Abstract: The invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

Abstract: The invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

Abstract: The invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

Abstract: The invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

Abstract: The Invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

Abstract: The invention relates to bacterial compositions useful in the treatment of cancer. In particular, the compositions can be used as a co-therapy with an immune checkpoint therapy. The invention also relates to methods for identifying a subject that will respond to therapy with an immune checkpoint inhibitor comprising determining the abundance of bacteria in a biological sample from said subject.

Abstract: A method of identifying by spectrometry unknown microorganisms from among a set of reference species, including a first step of supervised learning of a classification model of the reference species, a second step of predicting an unknown microorganism to be identified, including acquiring a spectrum of the unknown microorganism; and inferring from said spectrum and to the classification model at least one type of microorganism to which the unknown microorganism belong. The classification model is calculated by means of a structured multi-class SVM algorithm applied to the nodes of a tree-like hierarchical representation of the reference species in terms of evolution and/or of clinical phenotype and having margin constraints including so-called “loss” functions quantifying a proximity between the tree nodes.

Abstract: A method of identifying by spectrometry of unknown microorganisms from among a set of reference species, including a first step of supervised learning of a classification model of the reference species, a second step of predicting an unknown microorganism to be identified, including acquiring a spectrum of the unknown microorganism; and applying a prediction model according to said spectrum and to the classification model to infer at least one type of microorganism to which the unknown microorganism belong. The classification model is calculated by a structured multi-class SVM algorithm applied to the nodes of a tree-like hierarchical representation of the reference species in terms of evolution and/or of clinical phenotype and having margin constraints including so-called “loss” functions quantifying a proximity between the tree nodes.