Establishment of Genomic, Transcriptomic and Functional Characteristics of Tumor Cells in Hyperinflammatory Hemopathies

Auto-inflammatory Diseases (AIDs) are defined by disorders of the innate immunity. They manifest themselves as episodes of inflammation associated with general signs and organ damage, mainly to the cutaneous, musculoskeletal and digestive systems. The majority of monogenic AIDs described to date begin in childhood. Aside from impaired quality of life, and disease-related organ damage (e.g. deafness in periodic cryopyrin-associated syndromes), the most severe complication of AIDs is inflammatory amyloidosis (AA), which can lead to kidney failure and dialysis. More recently, late-onset AIDs have been described, secondary to somatic mutations in auto-inflammatory genes, mainly NLRP3 (1). This discovery comes in a more general context of highlighting new forms of late-onset genetic diseases linked to somatic mutations. These discoveries have been made possible by the revolution in sequencing techniques and in particular by the new generation sequencing which allows a more in-depth analysis compared to Sanger's technique.

Blood neoplasms, known as clonal hemopathies, whether myeloid (such as myelodysplastic syndrome) or lymphoid (such as multiple myeloma), are constantly increasing in the general population. They are associated with an accumulation of somatic gene mutations that confer survival and proliferation properties to tumor cells (2). A number of manifestations of these clonal hemopathies are related to the activation of inflammatory pathways and in particular the activation of an inflammasome. For example, it has been shown that pyroptosis via activation of the NLRP3 inflammasome could be one of the pathophysiological mechanisms of myelodysplastic syndromes (3). In addition, inflammatory cytokines such as IL1 and IL6 have been shown to play a role as growth factors in these hemopathies (4). However, the mechanisms behind the activation of the inflammasome and the production of those cytokines are currently unknown.

A number of patients with clonal hemopathies develop symptoms and complications similar to those encountered during AIDs. In particular, within the reference center for autoinflammatory diseases and amyloidosis in adults, we have identified patients with myelodysplastic syndromes or clonal gammopathies complicated by autoinflammatory symptoms or AA amyloidosis. These manifestations in the context of clonal hemopathies could be called "hyperinflammatory hemopathies ".

Our hypothesis is that the inflammatory manifestations occurring in these patients are secondary to the occurrence of somatic mutations in genes known to be involved in innate immunity and AIDs.

Our main objective is to perform in patients with hyperinflammatory hemopathy a functional study in search of the activation of inflammatory pathways; then a parallel genomic and transcriptomic study using an innovative methodology (5), in order to investigate whether there are somatic mutations of innate immunity genes in a clonal subpopulation and their impact on gene expression.

The first step will be to identify the inflammatory signature of mononuclear blood cells from patients. To do this, we will recover the cells from blood and bone marrow. Real-time quantitative ELISA (Enzyme Linked ImmunoSorbent Assay) and PCR (Polymerase Chain Reaction) experiments will quantify the production of pro-inflammatory cytokines. In addition, flow cytometry experiments with membrane and intracellular co-labelling will be performed. These experiments, performed routinely in the laboratory, will make it possible to identify the cell type responsible for the overproduction of cytokines that may explain the symptoms.

The second step, truly innovative and involving state-of-the-art techniques, will consist in carrying out genomic and transcriptomic analysis of tumor cells. For this we will use methods known as "single cell analysis" with parallel sequencing of the genome and transcriptome. The aim of genomic analysis is to search for somatic mutations present in tumor cells, and to compare them with those known to be associated with AIDs (comparison with the European Infevers database in particular. The genomic results will also be compared with international cancer cell databases to look for mutations in tumor cells that could explain this clinical presentation. These Big Data studies are necessary in view of the high number of mutations expected in tumor cells. The association with the parallel transcriptomic study will allow an unsupervised clustering analysis to study the effect of somatic mutations on gene expression. Indeed, it is currently recognized that the consequences of a genetic mutation must be analyzed both by its effect on the protein structure, but also by its effect on epigenetics. Today, this type of analysis is possible using the artificial intelligence analysis method.