Pancreatic cancer-associated diabetes mellitus: an open field for proteomic applications.

Background: Diabetes mellitus is associated with pancreatic cancer in more than 80% of the cases. Clinical, epidemiological, and experimental data indicate that pancreatic cancer causes diabetes mellitus by releasing soluble mediators which interfere with both beta-cell function and liver and muscle glucose metabolism. Methods: We analysed, by matrix-assisted laser desorption ionization time of flight (MALDI-TOF), a series of pancreatic cancer cell lines conditioned media, pancreatic cancer patients' peripheral and portal sera, comparing them with controls and chronic pancreatitis patients' sera. Results: MALDI-TOF analysis of pancreatic cancer cells conditioned media and patients' sera indicated a low molecular weight peptide to be the putative pancreatic cancer-associated diabetogenic factor. The sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis of tumor samples from diabetic and non-diabetic patients revealed the presence of a 1500 Da peptide only in diabetic patients. The amino acid sequence of this peptide corresponded to the N-terminal of an S-100 calcium binding protein, which was therefore suggested to be the pancreatic cancer-associated diabetogenic factor. Conclusions: We identified a tumor-derived peptide of 14 amino acids sharing a 100% homology with an S-100 calcium binding protein, which is probably the pancreatic cancer-associated diabetogenic facto

Pancreatic cancer-derived S-100A8 N-terminal peptide: a diabetes cause?

BACKGROUND: Our aim was to identify the pancreatic cancer diabetogenic peptide. METHODS: Pancreatic tumor samples from patients with (n=15) or without (n=7) diabetes were compared with 6 non-neoplastic pancreas samples using SDS-PAGE. RESULTS: A band measuring approximately 1500 Da was detected in tumors from diabetics, but not in neoplastic samples from non-diabetics or samples from non-neoplastic subjects. Sequence analysis revealed a 14 amino acid peptide (1589.88 Da), corresponding to the N-terminal of the S100A8. At 50 nmol/L and 2 mmol/L, this peptide significantly reduced glucose consumption and lactate production by cultured C(2)C(12) myoblasts. The 14 amino acid peptide caused a lack of myotubular differentiation, the presence of polynucleated cells and caspase-3 activation. CONCLUSIONS: The 14 amino acid peptide from S100A8 impairs the catabolism of glucose by myoblasts in vitro and may cause hyperglycemia in vivo. Its identification in biological fluids might be helpful in diagnosing pancreatic cancer in patients with recent onset diabetes mellitus

The molecular diversity of Luminal A breast tumors

Breast cancer is a collection of diseases with distinct molecular traits, prognosis, and therapeutic options. Luminal A breast cancer is the most heterogeneous, both molecularly and clinically. Using genomic data from over 1,000 Luminal A tumors from multiple studies, we analyzed the copy number and mutational landscape of this tumor subtype. This integrated analysis revealed four major subtypes defined by distinct copy-number and mutation profiles. We identified an atypical Luminal A subtype characterized by high genomic instability, TP53 mutations, and increased Aurora kinase signaling; these genomic alterations lead to a worse clinical prognosis. Aberrations of chromosomes 1, 8, and 16, together with PIK3CA, GATA3, AKT1, and MAP3K1 mutations drive the other subtypes. Finally, an unbiased pathway analysis revealed multiple rare, but mutually exclusive, alterations linked to loss of activity of co-repressor complexes N-Cor and SMRT. These rare alterations were the most prevalent in Luminal A tumors and may predict resistance to endocrine therapy. Our work provides for a further molecular stratification of Luminal A breast tumors, with potential direct clinical implications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10549-013-2699-3) contains supplementary material, which is available to authorized users

Mass Transfer Solver Tool: A software to calculate mass transfer coefficients for Packed-bed Columns

The Mass Transfer Solver Tool is a calculation software for gas-liquid mass transfer coefficients for random and structured packed-bed columns. This software refers to the work of Flagiello et al. (2021) entitled "A tool for mass transfer evaluation in packed-bed columns for chemical engineering students" and published in the scientific journal of Education for Chemical Engineers (https://doi.org/10.1016/j.ece.2021.08.001). The MT Solver Tool is based on the use of the most acknowledged models available in the pertinent literature (Onda et al., 1968; Bravo et al., 1985, 1992; Billet and Schultes, 1993; Brunazzi and Paglianti, 1997; Olujić et al. , 2004; Hanley and Chen, 2012) to calculate the gas-side (ky), liquid-side (kx) and interfacial area (ae) coefficients separately. The software includes a "Library File" where geometric data and model fitting parameters for 144 different packings in size and materials are available. The spreadsheet file "MT Solver" operating in default mode uses the data of the 144 packings available in the "Library File" to calculate the mass transfer coefficients. Futhermore, the software can also be operated in user-defined mode "User-defined MT Solver" in order to customize and expand its use when the considered packing is not included in the Library File. The MT Solver Tool was also used in teaching activities in the academic year 2020-2021 for the Unit Operation and Sustainable Process Design courses of the Master's degree in Chemical Engineering, at the University of Naples Federico II. All the instructions for use are given in the work: A tool for mass transfer evaluation in packed-bed columns for chemical engineering students (https://doi.org/10.1016/j.ece.2021.08.001). Any system bugs, calculation errors deriving from the model equations or the parameters set in the library can be reported to the email address: [email protected] (Dr. Domenico Flagiello). Suggestions for model equations updates or data and packing parameter values ​​included in the library (or new data packing) are also welcome

Mass Transfer Solver Tool: A software to calculate mass transfer coefficients for Packed-bed Columns

The Mass Transfer Solver Tool is a calculation software for gas-liquid mass transfer coefficients for random and structured packed-bed columns. This software refers to the work of Flagiello et al. (2021) entitled "A tool for mass transfer evaluation in packed-bed columns for chemical engineering students" and published in the scientific journal of Education for Chemical Engineers (https://doi.org/10.1016/j.ece.2021.08.001). The MT Solver Tool is based on the use of the most acknowledged models available in the pertinent literature (Onda et al., 1968; Bravo et al., 1985, 1992; Billet and Schultes, 1993; Brunazzi and Paglianti, 1997; Olujić et al. , 2004; Hanley and Chen, 2012) to calculate the gas-side (ky), liquid-side (kx) and interfacial area (ae) coefficients separately. The software includes a "Library File" where geometric data and model fitting parameters for 144 different packings in size and materials are available. The spreadsheet file "MT Solver" operating in default mode uses the data of the 144 packings available in the "Library File" to calculate the mass transfer coefficients. Futhermore, the software can also be operated in user-defined mode "User-defined MT Solver" in order to customize and expand its use when the considered packing is not included in the Library File. The MT Solver Tool was also used in teaching activities in the academic year 2020-2021 for the Unit Operation and Sustainable Process Design courses of the Master's degree in Chemical Engineering, at the University of Naples Federico II. All the instructions for use are given in the work: A tool for mass transfer evaluation in packed-bed columns for chemical engineering students (https://doi.org/10.1016/j.ece.2021.08.001). Any system bugs, calculation errors deriving from the model equations or the parameters set in the library can be reported to the email address: [email protected] (Dr. Domenico Flagiello). Suggestions for model equations updates or data and packing parameter values ​​included in the library (or new data packing) are also welcome

Hoxc5 and Hoxc8 Expression Are Selectively Turned on in Human Cervical Cancer Cells Compared to Normal Keratinocytes

A growing number of data have sustained the involvement of homeobox genes expression deregulation in cancer. In this study, we have performed an exhaustive survey of the expression of the 39 class I HOX genes expressed in normal and malignant human cervix keratinocytes. Using RT-PCR, we observed that the vast majority (34/39) of HOX genes are expressed in normal keratinocytes. Only HOXA2, HOXA7, HOXC5, HOXC8 and HOXD12 were found to be silent. Interestingly, this pattern is conserved in the transformed keratinocytes (SiHa cells) except for the appearance of HOXC5 and HOXC8 mRNA. The HOXC5 and HOXC8 expression was also observed in two other transformed keratinocytes cell lines of independent origins, Eil-8 and 18-11S3, and confirmed by in situ hybridization. Our data add weight to the body of evidence attributing to a specific adult tissue a particular combination of expressed HOX genes and suggest that HOXC5 and/or HOXC8 could be involved in the process leading to the transformation of cervical keratinocytes.ARC - Actions de recherche concertées N°96/00-19