LAMA4-Regulating miR-4274 and Its Host Gene SORCS2 Play a Role in IGFBP6-Dependent Effects on Phenotype of Basal-Like Breast Cancer
Specificity of RNAi to selected target is challenged by off-target effects, both canonical and non-canonical. Notably, more than half of all human microRNAs are co-expressed with hosting them proteincoding genes. Here we dissect regulatory subnetwork centered on IGFBP6 gene, which is associated with low proliferative state and high migratory activity of basal-like breast cancer. We inhibited expression of IGFBP6 gene in a model cell line for basal-like breast carcinoma MDA-MB-231, then traced secondary and tertiary effects of this knockdown to LAMA4, a laminin encoding gene that contributes to the phenotype of triple-negative breast cancer. LAMA4-regulating miRNA miR-4274 and its host gene SORCS2 were highlighted as intermediate regulators of the expression levels of LAMA4, which correlated in a basal-like breast carcinoma sample subset of TCGA to the levels of SORCS2 negatively. Overall, our study points that the secondary and tertiary layers of regulatory interactions are certainly underappreciated. As these types of molecular event may significantly contribute to the formation of the cell phenotypes after RNA interference based knockdowns, further studies of multilayered molecular networks affected by RNAi are warranted.
This study is an attempt to obtain reliable data on the natural history of breast cancer growth. The opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) were analysed in order to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. Our results suggest a new «Consolidated mathematical growth Model of the Primary tumor and the Secondary distant metastases» (CoMPaS). The CoMPaS is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations. The CoMPaS describes correctly the primary tumor growth (parameter T) and the secondary distant metastases growth (parameter M). Also, CoMPaS associates with data of 10–15-year survival in patients with the different tumor stage. Analysis of the metastases «nonvisible period» growth indicate the case of discrepancy between 15-year survival depending on tumor stage. In conclusion, the CoMPaS and supporting computer program were build to improve the accuracy of the forecast on survival of breast cancer and facilitate the optimisation of diagnosing secondary distant metastases. This led to completely original results that show how the growth rate of the metastases can change in relation to the growth rate of the primary tumour, taking into consideration its size and diameter of the tumour.
The search for novel parameters to predict the risk of relapse in breast cancer was conducted. Significant correlation between the risk of relapse and α-2A adrenergic receptor (ADRA2A) expression was revealed using public microarray datasets. This relationship was confirmed by validation on independent microarray dataset. It was found that when assessing the risk of BC relapse, the accuracy of prediction based solely on the expression of ADRA2A gene is close to that made using OncotypeDX and MammaPrint test systems. In this case, addition of only one or two supplemental prognostic markers (for instance, expression of SQLE gene or SQLE andDSCC1genes) to ADRA2A ensures the accuracy of prediction not inferior to reliability of these test systems.
Genes with significant differential expression are traditionally used to reveal the genetic background underlying phenotypic differences between cancer cells. We hypothesized that informative marker sets can be obtained by combining genes with a relatively low degree of individual differential expression. We developed a method for construction of highly informative gene combinations aimed at the maximization of the cumulative informative power and identified sets of 2–5 genes efficiently predicting recurrence for ER-positive breast cancer patients. The gene combinations constructed on the basis of microarray data were successfully applied to data acquired by RNA-seq. The developed method provides the basis for the generation of highly efficient prognostic and predictive gene signatures for cancer and other diseases. The identified gene sets can potentially reveal novel essential segments of gene interaction networks and pathways implied in cancer progression.
We propose a new mathematical growth model of primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer process using an original mathematical model referred to CoM-IV and corresponding software. The CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of patient survival; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimisation of diagnostic tests. The CoM-IV enables us, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) considering only on primary tumor sizes. Summarising: CoM-IV a) describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.
PRIMARY THERAPY OF EARLY BREAST CANCER
Evidence, Controversies, Consensus
This paper is devoted to mathematical modelling of the progression and stages of breast cancer. The Consolidated mathematical growth Model of primary tumor (PT) and secondary distant metastases (MTS) in patients with lymph nodes MTS (Stage III) (CoM-III) is proposed as a new research tool. The CoM-III rests on an exponential tumor growth model and consists of a system of determinate nonlinear and linear equations. The CoM-III describes correctly primary tumor growth (parameter T) and distant metastases growth (parameter M, parameter N). The CoM-III model and predictive software: a) detect di erent growth periods of primary tumor and distant metastases in patients with lymph nodes MTS; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes MTS; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimisation of diagnostic tests. The CoM-III enables us, for the rst time, to predict the whole natural history of PT and secondary distant MTS growth of patients with/without lymph nodes MTS on each stage relying only on PT sizes.
Inflammatory breast cancer (IBC) is an extremely malignant form of breast cancer which can be easily misdiagnosed. Conclusive prognostic IBC molecular biomarkers which are also providing the perspectives for targeted therapy are lacking so far. The aim of this study was to reveal the IBC-specific miRNA expression profile and to evaluate its association with clinicopathological parameters.
miRNA expression profiles of 13 IBC and 17 non-IBC patients were characterized using comprehensive Affymetrix GeneChip miRNA 3.0 microarray platform. Bioinformatic analysis was used to reveal IBC-specific miRNAs, deregulated pathways and potential miRNA targets.
31 differentially expressed miRNAs characterize IBC and mRNAs regulated by them and their associated pathways can functionally be attributed to IBC progression. In addition, a minimal predictive set of 4 miRNAs characteristic for the IBC phenotype and associated with the TP53 mutational status in breast cancer patients was identified.
We have characterized the complete miRNome of inflammatory breast cancer and found differentially expressed miRNAs which reliably classify the patients to IBC and non-IBC groups. We found that the mRNAs and pathways likely regulated by these miRNAs are highly relevant to cancer progression. Furthermore a minimal IBC-related predictive set of 4 miRNAs associated with the TP53 mutational status and survival for breast cancer patients was identified.
This book presents the results of analysis of human capital in Murmansk and Archangelsk regions, republics of Komi and Karelia, and Nenets Autonomous Region. The authors considered migration processes and their trends; some of these were analyzed at municipal level. Having taken in account the importance of life expectancy as a complex indicator of sustainable development, the authors identified the periods of its growth and decline. Age-specific differences were also scrutinized. The relative contributions of major causes of mortality in life expectancy at birth were estimated. The authors described the dynamics of population of small indigenous peoples of the North (Vepsians, Nenets, Komi), the problems associated with their self-identification, census administration, migration, childbirth and life expectancy. The authors analyzed climate change as the new health risk factor, which affects safety of food and drinking water, accessibility of medical services and specific practices of deer-herding. A separate chapter of the book is devoted to current and future trends in working-age population until 2002. Each territory of Barents Sea Region displayed its own peculiar behavior of this indicator. The authors compared selected social, economic and demographic indicators in European part of Russian Arctic with those in foreign countries which belong to Barents Sea Region. This monograph was a product of collaborative efforts of the researchers from Economic Forecasting Institute and Institute of Demography of Higher School of Economics. B. A. Revich, Doctor of Medicine, and B. N. Porfiryev, Corresponding Member of Russian Academy of Sciences, edited this book.
This prototype development explains the challenges encountered during the ISO/IEEE 11073 standard implementation process. The complexity of the standard and the consequent heavy requirements, which have not encouraged software engineers to adopt the standard. The developing complexity evaluation drives us to propose two possible implementation strategies that cover almost all possible use cases and eases handling the standard by non-expert users. The first one is focused on medical devices (MD) and proposes a low-memory and low-processor usage technique. It is based on message patterns that allow simple functions to generate ISO/IEEE 11073 messages and to process them easily. MD act as X73 agent. Second one is focused on more powerful device X73 manager, which do not have the MDs' memory and processor usage constraints. The protocol between Agent and Manager is point-to-point and we can distribute the functionality between devices.
Developed both implementation X73 Agent and Manager will cut developing time for applications based on ISO/EEE 11073.
In the internal medicine wide spectrum the gastroenterology is one of the chapters, less enlightened by the scientific evidence. It does not mean that the practice of the grasntroenterology may ot be improved by the systematic use of the approaches of the evidence based medicine