The endoscopic endonasal transsphenoidal approach (EETA) is an established technique for the resection of a large variety of benign sellar and suprasellar lesions, mostly pituitary adenomas. It has clear advantages over the microscopic approach, like a superior close-up view of the relevant anatomy and the tumor-gland interface, an enlarged working angle, as well as an increased panoramic vision inside the surgical area. We have been performing the EETA for over a decade, and this study will focus on perioperative and postoperative outcomes and complications and their association with the learning curve. All patients in our tertiary referral center (n = 369) undergoing an EETA for a lesion of the sellar and suprasellar region between January 1 2008 and December 31 2018 were included, and data were retrospectively retrieved from the electronic patient records. Median follow-up after surgery was 55 months. Pituitary adenomas (n = 322) were the most frequent pathology. Headache (43.4%) and loss of visiopic approach to the EETA in our cohort, the caseload increased and hospital stay was reduced, while no increase in peri- and postoperative complications was observed.The EETA is an excellent technique with complication rates comparable to or even lower than those in large microsurgical series in the literature. EETA has a significant learning curve affecting the procedure duration. Throughout the first 10 years following the transition from the microscopic approach to the EETA in our cohort, the caseload increased and hospital stay was reduced, while no increase in peri- and postoperative complications was observed.Chemotherapy resistance is a huge barrier for head and neck cancer (HNC) patients and therefore requires close attention to understand its underlay mechanisms for effective strategies. In this review, we first summarize the molecular mechanisms of chemotherapy resistance that occur during the treatment with cisplatin, 5-fluorouracil, and docetaxel/paclitaxel, including DNA/RNA damage repair, drug efflux, apoptosis inhibition, and epidermal growth factor receptor/focal adhesion kinase/nuclear factor-κB activation. Next, we describe the potential approaches to combining conventional therapies with previous cancer treatments such as immunotherapy, which may improve the treatment outcomes and prolong the survival of HNC patients. Overall, by parsing the reported molecular mechanisms of chemotherapy resistance within HNC patient's tumors, we can improve the prediction of chemotherapeutic responsiveness, and reveal new therapeutic targets for the future.Cervical cancer (CC) represents a major global health issue, particularly impacting women from resource constrained regions worldwide. Treatment refractoriness to standard chemoradiotheraphy has identified cancer stem cells as critical coordinators behind the biological mechanisms of resistance, contributing to CC recurrence. In this work, we evaluated differential gene expression in cervical cancer stem-like cells (CCSC) as biomarkers related to intrinsic chemoradioresistance in CC. A total of 31 patients with locally advanced CC and referred to Mário Penna Institute (Belo Horizonte, Brazil) from August 2017 to May 2018 were recruited for the study. Fluorescence-activated cell sorting was used to enrich CD34+/CD45- CCSC from tumor biopsies. Transcriptome was performed using ultra-low input RNA sequencing and differentially expressed genes (DEGs) using Log2 fold differences and adjusted p-value less then 0.05 were determined. The analysis returned 1050 DEGs when comparing the Non-Responder (NR) (n=10) and Responder (R) (n=21) groups to chemoradiotherapy. These included a wide-ranging pattern of underexpressed coding genes in the NR vs. R patients and a panel of lncRNAs and miRNAs with implications for CC tumorigenesis. A panel of biomarkers was selected using the rank-based AUC (Area Under the ROC Curve) and pAUC (partial AUC) measurements for diagnostic sensitivity and specificity. Genes overlapping between the 21 highest AUC and pAUC loci revealed seven genes with a strong capacity for identifying NR vs. R patients (ILF2, RBM22P2, ACO16722.1, AL360175.1 and AC092354.1), of which four also returned significant survival Hazard Ratios. selleck chemicals llc This study identifies DEG signatures that provide potential biomarkers in CC prognosis and treatment outcome, as well as identifies potential alternative targets for cancer therapy. While artificial intelligence has shown great promise in organs-at-risk (OARs) auto segmentation for head and neck cancer (HNC) radiotherapy, to reach the level of clinical acceptance of this technology in real-world routine practice is still a challenge. The purpose of this study was to validate a U-net-based full convolutional neural network (CNN) for the automatic delineation of OARs of HNC, focusing on clinical implementation and evaluation. In the first phase, the CNN was trained on 364 clinical HNC patients' CT images with annotated contouring from routine clinical cases by different oncologists. The automated delineation accuracy was quantified using the Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD). To assess efficiency, the time required to edit the auto-contours to a clinically acceptable standard was evaluated by a questionnaire. For subjective evaluation, expert oncologists (more than 10 years' experience) were randomly presented with automated delineations or manual contouency in clinical practice. Deep learning-based auto-segmentation shows great potential to alleviate the labor-intensive contouring of OAR for radiotherapy treatment planning.After retraining, the CNN developed for OARs automated delineation in HNC was proved to be more robust, efficiency and consistency in clinical practice. Deep learning-based auto-segmentation shows great potential to alleviate the labor-intensive contouring of OAR for radiotherapy treatment planning.Neuroblastoma (NB) is the commonest solid tumor outside the central nervous system in infancy and childhood with a unique biological heterogeneity. In patients with advanced, metastasizing neuroblastoma, treatment failure and poor prognosis is often marked by resistance to chemo- or immunotherapy. Thus, identification of robust biomarkers seems essential for understanding tumor progression and developing effective therapy. Here, we have studied the expression of human endogenous retroviruses (HERV) as potential targets in NB cell lines during stem-cell medium-induced microenvironmental change. Quantitative PCR revealed that relative expression of the HERV-K family and HERV-W1 ENV were increased in all three NB cell lines after incubation in stem-cell medium. Virus transcriptome analyses revealed the transcriptional activation of three endogenous retrovirus elements HERV-R ENV (ERV3-1), HERV-E1 and HERV-Fc2 ENV (ERVFC1-1). Known malignancy markers in NB, e.g. proto-oncogenic MYC or MYCN were expressed highly heterogeneously in the three investigated NB cell lines with up-regulation of MYC and MYCN upon medium-induced microenvironmental change.