands C_LIO_LITREM1+CD163+ Mreg produce high levels of TGF{beta} and populate fibrotic lesions C_LIO_LIThe density of TREM1+CD163+ Mreg increases in advanced HCC and associate with poor patient survival C_LIO_LIThe density of TREM1+CD163+ Mreg associates with resistance to immune checkpoint blockade in other solid tumors C_LI

immunology↗

bioRxiv2019

A Transcriptome Fingerprinting Assay for Clinical Immune Monitoring

BackgroundWhile our understanding of the role that the immune system plays in health and disease is growing at a rapid pace, available clinical tools to capture this complexity are lagging. We previously described the construction of a third-generation modular transcriptional repertoire derived from genome-wide transcriptional profiling of blood of 985 subjects across 16 diverse immunologic conditions, which comprises 382 distinct modules.\n\nResultsHere we describe the use of this modular repertoire framework for the development of a targeted transcriptome fingerprinting assay (TFA). The first step consisted in down-selection of the number of modules to 32, on the basis of similarities in changes in transcript abundance and functional interpretation. Next down-selection took place at the level of each of the 32 modules, with each one of them being represented by four transcripts in the final 128 gene panel. The assay was implemented on both the Fluidigm high throughput microfluidics PCR platform and the Nanostring platform, with the list of assays target probes being provided for both. Finally, we provide evidence of the versatility of this assay to assess numerous immune functions in vivo by demonstrating applications in the context of disease activity assessment in systemic lupus erythematosus and longitudinal immune monitoring during pregnancy.\n\nConclusionsThis work demonstrates the utility of data-driven network analysis applied to large-scale transcriptional profiling to identify key markers of immune responses, which can be downscaled to a rapid, inexpensive, and highly versatile assay of global immune function applicable to diverse investigations of immunopathogenesis and biomarker discovery.

immunology↗

bioRxiv2019

Elevation of FAM129A in neutrophils exposed to serum of patients with severe sepsis: in silico investigations during a hands on training workshop and follow on validation of protein expression in neutrophils

Steps involved in reductionist investigation approaches can be imitated using public transcriptome datasets as source of training material. In the present report trainees explored an apparent gap in biological knowledge for FAM129A (family with sequence similarity 129 member A). Elevated abundance of FAM129A transcripts were observed in a transcriptome dataset where neutrophils were exposed in vitro to plasma of patients with sepsis. However, no literature linking FAM129A and either neutrophils, sepsis or inflammation could be identified. Additional datasets were selected to independently validate this initial observation and further explore differential expression of FAM129A in the context of sepsis studies. Follow on investigations carried out at the bench confirmed restriction of the expression of FAM129A protein at the surface of circulating blood neutrophils and monocytes. A potential role for FAM129A in neutrophil survival was inferred from profiling of literature associated with FAM129A, which remains to be investigated in further follow on investigations.

immunology↗

bioRxiv2019

A Novel Repertoire of Blood Transcriptome Modules Based on Co-expression Patterns Across Sixteen Disease and Physiological States

As the capacity for generating large scale data continues to grow the ability to extract meaningful biological knowledge from it remains a limitation. Here we describe the development of a new fixed repertoire of transcriptional modules. It is meant to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome profiling data. It is supported by customized resources, which include analysis workflows, fingerprint grid plots data visualizations, interactive web applications providing access to a vast number of module-specific functional profiling reports, reference transcriptional profiles and give users the ability to visualize of changes in transcript abundance across the modular repertoire at different granularity levels. A use case focusing on a set of six modules comprising interferon-inducible genes is also provided. Altogether we hope that this resource will also serve as a framework for improving over time our collective understanding of the immunobiology underlying blood transcriptome profiling data.

immunology↗

bioRxiv2018

Serum GlycA level is a candidate biomarker for disease activity in systemic lupus erythematosus and for proliferative status of lupus nephritis, independent of renal function impairment.

ObjectiveGlycoprotein acetylation (GlycA) is a novel biomarker for chronic inflammation, associated to cardiovascular risk. Serum GlycA levels are increased in several inflammatory diseases, including systemic lupus erythematosus (SLE). We investigated the relevance of serum GlycA measurement in SLE and lupus nephritis (LN).\n\nMethodsGlycA was measured by NMR in 194 serum samples from patients and controls. Comparisons were performed between groups. Clinical and biological parameters were tested for correlation with GlycA levels. The predictive value of GlycA to differentiate proliferative from non-proliferative LN was determined using logistic regression models.\n\nResultsGlycA was correlated to C-reactive protein (CRP), neutrophil count, proteinuria and the SLE disease activity index (SLEDAI), and inversely with serum albumin. GlycA was higher in active (n=105) than in quiescent (n=39) SLE patients, in healthy controls (n=29), and in patients with non-lupus nephritis (n=21), despite a more altered renal function in the latter. In patients with biopsy-proven active LN, GlycA was higher in proliferative (n=32) than non-proliferative (n=11) LN, independent of renal function and proteinuria level. Logistic regression models showed that, in univariate models, GlycA outperforms traditional biomarkers. A bivariate model using GlycA and BMI better predicted the proliferative status of LN than a model comprising CRP, renal function (eGFR), serum albumin, proteinuria, C3 consumption and the presence of anti-dsDNA antibodies.\n\nConclusionSerum GlycA is elevated in SLE, and correlates with disease activity and LN. Serum GlycA, which summarizes different inflammatory processes, could be a valuable biomarker to discriminate proliferative from non-proliferative LN and should be tested in large, prospective cohorts.

immunology↗