Proteomics approaches to understanding mitogen-activated protein kinase inhibitor resistance in melanoma

Memory effects of prior subculture may impact the quality of multiomic perturbation profiles

Mass spectrometry-based omics technologies are increasingly used in perturbation studies to map drug effects to biological pathways by identifying significant molecular events. Significance is influenced by fold change and variation of each molecular parameter, but also by multiple testing corrections. While the fold change is largely determined by the biological system, the variation is determined by experimental workflows. Here, it is shown that memory effects of prior subculture can influence the variation of perturbation profiles using the two colon carcinoma cell lines SW480 and HCT116. These memory effects are largely driven by differences in growth states that persist into the perturbation experiment. In SW480 cells, memory effects combined with moderate treatment effects amplify the variation in multiple omics levels, including eicosadomics, proteomics, and phosphoproteomics. With stronger treatment effects, the memory effect was less pronounced, as demonstrated in HCT116 cells. Subculture homogeneity was controlled by real-time monitoring of cell growth. Controlled homogeneous subculture resulted in a perturbation network of 321 causal conjectures based on combined proteomic and phosphoproteomic data, compared to only 58 causal conjectures without controlling subculture homogeneity in SW480 cells. Some cellular responses and regulatory events were identified that extend the mode of action of arsenic trioxide (ATO) only when accounting for these memory effects. Controlled prior subculture led to the finding of a synergistic combination treatment of ATO with the thioredoxin reductase 1 inhibitor auranofin, which may prove useful in the management of NRF2-mediated resistance mechanisms.

Proteomic Technology "Lens" for Epithelial-Mesenchymal Transition Process Identification in Oncology

The epithelial-mesenchymal transition (EMT) is a complex transformation process that induces local and distant progression of many malignant tumours. Due to its complex array of proteins that are dynamically over-/underexpressed during this process, proteomic technologies gained their place in the EMT research in the last years. Proteomics has identified new molecular pathways of this process and brought important insights to develop new therapy targets. Various proteomic tools and multiple combinations were developed in this area. Out of the proteomic technology armentarium, mass spectrometry and array technologies are the most used approaches. The main characteristics of the proteomic technology used in this domain are high throughput and detection of minute concentration in small samples. We present herein, using various proteomic technologies, the identification in cancer cell lines and in tumour tissue EMT-related proteins, proteins that are involved in the activation of different cellular pathways. Proteomics has brought besides standard EMT markers (e.g., cell-cell adhesion proteins and transcription factors) other future potential markers for improving diagnosis, monitoring evolution, and developing new therapy targets. Future will increase the proteomic role in clinical investigation and validation of EMT-related biomarkers.

Proteomic identification of a marker signature for MAPKi resistance in melanoma

MAPK inhibitors (MAPKi) show outstanding clinical response rates in melanoma patients harbouring BRAF mutations, but resistance is common. The ability of melanoma cells to switch from melanocytic to mesenchymal phenotypes appears to be associated with therapeutic resistance. High-throughput, subcellular proteome analyses and RNAseq on two panels of primary melanoma cells that were either sensitive or resistant to MAPKi revealed that only 15 proteins were sufficient to distinguish between these phenotypes. The two proteins with the highest discriminatory power were PTRF and IGFBP7, which were both highly upregulated in the mesenchymal-resistant cells. Proteomic analysis of CRISPR/Cas-derived PTRF knockouts revealed targets involved in lysosomal activation, endocytosis, pH regulation, EMT, TGFβ signalling and cell migration and adhesion, as well as a significantly reduced invasive index and ability to form spheres in 3D culture. Overexpression of PTRF led to MAPKi resistance, increased cell adhesion and sphere formation. In addition, immunohistochemistry of patient samples showed that PTRF expression levels were a significant biomarker of poor progression-free survival, and IGFBP7 levels in patient sera were shown to be higher after relapse.

Does the distribution pattern of brain metastases during BRAF inhibitor therapy reflect phenotype switching?

Brain metastases (brain mets) are frequent in metastatic melanoma patients. The aim of this study was to investigate the morphology and progression pattern of brain mets in melanoma patients treated with BRAF inhibitors (BRAFi) compared with patients who did not receive targeted therapy (BRAFi group and control group). The number and size of brain mets were compared between a baseline and a comparative MRI at progression. The number of brain mets was grouped into seven number classes (N=1-4, N=5-10, N=11-20, N=21-30, N=31-40, N=41-50, and N>50) and its difference was reported as the change of class that occurred. The mean size of the newly developed lesions was determined by representative measurements and the evolution of three persisting target lesions was assessed on the basis of modified RECIST criteria. Of 96 patients studied, 42 were in the BRAFi group and 54 were in the control group. Patients under BRAFi treatment had a significantly greater increase in the number of brain mets, where the median change of class for the BRAFi compared with the control group was 2 versus 0 (P<0.01). The mean size of the new lesions was smaller in the BRAFi group. Pre-existing target lesions did not show any prominent or different patterns of how they evolved in either group. Brain mets in patients treated with BRAFi showed a progression pattern characterized by a high propensity to disseminate, which might reflect an in-vivo manifestation of phenotype switching in response to targeted therapy, with a predominance of the invasive/migratory tumor cell phenotype. Drivers of invasiveness may present promising targets for therapeutic interventions.

Proteomics-based insights into mitogen-activated protein kinase inhibitor resistance of cerebral melanoma metastases

Background

MAP kinase inhibitor (MAPKi) therapy for BRAF mutated melanoma is characterized by high response rates but development of drug resistance within a median progression-free survival (PFS) of 9-12 months. Understanding mechanisms of resistance and identifying effective therapeutic alternatives is one of the most important scientific challenges in melanoma. Using proteomics, we want to specifically gain insight into the pathophysiological process of cerebral metastases.

Methods

Cerebral metastases from melanoma patients were initially analyzed by a LC-MS shotgun approach performed on a QExactive HF hybrid quadrupole-orbitrap mass spectrometer. For further validation steps after bioinformatics analysis, a targeted LC-QQQ-MS approach, as well as Western blot, immunohistochemistry and immunocytochemistry was performed.

Results

In this pilot study, we were able to identify 5977 proteins by LC-MS analysis (data are available via ProteomeXchange with identifier PXD007592). Based on PFS, samples were classified into good responders (PFS ≥ 6 months) and poor responders (PFS [Formula: see text] 3 months). By evaluating these proteomic profiles according to gene ontology (GO) terms, KEGG pathways and gene set enrichment analysis (GSEA), we could characterize differences between the two distinct groups. We detected an EMT feature (up-regulation of N-cadherin) as classifier between the two groups, V-type proton ATPases, cell adhesion proteins and several transporter and exchanger proteins to be significantly up-regulated in poor responding patients, whereas good responders showed an immune activation, among other features. We identified class-discriminating proteins based on nearest shrunken centroids, validated and quantified this signature by a targeted approach and could correlate parts of this signature with resistance using the CPL/MUW proteome database and survival of patients by TCGA analysis. We further validated an EMT-like signature as a major discriminator between good and poor responders on primary melanoma cells derived from cerebral metastases. Higher immune activity is demonstrated in patients with good response to MAPKi by immunohistochemical staining of biopsy samples of cerebral melanoma metastases.

Conclusions

Employing proteomic analysis, we confirmed known extra-cerebral resistance mechanisms in the cerebral metastases and further discovered possible brain specific mechanisms of drug efflux, which might serve as treatment targets or as predictive markers for these kinds of metastasis.

Critical aspects to achieve a high-quality melanoma clinic

PURPOSE OF REVIEW

With incidence of melanoma growing worldwide and new therapies prolonging the survival of patients with advanced disease, complex medical care is needed.

RECENT FINDINGS

Best care of complicated melanoma cases is achieved in specialized referral centers. Aims to provide optimized melanoma therapy, best patient-reported treatment outcome, and successful clinical and translational research, necessitate a dedicated interdisciplinary team.

SUMMARY

We report on critical aspects of the interaction between patients, medical care givers, clinical trial and biobanking teams, and emphasize the importance of interdisciplinary tumor boards. Specialized skin cancer nurses and local patient advocacy groups should be involved in patient care and could be the binding link between the patients and the treatment team.

Proteomic Findings in Melanoma

Although the emergence of proteomics as an independent branch of science is fairly recent, within a short period of time it has contributed substantially in various disciplines. The tool of mass spectrometry has become indispensable in the analysis of complex biological samples. Clinical applications of proteomics include detection of predictive and diagnostic markers, understanding mechanism of action of drugs as well as resistance mechanisms against them and assessment of therapeutic efficacy and toxicity of drugs in patients. Here, we have summarized the major contributions of proteomics towards the study of melanoma, which is a deadly variety of skin cancer with a high mortality rate.