Novel functional proteins coded by the human genome discovered in metastases of melanoma patients.

In the advanced stages, malignant melanoma (MM) has a very poor prognosis. Due to tremendous efforts in cancer research over the last 10 years, and the introduction of novel therapies such as targeted therapies and immunomodulators, the rather dark horizon of the median survival has dramatically changed from under 1 year to several years. With the advent of proteomics, deep-mining studies can reach low-abundant expression levels. The complexity of the proteome, however, still surpasses the dynamic range capabilities of current analytical techniques. Consequently, many predicted protein products with potential biological functions have not yet been verified in experimental proteomic data. This category of 'missing proteins' (MP) is comprised of all proteins that have been predicted but are currently unverified. As part of the initiative launched in 2016 in the USA, the European Cancer Moonshot Center has performed numerous deep proteomics analyses on samples from MM patients. In this study, nine MPs were clearly identified by mass spectrometry in MM metastases. Some MPs significantly correlated with proteins that possess identical PFAM structural domains; and other MPs were significantly associated with cancer-related proteins. This is the first study to our knowledge, where unknown and novel proteins have been annotated in metastatic melanoma tumour tissue.

Clinical protein science in translational medicine targeting malignant melanoma.

Melanoma of the skin is the sixth most common type of cancer in Europe and accounts for 3.4% of all diagnosed cancers. More alarming is the degree of recurrence that occurs with approximately 20% of patients lethally relapsing following treatment. Malignant melanoma is a highly aggressive skin cancer and metastases rapidly extend to the regional lymph nodes (stage 3) and to distal organs (stage 4). Targeted oncotherapy is one of the standard treatment for progressive stage 4 melanoma, and BRAF inhibitors (e.g. vemurafenib, dabrafenib) combined with MEK inhibitor (e.g. trametinib) can effectively counter BRAFV600E-mutated melanomas. Compared to conventional chemotherapy, targeted BRAFV600E inhibition achieves a significantly higher response rate. After a period of cancer control, however, most responsive patients develop resistance to the therapy and lethal progression. The many underlying factors potentially causing resistance to BRAF inhibitors have been extensively studied. Nevertheless, the remaining unsolved clinical questions necessitate alternative research approaches to address the molecular mechanisms underlying metastatic and treatment-resistant melanoma. In broader terms, proteomics can address clinical questions far beyond the reach of genomics, by measuring, i.e. the relative abundance of protein products, post-translational modifications (PTMs), protein localisation, turnover, protein interactions and protein function. More specifically, proteomic analysis of body fluids and tissues in a given medical and clinical setting can aid in the identification of cancer biomarkers and novel therapeutic targets. Achieving this goal requires the development of a robust and reproducible clinical proteomic platform that encompasses automated biobanking of patient samples, tissue sectioning and histological examination, efficient protein extraction, enzymatic digestion, mass spectrometry-based quantitative protein analysis by label-free or labelling technologies and/or enrichment of peptides with specific PTMs. By combining data from, e.g. phosphoproteomics and acetylomics, the protein expression profiles of different melanoma stages can provide a solid framework for understanding the biology and progression of the disease. When complemented by proteogenomics, customised protein sequence databases generated from patient-specific genomic and transcriptomic data aid in interpreting clinical proteomic biomarker data to provide a deeper and more comprehensive molecular characterisation of cellular functions underlying disease progression. In parallel to a streamlined, patient-centric, clinical proteomic pipeline, mass spectrometry-based imaging can aid in interrogating the spatial distribution of drugs and drug metabolites within tissues at single-cell resolution. These developments are an important advancement in studying drug action and efficacy in vivo and will aid in the development of more effective and safer strategies for the treatment of melanoma. A collaborative effort of gargantuan proportions between academia and healthcare professionals has led to the initiation, establishment and development of a cutting-edge cancer research centre with a specialisation in melanoma and lung cancer. The primary research focus of the European Cancer Moonshot Lund Center is to understand the impact that drugs have on cancer at an individualised and personalised level. Simultaneously, the centre increases awareness of the relentless battle against cancer and attracts global interest in the exceptional research performed at the centre.

Inhibition of integrin αVß6 changes fibril thickness of stromal collagen in experimental carcinomas.

BACKGROUND: Chemotherapeutic efficacy can be improved by targeting the structure and function of the extracellular matrix (ECM) in the carcinomal stroma. This can be accomplished by e.g. inhibiting TGF-ß1 and -ß3 or treating with Imatinib, which results in scarcer collagen fibril structure in xenografted human KAT-4/HT29 (KAT-4) colon adenocarcinoma. METHODS: The potential role of αVß6 integrin-mediated activation of latent TGF-ß was studied in cultured KAT-4 and Capan-2 human ductal pancreatic carcinoma cells as well as in xenograft carcinoma generated by these cells. The monoclonal αVß6 integrin-specific monoclonal antibody 3G9 was used to inhibit the αVß6 integrin activity. RESULTS: Both KAT-4 and Capan-2 cells expressed the αVß6 integrin but only KAT-4 cells could utilize this integrin to activate latent TGF-ß in vitro. Only when Capan-2 cells were co-cultured with human F99 fibroblasts was the integrin activation mechanism triggered, suggesting a more complex, fibroblast-dependent, activation pathway. In nude mice, a 10-day treatment with 3G9 reduced collagen fibril thickness and interstitial fluid pressure in KAT-4 but not in the more desmoplastic Capan-2 tumors that, to achieve a similar effect, required a prolonged 3G9 treatment. In contrast, a 10-day direct inhibition of TGF-ß1 and -ß3 reduced collagen fibril thickness in both tumor models. CONCLUSION: Our data demonstrate that the αVß6-directed activation of latent TGF-ß plays a pivotal role in modulating the stromal collagen network in carcinoma, but that the sensitivity to αVß6 inhibition depends on the simultaneous presence of alternative paths for latent TGF-ß activation and the extent of desmoplasia.

Whole chromosome gain does not in itself confer cancer-like chromosomal instability.

Constitutional aneuploidy is typically caused by a single-event meiotic or early mitotic error. In contrast, somatic aneuploidy, found mainly in neoplastic tissue, is attributed to continuous chromosomal instability. More debated as a cause of aneuploidy is aneuploidy itself; that is, whether aneuploidy per se causes chromosomal instability, for example, in patients with inborn aneuploidy. We have addressed this issue by quantifying the level of somatic mosaicism, a proxy marker of chromosomal instability, in patients with constitutional aneuploidy by precise background-filtered dual-color FISH. In contrast to previous studies that used less precise methods, we find that constitutional trisomy, even for large chromosomes that are often trisomic in cancer, does not confer a significantly elevated rate of somatic chromosomal mosaicism in individual cases. Constitutional triploidy was associated with an increased level of somatic mosaicism, but this consisted mostly of reversion from trisomy to disomy and did not correspond to a proportionally elevated level of chromosome mis-segregation in triploids, indicating that the observed mosaicism resulted from a specific accumulation of cells with a hypotriploid chromosome number. In no case did the rate of somatic mosaicism in constitutional aneuploidy exceed that of "chromosomally stable" cancer cells. Our findings show that even though constitutional aneuploidy was in some cases associated with low-level somatic mosaicism, it was insufficient to generate the cancer-like levels expected if aneuploidy single-handedly triggered cancer-like chromosomal instability.

Cell proliferation, measured as flow cytometric S-phase fraction, is a strong prognostic indicator in FIGO stage I endometrioid endometrial carcinoma: a population-based study.

INTRODUCTION: In early-stage endometrial carcinoma, there is controversy regarding the prognostic value of the flow cytometric variables DNA ploidy (diploid vs. aneuploid) and S-phase fraction. In Sweden, the former is included in national guidelines despite poor scientific support and the latter is not used clinically. This study investigates the prognostic properties of these variables, together with classical histopathological variables, in multivariate analysis in a stringently stratified material. MATERIAL AND METHODS: Consecutive, population-based patient material restricted to International Federation of Gynecology and Obstetrics (FIGO) 2009 stage I endometrioid endometrial carcinoma (n = 1140) was retrospectively collected from routinely reported data from medical records. Data on age, FIGO stage, degree of differentiation, S-phase fraction, DNA ploidy status, and adjuvant treatment were included in the study. Cumulative incidence curves with other causes of death as a competing risk were used for univariable analysis for the primary endpoint endometrial cancer death. Cox proportional hazards regression analysis was used for multivariate modeling of all endpoints, and for univariable analysis for the secondary endpoints overall survival and time to progression. RESULTS: An S-phase fraction value of >5.5% was associated with worse outcome (for endometrial cancer death: hazard ratio 2.25; 95% CI 1.38-3.67; p = 0.001, adjusted) and DNA ploidy status was not, for all endpoints tested. CONCLUSIONS: In FIGO stage I endometrioid endometrial carcinoma, DNA ploidy status had no prognostic value, whereas the S-phase fraction may be used to identify those with a higher risk of adverse clinical outcome.

A new look at drugs targeting malignant melanoma--an application for mass spectrometry imaging.

Malignant melanoma (MM) patients are being treated with an increasing number of personalized medicine (PM) drugs, several of which are small molecule drugs developed to treat patients with specific disease genotypes and phenotypes. In particular, the clinical application of protein kinase inhibitors has been highly effective for certain subsets of MM patients. Vemurafenib, a protein kinase inhibitor targeting BRAF-mutated protein, has shown significant efficacy in slowing disease progression. In this paper, we provide an overview of this new generation of targeted drugs, and demonstrate the first data on localization of PM drugs within tumor compartments. In this study, we have introduced MALDI-MS imaging to provide new information on one of the drugs currently used in the PM treatment of MM, vemurafenib. In a proof-of-concept in vitro study, MALDI-MS imaging was used to identify vemurafenib applied to metastatic lymph nodes tumors of subjects attending the regional hospital network of Southern Sweden. The paper provides evidence of BRAF overexpression in tumors isolated from MM patients and localization of the specific drug targeting BRAF, vemurafenib, using MS fragment ion signatures. Our ability to determine drug uptake at the target sites of directed therapy provides important opportunity for increasing our understanding about the mode of action of drug activity within the disease environment.

Feasibility study on measuring selected proteins in malignant melanoma tissue by SRM quantification.

Currently there are no clinically recognized molecular biomarkers for malignant melanoma (MM) for either diagnosing disease stage or measuring response to therapy. The aim of this feasibility study was to develop targeted selected reaction monitoring (SRM) assays for identifying candidate protein biomarkers in metastatic melanoma tissue lysate. In a pilot study applying the SRM assay, the tissue expression of nine selected proteins [complement 3 (C3), T-cell surface glycoprotein CD3 epsilon chain E (CD3E), dermatopontin, minichromosome maintenance complex component (MCM4), premelanosome protein (PMEL), S100 calcium binding protein A8 (S100A8), S100 calcium binding protein A13 (S100A13), transgelin-2 and S100B] was quantified in a small cohort of metastatic malignant melanoma patients. The SRM assay was developed using a TSQ Vantage triple quadrupole mass spectrometer that generated highly accurate peptide quantification. Repeated injection of internal standards spiked into matrix showed relative standard deviation (RSD) from 6% to 15%. All nine target proteins were identified in tumor lysate digests spiked with heavy peptide standards. The multiplex SRM peptide assay panel was then measured and quantified on a set of frozen MM tissue samples obtained from the Malignant Melanoma Biobank collected in Lund, Sweden. All nine proteins could be accurately quantified using the new SRM assay format. This study provides preliminary data on the heterogeneity of biomarker expression within MM patients. The S100B protein, which is clinically used as the pathology identifier of MM, was identified in 9 out of 10 MM tissue lysates. The use of the targeted SRM assay provides potential advancements in the diagnosis of MM that can aid in future assessments of disease in melanoma patients.

Predicting immune checkpoint therapy response in three independent metastatic melanoma cohorts.

While Immune checkpoint inhibition (ICI) therapy shows significant efficacy in metastatic melanoma, only about 50% respond, lacking reliable predictive methods. We introduce a panel of six proteins aimed at predicting response to ICI therapy. Evaluating previously reported proteins in two untreated melanoma cohorts, we used a published predictive model (EaSIeR score) to identify potential proteins distinguishing responders and non-responders. Six proteins initially identified in the ICI cohort correlated with predicted response in the untreated cohort. Additionally, three proteins correlated with patient survival, both at the protein, and at the transcript levels, in an independent immunotherapy treated cohort. Our study identifies predictive biomarkers across three melanoma cohorts, suggesting their use in therapeutic decision-making.

Landscape of somatic allelic imbalances and copy number alterations in human lung carcinoma.

Lung cancer is the worldwide leading cause of death from cancer and has been shown to be a heterogeneous disease at the genomic level. To delineate the genomic landscape of copy number alterations, amplifications, loss-of-heterozygosity (LOH), tumor ploidy and copy-neutral allelic imbalance in lung cancer, microarray-based genomic profiles from 2,141 tumors and cell lines including adenocarcinomas (AC, n = 1,206), squamous cell carcinomas (SqCC, n = 467), large cell carcinomas (n = 37) and small cell lung carcinomas (SCLC, n = 88) were assembled from different repositories. Copy number alteration differences between lung cancer histologies were confirmed in 285 unrelated tumors analyzed by BAC array comparative genomic hybridization. Tumor ploidy patterns were validated by DNA flow cytometry analysis of 129 unrelated cases. Eighty-nine recurrent copy number alterations (55 gains, 34 losses) were identified harboring genes with gene expression putatively driven by gene dosage through integration with gene expression data for 496 cases. Thirteen and 26 of identified regions discriminated AC/SqCC and AC/SqCC/SCLC, respectively, while 48 regions harbored recurrent (n > 15) high-level amplifications comprising established and putative oncogenes, differing in frequency and coamplification patterns between histologies. Lung cancer histologies displayed differences in patterns/frequency of copy number alterations, genomic architecture, LOH, copy-neutral allelic imbalance and tumor ploidy, with AC generally displaying less copy number alterations and allelic imbalance. Moreover, a strong association was demonstrated between different types of copy number alterations and allelic imbalances with tumor aneuploidy. In summary, these analyses provide a comprehensive overview of the landscape of genomic alterations in lung cancer, highlighting differences but also similarities between subgroups of the disease.

A new murine IgG1 anti-Tn monoclonal antibody with in vivo anti-tumor activity.

The Tn antigen (GalNAc α-O-Ser/Thr) is heterogeneously synthesized by a variety of tumors and contains an epitope defined by lectins and antibodies as a cluster of αGalNAc carbohydrates synthesized within a peptide sequence, which is rich in serine and/or threonine. The Tn antigen has been utilized as a target in vaccine experiments and also used as a biomarker for prognosis of different cancer forms. In this paper, we present a new monoclonal antibody, GOD3-2C4, with the clear hallmarks of an anti-Tn antibody. It was generated through somatic cell hybridization after immunization of a mouse with a tumor cell line and a Tn carrying mucin. The antibody recognizes synthetic Tn antigen and binds breast, colon, lung, ovarian and pancreas cancer. The GOD3-2C4 antibody has antibody-dependent cellular cytotoxicity activity against Jurkat cells in vitro, and for the first time, it can be shown that an anti-Tn antibody has a significant in vivo effect on a human cancer cell line grown as a xenograft in severe combined immunodeficiency mice.

Landscape of somatic allelic imbalances and copy number alterations in HER2-amplified breast cancer.

INTRODUCTION: Human epidermal growth factor receptor 2 (HER2)-amplified breast cancer represents a clinically well-defined subgroup due to availability of targeted treatment. However, HER2-amplified tumors have been shown to be heterogeneous at the genomic level by genome-wide microarray analyses, pointing towards a need of further investigations for identification of recurrent copy number alterations and delineation of patterns of allelic imbalance. METHODS: High-density whole genome array-based comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) array data from 260 HER2-amplified breast tumors or cell lines, and 346 HER2-negative breast cancers with molecular subtype information were assembled from different repositories. Copy number alteration (CNA), loss-of-heterozygosity (LOH), copy number neutral allelic imbalance (CNN-AI), subclonal CNA and patterns of tumor DNA ploidy were analyzed using bioinformatical methods such as genomic identification of significant targets in cancer (GISTIC) and genome alteration print (GAP). The patterns of tumor ploidy were confirmed in 338 unrelated breast cancers analyzed by DNA flow cytometry with concurrent BAC aCGH and gene expression data. RESULTS: A core set of 36 genomic regions commonly affected by copy number gain or loss was identified by integrating results with a previous study, together comprising > 400 HER2-amplified tumors. While CNN-AI frequency appeared evenly distributed over chromosomes in HER2-amplified tumors, not targeting specific regions and often < 20% in frequency, the occurrence of LOH was strongly associated with regions of copy number loss. HER2-amplified and HER2-negative tumors stratified by molecular subtypes displayed different patterns of LOH and CNN-AI, with basal-like tumors showing highest frequencies followed by HER2-amplified and luminal B cases. Tumor aneuploidy was strongly associated with increasing levels of LOH, CNN-AI, CNAs and occurrence of subclonal copy number events, irrespective of subtype. Finally, SNP data from individual tumors indicated that genomic amplification in general appears as monoallelic, that is, it preferentially targets one parental chromosome in HER2-amplified tumors. CONCLUSIONS: We have delineated the genomic landscape of CNAs, amplifications, LOH, and CNN-AI in HER2-amplified breast cancer, but also demonstrated a strong association between different types of genomic aberrations and tumor aneuploidy irrespective of molecular subtype.

The GPER1 agonist G-1 attenuates endothelial cell proliferation by inhibiting DNA synthesis and accumulating cells in the S and G2 phases of the cell cycle.

G protein-coupled receptor 30 (GPR30) or G protein-coupled estrogen receptor 1 (GPER1) is expressed in the vasculature, but the importance of vascular GPER1 remains to be clarified. Here we investigate effects of the GPER1 agonist G-1 on endothelial cell proliferation using mouse microvascular endothelial bEnd.3 cells. The bEnd.3 cells express mRNA for GPER1. The bEnd.3 cells expressed both ERα and ERß immunoreactivities. Treatment with G-1 reduced DNA synthesis and cell number with IC(50) values of about 2 µM. GPER1 siRNA prevented G-1-induced attenuation of DNA synthesis. G-1 accumulated cells in S and G2 phases of the cell cycle, suggesting that G-1 blocks transition between G2 and M. G-1 had no effect on DNA synthesis in COS-7 cells only weakly expressing GPER1 mRNA. 17ß-Estradiol had no effect on DNA synthesis in physiological concentrations (nM). The ER blocker ICI182780 reduced DNA synthesis with similar potency as G-1. Treatment with the ERK/MAP kinase inhibitor PD98059 had no effect on G-1-induced attenuation of DNA synthesis. G-1- induced antiproliferation was observed not only in bEnd.3 cells but also in human umbilical vein endothelial cells and HMEC-1 endothelial cells. We conclude that the GPER1 agonist G-1 attenuates endothelial cell proliferation via inhibition of DNA synthesis and by accumulation of cells in S and G2.

Deep Proteomic Analysis on Biobanked Paraffine-Archived Melanoma with Prognostic/Predictive Biomarker Read-Out.

The discovery of novel protein biomarkers in melanoma is crucial. Our introduction of formalin-fixed paraffin-embedded (FFPE) tumor protocol provides new opportunities to understand the progression of melanoma and open the possibility to screen thousands of FFPE samples deposited in tumor biobanks and available at hospital pathology departments. In our retrospective biobank pilot study, 90 FFPE samples from 77 patients were processed. Protein quantitation was performed by high-resolution mass spectrometry and validated by histopathologic analysis. The global protein expression formed six sample clusters. Proteins such as TRAF6 and ARMC10 were upregulated in clusters with enrichment for shorter survival, and proteins such as AIFI1 were upregulated in clusters with enrichment for longer survival. The cohort's heterogeneity was addressed by comparing primary and metastasis samples, as well comparing clinical stages. Within immunotherapy and targeted therapy subgroups, the upregulation of the VEGFA-VEGFR2 pathway, RNA splicing, increased activity of immune cells, extracellular matrix, and metabolic pathways were positively associated with patient outcome. To summarize, we were able to (i) link global protein expression profiles to survival, and they proved to be an independent prognostic indicator, as well as (ii) identify proteins that are potential predictors of a patient's response to immunotherapy and targeted therapy, suggesting new opportunities for precision medicine developments.

The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome.

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

The human melanoma proteome atlas-Defining the molecular pathology.

The MM500 study is an initiative to map the protein levels in malignant melanoma tumor samples, focused on in-depth histopathology coupled to proteome characterization. The protein levels and localization were determined for a broad spectrum of diverse, surgically isolated melanoma tumors originating from multiple body locations. More than 15,500 proteoforms were identified by mass spectrometry, from which chromosomal and subcellular localization was annotated within both primary and metastatic melanoma. The data generated by global proteomic experiments covered 72% of the proteins identified in the recently reported high stringency blueprint of the human proteome. This study contributes to the NIH Cancer Moonshot initiative combining detailed histopathological presentation with the molecular characterization for 505 melanoma tumor samples, localized in 26 organs from 232 patients.

Protein Expression in Metastatic Melanoma and the Link to Disease Presentation in a Range of Tumor Phenotypes.

Malignant melanoma is among the most aggressive skin cancers and it has among the highest metastatic potentials. Although surgery to remove the primary tumor is the gold standard treatment, once melanoma progresses and metastasizes to the lymph nodes and distal organs, i.e., metastatic melanoma (MM), the usual outcome is decreased survival. To improve survival rates and life span, advanced treatments have focused on the success of targeted therapies in the MAPK pathway that are based on BRAF (BRAF V600E) and MEK. The majority of patients with tumors that have higher expression of BRAF V600E show poorer prognosis than patients with a lower level of the mutated protein. Based on the molecular basis of melanoma, these findings are supported by distinct tumor phenotypes determined from differences in tumor heterogeneity and protein expression profiles. With these aspects in mind, continued challenges are to: (1) deconvolute the complexity and heterogeneity of MM; (2) identify the signaling pathways involved; and (3) determine protein expression to develop targeted therapies. Here, we provide an overview of the results from protein expression in MM and the link to disease presentation in a variety of tumor phenotypes and how these will overcome the challenges of clinical problems and suggest new promising approaches in metastatic melanoma and cancer therapy.

Improved survival prognostication of node-positive malignant melanoma patients utilizing shotgun proteomics guided by histopathological characterization and genomic data.

Metastatic melanoma is one of the most common deadly cancers, and robust biomarkers are still needed, e.g. to predict survival and treatment efficiency. Here, protein expression analysis of one hundred eleven melanoma lymph node metastases using high resolution mass spectrometry is coupled with in-depth histopathology analysis, clinical data and genomics profiles. This broad view of protein expression allowed to identify novel candidate protein markers that improved prediction of survival in melanoma patients. Some of the prognostic proteins have not been reported in the context of melanoma before, and few of them exhibit unexpected relationship to survival, which likely reflects the limitations of current knowledge on melanoma and shows the potential of proteomics in clinical cancer research.

The Hidden Story of Heterogeneous B-raf V600E Mutation Quantitative Protein Expression in Metastatic Melanoma-Association with Clinical Outcome and Tumor Phenotypes.

In comparison to other human cancer types, malignant melanoma exhibits the greatest amount of heterogeneity. After DNA-based detection of the BRAF V600E mutation in melanoma patients, targeted inhibitor treatment is the current recommendation. This approach, however, does not take the abundance of the therapeutic target, i.e., the B-raf V600E protein, into consideration. As shown by immunohistochemistry, the protein expression profiles of metastatic melanomas clearly reveal the existence of inter- and intra-tumor variability. Nevertheless, the technique is only semi-quantitative. To quantitate the mutant protein there is a fundamental need for more precise techniques that are aimed at defining the currently non-existent link between the levels of the target protein and subsequent drug efficacy. Using cutting-edge mass spectrometry combined with DNA and mRNA sequencing, the mutated B-raf protein within metastatic tumors was quantitated for the first time. B-raf V600E protein analysis revealed a subjacent layer of heterogeneity for mutation-positive metastatic melanomas. These were characterized into two distinct groups with different tumor morphologies, protein profiles and patient clinical outcomes. This study provides evidence that a higher level of expression in the mutated protein is associated with a more aggressive tumor progression. Our study design, comprised of surgical isolation of tumors, histopathological characterization, tissue biobanking, and protein analysis, may enable the eventual delineation of patient responders/non-responders and subsequent therapy for malignant melanoma.

Regression analysis and modelling of data acquisition for SELDI-TOF mass spectrometry.

MOTIVATION: Pre-processing of SELDI-TOF mass spectrometry data is currently performed on a largel y ad hoc basis. This makes comparison of results from independent analyses troublesome and does not provide a framework for distinguishing different sources of variation in data. RESULTS: In this article, we consider the task of pooling a large number of single-shot spectra, a task commonly performed automatically by the instrument software. By viewing the underlying statistical problem as one of heteroscedastic linear regression, we provide a framework for introducing robust methods and for dealing with missing data resulting from a limited span of recordable intensity values provided by the instrument. Our framework provides an interpretation of currently used methods as a maximum-likelihood estimator and allows theoretical derivation of its variance. We observe that this variance depends crucially on the total number of ionic species, which can vary considerably between different pooled spectra. This variation in variance can potentially invalidate the results from naive methods of discrimination/classification and we outline appropriate data transformations. Introducing methods from robust statistics did not improve the standard errors of the pooled samples. Imputing missing values however-using the EM algorithm-had a notable effect on the result; for our data, the pooled height of peaks which were frequently truncated increased by up to 30%.

Endogenous expression mapping of malignant melanoma by mass spectrometry imaging.

BACKGROUND: Currently, only a limited number of molecular biomarkers for malignant melanoma exist. This is the case for both diagnosing the disease, staging, and efficiently measuring the response to therapy by tracing the progression of disease development and drug impact. There is a great need to identify novel landmarks of disease progression and alterations. METHODS: Matrix-assisted laser desorption ionisation mass spectrometry imaging (MALDI-MSI) has been developed within our group to study drug localisation within micro-environmental tissue compartments. Here, we expand further on this technology development and introduce for the first time melanoma tumour tissues to map metabolite localisation utilising high resolution mass spectrometry. MALDI-MSI can measure and localise the distribution pattern of a number of small molecule metabolites within tissue compartments of tumours isolated from melanoma patients. Data on direct measurements of metabolite identities attained at the local sites in tissue compartments has not been readily available as a measure of a clinical index for most cancer diseases. The current development on the mapping of endogenous molecular expression melanoma tumours by mass spectrometry imaging focuses on the establishment of a cancer tissue preparation process whereby a matrix crystal formation is homogenously built on the tissue surface, providing uniform molecular mapping. We apply this micro-preparation technology to disease presentation by mapping the molecular signatures from patient tumour sections. RESULTS: We have automated the process with a micro-technological dispensing platform. This provides the basis for thin film generation of the cancer patient tissues prior to imaging screening. Compartmentalisation of the tumour regions are displayed within the image analysis interfaced with histopathological grading and characterisation. CONCLUSIONS: This enables site localisation within the tumour with image mapping to disease target areas such as melanoma cells, macrophages, and lymphocytes.