SARS-CoV-2 complete genome sequencing from the Italian Campania region using a highly automated next generation sequencing system

Since the first complete genome sequencing of SARS-CoV-2 in December 2019, more than 550,000 genomes have been submitted into the GISAID database. Sequencing of the SARS-CoV-2 genome might allow identification of variants with increased contagiousness, different clinical patterns and/or different response to vaccines. A highly automated next generation sequencing (NGS)-based method might facilitate an active genomic surveillance of the virus

Correlation of NM23-H1 cytoplasmic expression with metastatic stage in human prostate cancer tissue

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Data set HRD comparison

Analysis of concordance for BRCA status, genomic instability value and HRD status between Myriad and the three Commercial assays (TSO500, OCAPlus and SOPHIA)

Optimizing response to gefitinib in the treatment of non-small-cell lung cancer

Pietro Carotenuto1, Cristin Roma1, Anna Maria Rachiglio1, Raffaella Pasquale1, Renato Franco2, Giuseppe Antinolfi3, Francovito Piantedosi4, Alfonso Illiano5, Gerardo Botti2, Alessandro Morabito6, Nicola Normanno7, Antonella De Luca71Pharmacogenomic Laboratory, CROM – Centro Ricerche Oncologiche di Mercogliano, Avellino, Italy; 2Surgical Pathology Unit, INT Fondazione "G. Pascale", Naples, Italy; 3Surgical Pathology Unit, Monaldi Hospital, Naples, Italy; 4Pneumoncology DH Unit, Monaldi Hospital, Naples, Italy; 5Pneumoncology Unit, Monaldi Hospital, Naples, Italy; 6Medical Oncology, Thoracic Department, INT Fondazione "G. Pascale", Naples, Italy; 7Cell Biology and Biotherapy Unit, INT Fondazione "G. Pascale", Naples, ItalyAbstract: The epidermal growth factor receptor (EGFR) is expressed in the majority of non-small-cell lung cancer (NSCLC). However, only a restricted subgroup of NSCLC patients respond to treatment with the EGFR tyrosine kinase inhibitor (EGFR TKI) gefitinib. Clinical trials have demonstrated that patients carrying activating mutations of the EGFR significantly benefit from treatment with gefitinib. In particular, mutations of the EGFR TK domain have been shown to increase the sensitivity of the EGFR to exogenous growth factors and, at the same time, to EGFR TKIs such as gefitinib. EGFR mutations are more frequent in patients with particular clinical and pathological features such as female sex, nonsmoker status, adenocarcinoma histology, and East Asian ethnicity. A close correlation was found between EGFR mutations and response to gefitinib in NSCLC patients. More importantly, randomized Phase III studies have shown the superiority of gefitinib compared with chemotherapy in EGFR mutant patients in the first-line setting. In addition, gefitinib showed a good toxicity profile with an incidence of adverse events that was significantly lower compared with chemotherapy. Therefore, gefitinib is a major breakthrough for the management of EGFR mutant NSCLC patients and represents the first step toward personalized treatment of NSCLC.Keywords: gefitinib, EGFR, NSCLC, EGFR mutation

The EGFR Signaling Modulates in Mesenchymal Stem Cells the Expression of miRNAs Involved in the Interaction with Breast Cancer Cells

We previously demonstrated that the epidermal growth factor receptor (EGFR) modulates in mesenchymal stem cells (MSCs) the expression of a number of genes coding for secreted proteins that promote breast cancer progression. However, the role of the EGFR in modulating in MSCs the expression of miRNAs potentially involved in the progression of breast cancer remains largely unexplored. Following small RNA-sequencing, we identified 36 miRNAs differentially expressed between MSCs untreated or treated with the EGFR ligand transforming growth factor α (TGFα), with a fold change (FC) < 0.56 or FC ≥ 1.90 (CI, 95%). KEGG analysis revealed a significant enrichment in signaling pathways involved in cancer development and progression. EGFR activation in MSCs downregulated the expression of different miRNAs, including miR-23c. EGFR signaling also reduced the secretion of miR-23c in conditioned medium from MSCs. Functional assays demonstrated that miR-23c acts as tumor suppressor in basal/claudin-low MDA-MB-231 and MDA-MB-468 cells, through the repression of IL-6R. MiR-23c downregulation promoted cell proliferation, migration and invasion of these breast cancer cell lines. Collectively, our data suggested that the EGFR signaling regulates in MSCs the expression of miRNAs that might be involved in breast cancer progression, providing novel information on the mechanisms that regulate the MSC-tumor cell cross-talk

The EGFR Signaling Modulates in Mesenchymal Stem Cells the Expression of miRNAs Involved in the Interaction with Breast Cancer Cells

We previously demonstrated that the epidermal growth factor receptor (EGFR) modulates in mesenchymal stem cells (MSCs) the expression of a number of genes coding for secreted proteins that promote breast cancer progression. However, the role of the EGFR in modulating in MSCs the expression of miRNAs potentially involved in the progression of breast cancer remains largely unexplored. Following small RNA-sequencing, we identified 36 miRNAs differentially expressed between MSCs untreated or treated with the EGFR ligand transforming growth factor &alpha; (TGF&alpha;), with a fold change (FC) &lt; 0.56 or FC &ge; 1.90 (CI, 95%). KEGG analysis revealed a significant enrichment in signaling pathways involved in cancer development and progression. EGFR activation in MSCs downregulated the expression of different miRNAs, including miR-23c. EGFR signaling also reduced the secretion of miR-23c in conditioned medium from MSCs. Functional assays demonstrated that miR-23c acts as tumor suppressor in basal/claudin-low MDA-MB-231 and MDA-MB-468 cells, through the repression of IL-6R. MiR-23c downregulation promoted cell proliferation, migration and invasion of these breast cancer cell lines. Collectively, our data suggested that the EGFR signaling regulates in MSCs the expression of miRNAs that might be involved in breast cancer progression, providing novel information on the mechanisms that regulate the MSC-tumor cell cross-talk

Bioinformatics: From NGS Data to Biological Complexity in Variant Detection and Oncological Clinical Practice

The use of next-generation sequencing (NGS) techniques for variant detection has become increasingly important in clinical research and in clinical practice in oncology. Many cancer patients are currently being treated in clinical practice or in clinical trials with drugs directed against specific genomic alterations. In this scenario, the development of reliable and reproducible bioinformatics tools is essential to derive information on the molecular characteristics of each patient&rsquo;s tumor from the NGS data. The development of bioinformatics pipelines based on the use of machine learning and statistical methods is even more relevant for the determination of complex biomarkers. In this review, we describe some important technologies, computational algorithms and models that can be applied to NGS data from Whole Genome to Targeted Sequencing, to address the problem of finding complex cancer-associated biomarkers. In addition, we explore the future perspectives and challenges faced by bioinformatics for precision medicine both at a molecular and clinical level, with a focus on an emerging complex biomarker such as homologous recombination deficiency (HRD)

Detection of EGFR Mutations by TaqMan Mutation Detection Assays Powered by Competitive Allele-Specific TaqMan PCR Technology

Epidermal growth factor receptor (EGFR) mutations in non-small-cell lung cancer (NSCLC) are predictive of response to treatment with tyrosine kinase inhibitors. Competitive Allele-Specific TaqMan PCR (castPCR) is a highly sensitive and specific technology. EGFR mutations were assessed by TaqMan Mutation Detection Assays (TMDA) based on castPCR technology in 64 tumor samples: a training set of 30 NSCLC and 6 colorectal carcinoma (CRC) samples and a validation set of 28 NSCLC cases. The sensitivity and specificity of this method were compared with routine diagnostic techniques including direct sequencing and the EGFR Therascreen RGQ kit. Analysis of the training set allowed the identification of the threshold value for data analysis (0.2); the maximum cycle threshold (Ct = 37); and the cut-off.Ct value (7) for the EGFR TMDA. By using these parameters, castPCR technology identified both training and validation set EGFR mutations with similar frequency as compared with the Therascreen kit. Sequencing detected rare mutations that are not identified by either castPCR or Therascreen, but in samples with low tumor cell content it failed to detect common mutations that were revealed by real-time PCR based methods. In conclusion, our data suggest that castPCR is highly sensitive and specific to detect EGFR mutations in NSCLC clinical samples