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Proteomic profiling to predict therapeutic response to anti-PD1 therapy in advanced melanoma

ABSTRACT: Purpose Antibody-blockade of PD-1 shows durable responses, but so far, few biomarkers accurately predict if patients with metastatic melanoma will respond. Experimental design We analyzed baseline serum samples (n=56) and tumor cell cultures (n=8), from melanoma patients treated with anti-PD1 therapy. Two approaches concentrating low abundant proteins in serum and two different mass spectrometry (MS) methods were applied: depletion of high abundant proteins with shotgun-MS, and N-glycosite enrichment combined with SWATH-MS. Tumor cell cultures were processed as whole cell lysates with subsequent shotgun-MS. Results Focusing on the non-responder proteome, we identified pathways such as inflammatory processes, cell adhesion and migration, scavenger receptor activity, RAGE receptor binding, platelet aggregation, neutrophil degranulation and integrin signaling to be upregulated. Analyzing the tumor cell proteome revealed a distinctive immunophenotype with CD antigens highly overexpressed in non-responders. Validation of a subset of these markers, performed by immunofluorescence staining of a tissue microarray, revealed a higher mean of positive cells in the tumor microenvironment of non-responders. Validation of serum proteome markers on a second baseline cohort by using a timsTOF for ion mobility MS, revealed significant differences between responder and non-responder for the proteins ORM2, SERPINA1, EFEMP1, and VASN. TCGA survival analysis demonstrated prognostic significance for multiple proteins of our signature correlating with lower overall survival in melanoma patients. Based on this study, we suggest a protein-panel for responsiveness to PD-1 blockade consisting of 14 serum and 33 tumor cell markers that will be the basis for further research.

INSTRUMENT(S): timsTOF Pro

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Serum

DISEASE(S): Melanoma

SUBMITTER: Christopher Gerner

LAB HEAD: Christopher Gerner

PROVIDER: PXD027525 | Pride | 2023-08-18

REPOSITORIES: Pride

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Project description:Steroid-refractory acute rejection is a risk factor for inferior renal allograft outcome. We aimed to gain insight into the mechanisms underlying steroid resistance by identifying novel molecular markers of steroid-refractory acute rejection. Eighty-three kidney transplant recipients (1995-2005), who were treated with methylprednisolone during a first acute rejection episode, were included in this study. Gene expression patterns were investigated in a discovery cohort of 36 acute rejection biopsies, and verified in a validation cohort of 47 acute rejection biopsies. In the discovery set, expression of metallothioneins (MT) was significantly (P<0.000001) associated with decreased response to steroid treatment. Multivariate analysis resulted in a predictive model containing MT-1 as an independent covariate (AUC=0.88, P<0.0000001). In the validation set, MT-1 expression was also significantly associated with steroid resistance (P=0.029). Metallothionein expression was detected in macrophages and tubular epithelial cells. Parallel to the findings in patients, in vitro experiments of peripheral blood mononuclear cells from 11 donors showed that non-response to methylprednisolone treatment is related to highly elevated MT levels. High expression of metallothioneins in renal allografts is associated with resistance to steroid treatment. Metallothioneins regulate intracellular concentrations of zinc, through which they may diminish the zinc-requiring anti-inflammatory effect of the glucocorticoid receptor. Transcriptional profiles of 40 renal allograft biopsy samples were analyzed using Illumina HumanRef-8 v3.0 BeadChips (Illumina, San Diego, CA). Expression profiles were investigated in total RNA isolated from biopsy samples of 18 patients with steroid responsive acute rejection and 18 patients with steroid resistant acute rejection. Four biopsies, taken during acute decrease of graft function but with no histomorphologic indication of rejection, were included as controls.

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Project description:An evaluation of multifocal lesions from patients with in-transit extremity melanoma to determine if all lesions from a patient harbor homogeneous patterns of gene expression; Gene expression profiling studies can help guide treatment for cancer patients by providing tools in the form of gene-expression signatures to characterize a tumor in terms of underlying biology, predicted response to therapy, metastatic progression and/or recurrence. The utility of gene signatures for defining therapeutic strategies in the treatment of extremity in-transit melanoma will be dependent on the genetic relationship between the multifocal lesions typically present in this disease and the extent to which a single lesion is representative of residual tumor burden. Using microarray-based gene expression profiling we examined 43 in-transit melanoma lesions across 17 patients with multifocal disease to determine whether one lesion could accurately characterize the underlying biology and genetic profile of a patient's tumor. Principal component analysis, unsupervised hierarchical clustering, one-way analysis of variance (ANOVA) and gene signatures predictive of chemosensitivity and oncogenic pathway activation showed gene expression patterns to be highly similar (p-values: <0.006; average r = 0.979) between lesions from a single patient but to be significantly different across patients (p<0.05). These findings demonstrate that individual melanoma tumor nodules in patients with multifocal disease are genetically similar and a single lesion can be used to predict response to chemotherapy, evaluate the activation status of oncogenic signaling pathways and characterize other aspects of the biology of an individual patient's disease. These results will facilitate the utilization of gene expression profiling in clinical trials of targeted therapy in melanoma allowing for more rational identification of candidates for specific therapies. Experiment Overall Design: Gene expression profiles were obtained from 43 lesions across 17 patients and evaluated using several different algorithms to determine the degree of correlation across multifocal lesions and to evaluate patterns of gene expression that are different across patients

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Proteomic profiling to predict therapeutic response to anti-PD1 therapy in advanced melanoma

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