In situ tumour arrays reveal early environmental control of cancer immunity.

The immune phenotype of a tumour is a key predictor of its response to immunotherapy1-4. Patients who respond to checkpoint blockade generally present with immune-inflamed5-7 tumours that are highly infiltrated by T cells. However, not all inflamed tumours respond to therapy, and even lower response rates occur among tumours that lack T cells (immune desert) or that spatially exclude T cells to the periphery of the tumour lesion (immune excluded)8. Despite the importance of these tumour immune phenotypes in patients, little is known about their development, heterogeneity or dynamics owing to the technical difficulty of tracking these features in situ. Here we introduce skin tumour array by microporation (STAMP)-a preclinical approach that combines high-throughput time-lapse imaging with next-generation sequencing of tumour arrays. Using STAMP, we followed the development of thousands of arrayed tumours in vivo to show that tumour immune phenotypes and outcomes vary between adjacent tumours and are controlled by local factors within the tumour microenvironment. Particularly, the recruitment of T cells by fibroblasts and monocytes into the tumour core was supportive of T cell cytotoxic activity and tumour rejection. Tumour immune phenotypes were dynamic over time and an early conversion to an immune-inflamed phenotype was predictive of spontaneous or therapy-induced tumour rejection. Thus, STAMP captures the dynamic relationships of the spatial, cellular and molecular components of tumour rejection and has the potential to translate therapeutic concepts into successful clinical strategies.

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.

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.

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.

Semi-automated biobank sample processing with a 384 high density sample tube robot used in cancer and cardiovascular studies.

BACKGROUND: In the postgenomic era, it has become evident that analysis of genetic and protein expression changes alone is not sufficient to understand most disease processes in e.g. cardiovascular and cancer disease. Biobanking has been identified as an important area for development and discovery of better diagnostic tools and new treatment modalities. Biobanks are developed in order to integrate the collection of clinical samples from both healthy individuals and patients and provide valuable information that will make possible improved patient care. Modern healthcare developments are intimately linked to information based on studies of patient samples from biobank archives in large scale studies. Today biobanks form important national, as well as international, networks that share and combine global resources. METHODS: We have developed and validated a novel biobanking workflow process that utilizes 384-tube systems with a high speed sample array robot with unique processing principles. RESULTS: The 384-tube format and robotic processing is incorporated into a cancer and cardiovascular diagnostic/prognostic research program with therapeutic interventions. Our biobank practice has gained acceptance within many hospitals and research units and is based on high-density sample storage with small aliquot sample volumes. The previous standard of 5-10 mL sample volume tubes is being replaced by smaller volumes of 50-70 µL blood fractions that typically result in hundreds of thousands of aliquot fractions in 384-tube systems. CONCLUSIONS: Our novel biobanking workflow process is robust and well suited for clinical studies.

Liquid chromatography-tandem mass spectrometry approach for quantification of mucins from sputum using 13C,15N-labeled peptides as internal standards.

Mucins are of great interest owing to their involvement in physiological and pathological processes in the airways. A method that allows accurate quantification of such proteins in sputum samples may be helpful for research in this field. A liquid chromatographic selected reaction monitoring (SRM) method was developed for the quantification of two mucins, MUC5AC and MUC5B, in induced sputum samples. Sample preparation for the assay included solubilization, reduction, and alkylation prior to tryptic digestion. Solid phase extraction using C18 sorbent was used for sample cleanup prior to the liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. A cysteine-containing peptide was selected for quantification of MUC5AC protein, whereas a non-cysteine peptide was used for the quantification of MUC5B protein. Stable isotope-labeled synthetic peptides were used as internal standards, and linear calibration curves were constructed in the range of 0.3 to 40 pmol/L. Both mucins could be determined with a precision of 6 to 19% and an accuracy of 98 to 114%. The method is transferable to robotics and is suitable to be run in a 96-well format.

Chromosome 19 annotations with disease speciation: a first report from the Global Research Consortium.

A first research development progress report of the Chromosome 19 Consortium with members from Sweden, Norway, Spain, United States, China and India, a part of the Chromosome-centric Human Proteome Project (C-HPP) global initiative, is presented ( http://www.c-hpp.org ). From the chromosome 19 peptide-targeted library constituting 6159 peptides, a pilot study was conducted using a subset with 125 isotope-labeled peptides. We applied an annotation strategy with triple quadrupole, ESI-Qtrap, and MALDI mass spectrometry platforms, comparing the quality of data within and in between these instrumental set-ups. LC-MS conditions were outlined by multiplex assay developments, followed by MRM assay developments. SRM was applied to biobank samples, quantifying kallikrein 3 (prostate specific antigen) in plasma from prostate cancer patients. The antibody production has been initiated for more than 1200 genes from the entire chromosome 19, and the progress developments are presented. We developed a dedicated transcript microarray to serve as the mRNA identifier by screening cancer cell lines. NAPPA protein arrays were built to align with the transcript data with the Chromosome 19 NAPPA chip, dedicated to 90 proteins, as the first development delivery. We have introduced an IT-infrastructure utilizing a LIMS system that serves as the key interface for the research teams to share and explore data generated within the project. The cross-site data repository will form the basis for sample processing, including biological samples as well as patient samples from national Biobanks.

Standardization developments for large scale biobanks in smoking related diseases - a model system for blood sample processing and storage.

BACKGROUND: Biobank samples stored in biobanks give researchers and respiratory healthcare institutions access to datasets of analytes valuable for both diagnostic and research practices. The usefulness of these samples in clinical decision-making is highly dependent on their quality and integrity. New procedures that better preserve sample integrity and reduce degradation are being developed to meet the needs of both present and future biobanking. Hereby we present an automatic sample workflow scheme that is designed to handle high numbers of blood samples. METHODS: Blood fractions are aliquoted, heat sealed using novel technology, and stored in 384 tube high-density sample arrays. RESULTS: The newly developed 384 biobank rack system is especially suited for preserving identical small aliquots. We provide data on robotic processing of clinical samples at -80°C, following initial processing, analysis and shipping between laboratories throughout Europe. Subsequent to unpacking, re-sorting, and storage at these sites, the samples have been returned for analysis. Biomarker analysis of 13 common tests in the clinical chemistry unit of the hospital provides evidence of qualitative and stable logistics using the 384-sample tube system. CONCLUSIONS: This technology development allows rapid access to a given sample in the frozen archive while maintaining individual sample integrity with sample tube confinement and quality management.

Human bronchoalveolar lavage: biofluid analysis with special emphasis on sample preparation.

Respiratory diseases are an important health problem throughout the world. Whether caused by industrial pollutants, infections, smoking, cancer or metabolic diseases, damage to the lungs and airways often lead to morbidity or death. Bronchoalveolar lavage (BAL) obtained by fiber-optic bronchoscopy is a biofluid mirroring the expression of normally secreted pulmonary proteins and the products of activated cells and destructive processes. The characterization of the proteome within this compartment provides an opportunity to establish temporal and prognostic indicators of airway disease. The objective of this study was to develop methods of analysis of BAL samples, which achieved the highest level of annotation of the expression map of this proteome. We have optimized the process of sample preparation after investigating a variety of techniques including dialysis, ultramembrane filtration, precipitation and gel filtration. We have further studied methods to remove albumin from BAL in order to unmask proteins hidden on two-dimensional gels. In a pilot application of the method, BAL protein profiles obtained from healthy nonsmokers and smokers at risk for developing chronic obstructive pulmonary disease showed distinct differences.