Challenging the heterogeneity of disease presentation in malignant melanoma-impact on patient treatment

There is an increasing global interest to support research areas that can assist in understanding disease and improving patient care. The National Cancer Institute (NIH) has identified precision medicine-based approaches as key research strategies to expedite advances in cancer research. The Cancer Moonshot program ( https://www.cancer.gov/research/key-initiatives/moonshot-cancer-initiative ) is the largest cancer program of all time, and has been launched to accelerate cancer research that aims to increase the availability of therapies to more patients and, ultimately, to eradicate cancer. Mass spectrometry-based proteomics has been extensively used to study the molecular mechanisms of cancer, to define molecular subtypes of tumors, to map cancer-associated protein interaction networks and post-translational modifications, and to aid in the development of new therapeutics and new diagnostic and prognostic tests. To establish the basis for our melanoma studies, we have established the Southern Sweden Malignant Melanoma Biobank. Tissues collected over many years have been accurately characterized with respect to the tumor and patient information. The extreme variability displayed in the protein profiles and the detection of missense mutations has confirmed the complexity and heterogeneity of the disease. It is envisaged that the combined analysis of clinical, histological, and proteomic data will provide patients with a more personalized medical treatment. With respect to disease presentation, targeted treatment and medical mass spectrometry analysis and imaging, this overview report will outline and summarize the current achievements and status within malignant melanoma. We present data generated by our cancer research center in Lund, Sweden, where we have built extensive capabilities in biobanking, proteogenomics, and patient treatments over an extensive time period.

Isoelectric point optimization using peptide descriptors and support vector machines

IPG (Immobilized pH Gradient) based separations are frequently used as the first step in shotgun proteomics methods; it yields an increase in both the dynamic range and resolution of peptide separation prior to the LC-MS analysis. Experimental isoelectric point (pI) values can improve peptide identifications in conjunction with MS/MS information. Thus, accurate estimation of the pI value based on the amino acid sequence becomes critical to perform these kinds of experiments. Nowadays, pI is commonly predicted using the charge-state model [1], and/or the cofactor algorithm [2]. However, none of these methods is capable of calculating the pI value for basic peptides accurately. In this manuscript, we present an new approach that can significant improve the pI estimation, by using Support Vector Machines (SVM) [3], an experimental amino acid descriptor taken from the AAIndex database [4] and the isoelectric point predicted by the charge-state model. Our results have shown a strong correlation (R(2)=0.98) between the predicted and observed values, with a standard deviation of 0.32 pH units across the complete pH range.

Dextranase (alpha-1,6 glucan-6-glucanohydrolase) from Penicillium minioluteum expressed in Pichia pastoris: two host cells with minor differences in N-glycosylation

Differences in glycosylation between the natural alpha-1,6 glucan-6-glucanohydrolase from Penicillium minioluteum and the heterologous protein expressed in the yeast Pichia pastoris were analyzed. Glycosylation profiling was carried out using fluorophore-assisted carbohydrate electrophoresis and amine absorption high-performance liquid chromatography (NH(2)-HPLC) in combination with matrix-assisted laser desorption-time of flight-mass spectrometry. Both microorganisms produce only oligomannosidic type structures, but the oligosaccharide population differs in both enzymes. The native enzyme has mainly short oligosaccharide chains ranging from Man(5)GlcNAc(2) to Man(9)GlcNAc(2), of which Man(8)GlcNAc(2) was the most represented oligosaccharide. The oligosaccharides linked to the protein produced in P. pastoris range from Man(7)GlcNAc(2) up to Man(14)GlcNAc(2), with Man(8)GlcNAc(2) and Man(9)GlcNAc(2) being the most abundant structures. In both enzymes the first glycosylation site (Asn(5)) is always glycosylated. However, Asn(537) and Asn(540) are only partially glycosylated in an alternate manner.