Influence of pathogenetic factors of type 2 diabetes on activation of PI3K/AkT/mTOR pathway and on the development of endometrial and breast cancer

Insulin Resistance: The Increased Risk of Cancers

Insulin resistance, also known as impaired insulin sensitivity, is the result of a decreased reaction of insulin signaling to blood glucose levels. This state is observed when muscle cells, adipose tissue, and liver cells, improperly respond to a particular concentration of insulin. Insulin resistance and related increased plasma insulin levels (hyperinsulinemia) may cause metabolic impairments, which are pathological states observed in obesity and type 2 diabetes mellitus. Observations of cancer patients confirm that hyperinsulinemia is a major factor influencing obesity, type 2 diabetes, and cancer. Obesity and diabetes have been reported as risks of the initiation, progression, and metastasis of several cancers. However, both of the aforementioned pathologies may independently and additionally increase the cancer risk. The state of metabolic disorders observed in cancer patients is associated with poor outcomes of cancer treatment. For example, patients suffering from metabolic disorders have higher cancer recurrence rates and their overall survival is reduced. In these associations between insulin resistance and cancer risk, an overview of the various pathogenic mechanisms that play a role in the development of cancer is discussed.

Updates on Triple-Negative Breast Cancer in Type 2 Diabetes Mellitus Patients: From Risk Factors to Diagnosis, Biomarkers and Therapy

Triple-negative breast cancer (TNBC) is usually the most malignant and aggressive mammary epithelial tumor characterized by the lack of expression for estrogen receptors and progesterone receptors, and the absence of epidermal growth factor receptor (HER)2 amplification. Corresponding to 15-20% of all breast cancers and well-known by its poor clinical outcome, this negative receptor expression deprives TNBC from targeted therapy and makes its management therapeutically challenging. Type 2 diabetes mellitus (T2DM) is the most common ageing metabolic disorder due to insulin deficiency or resistance resulting in hyperglycemia, hyperinsulinemia, and hyperlipidemia. Due to metabolic and hormonal imbalances, there are many interplays between both chronic disorders leading to increased risk of breast cancer, especially TNBC, diagnosed in T2DM patients. The purpose of this review is to provide up-to-date information related to epidemiology and clinicopathological features, risk factors, diagnosis, biomarkers, and current therapy/clinical trials for TNBC patients with T2DM compared to non-diabetic counterparts. Thus, in-depth investigation of the diabetic complications on TNBC onset, development, and progression and the discovery of biomarkers would improve TNBC management through early diagnosis, tailoring therapy for a better outcome of T2DM patients diagnosed with TNBC.

Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning

Alternative splicing introduces an additional layer of protein diversity and complexity in regulating cellular functions that can be specific to the tissue and cell type, physiological state of a cell, or disease phenotype. Recent high-throughput experimental studies have illuminated the functional role of splicing events through rewiring protein-protein interactions; however, the extent to which the macromolecular interactions are affected by alternative splicing has yet to be fully understood. In silico methods provide a fast and cheap alternative to interrogating functional characteristics of thousands of alternatively spliced isoforms. Here, we develop an accurate feature-based machine learning approach that predicts whether a protein-protein interaction carried out by a reference isoform is perturbed by an alternatively spliced isoform. Our method, called the alternatively spliced interactions prediction (ALT-IN) tool, is compared with the state-of-the-art PPI prediction tools and shows superior performance, achieving 0.92 in precision and recall values.