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In the past decade, research efforts were made to identify molecular biomarkers useful as therapeutic targets in Non-Small Cell Lung Cancer (NSCLC), the most frequent type of lung carcinoma. NSCLC presents different histological subtypes being the most prevalent LUSC (Lung Squamous Cell Cancer) and LUAD (Lung Adenocarcinoma), and only a subset of LUAD patients' present tumors expressing known targetable genetic alterations. Telomeres and its components, including telomerase, the enzyme that replenishes telomeres, have been considered potential cancer biomarkers due to their crucial role in cell proliferation and genome stability. Our study aims to quantify expression changes affecting telomere-associated genes and ncRNAs associated with telomere regulation and maintenance in NSCLC. We first assessed the transcriptome (RNA-Seq) data of NSCLC patients from The Cancer Genome Atlas (TCGA) and then we tested the expression of telomere-associated genes and telomeric ncRNAs (TERC, telomerase RNA component, and TERRA, telomere repeat-containing RNA) in Brazilian NCSLC patient samples by quantitative RT-PCR, using matched normal adjacent tissue samples as the control. We also estimated the mean size of terminal restriction fragments (TRF) of some Brazilian NSCLC patients using telomeric Southern blot. The TCGA analysis identified alterations in the expression profile of TERT and telomere damage repair genes, mainly in the LUSC subtype. The study of Brazilian NSCLC samples by RT-qPCR showed that LUSC and LUAD express high amounts of TERT and that although the mean TRF size of tumor samples was shorter compared to normal cells, telomeres in NSCLC are probably maintained by telomerase. Also, the expression analysis of Brazilian NSCLC samples identified statistically significant alterations in the expression of genes involved with telomere damage repair, as well as in TERC and TERRA, mainly in the LUSC subtype. We, therefore, concluded that telomere maintenance genes are significantly deregulated in NSCLC, representing potential biomarkers in the LUSC subtype., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Introduction: The current edition of the tumor, node and metastasis (TNM) classification of lung cancer (LC) divides the presence of metastasis (M1) into two categories: M1a and M1b, depending on its anatomical location. To assess this new classification, the survival and the M descriptors of LC patients with metastatic disease registered by the Bronchogenic Carcinoma Cooperative Group of the Spanish Society of Pneumology and Thoracic Surgery II (GCCB-S-II), were analyzed., Methods: Non-small cell lung cancer (NSCLC) patients, with M1a or M1b disease, included in the GCCB-S-II, from April 2009 to December 2010, staged in accordance with the prospective staging project protocol of the International Association for the Study of Lung Cancer (IASLC), and with complete TNM staging and follow-up data, were studied. The overall survival associated with each M1 category and each M descriptor, besides other prognostic factors (sex, age, performance status [PS] and others) were analyzed by univariate and multivariate models., Results: 640 NSCLC patients (195 M1a and 445 M1b) were included. M1b tumors had significantly worse survival than M1a tumors (p < 0.001). The prognostic value of M1 category was independent from other prognostic variables such as PS, weight loss, and others. The number of metastatic sites (isolated versus multiple) and the number of lesions (single versus multiple) in patients with isolated metastasis showed prognostic value, especially in those with brain metastasis., Conclusion: The current division of the M1 category into two subsets (M1a and M1b) is warranted by their prognostic significance. The number of metastatic sites and the number of lesions in patients with isolated metastasis should be taken into account, because they also have prognostic relevance., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Background: Transmission over the Internet of low-resolution images acquired by automated screening of cervical cytology specimens has the potential to provide remote interpretation and, hence, centralization of a cytology workforce., Methods: Liquid-based cervical cytology slides were scanned using the FocalPoint(R) System. Ten black-and-white images that had the greatest probability of containing abnormality were acquired from each of 32 reference slides (16 negative samples, 3 samples of atypical squamous cells of uncertain significance, 5 samples of low-grade squamous intraepithelial lesions [LSIL], 5 samples of high-grade squamous intraepithelial lesions [HSIL], 1 adenocarcinoma in situ sample, and 2 carcinoma samples) and were transmitted as e-mail attachments in JPEG format to remote reading stations. The slides were interpreted independently by two pathologists and were assigned to either of two groups: 1) suspicious for >or=HSIL or 2)