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Characteristics of the Intestinal Microbiota in Patients With Cancer

ABSTRACT: In order to understand how the intestinal microbiota plays a role in the effectiveness of an anti-cancer treatment by an immune control point inhibitor, this study aims to constitute a catalog of microbial genes of a patient with cancer. This catalog will help to characterize the intestinal microbiota of cancer patients and to be able to use this catalog as a reference tool for screening the microbiota of patients treated with immune control point inhibitors. To produce this catalog, five types of cancer were selected: non-small cell lung cancer, colorectal cancer, hepatocellular carcinoma, breast cancer and prostate cancer. The metagenomic analysis of a group of five different types of cancers introduces a lot of heterogeneity which is favorable to the richness of a catalog. For non-small cell lung cancer treated with immune control point inhibitors, two stool collections will be performed per patient (one stool collection before setting up an immune control point inhibitor and one collection after one month of being inhibited Of immune control point) to assess the impact of the immune control point inhibitor on the microbiota (pilot study). For this study, two stool collection tubes containing different preservative solutions will be used (one RNAlater tube and one DMSO-EDTA tube for Dimethylsulfoxide-Ethylene diamine tetraacetic acid). In parallel, we will also collect samples of serum and plasma to evaluate, in a second step, protein markers in circulating blood.

DISEASE(S): Oncology,Neoplasms

PROVIDER: 2247716 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

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Project description:This ordinary differential equation model simulating the mechanisms that govern cancer-immune dynamics and their role in tumor responses to immunotherapy is described by the publication: Creemers JHA, Lesterhuis WJ, Mehra N, et al. "A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery." Journal for ImmunoTherapy of Cancer 2021;9:e002032. doi:10.1136/jitc-2020-002032 Comment: Simulation parameters in supplementary table 1 mismatch with figure 1 in manuscript. Therefore, to clarify, the following parameter values were used: Reproduction of Fig. 1(C), xi = 0.0005 Reproduction of Fig. 1(D), xi = 0.00025 Abstract: Background: Predicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice. Methods: A computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs. Results: Our model shows that a tipping point—a sharp state transition between immune control and immune evasion—induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments. Conclusion: These findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patient’s distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for patients with cancer.

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Characteristics of the Intestinal Microbiota in Patients With Cancer

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