24 research outputs found
Rapid serological and SARS-CoV-2 RT-PCR assays: comparison performed simultaneously in symptomatic COVID-19 patients
RT-PCR testing for the identification of viral nucleic acid is the current standard diagnostic method for the diagnosis of SARS-CoV-2 infection but technical reasons limit its utilization for large-scale screening. Serological IgM/IgG testing has been proposed as a useful tool to detect SARS-CoV-2 exposure
Proteomic Profile and <i>In Silico</i> Analysis in Metastatic Melanoma with and without BRAF Mutation
<div><p>Introduction</p><p>Selective inhibitors of BRAF, vemurafenib and dabrafenib are the standard of care for metastatic melanoma patients with BRAF V600, while chemotherapy continued to be widely used in BRAF wild type patients.</p><p>Materials and Methods</p><p>In order to discover novel candidate biomarkers predictive to treatment, serum of 39 metastatic melanoma vemurafenib (n = 19) or chemotherapy (n = 20) treated patients at baseline, at disease control and at progression, were analyzed using SELDI-TOF technology. In silico analysis was used to identify more significant peaks.</p><p>Results</p><p>In patients with different BRAF status, we found 5 peptides significantly deregulated, with the down-regulation of the m/z 9176 peak strongly associated with BRAF mutation. At baseline as predictive biomarkers we identified 2 peptides - m/z 6411, 4075 – as significantly up-regulated in responders to chemotherapy and 4 peaks - m/z 5900, 12544, 49124 and 11724 - significantly up-regulated in longer vs shorter responders to vemurafenib. After response, 3 peptides (m/z 4658, 18639, and 9307) resulted significantly down regulated while 3 peptides m/z 9292, 7765 and 9176 appeared up-regulated respectively in chemotherapy and vemurafenib responder patients. In vemurafenib treated patients, 16 peaks appeared deregulated at progression compared to baseline time. In silico analysis identified proteins involved in invasiveness (SLAIN1) and resistance (ABCC12) as well as in the pathway of detoxification (NQO1) and apoptosis (RBM10, TOX3, MTEFD1, TSPO2). Proteins associated with the modulation of neuronal plasticity (RIN1) and regulatory activity factors of gene transcription (KLF17, ZBTB44) were also highlighted.</p><p>Conclusion</p><p>Our exploratory study highlighted some factors that deserve to be further investigated in order to provide a framework for improving melanoma treatment management through the development of biomarkers which could act as the strongest surrogates of the key biological events in stage IV melanoma.</p></div
BMI and pausal status in 300 subjects affected by breast cancer and 300 control cases.
<p>Mantel – Haenszel χ<sup>2</sup> p<0.05.</p
The 4 discriminating m/z peaks among BRAF V600E/K mutated and BRAFwt MM patients. m/z: mass-to-charge ratio; P was generated by peak comparison between BRAF mutated and wild type patients.
<p>The 4 discriminating m/z peaks among BRAF V600E/K mutated and BRAFwt MM patients. m/z: mass-to-charge ratio; P was generated by peak comparison between BRAF mutated and wild type patients.</p
Mascot search result for BRAF wild-type patients.
<p>Mascot search result for BRAF wild-type patients.</p
Comparison of peak intensities average (μA) between high BMI breast cancer patients and healthy subjects.
<p>Only significant peaks (P-value<0.01) are reported.</p><p>
<b>Legend:</b></p>*<p> = From IMAC 30 Dataset.</p>**<p> = From CM 10 Dataset.</p
Logistic multivariate model with breast cancer as dependent variable.
<p>Logistic multivariate model with breast cancer as dependent variable.</p
Comparison of peak intensities average (μA) between Breast cancer patients with high BMI and low BMI.
<p>Only significant peaks (P-value<0.01) are reported.</p><p>
<b>Legend:</b></p>*<p> = From IMAC 30 Dataset.</p>**<p> = From CM 10 Dataset.</p
Clinicopathological features in a case study of 300 patients affected by breast cancer and 300 control with negative mammography result.
*<p>: χ<sup>2</sup> test.</p
Clinical-pathological breast cancer characteristics and BMI, χ<sup>2</sup> test was used to calculate p-value.
<p>Clinical-pathological breast cancer characteristics and BMI, χ<sup>2</sup> test was used to calculate p-value.</p