Yutaka Sugihara

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.

Limited tumor tissue drug penetration contributes to primary resistance against angiogenesis inhibitors

Resistance mechanisms against antiangiogenic drugs are unclear. Here, we correlated the antitumor and antivascular properties of five different antiangiogenic receptor tyrosine kinase inhibitors (RTKIs) (motesanib, pazopanib, sorafenib, sunitinib, vatalanib) with their intratumoral distribution data obtained by matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI). In the first mouse model, only sunitinib exhibited broad-spectrum antivascular and antitumor activities by simultaneously suppressing vascular endothelial growth factor receptor-2 (VEGFR2) and desmin expression, and by increasing intratumoral hypoxia and inhibiting both tumor growth and vascularisation significantly. Importantly, the highest and most homogeneous intratumoral drug concentrations have been found in sunitinib-treated animals. In another animal model, where - in contrast to the first model - vatalanib was detectable at homogeneously high intratumoral concentrations, the drug significantly reduced tumor growth and angiogenesis. In conclusion, the tumor tissue penetration and thus the antiangiogenic and antitumor potential of antiangiogenic RTKIs vary among the tumor models and our study demonstrates the potential of MALDI-MSI to predict the efficacy of unlabelled small molecule antiangiogenic drugs in malignant tissue. Our approach is thus a major technical and preclinical advance demonstrating that primary resistance to angiogenesis inhibitors involves limited tumor tissue drug penetration. We also conclude that MALDI-MSI may significantly contribute to the improvement of antivascular cancer therapies.

A protein deep sequencing evaluation of metastatic melanoma tissues.

Malignant melanoma has the highest increase of incidence of malignancies in the western world. In early stages, front line therapy is surgical excision of the primary tumor. Metastatic disease has very limited possibilities for cure. Recently, several protein kinase inhibitors and immune modifiers have shown promising clinical results but drug resistance in metastasized melanoma remains a major problem. The need for routine clinical biomarkers to follow disease progression and treatment efficacy is high. The aim of the present study was to build a protein sequence database in metastatic melanoma, searching for novel, relevant biomarkers. Ten lymph node metastases (South-Swedish Malignant Melanoma Biobank) were subjected to global protein expression analysis using two proteomics approaches (with/without orthogonal fractionation). Fractionation produced higher numbers of protein identifications (4284). Combining both methods, 5326 unique proteins were identified (2641 proteins overlapping). Deep mining proteomics may contribute to the discovery of novel biomarkers for metastatic melanoma, for example dividing the samples into two metastatic melanoma “genomic subtypes”, (“pigmentation” and “high immune”) revealed several proteins showing differential levels of expression. In conclusion, the present study provides an initial version of a metastatic melanoma protein sequence database producing a total of more than 5000 unique protein identifications. The raw data have been deposited to the ProteomeXchange with identifiers PXD001724 and PXD001725.

Drug compound characterization by mass spectrometry imaging in cancer tissue

Abstract MALDI mass spectrometry imaging (MSI) provides a technology platform that allows the accurate visualization of unlabeled small molecules within the two-dimensional spaces of tissue samples. MSI has proven to be a powerful tool-box concept in the development of new drugs. MSI allows unlabeled drug compounds and drug metabolites to be detected and identified and quantified according to their mass-to-charge ratios (m/z) at high resolution in complex tissue environments. Such drug characterization in situ, by both spatial and temporal behaviors within tissue compartments, provide new understandings of the dynamic processes impacting drug uptake and metabolism at the local sites targeted by therapy. Further, MSI in combination with histology and immunohistochemistry, provides the added value of defining the context of cell biology present at the sites of drug localization thus providing invaluable information relating to treatment efficacy. In this report we provide mass spectrometry imaging data within various cancers such as malignant melanoma in patients administered with vemurafenib, a protein kinase inhibitor that is targeting BRAF mutated proteins and that has shown significant efficacy in restraining disease progression. We also provide an overview of other examples of the new generation of targeted drugs, and demonstrate the data on personalized medicine drugs localization within tumor compartments within in vivo models. In these cancer models we provide detailed data on drug and target protein co-localization of YCG185 and sunitinib. These drugs are targeting VEGFR2 within the angiogenesis mechanism. Our ability to resolve drug uptake at targeted sites of directed therapy provides important opportunities for increasing our understanding about the mode of action of drug activity within the environment of disease.

Correlation of histopathologic characteristics to protein expression and function in malignant melanoma

Background Metastatic melanoma is still one of the most prevalent skin cancers, which upon progression has neither a prognostic marker nor a specific and lasting treatment. Proteomic analysis is a versatile approach with high throughput data and results that can be used for characterizing tissue samples. However, such analysis is hampered by the complexity of the disease, heterogeneity of patients, tumors, and samples themselves. With the long term aim of quest for better diagnostics biomarkers, as well as predictive and prognostic markers, we focused on relating high resolution proteomics data to careful histopathological evaluation of the tumor samples and patient survival information. Patients and methods Regional lymph node metastases obtained from ten patients with metastatic melanoma (stage III) were analyzed by histopathology and proteomics using mass spectrometry. Out of the ten patients, six had clinical follow-up data. The protein deep mining mass spectrometry data was related to the histopathology tumor tissue sections adjacent to the area used for deep-mining. Clinical follow-up data provided information on disease progression which could be linked to protein expression aiming to identify tissue-based specific protein markers for metastatic melanoma and prognostic factors for prediction of progression of stage III disease. Results In this feasibility study, several proteins were identified that positively correlated to tumor tissue content including IF6, ARF4, MUC18, UBC12, CSPG4, PCNA, PMEL and MAGD2. The study also identified MYC, HNF4A and TGFB1 as top upstream regulators correlating to tumor tissue content. Other proteins were inversely correlated to tumor tissue content, the most significant being; TENX, EHD2, ZA2G, AOC3, FETUA and THRB. A number of proteins were significantly related to clinical outcome, among these, HEXB, PKM and GPNMB stood out, as hallmarks of processes involved in progression from stage III to stage IV disease and poor survival. Conclusion In this feasibility study, promising results show the feasibility of relating proteomics to histopathology and clinical outcome, and insight thus can be gained into the molecular processes driving the disease. The combined analysis of histological features including the sample cellular composition with protein expression of each metastasis enabled the identification of novel, differentially expressed proteins. Further studies are necessary to determine whether these putative biomarkers can be utilized in diagnostics and prognostic prediction of metastatic melanoma.

Novel insights in drug metabolism by MS imaging

During the last decade, lateral and temporal localization of drug compounds and their metabolites have been demonstrated and dynamically developed using MS imaging. The pharmaceutical industry has recognized the potential of the technology that provides simultaneous distribution and quantitative data. In this review, we present the latest technological achievements and summarize applications of drug imaging focusing on studies about metabolites by MALDI-MS imaging. We also introduce potential areas with pharmaceutical applications that are currently under exploration, including pharmacological, toxicological characterizations and metabolic enzyme localization in comparison with drug and metabolite distribution.

Localization of sunitinib in in vivo animal and in vitro experimental models by MALDI mass spectrometry imaging

The spatial distribution of an anticancer drug and its intended target within a tumor plays a major role on determining how effective the drug can be at tackling the tumor. This study provides data regarding the lateral distribution of sunitinib, an oral antiangiogenic receptor tyrosine kinase inhibitor using an in vitro animal model as well as an in vitro experimental model that involved deposition of a solution of sunitinib onto tissue sections. All tumor sections were analyzed by matrix-assisted laser desorption/ionization mass spectrometry imaging and compared with subsequent histology staining. Six tumors at four different time points after commencement of in vivo sunitinib treatment were examined to observe the patterns of drug uptake. The levels of sunitinib present in in vivo treated tumor sections increased continuously until day 7, but a decrease was observed at day 10. Furthermore, the in vitro experimental model was adjustable to produce a drug level similar to that obtained in the in vivo model experiments. The distribution of sunitinib in tissue sections treated in vitro appeared to agree with the histological structure of tumors, suggesting that this approach may be useful for testing drug update.

Clinical initiatives linking Japanese and Swedish healthcare resources on cancer studies utilizing Biobank Repositories.

The Tokyo Medical University Hospital in Japan and the Lund University hospital in Sweden have recently initiated a research program with the objective to impact on patient treatment by clinical disease stage characterization (phenotyping), utilizing proteomics sequencing platforms. By sharing clinical experiences, patient treatment principles, and biobank strategies, our respective clinical teams in Japan and Sweden will aid in the development of predictive and drug related protein biomarkers.Data from joint lung cancer studies are presented where protein expression from Neuro- Endocrine lung cancer (LCNEC) phenotype patients can be separated from Small cell- (SCLC) and Large Cell lung cancer (LCC) patients by deep sequencing and spectral counting analysis. LCNEC, a subtype of large cell carcinoma (LCC), is characterized by neuroendocrine differentiation that small cell lung carcinoma (SCLC) shares. Pre-therapeutic histological distinction between LCNEC and SCLC has so far been problematic, leading to adverse clinical outcome. An establishment of protein targets characteristic of LCNEC is quite helpful for decision of optimal therapeutic strategy by diagnosing individual patients. Proteoform annotation and clinical biobanking is part of the HUPO initiative (http://www.hupo.org) within chromosome 10 and chromosome 19 consortia.

Biobank integration of large-scale clinical and histopathology melanoma studies within the European Cancer Moonshot Lund Center

We present the Cancer Moonshot clinical project located at the European center in Lund. Here, tissue and blood samples have been collected and stored in a large-scale biobank. Multiple clinical centers around the world are participating and tissue and blood samples are sent to the European Cancer Moonshot Lund Center that acts as the clinical hub. Our center has been developed to generate and build large-scale biostorage archives of patient melanoma samples, which is then combined with a histopathological capability to characterize the patient tumours. Such a large-scale clinical sample processing initiative has begun with the aim of creating high-end histopathology indexing with database computational power and including proteogenomic analysis. The biobank at Lund has become an important resource in clinical research worldwide. Following suite, several national health programs are being initiated with the aim of also building large-scale biobank storages with a wealth of high-quality patient samples. In our Cancer Moonshot R&D activities, samples in the biobanks and the data derived from these samples are being used to build an understanding of disease presentation and using this information to move towards ‘Big Data’ proteogenomic and mass spectrometry imaging studies. Additionally, we report here a sample processing workflow that has been adapted to a fully-automated biobank processing strategy for large-scale studies.

Endogenous expression mapping of malignant melanoma by mass spectrometry imaging

BackgroundCurrently, 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.MethodsMatrix-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.ResultsWe 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.ConclusionsThis enables site localisation within the tumour with image mapping to disease target areas such as melanoma cells, macrophages, and lymphocytes.