Inflammation and Apolipoproteins Are Potential Biomarkers for Stratification of Cutaneous Melanoma Patients for Immunotherapy and Targeted Therapy.

Malignant cutaneous melanoma is one of the most common cancers in young adults. During the last decade, targeted and immunotherapies have significantly increased the overall survival of patients with malignant cutaneous melanoma. Nevertheless, disease progression is common, and a lack of predictive biomarkers of patient response to therapy hinders individualized treatment strategies. To address this issue, we performed a longitudinal study using an unbiased proteomics approach to identify and quantify proteins in plasma both before and during treatment from 109 patients treated with either targeted or immunotherapy. Linear modeling and machine learning approaches identified 43 potential prognostic and predictive biomarkers. A reverse correlation between apolipoproteins and proteins related to inflammation was observed. In the immunotherapy group, patients with low pretreatment expression of apolipoproteins and high expression of inflammation markers had shorter progression-free survival. Similarly, increased expression of LDHB during treatment elicited a significant impact on response to immunotherapy. Overall, we identified potential common and treatment-specific biomarkers in malignant cutaneous melanoma, paving the way for clinical use of these biomarkers following validation on a larger cohort. SIGNIFICANCE: This study identifies a potential biomarker panel that could improve the selection of therapy for patients with cutaneous melanoma.

Dramatic changes in blood protein levels during the first week of life in extremely preterm infants.

BACKGROUND: Preterm birth and its complications are the primary cause of death among children under the age of 5. Among the survivors, morbidity both perinatally and later in life is common. The dawn of novel technical platforms for comprehensive and sensitive analysis of protein profiles in blood has opened up new possibilities to study both health and disease with significant clinical accuracy, here used to study the preterm infant and the physiological changes of the transition from intrauterine to extrauterine life. METHODS: We have performed in-depth analysis of the protein profiles of 14 extremely preterm infants using longitudinal sampling. Medical variables were integrated with extensive profiling of 448 unique protein targets. RESULTS: The preterm infants have a distinct unified protein profile in blood directly at birth regardless of clinical background; however, the pattern changed profoundly postnatally, expressing more diverse profiles only 1 week later and further on up to term-equivalent age. Clusters of proteins depending on temporal trend were identified. CONCLUSION: The protein profiles and the temporal trends here described will contribute to the understanding of the physiological changes in the intrauterine-extrauterine transition, which is essential to adjust early-in-life interventions to prone a normal development in the vulnerable preterm infants. IMPACT: We have performed longitudinal and in-depth analysis of the protein profiles of 14 extremely preterm infants using a novel multiplex protein analysis platform. The preterm infants had a distinct unified protein profile in blood directly at birth regardless of clinical background. The pattern changed dramatically postnatally, expressing more diverse profiles only 1 week later and further on up to term-equivalent age. Certain clusters of proteins were identified depending on their temporal trend, including several liver and immune proteins. The study contributes to the understanding of the physiological changes in the intrauterine-extrauterine transition.

Integration of molecular profiles in a longitudinal wellness profiling cohort.

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.

Longitudinal Plasma Protein Profiling Using Targeted Proteomics and Recombinant Protein Standards.

Spike-in of standards of known concentrations used in proteomics-based workflows is an attractive approach for both accurate and precise multiplexed protein quantification. Here, a quantitative method based on targeted proteomics analysis of plasma proteins using isotope-labeled recombinant standards originating from the Human Protein Atlas project has been established. The standards were individually quantified prior to being employed in the final multiplex assay. The assays are mainly directed toward actively secreted proteins produced in the liver, but may also originate from other parts of the human body. This study included 21 proteins classified by the FDA as either drug targets or approved clinical protein biomarkers. We describe the use of this multiplex assay for profiling a well-defined human cohort with sample collection spanning over a one-year period. Samples were collected at four different time points, which allowed for a longitudinal analysis to assess the variable plasma proteome within individuals. Two assays toward APOA1 and APOB had available clinical data, and the two assays were benchmarked against each other. The clinical assay is based on antibodies and shows high correlation between the two orthogonal methods, suggesting that targeted proteomics with highly parallel, multiplex analysis is an attractive alternative to antibody-based protein assays.

Whole-genome sequence association analysis of blood proteins in a longitudinal wellness cohort.

BACKGROUND: The human plasma proteome is important for many biological processes and targets for diagnostics and therapy. It is therefore of great interest to understand the interplay of genetic and environmental factors to determine the specific protein levels in individuals and to gain a deeper insight of the importance of genetic architecture related to the individual variability of plasma levels of proteins during adult life. METHODS: We have combined whole-genome sequencing, multiplex plasma protein profiling, and extensive clinical phenotyping in a longitudinal 2-year wellness study of 101 healthy individuals with repeated sampling. Analyses of genetic and non-genetic associations related to the variability of blood levels of proteins in these individuals were performed. RESULTS: The analyses showed that each individual has a unique protein profile, and we report on the intra-individual as well as inter-individual variation for 794 plasma proteins. A genome-wide association study (GWAS) using 7.3 million genetic variants identified by whole-genome sequencing revealed 144 independent variants across 107 proteins that showed strong association (P < 6 × 10-11) between genetics and the inter-individual variability on protein levels. Many proteins not reported before were identified (67 out of 107) with individual plasma level affected by genetics. Our longitudinal analysis further demonstrates that these levels are stable during the 2-year study period. The variability of protein profiles as a consequence of environmental factors was also analyzed with focus on the effects of weight loss and infections. CONCLUSIONS: We show that the adult blood levels of many proteins are determined at birth by genetics, which is important for efforts aimed to understand the relationship between plasma proteome profiles and human biology and disease.

A genome-wide transcriptomic analysis of protein-coding genes in human blood cells.

Blood is the predominant source for molecular analyses in humans, both in clinical and research settings. It is the target for many therapeutic strategies, emphasizing the need for comprehensive molecular maps of the cells constituting human blood. In this study, we performed a genome-wide transcriptomic analysis of protein-coding genes in sorted blood immune cell populations to characterize the expression levels of each individual gene across the blood cell types. All data are presented in an interactive, open-access Blood Atlas as part of the Human Protein Atlas and are integrated with expression profiles across all major tissues to provide spatial classification of all protein-coding genes. This allows for a genome-wide exploration of the expression profiles across human immune cell populations and all major human tissues and organs.

The human secretome.

The proteins secreted by human cells (collectively referred to as the secretome) are important not only for the basic understanding of human biology but also for the identification of potential targets for future diagnostics and therapies. Here, we present a comprehensive analysis of proteins predicted to be secreted in human cells, which provides information about their final localization in the human body, including the proteins actively secreted to peripheral blood. The analysis suggests that a large number of the proteins of the secretome are not secreted out of the cell, but instead are retained intracellularly, whereas another large group of proteins were identified that are predicted to be retained locally at the tissue of expression and not secreted into the blood. Proteins detected in the human blood by mass spectrometry-based proteomics and antibody-based immunoassays are also presented with estimates of their concentrations in the blood. The results are presented in an updated version 19 of the Human Protein Atlas in which each gene encoding a secretome protein is annotated to provide an open-access knowledge resource of the human secretome, including body-wide expression data, spatial localization data down to the single-cell and subcellular levels, and data about the presence of proteins that are detectable in the blood.