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 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, TGFß 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.

Mode of action, indications and recommendations on extracorporeal photopheresis (ECP).

Extracorporeal photopheresis (ECP) has gained importance in the treatment of several diseases. Initially introduced as a new therapeutic modality for the treatment of patients with cutaneous T-cell lymphoma, the indications for the use of ECP have expanded to include hematology and transplantation immunology. Extracorporeal photopheresis has found its place in the treatment plan of cutaneous T-cell lymphoma, systemic sclerosis, graft-versus-host disease, organ transplantation such as heart and lung, sometimes as first-line therapy and very often in combination with various systemic immunosuppressive therapies. The procedure basically consists of three steps: leukapheresis, photoactivation and reinfusion. The following article presents possible theories about the mechanism of action, which is not yet fully understood, and discusses the five most common indications for ECP treatment with corresponding therapy recommendations.

[Eosinophilic annular erythema in a 20-month-old girl]. / Eosinophiles anuläres Erythem bei einem 20 Monate alten Mädchen.

We report on a 20-month-old girl with urticarial and partially annular skin lesions that were disseminated over the whole integument. The lesions persisted over 1 week and then gradually faded and reappeared on new body sites. The histological examination of a skin biopsy revealed an urticarial inflammation pattern with interstitial edema and a diffuse infiltration with many eosinophilic granulocytes without flame figures, neutrophils and lymphocytes. Laboratory investigations were inconspicuous and there was no eosinophilia. A diagnosis of eosinophilic annular erythema (EAE) of childhood was made which is a benign self-limiting skin disorder belonging to the group of eosinophilic dermatoses.

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.

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

PURPOSE OF REVIEW: BRAF inhibitors achieve outstanding clinical response rates in BRAF-mutated melanoma patients but therapeutic resistance is common. Although combinatorial targeted therapy has recently improved patient survival, resistance still occurs, which might be because of the plasticity and heterogeneity of melanoma. Proteomics complements the mostly genomics-based approaches used so far to gain additional insights into the pathophysiological mechanisms driving melanoma progression under treatment. RECENT FINDINGS: Few proteomics studies have investigated mitogen-activated protein kinase inhibitor (MAPKi) resistance. Three technologies have been described: shotgun analysis, pressure cycling technology-sequential window acquisition of all theoretical masses (which offers an optimized protein extraction by the pressure cycling technology), and selected reaction monitoring for selected candidate evaluation. Preliminary data demonstrate that BRAFi resistance might be associated with enhanced expression of the lysosomal compartment, cell adhesion, and epithelial-mesenchymal transformation. Melanoma cells change their phenotypes in response to targeted therapy with MAPKi from a proliferative to an invasive state gaining epithelial-mesenchymal transformation features, which are associated with drug resistance. SUMMARY: Performing proteomics may lead to an enhanced understanding of the underlying mechanisms of MAPKi resistance and might offer new insights for rational therapies. Selected reaction monitoring can be used to evaluate predictive or pharmacodynamic biomarkers for tracking therapeutic responses and identifying early features of resistance.

Sphaeropsidin A shows promising activity against drug-resistant cancer cells by targeting regulatory volume increase.

Despite the recent advances in the treatment of tumors with intrinsic chemotherapy resistance, such as melanoma and renal cancers, their prognosis remains poor and new chemical agents with promising activity against these cancers are urgently needed. Sphaeropsidin A, a fungal metabolite whose anticancer potential had previously received little attention, was isolated from Diplodia cupressi and found to display specific anticancer activity in vitro against melanoma and kidney cancer subpanels in the National Cancer Institute (NCI) 60-cell line screen. The NCI data revealed a mean LC50 of ca. 10 µM and a cellular sensitivity profile that did not match that of any other agent in the 765,000 compound database. Subsequent mechanistic studies in melanoma and other multidrug-resistant in vitro cancer models showed that sphaeropsidin A can overcome apoptosis as well as multidrug resistance by inducing a marked and rapid cellular shrinkage related to the loss of intracellular Cl(-) and the decreased HCO3 (-) concentration in the culture supernatant. These changes in ion homeostasis and the absence of effects on the plasma membrane potential were attributed to the sphaeropsidin A-induced impairment of regulatory volume increase (RVI). Preliminary results also indicate that depending on the type of cancer, the sphaeropsidin A effects on RVI could be related to Na-K-2Cl electroneutral cotransporter or Cl(-)/HCO3 (-) anion exchanger(s) targeting. This study underscores the modulation of ion-transporter activity as a promising therapeutic strategy to combat drug-resistant cancers and identifies the fungal metabolite, sphaeropsidin A, as a lead to develop anticancer agents targeting RVI in cancer cells.

Curing advanced melanoma by 2025.

PURPOSE OF REVIEW: To outline the most urgent challenges in the management of advanced melanoma. RECENT FINDINGS: Considerable progress in targeted and immunotherapy of advanced melanoma has opened a perspective for a cure if all molecular and medical information is integrated in a rational precision treatment algorithm. SUMMARY: Bioinformatics and system biology approaches will be needed to deal with omics databases. The support of patient advocacy groups may help to increase the acceptance of large scale, routine biobanking.

Proteome profiling of keratinocytes transforming to malignancy.

To shed light on the multistep process of squamous cell carcinoma development and the underlying pathologic mechanisms, we performed comparative proteome analysis of keratinocytes, keratinocytes stimulated with Il-1beta, and A431 epidermoid carcinoma cells. Fractionation of the cells into supernatant, nucleus, and cytoplasm was followed by protein separation, proteolytic digest, and nano-LC separation, and fragmentation using an ion trap mass spectrometer. Specific bioinformatics tools were used to generate a list of keratinocyte-specific proteins. Ninety percent of these proteins were found to be upregulated in keratinocytes versus the A431 cells. Classification of the identified proteins by biologic function and gene set enrichment analysis revealed that keratinocytes produced more proteins involved in cell differentiation, cell adhesion, cell junction, calcium ion, calmodulin binding, cytoskeleton organization, and cytokinesis, whereas A431 produced more proteins involved in cell cycle checkpoint, cell cycle process, RNA processing and transport, DNA damage and repair, RNA and DNA binding, and chromatin remodeling. The protein signatures of A431 and normal keratinocytes treated with IL-1beta showed marked similarity, confirming that inflammation is an important step in malignant transformation in nonmelanoma skin cancer. Thus, proteome profiling and bioinformatic processing may support the understanding of the underlying mechanisms, with the potential to facilitate development of early biomarkers and patient-tailored therapy.

Plasticity of fibroblasts demonstrated by tissue-specific and function-related proteome profiling.

BACKGROUND: Fibroblasts are mesenchymal stromal cells which occur in all tissue types. While their main function is related to ECM production and physical support, they are also important players in wound healing, and have further been recognized to be able to modulate inflammatory processes and support tumor growth. Fibroblasts can display distinct phenotypes, depending on their tissue origin, as well as on their functional state. RESULTS: In order to contribute to the proteomic characterization of fibroblasts, we have isolated primary human fibroblasts from human skin, lung and bone marrow and generated proteome profiles of these cells by LC-MS/MS. Comparative proteome profiling revealed characteristic differences therein, which seemed to be related to the cell's tissue origin. Furthermore, the cells were treated in vitro with the pro-inflammatory cytokine IL-1beta. While all fibroblasts induced the secretion of Interleukins IL-6 and IL-8 and the chemokine GRO-alpha, other inflammation-related proteins were up-regulated in an apparently tissue-dependent manner. Investigating fibroblasts from tumorous tissues of skin, lung and bone marrow with respect to such inflammation-related proteins revealed hardly any conformity but rather individual and tumor type-related variations. However, apparent up-regulation of IGF-II, PAI-1 and PLOD2 was observed in melanoma-, lung adenocarcinoma- and multiple myeloma-associated fibroblasts, as well as in hepatocellular carcinoma-associated fibroblasts. CONCLUSIONS: Inflammation-related proteome alterations of primary human fibroblasts were determined by the analysis of IL-1beta treated cells. Tumor-associated fibroblasts from different tissue types hardly showed signs of acute inflammation but displayed characteristic functional aberrations potentially related to chronic inflammation. The present data suggest that the state of the tumor microenvironment is relevant for tumor progression and targeted treatment of tumor-associated fibroblasts may support anti-cancer strategies.

Determination of cell type-specific proteome signatures of primary human leukocytes, endothelial cells, keratinocytes, hepatocytes, fibroblasts and melanocytes by comparative proteome profiling.

Cells gain their functional specialization by different protein synthesis. A lot of knowledge with respect to cell type-specific proteins has been collected during the last thirty years. This knowledge was built mainly by using antibodies. Nowadays, modern MS, which supports comprehensive proteome analyses of biological samples, may render possible the search for cell type-specific proteins as well. However, a therefore necessary systematic MS study comprising many different cell types has not been performed until now. Here we present a proteome analysis strategy supporting the automated and meaningful comparison of any biological samples. We have presently applied this strategy to six different primary human cell types, namely leukocytes, endothelial cells, keratinocytes, hepatocytes, fibroblasts, and melanocytes. Comparative analysis of the resulting proteome profiles allowed us to select proteins specifically identified in one of the six cell types and not in any of the five others. Based on these results, we designated cell type-specific proteome signatures consisting each of six such characteristic proteins. These signatures independently reproduced well-known marker proteins already established for FACS analyses in addition to novel candidate marker proteins. We applied these signatures for the interpretation of proteome profiles obtained from the analyses of hepatocellular carcinoma-associated tissue homogenates and normal liver tissue homogenates. The identification of members of the above described signatures gave us an indication of the presence of characteristic cells in the diseased tissues and thus supported the interpretation of the proteomics data of these complex biological samples.

Proteomic Profiling of Advanced Melanoma Patients to Predict Therapeutic Response to Anti-PD-1 Therapy.

PURPOSE: Despite high clinical need, there are no biomarkers that accurately predict the response of patients with metastatic melanoma to anti-PD-1 therapy. EXPERIMENTAL DESIGN: In this multicenter study, we applied protein depletion and enrichment methods prior to various proteomic techniques to analyze a serum discovery cohort (n = 56) and three independent serum validation cohorts (n = 80, n = 12, n = 17). Further validation analyses by literature and survival analysis followed. RESULTS: We identified several significantly regulated proteins as well as biological processes such as neutrophil degranulation, cell-substrate adhesion, and extracellular matrix organization. Analysis of the three independent serum validation cohorts confirmed the significant differences between responders (R) and nonresponders (NR) observed in the initial discovery cohort. In addition, literature-based validation highlighted 30 markers overlapping with previously published signatures. Survival analysis using the TCGA database showed that overexpression of 17 of the markers we identified correlated with lower overall survival in patients with melanoma. CONCLUSIONS: Ultimately, this multilayered serum analysis led to a potential marker signature with 10 key markers significantly altered in at least two independent serum cohorts: CRP, LYVE1, SAA2, C1RL, CFHR3, LBP, LDHB, S100A8, S100A9, and SAA1, which will serve as the basis for further investigation. In addition to patient serum, we analyzed primary melanoma tumor cells from NR and found a potential marker signature with four key markers: LAMC1, PXDN, SERPINE1, and VCAN.

Functional classification of cellular proteome profiles support the identification of drug resistance signatures in melanoma cells.

Drug resistance is a major obstacle in melanoma treatment. Recognition of specific resistance patterns, the understanding of the patho-physiology of drug resistance, and identification of remaining options for individual melanoma treatment would greatly improve therapeutic success. We performed mass spectrometry-based proteome profiling of A375 melanoma cells and HeLa cells characterized as sensitive to cisplatin in comparison to cisplatin resistant M24met and TMFI melanoma cells. Cells were fractionated into cytoplasm, nuclei and secretome and the proteome profiles classified according to Gene Ontology. The cisplatin resistant cells displayed increased expression of lysosomal as well as Ca²âº ion binding and cell adherence proteins. These findings were confirmed using Lysotracker Red staining and cell adhesion assays with a panel of extracellular matrix proteins. To discriminate specific survival proteins, we selected constitutively expressed proteins of resistant M24met cells which were found expressed upon challenging the sensitive A375 cells. Using the CPL/MUW proteome database, the selected lysosomal, cell adherence and survival proteins apparently specifying resistant cells were narrowed down to 47 proteins representing a potential resistance signature. These were tested against our proteomics database comprising more than 200 different cell types/cell states for its predictive power. We provide evidence that this signature enables the automated assignment of resistance features as readout from proteome profiles of any human cell type. Proteome profiling and bioinformatic processing may thus support the understanding of drug resistance mechanism, eventually guiding patient tailored therapy.

ROS Induction Targets Persister Cancer Cells with Low Metabolic Activity in NRAS-Mutated Melanoma.

Clinical management of melanomas with NRAS mutations is challenging. Targeting MAPK signaling is only beneficial to a small subset of patients due to resistance that arises through genetic, transcriptional, and metabolic adaptation. Identification of targetable vulnerabilities in NRAS-mutated melanoma could help improve patient treatment. Here, we used multiomics analyses to reveal that NRAS-mutated melanoma cells adopt a mesenchymal phenotype with a quiescent metabolic program to resist cellular stress induced by MEK inhibition. The metabolic alterations elevated baseline reactive oxygen species (ROS) levels, leading these cells to become highly sensitive to ROS induction. In vivo xenograft experiments and single-cell RNA sequencing demonstrated that intratumor heterogeneity necessitates the combination of a ROS inducer and a MEK inhibitor to inhibit both tumor growth and metastasis. Ex vivo pharmacoscopy of 62 human metastatic melanomas confirmed that MEK inhibitor-resistant tumors significantly benefited from the combination therapy. Finally, oxidative stress response and translational suppression corresponded with ROS-inducer sensitivity in 486 cancer cell lines, independent of cancer type. These findings link transcriptional plasticity to a metabolic phenotype that can be inhibited by ROS inducers in melanoma and other cancers. SIGNIFICANCE: Metabolic reprogramming in drug-resistant NRAS-mutated melanoma cells confers sensitivity to ROS induction, which suppresses tumor growth and metastasis in combination with MAPK pathway inhibitors.

Systematic Analysis of the Transcriptome Profiles and Co-Expression Networks of Tumour Endothelial Cells Identifies Several Tumour-Associated Modules and Potential Therapeutic Targets in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the sixth most common cancer and the third most common cause of cancer-related death, with tumour associated liver endothelial cells being thought to be major drivers in HCC progression. This study aims to compare the gene expression profiles of tumour endothelial cells from the liver with endothelial cells from non-tumour liver tissue, to identify perturbed biologic functions, co-expression modules, and potentially drugable hub genes that could give rise to novel therapeutic targets and strategies. Gene Set Variation Analysis (GSVA) showed that cell growth-related pathways were upregulated, whereas apoptosis induction, immune and inflammatory-related pathways were downregulated in tumour endothelial cells. Weighted Gene Co-expression Network Analysis (WGCNA) identified several modules strongly associated to tumour endothelial cells or angiogenic activated endothelial cells with high endoglin (ENG) expression. In tumour cells, upregulated modules were associated with cell growth, cell proliferation, and DNA-replication, whereas downregulated modules were involved in immune functions, particularly complement activation. In ENG+ cells, upregulated modules were associated with cell adhesion and endothelial functions. One downregulated module was associated with immune system-related functions. Querying the STRING database revealed known functional-interaction networks underlying the modules. Several possible hub genes were identified, of which some (for example FEN1, BIRC5, NEK2, CDKN3, and TTK) are potentially druggable as determined by querying the Drug Gene Interaction database. In summary, our study provides a detailed picture of the transcriptomic differences between tumour and non-tumour endothelium in the liver on a co-expression network level, indicates several potential therapeutic targets and presents an analysis workflow that can be easily adapted to other projects.