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.

Identifying Ferroptosis Inducers, HDAC, and RTK Inhibitor Sensitivity in Melanoma Subtypes through Unbiased Drug Target Prediction.

The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies still poses a significant problem. Here we mine large scale MM proteogenomic data integrating it with MM cell line dependency screen, and drug sensitivity data to identify druggable targets and forecast treatment efficacy and resistance. Leveraging protein profiles from established MM subtypes and molecular structures of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC and AKT1, across five distinct MM subtypes. These proteins serve as potential drug targets applicable to one or multiple MM subtypes. By analyzing transcriptomic data from 48 publicly accessible melanoma cell lines sourced from Achilles and CRISPR dependency screens, we forecasted 162 potentially targetable genes. We also identified genetic resistance in 260 genes across at least one melanoma subtype. In addition, we employed publicly available compound sensitivity data (Cancer Therapeutics Response Portal, CTRPv2) on the cell lines to assess the correlation of compound effectiveness within each subtype. We have identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype. Remarkably, employing this unbiased approach, we have uncovered compounds targeting ferroptosis, that demonstrate a striking 30x fold difference in sensitivity among different subtypes. This implies that the proteogenomic classification of melanoma has the potential to predict sensitivity to ferroptosis compounds. Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy. Highlights: (1) Proteogenomic subtype classification can define the landscape of genetic dependencies in melanoma (2) Nine proteins from molecular subtypes were identified as potential drug targets for specified MM patients (3) 20 compounds identified that show potential effectiveness in at least one melanoma subtype (4) Proteogenomics can predict specific ferroptosis inducers, HDAC, and RTK Inhibitor sensitivity in melanoma subtypes.

Novel protein markers of androgen activity in humans: proteomic study of plasma from young chemically castrated men.

BACKGROUND: Reliable biomarkers of androgen activity in humans are lacking. The aim of this study was, therefore, to identify new protein markers of biological androgen activity and test their predictive value in relation to low vs normal testosterone values and some androgen deficiency linked pathologies. METHODS: Blood samples from 30 healthy GnRH antagonist treated males were collected at three time points: (1) before GnRH antagonist administration; (2) 3 weeks later, just before testosterone undecanoate injection, and (3) after additional 2 weeks. Subsequently, they were analyzed by mass spectrometry to identify potential protein biomarkers of testosterone activity. Levels of proteins most significantly associated with testosterone fluctuations were further tested in a cohort of 75 hypo- and eugonadal males suffering from infertility. Associations between levels of those markers and cardiometabolic parameters, bone mineral density as well as androgen receptor (AR) CAG repeat lengths, were explored. RESULTS: Using receiver operating characteristic analysis, 4-hydroxyphenylpyruvate dioxygenase (4HPPD), insulin-like growth factor-binding protein 6 (IGFBP6), and fructose-bisphosphate aldolase (ALDOB), as well as a Multi Marker Algorithm, based on levels of 4HPPD and IGFBP6, were shown to be best predictors of low (<8 nmol/l) vs normal (>12 nmol/l) testosterone. They were also more strongly associated with metabolic syndrome and diabetes than testosterone levels. Levels of ALDOB and 4HPPD also showed association with AR CAG repeat lengths. CONCLUSIONS: We identified potential new protein biomarkers of testosterone action. Further investigations to elucidate their clinical potential are warranted. FUNDING: The work was supported by ReproUnion2.0 (grant no. 20201846), which is funded by the Interreg V EU program.

Although it is best known for its role in developing male sex organs and maintaining sexual function, the hormone testosterone is important for many parts of the human body. A deficiency can cause an increased risk of serious conditions such as diabetes, cancer and osteoporosis. Testosterone deficiency can develop due to disease or age-related changes, and men affected by this can be given supplements of this hormone to restore normal levels. The most common way to test for testosterone deficiency is by measuring the concentration of the hormone in the blood. However, this does not accurately reflect the activity of the hormone in the body. This may lead to men who need more testosterone not receiving enough, and to others being unnecessarily treated. Several factors may lead to discrepancy between testosterone concentration in blood and its physiological activity. One of the most common is obesity. Additionally, certain genetic factors, which cannot be controlled for yet, regulate sensitivity to this hormone: some people do well at low levels, while others need high concentrations to be healthy. Therefore, to improve the diagnosis of testosterone deficiency it is necessary to identify biological markers whose levels act as a proxy for testosterone activity. Giwercman, Sahlin et al. studied the levels of a large number of proteins in the blood of 30 young men before and after blocking testosterone production. The analysis found three proteins whose concentrations changed significantly after testosterone deprivation. Giwercman, Sahlin et al. then validated these markers for testosterone deficiency by checking the levels of the three proteins in a separate group of 75 men with fertility problems. The results also showed that the three protein markers were better at predicting diabetes and metabolic syndrome than testosterone levels alone. These newly discovered markers could be used to create a test for measuring testosterone activity. This could help to identify deficiencies and finetune the amount of supplementary hormone given to men as treatment. However, further research is needed to understand the clinical value of such a test in men, as well as women and children.

Mapping the Melanoma Plasma Proteome (MPP) Using Single-Shot Proteomics Interfaced with the WiMT Database.

Plasma analysis by mass spectrometry-based proteomics remains a challenge due to its large dynamic range of 10 orders in magnitude. We created a methodology for protein identification known as Wise MS Transfer (WiMT). Melanoma plasma samples from biobank archives were directly analyzed using simple sample preparation. WiMT is based on MS1 features between several MS runs together with custom protein databases for ID generation. This entails a multi-level dynamic protein database with different immunodepletion strategies by applying single-shot proteomics. The highest number of melanoma plasma proteins from undepleted and unfractionated plasma was reported, mapping >1200 proteins from >10,000 protein sequences with confirmed significance scoring. Of these, more than 660 proteins were annotated by WiMT from the resulting ~5800 protein sequences. We could verify 4000 proteins by MS1t analysis from HeLA extracts. The WiMT platform provided an output in which 12 previously well-known candidate markers were identified. We also identified low-abundant proteins with functions related to (i) cell signaling, (ii) immune system regulators, and (iii) proteins regulating folding, sorting, and degradation, as well as (iv) vesicular transport proteins. WiMT holds the potential for use in large-scale screening studies with simple sample preparation, and can lead to the discovery of novel proteins with key melanoma disease functions.

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.

Identification and Validation of VEGFR2 Kinase as a Target of Voacangine by a Systematic Combination of DARTS and MSI.

Although natural products are an important source of drugs and drug leads, identification and validation of their target proteins have proven difficult. Here, we report the development of a systematic strategy for target identification and validation employing drug affinity responsive target stability (DARTS) and mass spectrometry imaging (MSI) without modifying or labeling natural compounds. Through a validation step using curcumin, which targets aminopeptidase N (APN), we successfully standardized the systematic strategy. Using label-free voacangine, an antiangiogenic alkaloid molecule as the model natural compound, DARTS analysis revealed vascular endothelial growth factor receptor 2 (VEGFR2) as a target protein. Voacangine inhibits VEGFR2 kinase activity and its downstream signaling by binding to the kinase domain of VEGFR2, as was revealed by docking simulation. Through cell culture assays, voacangine was found to inhibit the growth of glioblastoma cells expressing high levels of VEGFR2. Specific localization of voacangine to tumor compartments in a glioblastoma xenograft mouse was revealed by MSI analysis. The overlap of histological images with the MSI signals for voacangine was intense in the tumor regions and showed colocalization of voacangine and VEGFR2 in the tumor tissues by immunofluorescence analysis of VEGFR2. The strategy employing DARTS and MSI to identify and validate the targets of a natural compound as demonstrated for voacangine in this study is expected to streamline the general approach of drug discovery and validation using other biomolecules including natural products.

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.

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.

Short-term effect of pharmacologically induced alterations in testosterone levels on common blood biomarkers in a controlled healthy human model.

Testosterone deficiency in males is associated with serious comorbidities such as cardiovascular disease, diabetes type two, and also an increased risk of premature death. The pathogenetic mechanism behind this association, however, has not yet been clarified and is potentially bidirectional. The aim of this clinical trial was to gain insight into the short-term effect of changes in testosterone on blood analytes in healthy young men. Thirty healthy young male volunteers were recruited and monitored in our designed human model. Blood sampling was performed prior to and 3 weeks after pharmacological castration with a gonadotropin-releasing hormone antagonist. Subsequently, testosterone replacement with 1000 mg testosterone undecanoate was given and additional blood samples were collected 2 weeks later. The alterations in the levels of 37 routine biomarkers were statistically analysed. Eight biomarkers changed significantly in a similar manner as testosterone between the time points (e.g. prostate specific antigen, creatinine and magnesium), whereas seven other markers changed in the inverse manner as testosterone, including sexual hormone-binding globulin, urea, aspartate aminotransferase and alanine aminotransferase. Most of our results were supported by data from other studies. The designed controlled human model yielded changes in known biomarkers suggesting that low testosterone has a negative effect on health in young healthy men.

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.

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.

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.

Biomarkers of early chronic obstructive pulmonary disease (COPD) in smokers and former smokers. Protocol of a longitudinal study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an irreversible disease, diagnosed predominantly in smokers. COPD is currently the third leading cause of death worldwide. Far more than 15 % of smokers get COPD: in fact, most develop some amount of pulmonary impairment. Smoking-related COPD is associated with both acute exacerbations and is closely correlated to comorbidities, such as cardiovascular disease and lung cancer. The objective of our study (KOL-Örestad) is to identify biomarkers in smokers and ex-smokers, with early signs of COPD, and compare these biomarkers with those of non-smokers and healthy smokers/ex-smokers. The participants in the study are recruited from Örestadskliniken, a primary health care clinic in Malmö, Sweden. METHODS: Two hundred smokers and ex-smokers diagnosed with COPD with airflow restriction according to GOLD stages 1-4 will be included and compared with 50 healthy never-smokers, and 50 healthy smokers/ex-smokers without airflow restriction (total n = 300). The age distribution is 35-80 years. The participants undergo a health examination including medical history, smoking history, lung function measurements, and respond to a "Quality of Life" questionnaire. Blood samples are drawn every 6 months during a period of 5 years. Additional blood sample collection is performed if participants are experiencing an exacerbation. The blood fractions will be analyzed by standard clinical chemistry assays and by proteomics utilizing mass spectrometry platforms. Optimal sample integrity is ensured by rapid handling with robotic biobank processing followed by storage at -80 °C. The study has been approved by the Regional Ethical Review Board in Lund ( http://epn.se/en ), (Approval number: DNR 2013/480), and registered at the NIH clinical trial registry ( http://clinicaltrials.gov ). RESULTS AND DISCUSSION: Currently, 220 subjects are enrolled in the study. CONCLUSIONS AND FUTURE DIRECTIONS: The study design will enable discovery of new biomarkers by using novel mass spectrometric techniques that define early changes of COPD. Such panels of novel biomarkers may be able to distinguish COPD from closely related diseases, co-morbidities, and contribute to an increased understanding of these diseases. Graphical abstract KOL-Örestad Study.

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.

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.