Bexmarilimab-induced macrophage activation leads to treatment benefit in solid tumors:The phase I/II first-in-human MATINS trial

Macrophage Clever-1 contributes to impaired antigen presentation and suppression of anti-tumor immunity. This first-in-human trial investigates the safety and tolerability of Clever-1 blockade with bexmarilimab in patients with treatment-refractory solid tumors and assesses preliminary anti-tumor efficacy, pharmacodynamics, and immunologic correlates. Bexmarilimab shows no dose-limiting toxicities in part I (n = 30) and no additional safety signals in part II (n = 108). Disease control (DC) rates of 25%–40% are observed in cutaneous melanoma, gastric, hepatocellular, estrogen receptor-positive breast, and biliary tract cancers. DC associates with improved survival in a landmark analysis and correlates with high pre-treatment intratumoral Clever-1 positivity and increasing on-treatment serum interferon γ (IFNγ) levels. Spatial transcriptomics profiling of DC and non-DC tumors demonstrates bexmarilimab-induced macrophage activation and stimulation of IFNγ and T cell receptor signaling selectively in DC patients. These data suggest that bexmarilimab therapy is well tolerated and show that macrophage targeting can promote immune activation and tumor control in late-stage cancer

A comprehensive approach to the molecular determinants of lifespan using a Boolean model of geroconversion

International audienceAltered molecular responses to insulin and growth factors (GF) are responsible for late-life shortening diseases such as type-2 diabetes mellitus (T2DM) and cancers. We have built a network of the signaling pathways that control S-phase entry and a specific type of senescence called geroconversion. We have translated this network into a Boolean model to study possible cell phenotype outcomes under diverse molecular signaling conditions. In the context of insulin resistance, the model was able to reproduce the variations of the senescence level observed in tissues related to T2DM's main morbidity and mortality. Furthermore, by calibrating the pharmacodynamics of mTOR inhibitors, we have been able to reproduce the dose-dependent effect of rapamycin on liver degeneration and lifespan expansion in wild-type and HER2–neu mice. Using the model, we have finally performed an in silico prospective screen of the risk–benefit ratio of rapamycin dosage for healthy lifespan expansion strategies. We present here a comprehensive prognostic and predictive systems biology tool for human aging

Quelle vision des biomarqueurs en 2017 ? Promesses et défis de la médecine personnalisée en oncologie

International audienceThe development of personalized medicine in oncology is based on biomarkers that help select populations for more efficient and less toxic therapies. The onset of molecular biology led to new paradigms in drug development, with efficacy data reported in early clinical trials and accelerated approvals. Multiple clinical trials, including SHIVA, SAFIR-01 and MOSCATO-01, have been developed to evaluate the interest of treatment decision-making based on tumor molecular profiling, with the ambition to replace historical clinical and pathological classifications. Targeted molecular therapies have also drastically enhanced the prognosis of patients in several cancer subtypes, with increased use in the context of advanced palliative care. Breaking through those boundaries might lead to a true precision medicine in oncology, which implementation in clinical routine is now expected by patients and physicians

A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective multicohort study

International audienceBackground : Because responses of patients with cancer to immunotherapy can vary in success, innovative predictors of response to treatment are urgently needed to improve treatment outcomes. We aimed to develop and independently validate a radiomics-based biomarker of tumour-infiltrating CD8 cells in patients included in phase 1 trials of anti-programmed cell death protein (PD)-1 or anti-programmed cell death ligand 1 (PD-L1) monotherapy. We also aimed to evaluate the association between the biomarker, and tumour immune phenotype and clinical outcomes of these patients.Methods : In this retrospective multicohort study, we used four independent cohorts of patients with advanced solid tumours to develop and validate a radiomic signature predictive of immunotherapy response by combining contrast-enhanced CT images and RNA-seq genomic data from tumour biopsies to assess CD8 cell tumour infiltration. To develop the radiomic signature of CD8 cells, we used the CT images and RNA sequencing data of 135 patients with advanced solid malignant tumours who had been enrolled into the MOSCATO trial between May 1, 2012, and March 31, 2016, in France (training set). The genomic data, which are based on the CD8B gene, were used to estimate the abundance of CD8 cells in the samples and data were then aligned with the images to generate the radiomic signatures. The concordance of the radiomic signature (primary endpoint) was validated in a Cancer Genome Atlas [TGCA] database dataset including 119 patients who had available baseline preoperative imaging data and corresponding transcriptomic data on June 30, 2017. From 84 input variables used for the machine-learning method (78 radiomic features, five location variables, and one technical variable), a radiomics-based predictor of the CD8 cell expression signature was built by use of machine learning (elastic-net regularised regression method). Two other independent cohorts of patients with advanced solid tumours were used to evaluate this predictor. The immune phenotype internal cohort (n=100), were randomly selected from the Gustave Roussy Cancer Campus database of patient medical records based on previously described, extreme tumour-immune phenotypes: immune-inflamed (with dense CD8 cell infiltration) or immune-desert (with low CD8 cell infiltration), irrespective of treatment delivered; these data were used to analyse the correlation of the immune phenotype with this biomarker. Finally, the immunotherapy-treated dataset (n=137) of patients recruited from Dec 1, 2011, to Jan 31, 2014, at the Gustave Roussy Cancer Campus, who had been treated with anti-PD-1 and anti-PD-L1 monotherapy in phase 1 trials, was used to assess the predictive value of this biomarker in terms of clinical outcome.Findings :We developed a radiomic signature for CD8 cells that included eight variables, which was validated with the gene expression signature of CD8 cells in the TCGA dataset (area under the curve [AUC]=0·67; 95% CI 0·57–0·77; p=0·0019). In the cohort with assumed immune phenotypes, the signature was also able to discriminate inflamed tumours from immune-desert tumours (0·76; 0·66–0·86; p<0·0001). In patients treated with anti-PD-1 and PD-L1, a high baseline radiomic score (relative to the median) was associated with a higher proportion of patients who achieved an objective response at 3 months (vs those with progressive disease or stable disease; p=0·049) and a higher proportion of patients who had an objective response (vs those with progressive disease or stable disease; p=0·025) or stable disease (vs those with progressive disease; p=0·013) at 6 months. A high baseline radiomic score was also associated with improved overall survival in univariate (median overall survival 24·3 months in the high radiomic score group, 95% CI 18·63–42·1; vs 11·5 months in the low radiomic score group, 7·98–15·6; hazard ratio 0·58, 95% CI 0·39–0·87; p=0·0081) and multivariate analyses (0·52, 0·35–0·79; p=0·0022).Interpretation : The radiomic signature of CD8 cells was validated in three independent cohorts. This imaging predictor provided a promising way to predict the immune phenotype of tumours and to infer clinical outcomes for patients with cancer who had been treated with anti-PD-1 and PD-L1. Our imaging biomarker could be useful in estimating CD8 cell count and predicting clinical outcomes of patients treated with immunotherapy, when validated by further prospective randomised trials

Supplementary Tables S1-S11 from Integrative Pan-Cancer Genomic and Transcriptomic Analyses of Refractory Metastatic Cancer

These tables present clinical data, sample data, whole-exome and transcriptome sequencing results, literature references, and external data sources that were used for the analyses presented in the main text.</p

Sustained type I interferon signaling as a mechanism of resistance to PD-1 blockade

PD-1 blockade represents a major therapeutic avenue in anticancer immunotherapy. Delineating mechanisms of secondary resistance to this strategy is increasingly important. Here, we identified the deleterious role of signaling via the type I interferon (IFN) receptor in tumor and antigen presenting cells, that induced the expression of nitric oxide synthase 2 (NOS2), associated with intratumor accumulation of regulatory T cells (Treg) and myeloid cells and acquired resistance to anti-PD-1 monoclonal antibody (mAb). Sustained IFNβ transcription was observed in resistant tumors, in turn inducing PD-L1 and NOS2 expression in both tumor and dendritic cells (DC). Whereas PD-L1 was not involved in secondary resistance to anti-PD-1 mAb, pharmacological or genetic inhibition of NOS2 maintained long-term control of tumors by PD-1 blockade, through reduction of Treg and DC activation. Resistance to immunotherapies, including anti-PD-1 mAb in melanoma patients, was also correlated with the induction of a type I IFN signature. Hence, the role of type I IFN in response to PD-1 blockade should be revisited as sustained type I IFN signaling may contribute to resistance to therapy