Project description:This is a simple mathematical population model for pembrolizumab-treated advanced melanoma patients, used to predict the response of melanoma patients to immune checkpoint inhibitors.
Project description:This study investigates the expression profiles of LncRNA in renal cancer tissues from patients treated with immune checkpoint inhibitors.
Project description:Plasma proteomic profiles of small cell lung cancer patients treated with immune checkpoint inhibitors combined with anti-angiogenic therapy as second- or further-line treatment
Project description:Epithelial Ovarian Cancer (EOC) is the leading cause of gynecologic cancer death. Despite many patients achieving remission with first-line therapy, up to 80% of patients will recur and require additional treatment. Retrospective clinical analysis of OC patients indicates antibiotic use during chemotherapy treatment is associated with poor overall survival. We assessed whether antibiotic (ABX) therapy would impact growth of EOC and sensitivity to cisplatin in murine models. Immune competent or compromised mice were given control or ABX containing water (metronidazole, ampicillin, vancomycin, and neomycin) before being intraperitoneally injected with murine EOC cells. Stool was collected to confirm microbiome disruption and tumors were monitored, and cisplatin therapy was administered weekly until endpoint. EOC tumor-bearing mice demonstrate accelerated tumor growth and resistance to cisplatin therapy in ABX treated compared with nonABX treatment. Stool analysis indicated most gut microbial species were disrupted by ABX treatment except for ABX resistant bacteria. To test for role of the gut microbiome, cecal microbiome transplants (CMTs) of microbiota derived from ABX or nonABX treated mice were used to recolonize the microbiome of ABX treated mice. nonABX cecal microbiome was sufficient to ameliorate the chemoresistance and survival of ABX treated mice indicative of a gut derived tumor suppressor. Mechanistically, tumors from ABX treated compared to nonABX treated mice contained a high frequency of cancer stem cells that were augmented by cisplatin. These studies indicate an intact microbiome provides a gut derived tumor suppressor and maintains chemosensitivity that is disrupted by ABX treatment.
Project description:The microbiome has a significant impact on immune health and response to immune-stimulating treatments, including cancer immunotherapy. However, the molecular mechanisms by which commensal microbes influence cancer immunology remain poorly understood. Here, we report on the discovery of a class of microbiome-derived metabolites called hydroxyphenyl propanoates (HPP) that enhance tumour immune surveillance in mice and synergize with immune checkpoint blockade (ICB) therapy. HPP molecules act as broad spectrum potentiators of innate immune signalling pathways in tumour-associated myeloid cells by promoting cleavage of the pore-forming protein gasdermin D (GSDMD), a critical effector of canonical and non-canonical inflammasome signalling. Heightened secretion of proinflammatory cytokines from HPP-treated myeloid cells, including IL-1β, promotes NF-κB activity within tumour-infiltrating leukocytes. This leads to heightened anticancer CD8 T cell accumulation, tumour regression, and long-term cancer control by immune checkpoint therapy in mice. Human peripheral blood mononuclear cells (PBMCs) respond to HPP treatment in a similar way. GSDMD cleavage also associates with a favourable response to ICB therapy in advanced stage melanoma patients. Taken together, our study uncovers a mechanism of microbiome-mediated modulation of host antitumour immunity that is modifiable and can be harnessed to enhance the efficacy of cancer immunotherapy. The proteomics part involved searching for hydroxuphenyl pyruvate interactors by using thermal profiling. TMT 10 plex and a method utilizing real-time search was used for quantification.
Project description:<p>Immune checkpoint inhibitors yield clinical benefit in many cancer types, but molecular predictors of response have not yet been robustly characterized. In this study, we pursued whole exome sequencing (WES) of pre-treatment tumors from patients treated with immune checkpoint therapies - including monoclonal antibodies targeting programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). Using these data, we aim to apply computational pipelines for mutation-calling, neoantigen prediction, and other analyses to validate pre-existing hypotheses regarding response to immune checkpoint therapies and discover new relationships with greater power. Further, by pursuing genomic characterization of tumors from patients with a variety of cancer types, we hope to describe molecular features of intrinsically sensitive or resistant tumors that are both context-specific and shared across cancer types.</p>
Project description:There is a growing appreciation of the role of the microbiome in cancer, and evidence in pre-clinical models that the gut microbiome may modulate responses to immune checkpoint blockade though this has not been well-characterized in patients. We analyzed the oral (n=86)and gut (n=43) 16S microbiome in melanoma patients on PD-1 blockade. Significant differences were noted in the diversity and composition of the gut microbiome between responders and non-responders in patients with a fecal microbiome sample, with significantly higher alpha diversity and relative abundance of Ruminococcaceae bacteria) in R. Metagenomic studies (n=25) revealed functional differences in gut bacteria in R including enrichment of anabolic pathways. Immune profiling demonstrated enhanced systemic and anti-tumor immunity in patients with a favorable gut microbiome as well as in germ-free mice receiving fecal transplant from responding patients. Together, these data have important implications for treatment with immune checkpoint blockade in cancer.
Project description:In this study, the authors had developed a machine learning model to predict immune checkpoint blockade (ICB) response by integrating genomic, molecular, demographic and clinical data from a curated cohort (MSK-IMPACT) with 1479 patients treated with ICB across 16 different types of cancer. This model significantly outperformed the predictions based on Tumor Mutational Burden (TCB). This model uses two types of random forests, one uses 16 features and the other uses 11 features. These features are selected based on their permutation importance score. The model was deployed on docker to reproduce the results and the data was shared to promote FAIReR sharing of machine learning models.
Project description:The gut microbiome modulates immunotherapy treatment responses, and this may explain why immune checkpoint inhibitors (ICI), such as anti-PD-1, are only effective in some patients. Previous studies correlated lipopolysaccharide (LPS)-producing gut microbes with poorer prognosis; however, LPS from diverse bacterial species can range from immunostimulatory to inhibitory. By functionally analyzing fecal metagenomes from 112 melanoma patients, we found that a subset of LPS-producing bacteria encoding immunostimulatory hexa-acylated LPS was enriched in microbiomes of clinical responders. In an implanted tumor mouse model of anti-PD-1 treatment, microbiota-derived hexa-acylated LPS was required for effective anti-tumor immune responses, and LPS-binding antibiotics and a small molecule TLR4 antagonist abolished anti-PD-1 efficacy. Conversely, oral administration of hexa-acylated LPS to mice significantly augmented anti-PD-1-mediated anti-tumor immunity. Penta-acylated LPS did not improve anti-PD-1 efficacy in vivo and inhibited hexa-acylated LPS-induced immune activation in vitro. Microbiome hexa-acylated LPS therefore represents an accessible predictor and potential enhancer of immunotherapy responses.