Discovery of new therapeutic targets in ovarian cancer through identifying significantly non-mutated genes

Multi-organ transcriptome atlas of a mouse model of relative energy deficiency in sport

Insufficient energy intake to meet energy expenditure demands of physical activity can result in systemic neuroendocrine and metabolic abnormalities in activity-dependent anorexia and relative energy deficiency in sport (REDs). REDs affects >40% of athletes, yet the lack of underlying molecular changes has been a hurdle to have a better understanding of REDs and its treatment. To assess the molecular changes in response to energy deficiency, we implemented the "exercise-for-food" paradigm, in which food reward size is determined by wheel-running activity. By using this paradigm, we replicated several aspects of REDs in female and male mice with high physical activity and gradually reduced food intake, which results in weight loss, compromised bone health, organ-specific mass changes, and altered rest-activity patterns. By integrating transcriptomics of 19 different organs, we provide a comprehensive dataset that will guide future understanding of REDs and may provide important implications for metabolic health and (athletic) performance.

Molecular functions of ANKLE2 and its implications in human disease

Ankyrin repeat and LEM domain-containing 2 (ANKLE2) is a scaffolding protein with established roles in cell division and development, the dysfunction of which is increasingly implicated in human disease. ANKLE2 regulates nuclear envelope disassembly at the onset of mitosis and its reassembly after chromosome segregation. ANKLE2 dysfunction is associated with abnormal nuclear morphology and cell division. It regulates the nuclear envelope by mediating protein-protein interactions with barrier to autointegration factor (BANF1; also known as BAF) and with the kinase and phosphatase that modulate the phosphorylation state of BAF. In brain development, ANKLE2 is crucial for proper asymmetric division of neural progenitor cells. In humans, pathogenic loss-of-function mutations in ANKLE2 are associated with primary congenital microcephaly, a condition in which the brain is not properly developed at birth. ANKLE2 is also linked to other disease pathologies, including congenital Zika syndrome, cancer and tauopathy. Here, we review the molecular roles of ANKLE2 and the recent literature on human diseases caused by its dysfunction.

Signatures of tumor-associated macrophages correlate with treatment response in ovarian cancer patients

Ovarian cancer (OC) ranks as the second leading cause of death among gynecological cancers. Numerous studies have indicated a correlation between the tumor microenvironment (TME) and the clinical response to treatment in OC patients. Tumor-associated macrophages (TAMs), a crucial component of the TME, exert influence on invasion, metastasis, and recurrence in OC patients. To delve deeper into the role of TAMs in OC, this study conducted an extensive analysis of single-cell data from OC patients. The aim is to develop a new risk score (RS) to characterize the response to treatment in OC patients to inform clinical treatment. We first identified TAM-associated genes (TAMGs) in OC patients and examined the protein and mRNA expression levels of TAMGs by Western blot and PCR experiments. Additionally, a scoring system for TAMGs was constructed, successfully categorizing patients into high and low RS subgroups. Remarkably, significant disparities were observed in immune cell infiltration and immunotherapy response between the high and low RS subgroups. The findings revealed that patients in the high RS group had a poorer prognosis but displayed greater sensitivity to immunotherapy. Another important finding was that patients in the high RS subgroup had a higher IC50 for chemotherapeutic agents. Furthermore, further experimental investigations led to the discovery that THEMIS2 could serve as a potential target in OC patients and is associated with EMT (epithelial-mesenchymal transition). Overall, the TAMGs-based scoring system holds promise for screening patients who would benefit from therapy and provides valuable information for the clinical treatment of OC.

A Strategy Utilizing Protein-Protein Interaction Hubs for the Treatment of Cancer Diseases

We describe a strategy for the development of a rational approach of neoplastic disease therapy based on the demonstration that scale-free networks are susceptible to specific attacks directed against its connective hubs. This strategy involves the (i) selection of up-regulated hubs of connectivity in the tumors interactome, (ii) drug repurposing of these hubs, (iii) RNA silencing of non-druggable hubs, (iv) in vitro hub validation, (v) tumor-on-a-chip, (vi) in vivo validation, and (vii) clinical trial. Hubs are protein targets that are assessed as targets for rational therapy of cancer in the context of personalized oncology. We confirmed the existence of a negative correlation between malignant cell aggressivity and the target number needed for specific drugs or RNA interference (RNAi) to maximize the benefit to the patient's overall survival. Interestingly, we found that some additional proteins not generally targeted by drug treatments might justify the addition of inhibitors designed against them in order to improve therapeutic outcomes. However, many proteins are not druggable, or the available pharmacopeia for these targets is limited, which justifies a therapy based on encapsulated RNAi.

Discovery and ranking of the most robust prognostic biomarkers in serous ovarian cancer

Progress in ovarian cancer treatment lags behind other tumor types. With diagnosis usually at an advanced stage, there is a high demand for reliable prognostic biomarkers capable of the selection of effective chemo- and targeted therapies. Our goal was to establish a large-scale transcriptomic database and use it to uncover and rank survival-associated genes. Ovarian cancer cohorts with transcriptome-level gene expression data and clinical follow-up were identified from public repositories. All samples were normalized and entered into an integrated database. Cox univariate survival analysis was performed for all genes and was followed by multivariate analysis for selected genes involving clinical and pathological variables. False discovery rate was computed for multiple hypothesis testing and a 1% cutoff was used to determine statistical significance. The complete integrated database comprises 1816 samples from 17 datasets. Altogether, 2468 genes were correlated to progression-free survival (PFS), and 704 genes were correlated with overall survival (OS). The most significant genes were WBP1L, ASAP3, CNNM2, and NCAPH2 for progression-free survival and CSE1L, NUAK1, ALPK2, and SHKBP1 for overall survival. Genes significant for PFS were also preferentially significant for predicting OS as well. All data including HR and p values as well as the used cutoff values for all genes for both PFS and OS are provided to enable the ranking of future biomarker candidates across all genes. Our results help to prioritize genes and to neglect those which are most likely to fail in studies aiming to establish new clinically useful biomarkers and therapeutic targets in serous ovarian cancer.