Web tool for estimating the cancer hazard rates in aging.

A computational approach for estimating the overall, population, and individual cancer hazard rates was developed. The population rates characterize a risk of getting cancer of a specific site/type, occurring within an age-specific group of individuals from a specified population during a distinct time period. The individual rates characterize an analogous risk but only for the individuals susceptible to cancer. The approach uses a novel regularization and anchoring technique to solve an identifiability problem that occurs while determining the age, period, and cohort (APC) effects. These effects are used to estimate the overall rate, and to estimate the population and individual cancer hazard rates. To estimate the APC effects, as well as the population and individual rates, a new web-based computing tool, called the CancerHazard@Age, was developed. The tool uses data on the past and current history of cancer incidences collected during a long time period from the surveillance databases. The utility of the tool was demonstrated using data on the female lung cancers diagnosed during 1975-2009 in nine geographic areas within the USA. The developed tool can be applied equally well to process data on other cancer sites. The data obtained by this tool can be used to develop novel carcinogenic models and strategies for cancer prevention and treatment, as well as to project future cancer burden

Современные мессенджеры в качестве помощника администратора базы данных

This article considers usage of modern messengers and their capabilities by database administrators. The process of creating a bot, which allows the administrator to receive timely notifications about problems and errors that occurred with the database, as well as receive usage statistics, are described. The main difference from other similar products is the implementation for instant messengers, which are currently popular. The article provides a description of the development using platforms Telegram, Facebook Messenger and Slack, based on a single libraryВ данной статье рассматривается вопрос использования современных мессенджеров и их возможностей администраторами баз данных. Описывается процесс создания бота, который позволяет администратору получать своевременные уведомления о проблемах и ошибках, произошедших с базой данных, а также получать статистику использования. Принципиальным отличием от других подобных продуктов является реализация для мессенджеров, которые в данный момент пользуются популярностью. Предусматривается описание разработки с использованием платформ Telegram, Facebook Messenger и Slack, на основе единой библиотек

Relaxin and the Immune Landscape of Benign and Malignant Thyroid Disease

Thyroid cancer is the most common endocrine cancer, and its incidence has significantly increased over the last 40 years. Recent studies have suggested relaxin—a peptide hormone secreted by the ovaries during pregnancy with anti-fibrotic actions in chronic inflammation—as a potential marker of thyroid cancer occurrence and progression. However, it is unknown how relaxin behaves in benign versus malignant thyroid tissue. We hypothesized that relaxin levels would be decreased in benign and normal cancer-adjacent thyroid tissue relative to malignant tissue and increased in patients with lymphocytic thyroiditis, an autoimmune disorder involving chronic inflammation of the thyroid. Using the Integrated Cancer Repository for Cancer Research, benign, malignant, and normal cancer-adjacent thyroid tissue and accompanying clinical information were obtained. Tissue microarrays of each group were created, and immunofluorescence was performed to evaluate levels of relaxin. Our results indicated that relaxin is increased in malignant tissue relative to both normal cancer-adjacent and benign thyroid tissue, but there is no significant difference between benign and normal cancer-adjacent thyroid tissue. There is also an association between increased relaxin levels and lymphocytic thyroiditis. However, there is no association between significant differences in relaxin and other clinical factors like hypothyroidism and hyperthyroidism.https://digitalcommons.unmc.edu/surp2022/1016/thumbnail.jp

Should BRAFV600E be Incorporated into Treatment Recommendations for Thyroid Cancer?

Around 90% of all well-differentiated thyroid cancers are papillary thyroid carcinomas (PTC). PTCs have a recurrence rate of around 20% and a low mortality rate of around 5%. Within PTCs, around 60% of them have the BRAFV600E mutation. Currently, there is a debate on whether BRAFV600E is an independent predictor of tumor aggressiveness and recurrence. This study looks at whether BRAFV600E is an independent predictor of recurrence and outcomes in PTC. Tissue microarrays (TMA) were made from well-differentiated thyroid tumors and stained for the BRAFV600E mutation. BRAFV600E expression was calculated using an H-score: the staining intensity (0-3) multiplied by the amount of tumor that stained positive. A univariate analysis showed that BRAFV600E was significantly associated with age (p=0.0259), gender (p=0.019), extrathyroidal extension (p=0.049), positive margins (p=0.033), lymph node ratio (p=0.0106), N stage (p=0.015), AJCC 8 stage (p=0.0042), ATA risk category (p=0.018), and time to recurrence (p=0.0487). A multivariable analysis found that only extrathyroidal extension was an independent predictor of recurrence. Overall, BRAFV600E was not an independent predictor of recurrence in this cohort. Current treatment plans based on risk of recurrence appear to be appropriate, and it is not recommended that BRAFV600E be included as an independent variable.https://digitalcommons.unmc.edu/surp2021/1058/thumbnail.jp

PCCR: Pancreatic Cancer Collaborative Registry

The Pancreatic Cancer Collaborative Registry (PCCR) is a multi-institutional web-based system aimed to collect a variety of data on pancreatic cancer patients and high-risk subjects in a standard and efficient way. The PCCR was initiated by a group of experts in medical oncology, gastroenterology, genetics, pathology, epidemiology, nutrition, and computer science with the goal of facilitating rapid and uniform collection of critical information and biological samples to be used in developing diagnostic, prevention and treatment strategies against pancreatic cancer. The PCCR is a multi-tier web application that utilizes Java/JSP technology and has Oracle 10 g database as a back-end. The PCCR uses a “confederation model” that encourages participation of any interested center, irrespective of its size or location. The PCCR utilizes a standardized approach to data collection and reporting, and uses extensive validation procedures to prevent entering erroneous data. The PCCR controlled vocabulary is harmonized with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT). The PCCR questionnaire has accommodated standards accepted in cancer research and healthcare. Currently, seven cancer centers in the USA, as well as one center in Italy are participating in the PCCR. At present, the PCCR database contains data on more than 2,700 subjects (PC patients and individuals at high risk of getting this disease). The PCCR has been certified by the NCI Center for Biomedical Informatics and Information Technology as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product. The PCCR provides a foundation for collaborative PC research. It has all the necessary prerequisites for subsequent evolution of the developed infrastructure from simply gathering PC-related data into a biomedical computing platform vital for successful PC studies, care and treatment. Studies utilizing data collected in the PCCR may engender new approaches to disease prognosis, risk factor assessment, and therapeutic interventions

Multicenter Breast Cancer Collaborative Registry

The Breast Cancer Collaborative Registry (BCCR) is a multicenter web-based system that efficiently collects and manages a variety of data on breast cancer (BC) patients and BC survivors. This registry is designed as a multi-tier web application that utilizes Java Servlet/JSP technology and has an Oracle 11g database as a back-end. The BCCR questionnaire has accommodated standards accepted in breast cancer research and healthcare. By harmonizing the controlled vocabulary with the NCI Thesaurus (NCIt) or Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), the BCCR provides a standardized approach to data collection and reporting. The BCCR has been recently certified by the National Cancer Institute’s Center for Biomedical Informatics and Information Technology (NCI CBIIT) as a cancer Biomedical Informatics Grid (caBIG®) Bronze Compatible product

Investigating Immune Profiles in Differentiated Thyroid Cancer by Multiplex Immunofluorescence

BACKGROUND: As the most common endocrine malignancy in the United States (U.S.), differentiated thyroid cancer (DTC) accounts for 3.8% of all cancers in the U.S., with roughly 10% of cases progressing to distant metastatic DTC, which is associated with a poor five year survival outcome despite conventional management, including surgery and radioactive iodine ablation. Recently, novel immunotherapies have garnered attention as a viable therapeutic resource for patients with advanced DTC. However, the response to therapy has been variable and unpredictable, which may be associated with an immune suppressive circulating phenotype. Nonetheless, the intra-tumoral immune infiltrate remains to be elucidated, demonstrating a critical need to address the gap in understanding in order to better prognosticate the disease. OBJECTIVE: To identify and compare tumor-infiltrating immune markers with those present in the adjacent normal thyroid tissue, and collate these immune infiltrates with tumor characteristics. METHODS: Twenty-nine adult tissue samples containing tumor and stromal regions were collected from patients with DTC. The samples were analyzed using multiplex immunofluorescence (MxIF) with antibodies against cell-surface molecules CD56, PD-1, PD-L1, FOXP3, CD3, CD8, CD4, CD45, CD68, CD163, INOS, HLA-DR, CD33, and CD19. 17 of the specimens were analyzed using HALO and a positive threshold was assigned based on review by a trained researcher. RESULTS: In evaluating the immune profiles, important differences in the immune infiltrates between different stages of the cancer were observed. Generally, PD-1 and PD-L1 were highly expressed within the tumor, despite variability in lymphocyte infiltration, indicating the importance of PD-1 and PD-L1 as potential predictive biomarkers for the aggressiveness of thyroid cancer. Tumor from patients with distant metastases demonstrated higher T cell infiltration, T regulatory cells, macrophages and PD-L1 positive cells as compared to localized tumor. CONCLUSION: Immune profiling demonstrated significant differences between tumor and adjacent healthy regions, particularly in terms of PD-1 and PD-L1 expression and lymphocyte infiltration, indicating that higher intratumor infiltration of T regulatory cells, macrophages and PD-1/PD-L1 positive cells may be associated with advanced thyroid cancer. Therefore, the data demonstrates the efficacy of MxIF in gathering valuable information regarding the tumor microenvironment, which will have major implications in guiding the selection of patients for immunotherapy.https://digitalcommons.unmc.edu/surp2021/1042/thumbnail.jp

Grid-Layout Visualization Method in the Microarray Data Analysis Interactive Graphics Toolkit

The expression levels of thousands of genes in different tissues or cells in different conditions can be detected all at one time by DNA microarray technology. A new, gridlayout method for the visualization results of hierarchical cluster analysis of DNA microarray data is proposed and incorporated in the Microarray Interactive Graphics Toolkit (MIGT). The grid-layout consists of a set of regular, two-dimensional grid units. Each unit represents a cluster or a group of gene clusters. The units are connected to adjacent ones by the neighborhood relation of the clusters in a hierarchical tree. Nodes lying near each other in the hierarchical tree are mapped onto nearby grid-layout units. The number of units may vary on a scale from a few dozen up to several thousands, depending on the number of the nodes in a hierarchical tree. Different colors are assigned to the units with RGB value according to the coordinates of the units, and the inter-distances, which are the distances between clusters in a hierarchical tree, and the intra-distances, which are the distances between genes within one cluster. The closer the inter-distances, the more similar the color of the units are, the smaller the intra-distances, the warmer the color of the unit is. 1

Web Tool for Estimating the Cancer Hazard Rates in Aging

A computational approach for estimating the overall, population, and individual cancer hazard rates was developed. The population rates characterize a risk of getting cancer of a specific site/type, occurring within an age-specific group of individuals from a specified population during a distinct time period. The individual rates characterize an analogous risk but only for the individuals susceptible to cancer. The approach uses a novel regularization and anchoring technique to solve an identifiability problem that occurs while determining the age, period, and cohort (APC) effects. These effects are used to estimate the overall rate, and to estimate the population and individual cancer hazard rates. To estimate the APC effects, as well as the population and individual rates, a new web-based computing tool, called the CancerHazard@Age , was developed. The tool uses data on the past and current history of cancer incidences collected during a long time period from the surveillance databases. The utility of the tool was demonstrated using data on the female lung cancers diagnosed during 1975–2009 in nine geographic areas within the USA. The developed tool can be applied equally well to process data on other cancer sites. The data obtained by this tool can be used to develop novel carcinogenic models and strategies for cancer prevention and treatment, as well as to project future cancer burden

Thyroid Cancer and Tumor Collaborative Registry (TCCR)

A multicenter, web-based Thyroid Cancer and Tumor Collaborative Registry (TCCR, http://tccr.unmc.edu ) allows for the collection and management of various data on thyroid cancer (TC) and thyroid nodule (TN) patients. The TCCR is coupled with OpenSpecimen, an open-source biobank management system, to annotate biospecimens obtained from the TCCR subjects. The demographic, lifestyle, physical activity, dietary habits, family history, medical history, and quality of life data are provided and may be entered into the registry by subjects. Information on diagnosis, treatment, and outcome is entered by the clinical personnel. The TCCR uses advanced technical and organizational practices, such as (i) metadata-driven software architecture (design); (ii) modern standards and best practices for data sharing and interoperability (standardization); (iii) Agile methodology (project management); (iv) Software as a Service (SaaS) as a software distribution model (operation); and (v) the confederation principle as a business model (governance). This allowed us to create a secure, reliable, user-friendly, and self-sustainable system for TC and TN data collection and management that is compatible with various end-user devices and easily adaptable to a rapidly changing environment. Currently, the TCCR contains data on 2,261 subjects and data on more than 28,000 biospecimens. Data and biological samples collected by the TCCR are used in developing diagnostic, prevention, treatment, and survivorship strategies against TC