FOLFIRINOX after first-line gemcitabine-based chemotherapy in advanced pancreatic cancer: a retrospective comparison with FOLFOX and FOLFIRI schedules

Background: Pancreatic adenocarcinoma is the fourth leading cause of cancer-related death. In cases with metastasis, the combination of 5-fluorouracil, irinotecan, and oxaliplatin (FOLFIRINOX) or gemcitabine-based chemotherapy regimens are considered the standard of care. However, the optimal sequence of these regimens is unclear. Methods: This retrospective study initially evaluated 186 patients with locally advanced/metastatic pancreatic cancer at three Italian institutions between February 2013 and October 2019. All patients had progressed after receiving gemcitabine-based first-line chemotherapy and were subsequently offered second-line FOLFIRINOX, FOLFOX-6, or FOLFIRI treatment. This study evaluated progression-free survival (PFS), overall survival from the start of second-line treatment (OS2), overall survival from the start of first-line treatment (OS1), and safety outcomes. Results: A total of 77 patients received ⩾4 cycles of second-line chemotherapy and were considered eligible: 15 patients received FOLFIRINOX, 32 patients received FOLFOX-6, and 30 patients received FOLFIRI. The FOLFIRINOX group had median PFS of 26.29 weeks and median OS2 of 47.86 weeks, while the FOLFIRI group had median PFS of 10.57 weeks and median OS2 of 25.00 weeks (p = 0.038). No significant differences were observed between the FOLFIRINOX and FOLFOX-6 groups in terms of PFS (26.29 weeks versus 23.07 weeks) or OS2 (47.86 weeks versus 42.00 weeks). The most common grade 3–4 toxicities were anemia, neutropenia, and thrombocytopenia, which occurred more frequently in the FOLFIRINOX and FOLFOX-6 groups. Conclusion: Relative to the FOLFIRI regimen, the FOLFIRINOX regimen had a favorable toxicity profile and better survival outcomes. No significant differences were observed relative to the FOLFOX-6 regimen

Bone Tissue Response to Porous and Functionalized Titanium and Silica Based Coatings

Background: Topography and presence of bio-mimetic coatings are known to improve osseointegration. The objective of this study was to evaluate the bone regeneration potential of porous and osteogenic coatings. Methodology: Six-implants [Control (CTR); porous titanium coatings (T1, T2); thickened titanium (Ti) dioxide layer (TiO2); Amorphous Microporous Silica (AMS) and Bio-active Glass (BAG)] were implanted randomly in tibiae of 20-New Zealand white rabbits. The animals were sacrificed after 2 or 4 weeks. The samples were analyzed histologically and histomorphometrically. In the initial bone-free areas (bone regeneration areas (BRAs)), the bone area fraction (BAF) was evaluated in the whole cavity (500 mm, BAF-500), in the implant vicinity (100 mm, BAF-100) and further away (100–500 mm, BAF-400) from the implant. Bone-to-implant contact (BIC-BAA) was measured in the areas where the implants were installed in contact to the host bone (bone adaptation areas (BAAs)) to understand and compare the bone adaptation. Mixed models were used for statistical analysis. Principal Findings: After 2 weeks, the differences in BAF-500 for different surfaces were not significant (p.0.05). After 4 weeks, a higher BAF-500 was observed for BAG than CTR. BAF-100 for AMS was higher than BAG and BAF-400 for BAG was higher than CTR and AMS. For T1 and AMS, the bone regeneration was faster in the 100-mm compared to the 400-mm zone. BIC-BAA for AMS and BAG was lower after 4 than 2 weeks. After 4 weeks, BIC-BAA for BAG was lower than AMS and CTR. Conclusions: BAG is highly osteogenic at a distance from the implant. The porous titanium coatings didn’t stimulate bone regeneration but allowed bone growth into the pores. Although AMS didn’t stimulate higher bone response, it has a potential of faster bone growth in the vicinity compared to further away from the surface. BIC-BAA data were inconclusive to understand the bone adaptation.status: publishe

A Multi-Sample Based Method for Identifying Common CNVs in Normal Human Genomic Structure Using High-Resolution aCGH Data

BACKGROUND: It is difficult to identify copy number variations (CNV) in normal human genomic data due to noise and non-linear relationships between different genomic regions and signal intensity. A high-resolution array comparative genomic hybridization (aCGH) containing 42 million probes, which is very large compared to previous arrays, was recently published. Most existing CNV detection algorithms do not work well because of noise associated with the large amount of input data and because most of the current methods were not designed to analyze normal human samples. Normal human genome analysis often requires a joint approach across multiple samples. However, the majority of existing methods can only identify CNVs from a single sample. METHODOLOGY AND PRINCIPAL FINDINGS: We developed a multi-sample-based genomic variations detector (MGVD) that uses segmentation to identify common breakpoints across multiple samples and a k-means-based clustering strategy. Unlike previous methods, MGVD simultaneously considers multiple samples with different genomic intensities and identifies CNVs and CNV zones (CNVZs); CNVZ is a more precise measure of the location of a genomic variant than the CNV region (CNVR). CONCLUSIONS AND SIGNIFICANCE: We designed a specialized algorithm to detect common CNVs from extremely high-resolution multi-sample aCGH data. MGVD showed high sensitivity and a low false discovery rate for a simulated data set, and outperformed most current methods when real, high-resolution HapMap datasets were analyzed. MGVD also had the fastest runtime compared to the other algorithms evaluated when actual, high-resolution aCGH data were analyzed. The CNVZs identified by MGVD can be used in association studies for revealing relationships between phenotypes and genomic aberrations. Our algorithm was developed with standard C++ and is available in Linux and MS Windows format in the STL library. It is freely available at: http://embio.yonsei.ac.kr/~Park/mgvd.php

A novel SNP analysis method to detect copy number alterations with an unbiased reference signal directly from tumor samples

<p>Abstract</p> <p>Background</p> <p>Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples.</p> <p>Methods</p> <p>To address these limitations, we designed a novel "Virtual Normal" algorithm (VN), which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set.</p> <p>Results</p> <p>The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions.</p> <p>Conclusions</p> <p>We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.</p

A study of some fundamental physicochemical variables on the morphology of mesoporous silica nanoparticles MCM-41 type

[EN] All variables affecting the morphology of mesoporous silica nanoparticles (MSN) should be carefully analyzed in order to truly tailored design their mesoporous structure according to their final use. Although complete control on MCM-41 synthesis has been already claimed, reproducibility and repeatability of results remain a big issue due to the lack of information reported in literature. Stirring rate, reaction volume, and system configuration (i.e., opened or closed reactor) are three variables that are usually omitted, making the comparison of product characteristics difficult. Specifically, the rate of solvent evaporation is seldom disclosed, and its influence has not been previously analyzed. These variables were systematically studied in this work, and they were proven to have a fundamental impact on final particle morphology. Hence, a high degree of circularity (C = 0.97) and monodispersed particle size distributions were only achieved when a stirring speed of 500 rpm and a reaction scale of 500 mL were used in a partially opened system, for a 2 h reaction at 80 degrees C. Well-shaped spherical mesoporous silica nanoparticles with a diameter of 95 nm, a pore size of 2.8 nm, and a total surface area of 954 m(2) g(-1) were obtained. Final characteristics made this product suitable to be used in biomedicine and nanopharmaceutics, especially for the design of drug delivery systems.This study was funded partially by Departamento Administrativo de Ciencia Tecnología e Innovación–COLCIENCIAS (recipient, Angela A. Beltrán-Osuna); Ministerio de Economía y Competitividad, MINECO, research number MAT2016-76039-C4-1-R (Recipient, José L. Gómez-Ribelles); and Universidad Nacional de Colombia, grant number DIB201010021438 (Recipient, Jairo E. Perilla).Beltrán-Osuna, A.; Gómez Ribelles, JL.; Perilla-Perilla, JE. (2017). 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