Project description:We performed a phase I clinical trial to assess the safety and feasibility of fecal microbiota transplantation (FMT) and re-induction of anti-PD-1 immunotherapy in patients with anti-PD-1-refractory metastatic melanoma. FMT donors were two metastatic melanoma patients who achieved a durable complete response. FMT recipient patients were metastatic melanoma patients who failed at least one anti-PD-1 line of treatment. Each recipient patient received FMT implants from only one of the two donors. FMT was conducted by both colonoscopy and oral ingestion of stool capsules, followed by anti-PD-1 re-treatment (Nivolumab, BMS). Recipient patients underwent pre- and post-treatment stool sampling, tissue biopsy of both gut and tumor, and total body imaging. Clinical responses were observed in three patients, including two partial responses and one complete response. Notably, treatment with FMT was associated with favorable changes in immune cell infiltrates and gene expression profiles in both the gut lamina propria and the tumor microenvironment.
Project description:Both genomic and transcriptomic signatures have been developed to predict responses of metastatic melanoma to immune checkpoint blockade (ICB) therapies; however, most of these signatures were derived from pre-treatment biopsy samples. Here, we developed pathway-based signatures that predict response of metastatic melanoma to anti-PD1-based therapies in four independent datasets with RNAseq and clinical response data available for both pre- and on-treatment metastatic melanomas. We first identified pathway signatures that were significantly enriched in tumor specimens from anti-PD1 responders (R) compared to non-responders (NR) at pre-treatment and on-treatment time points, respectively. We also identified pathway signatures that were differentially expressed in pre-treatment versus on-treatment samples derived from R. Finally, we interrogated the capacity of the two types of signatures in predicting response of metastatic melanoma to anti-PD1 therapies in comparison with existing gene expression signatures. And we also investigated the effect of biopsy sites at the same biopsy time point on predictive performance of response to anti-PD1 therapy. Overall, we demonstrate that pathway-based signatures derived from on-treatment tumor specimens are highly predictive of response to anti-PD1 blockade therapies in patients with metastatic melanoma.
Project description:<p>Immune checkpoint therapies, including monoclonal antibodies to programmed cell death-1 (PD-1) and cytotoxic % lymphocyte associated protein-4 (CTLA-4), yield durable clinical responses across many tumor types, including metastatic melanoma, non-small cell lung cancer (NSCLC), and renal cell carcinoma (RCC). However, predictors of response to these therapies in RCC are still unknown. Genomic characterization of large clinical cohorts of patients treated with anti-CTLA-4 and anti-PD-1 agents in melanoma and NSCLC have suggested that high mutational burden, high neoantigen burden, and high expression of certain genes in pre-treatment tumors may be associated with patient response to these therapies. In this study, we sought to investigate genomic predictors of response to anti-PD1 therapy in metastatic RCC in two independent clinical cohorts using whole exome and whole transcriptome sequencing.</p>
Project description:Although high clinical response rates are seen for immune checkpoint blockade (ICB) of metastatic melanoma, both intrinsic and acquired ICB resistance remain formidable challenges. Combination ICB shows improved clinical benefit, but is associated with severe adverse events and exceedingly high cost. Therefore, there is a dire need to stratify individual patients for their likelihood of responding to either anti-PD-1 or anti-CTLA-4 monotherapy, or the combination. Since it is conceivable that ICB responses are influenced by both tumor cell-intrinsic and stromal factors, we hypothesized that a predictive classifier ought to mirror both of these distinct features. We used a panel of melanoma patient-derived xenografts (PDX), in which human stromal cells upon transplantation are naturally replaced by their murine counterparts, to computationally subtract PDX RNA expression signals from those in patients’ melanomas. We thus derived both “Stromal immune” (SIM) and tumor cell-specific “Tumor-autonomous inflammation” (TAF) signatures. Here we report that the SIM signature predicts response to anti-CTLA-4 but not anti-PD-1 treatment, whereas the tumor TAF signature predicts response to anti-PD-1 but not anti-CTLA-4. Moreover, when used in conjunction, the signatures accurately predict response in two independent patient cohorts treated with the anti-CTLA-4 + anti-PD-1 combination. These signatures may be clinically exploited for personalized treatment advice based on the predicted benefit from either anti-CTLA-4 or anti-PD-1 monotherapy or their combination.
Project description:In this comprehensive study, the authors have developed concise models integrating clinical, genomic and transcriptomic features to predict intrinsic resistance to anti-PD1 Immune Checkpoint Blockade (ICB) treatment in individual tumors. It's important to note that their validation was performed in smaller, independent cohorts, constrained by data availability. The authors have developed two Logistic Regression based models for Ipilimumab treated and Ipilimumab naive patients with metastatic melanoma. The main predictive features for the Ipilimumab treated patients are MHC-II HLA, LDH at treatment initiation and the presence of lymph node metastases (LN met), chosen using forward selection methodology. The main predictive features for the Ipilimumab naive patients are tumor heterogeneity, tumor ploidy and tumor purity, chosen using forward selection methodology.
Please note that in these models, the output ‘1’ means progressive disease (PD) and ‘0’ means non-PD. The original GitHub repository can be accessed at https://github.com/vanallenlab/schadendorf-pd1
Project description:B cells potentially play a role in the immune response to melanoma, including during treatment with immune modulators. We profiled (transcriptome analysis) effects of anti-PD-L1 antibody therapy on gene expression in B16 melanoma tumors of B cells depleted and WT syngeneic mice. After 7 days of B16 tumors implantation, mice were treated or untreated with anti-PD-L1 antibody (every three days).
2022-05-15 | GSE202879 | GEO
Project description:Investigating anti-PD-1 antibody resistance in melanoma
Project description:Immunotherapy with checkpoint inhibitors is an efficient treatment for metastatic melanoma. Development of vitiligo upon immunotherapy represents a specific immune-related adverse event (irAE) diagnosed in 15% of patients and associated with a positive clinical response. Therefore, a detailed characterization of immune cells during vitiligo onset in melanoma patients would give insight into the immune mechanisms mediating both this irAE and the anti-tumor response. To better understand these aspects, we analyzed T cell subsets from peripheral blood of metastatic melanoma patients undergoing treatment with anti-programmed cell death protein (PD)-1 antibodies. Stratification of patients for developing or not developing vitiligo during therapy revealed an association between blood reduction of mucosal associated invariant T (MAIT), T helper (h) 17, natural killer (NK) CD56bright, and T regulatory (T-reg) cells and vitiligo onset. To deeply characterize the tumoral T cell response concomitant to vitiligo onset, we analyzed T cell content in skin biopsies collected from melanoma patients who developed vitiligo. Consistently with the observed blood reduction of Th17 cells in melanoma patients developing vitiligo during immunotherapy, we found an enrichment of Th17 cells in the vitiligo skin biopsy, suggesting a migration of Th17 cells from the blood into the autoimmune lesion. To further characterize T cells in vitiligo skin lesion of melanoma patients, we sequenced T cell receptor (TCR) of cells derived from biopsies of vitiligo and primary melanoma of the same patient. Interestingly, we found different TCR sequences between vitiligo and primary melanoma lesions, except for a few cases showing the same TCR sequences. In contrast, shared TCR sequences were identified between vitiligo and metastatic tissues of the same patient. These data indicate that T cell response against normal melanocytes, which is involved in vitiligo onset, is not mainly mediated by the reactivation of specific T cell clones infiltrating primary melanoma but may be elicited by T cell clones targeting metastatic tissues. Altogether, our data indicate that anti-PD-1 therapy induces a de novo immune response, composed of different T cell subtypes, whose role may be related to the development of vitiligo and the response against metastatic tumor.
Project description:Emerging evidence indicates BAFF to be an important cytokine influencing anti-tumoral immunity. We generated a BAFF-overexpressing B16.F10 (BAFF) melanoma cell model and found that a significant survival advantage was conferred to C57BL/6 mice inoculated with BAFF cells. BAFF tumors had decreased myeloid infiltrates with lower PD-L1 expression. Monocyte depletion and anti-PD-L1 antibody treatment confirmed the functional significance on the phenotype. RNA-Seq analysis confirmed that monocytes isolated from BAFF tumors where characterized by a decreased exhaustive phenotype and enriched for in genes activating adaptive immune responses and NF- signaling. We wondered about the clinical relevance of BAFF plasma levels in melanoma patients. Evaluation of late stage metastatic melanoma patients treated with inhibitors of the PD-1/PD-L1 axis demonstrated a stratification of patients with high and low BAFF plasma levels, the former of which experienced lower responses to anti-PD-1 immunotherapies. In summary, we have shown that BAFF, through effects on tumor infiltrating monocytes not only impacts primary tumor growth but as biomarker can contribute to predicting response to anti-PD1 immunotherapy in later stages of advanced disease.