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The function of group 3 innate lymphoid cells (ILC3 cells) is still being determined. Vivier and colleagues describe the development of ILC3 subsets and show that NCR + ILC3 cells are not needed to control infection with Citrobacter rodentium in the presence of an intact T cell compartment. Intestinal T cells and group 3 innate lymphoid cells (ILC3 cells) control the composition of the microbiota and gut immune responses. Within the gut, ILC3 subsets coexist that either express or lack the natural cytoxicity receptor (NCR) NKp46. We identified here the transcriptional signature associated with the transcription factor T-bet–dependent differentiation of NCR − ILC3 cells into NCR + ILC3 cells. Contrary to the prevailing view, we found by conditional deletion of the key ILC3 genes Stat3 , Il22 , Tbx21 and Mcl1 that NCR + ILC3 cells were redundant for the control of mouse colonic infection with Citrobacter rodentium in the presence of T cells. However, NCR + ILC3 cells were essential for cecal homeostasis. Our data show that interplay between intestinal ILC3 cells and adaptive lymphocytes results in robust complementary failsafe mechanisms that ensure gut homeostasis.

Recent advancements in probe-based, full-transcriptome technologies for FFPE tissues, such as Visium CytAssist, Chromium Flex, and GeoMx DSP, enable analysis of archival samples, facilitating the generation of data from extensive cohorts. However, these methods can be labor-intensive and costly, requiring informed selection based on research objectives. We compare these methods on FFPE tumor samples in Breast, NSCLC and DLBCL showing 1) good-quality, highly reproducible data from all methods; 2) GeoMx data containing cell mixtures despite marker-based preselection; 3) Visium and Chromium outperform GeoMx in discovering tumor heterogeneity and potential drug targets. We recommend the use of Visium and Chromium for high-throughput and discovery projects, while the manually more challenging GeoMx platform with targeted regions remains valuable for specialized questions. Currently, there is an urgent need to evaluate the strengths and limitations of various probe-based full transcriptome methods for formalin-fixed paraffin-embedded tumor tissues. Here, the authors analyze three commonly used methods and highlight relative advantages and disadvantages of each method in the context of operational challenges, bioinformatic analyses and biological discoveries.

Genomic grade (GG) is a 97-gene signature which improves the accuracy and prognostic value of histological grade (HG) in invasive breast carcinoma. Since most of the genes included in the GG are involved in cell proliferation, we performed a retrospective study to compare the prognostic value of GG, Mitotic Index and Ki67 score. A series of 163 consecutive breast cancers was retained (pT1-2, pN0, pM0, 10-yr follow-up). GG was computed using MapQuant Dx(R). GG was low (GG-1) in 48%, high (GG-3) in 31% and equivocal in 21% of cases. For HG-2 tumors, 50% were classified as GG-1, 18% as GG-3 whereas 31% remained equivocal. In a subgroup of 132 ER+/HER2- tumors GG was the most significant prognostic factor in multivariate Cox regression analysis adjusted for age and tumor size (HR = 5.23, p = 0.02). In a reference comprehensive cancer center setting, compared to histological grade, GG added significant information on cell proliferation in breast cancers. In patients with HG-2 carcinoma, applying the GG to guide the treatment scheme could lead to a reduction in adjuvant therapy prescription. However, based on the results observed and considering (i) the relatively close prognostic values of GG and Ki67, (ii) the reclassification of about 30% of HG-2 tumors as Equivocal GG and (iii) the economical and technical requirements of the MapQuant micro-array GG test, the availability in the near future of a PCR-based Genomic Grade test with improved performances may lead to an introduction in clinical routine of this test for histological grade 2, ER positive, HER2 negative breast carcinoma.

BackgroundCoronavirus disease 2019 (COVID-19) is a new pandemic disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The C5a anaphylatoxin and its receptor C5aR1 (CD88) play a key role in the initiation and maintenance of several inflammatory responses, by recruiting and activating neutrophils and monocytes in the lungs.MethodsWe provide a longitudinal analysis of immune responses, including immune cell phenotyping and assessments of the soluble factors present in the blood and broncho-alveolar lavage fluid (BALF) of patients at various stages of COVID-19 severity: paucisymptomatic, pneumonia and acute respiratory distress syndrome (ARDS)ResultsWe report an increase in soluble C5a levels proportional to COVID-19 severity and high levels of C5aR1 expression in blood and pulmonary myeloid cells, supporting a role for the C5a-C5aR1 axis in the pathophysiology of ARDS. Avdoralimab, an anti-C5aR1 therapeutic monoclonal antibodies (mAbs) prevented C5a-mediated human myeloid cell recruitment and activation, and inhibited acute lung injury (ALI) in human C5aR1 knockin mice.ConclusionsThese results support the evaluation of avdoralimab to block C5a-C5aR1 axis as a mean of limiting myeloid cell infiltration in damaged organs and preventing the excessive lung inflammation and endothelialitis associated with ARDS in COVID-19 patientsAcknowledgementsThe Explore COVID-19 IPH group, the Explore COVID-19 Marseille Immunopole group.Ethics ApprovalHuman study protocol was approved by the Committee for the Protection of Persons Ile-de-France III – France (#2020-A00757-32). Animal experiments were approved by the ministere de l’enseignement superieur, de la recherche et de l’innovation – France (APAFIS#25418-2020051512242806 v2).

Coronavirus disease 2019 (COVID-19) is a disease caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has resulted in a pandemic 1 . The C5a complement factor and its receptor C5aR1 (also known as CD88) have a key role in the initiation and maintenance of several inflammatory responses by recruiting and activating neutrophils and monocytes 1 . Here we provide a longitudinal analysis of immune responses, including phenotypic analyses of immune cells and assessments of the soluble factors that are present in the blood and bronchoalveolar lavage fluid of patients at various stages of COVID-19 severity, including those who were paucisymptomatic or had pneumonia or acute respiratory distress syndrome. The levels of soluble C5a were increased in proportion to the severity of COVID-19 and high expression levels of C5aR1 receptors were found in blood and pulmonary myeloid cells, which supports a role for the C5a–C5aR1 axis in the pathophysiology of acute respiratory distress syndrome. Anti-C5aR1 therapeutic monoclonal antibodies prevented the C5a-mediated recruitment and activation of human myeloid cells, and inhibited acute lung injury in human C5aR1 knock-in mice. These results suggest that blockade of the C5a–C5aR1 axis could be used to limit the infiltration of myeloid cells in damaged organs and prevent the excessive lung inflammation and endothelialitis that are associated with acute respiratory distress syndrome in patients with COVID-19. Blockade of the C5a–C5aR1 axis using anti-C5aR1 monoclonal antibodies prevented inflammation associated with COVID-19.

The correct version of Table 5 can be seen here: thumbnail Download: * PPT PowerPoint slide * PNG larger image * TIFF original image [^] Figures Citation: Reyal F, Bollet MA, Caly M, Gentien D, Carpentier S, Peyro-Saint-Paul H, et al. (2012) Correction: Respective Prognostic Value of Genomic Grade and Histological Proliferation Markers in Early Stage (pN0) Breast Carcinoma.

Background Recent advances in the analysis of high-throughput expression data have led to the development of tools that scaled-up their focus from single-gene to gene set level. For example, the popular Gene Set Enrichment Analysis (GSEA) algorithm can detect moderate but coordinated expression changes of groups of presumably related genes between pairs of experimental conditions. This considerably improves extraction of information from high-throughput gene expression data. However, although many gene sets covering a large panel of biological fields are available in public databases, the ability to generate home-made gene sets relevant to one’s biological question is crucial but remains a substantial challenge to most biologists lacking statistic or bioinformatic expertise. This is all the more the case when attempting to define a gene set specific of one condition compared to many other ones. Thus, there is a crucial need for an easy-to-use software for generation of relevant home-made gene sets from complex datasets, their use in GSEA, and the correction of the results when applied to multiple comparisons of many experimental conditions. Result We developed BubbleGUM (GSEA Unlimited Map), a tool that allows to automatically extract molecular signatures from transcriptomic data and perform exhaustive GSEA with multiple testing correction. One original feature of BubbleGUM notably resides in its capacity to integrate and compare numerous GSEA results into an easy-to-grasp graphical representation. We applied our method to generate transcriptomic fingerprints for murine cell types and to assess their enrichments in human cell types. This analysis allowed us to confirm homologies between mouse and human immunocytes. Conclusions BubbleGUM is an open-source software that allows to automatically generate molecular signatures out of complex expression datasets and to assess directly their enrichment by GSEA on independent datasets. Enrichments are displayed in a graphical output that helps interpreting the results. This innovative methodology has recently been used to answer important questions in functional genomics, such as the degree of similarities between microarray datasets from different laboratories or with different experimental models or clinical cohorts. BubbleGUM is executable through an intuitive interface so that both bioinformaticians and biologists can use it. It is available at http://www.ciml.univ-mrs.fr/applications/BubbleGUM/index.html .

ObjectivesSystemic autoinflammatory diseases (SAIDs) represent a set of conditions with exaggerated innate immune responses. IL-1β and IL-18 are key cytokines involved in the pathogenesis of some SAID. We aimed to assess the diagnostic value of serum levels of IL-1β, IL-18, their respective inhibitors IL-1Ra and IL-18 binding protein (IL-18BP), and IFN-γ in SAID.MethodsA cohort of patients with active SAID, including monogenic (mSAID) and genetically undiagnosed SAID (guSAID) from different European countries, with active disease at inclusion, was established. Serum levels of cytokines were measured by immunoassays.ResultsSera from 53 mSAID, 220 guSAID and 49 controls without inflammatory disease were analysed. Serum levels of total and free IL-18 were significantly increased in Still’s disease in comparison to most SAID and non-inflammatory controls. Levels of total IL-18 were also elevated in patients with familial Mediterranean fever to a comparable extent as in Still’s disease. In contrast, free IL-18 levels were selectively higher in Still’s disease. Receiver operating characteristic curve analysis showed that total IL-18 was the most sensitive and specific marker for the diagnosis of Still’s disease (area under the curve=0.91). There was a positive correlation between IL-18 and ferritin. In 10 patients with Still’s disease who had a second blood collection, we found a significant decrease in serum levels of free IL-18 after treatment.ConclusionsOur results show that IL-18 can discriminate Still’s disease from other SAID, and free IL-18 levels may be relevant to assess response to therapy in these patients.

Long term mine planning is characterized by several uncertain parameters. Among these, geological uncertainty is the most critical due to its major impact on project feasibility. Indeed, an unexpected mine closure is frequently explained by an overvalued economic potential of the deposit. Furthermore, costs associated to exploration drilling are substantial and consequently, it is imperative to well represent, interpret and use the data collected. Conventionally, deterministic approaches are selected for underground mine planning where an estimated representation of the orebody is used. However, this type of reproduction leads to destruction of extreme values and misrepresentation of the grade variability. This context inspired the subject of this thesis, where, mainly, it aims to integrate and to manage risks related to geological uncertainty while optimizing long-term underground schedule. The selected approach is a stochastic optimization using a set of simulations corresponding to the deposit. First, the objective consists on developing a mathematical model for mine scheduling while considering geological uncertainty. It also aims for risk management regarding production targets. The method suggested is applied to a case study and results obtained are conclusive. Indeed, it leads to a significant increase of the project NPV and an improvement of risk management regarding production expectations. However, the large size of this problem made the resolution difficult and that is why, further studies should work on acceleration strategic without compromising the results quality.

Genomic grade (GG) is a 97-gene signature which improves the accuracy and prognostic value of histological grade (HG) in invasive breast carcinoma. Since most of the genes included in the GG are involved in cell proliferation, we performed a retrospective study to compare the prognostic value of GG, Mitotic Index and Ki67 score. A series of 163 consecutive breast cancers was retained (pT1-2, pN0, pM0, 10-yr follow-up). GG was computed using MapQuant Dx(R). GG was low (GG-1) in 48%, high (GG-3) in 31% and equivocal in 21% of cases. For HG-2 tumors, 50% were classified as GG-1, 18% as GG-3 whereas 31% remained equivocal. In a subgroup of 132 ER+/HER2- tumors GG was the most significant prognostic factor in multivariate Cox regression analysis adjusted for age and tumor size (HR = 5.23, p = 0.02). In a reference comprehensive cancer center setting, compared to histological grade, GG added significant information on cell proliferation in breast cancers. In patients with HG-2 carcinoma, applying the GG to guide the treatment scheme could lead to a reduction in adjuvant therapy prescription. However, based on the results observed and considering (i) the relatively close prognostic values of GG and Ki67, (ii) the reclassification of about 30% of HG-2 tumors as Equivocal GG and (iii) the economical and technical requirements of the MapQuant micro-array GG test, the availability in the near future of a PCR-based Genomic Grade test with improved performances may lead to an introduction in clinical routine of this test for histological grade 2, ER positive, HER2 negative breast carcinoma.