Modeling glands with PTEN deficient cells and microscopic methods for assessing PTEN loss: endometrial cancer as a model

Nanocarrier-based targeting of metabolic pathways for endometrial cancer: Status and future perspectives

Cancer is the second-most lethal global disease, as per health reports, and is responsible for around 70% of deaths in low- and middle-income countries. Endometrial cancer is one of the emerging malignancies and has been predicted as a public health challenge for the future. Insulin resistance, obesity, and diabetes mellitus are the key metabolic factors that promote risks for the development of endometrial cancer. Various signaling pathways and associated genes are involved in the genesis of endometrial cancer, and any mutation or deletion in such related factors leads to the induction of endometrial cancer. The conventional way of drug delivery has been used for ages but is associated with poor management of cancer due to non-targeting of the endometrial cancer cells, low efficacy of the therapy, and toxicity issues as well. In this context, nanocarrier-based therapy for the management of endometrial cancer is an effective alternate choice that overcomes the problems associated with conventional therapy. In this review article, we highlighted the nanocarrier-based targeting of endometrial cancer, with a special focus on targeting various metabolic signaling pathways. Furthermore, the future perspectives of nanocarrier-based targeting of metabolic pathways in endometrial cancer were also underpinned. It is concluded that targeting metabolic signaling pathways in endometrial cancer via nanocarrier scaffolds is the future of pharmaceutical design for the significant management and treatment of endometrial cancer.

Development of adverse outcome pathways relevant for the identification of substances having endocrine disruption properties Uterine adenocarcinoma as adverse outcome

Development of adverse outcome pathways (AOPs) for uterine adenocarcinoma can provide a practical tool to implement the EFSA-ECHA Guidance (2018) for the identification of endocrine disruptors in the context of Regulations (EU) No 528/2012 and (EC) No 1107/2009. AOPs can give indications about the strength of the relationship between an adverse outcome (intended as a human health outcome) and chemicals (pesticides but not only) affecting the pathways. In this scientific opinion, the PPR Panel explored the development of AOPs for uterine adenocarcinoma. An evidence-based approach methodology was applied, and literature reviews were produced using a structured framework assuring transparency, objectivity, and comprehensiveness. Several AOPs were developed; these converged to a common critical node, that is increased estradiol availability in the uterus followed by estrogen receptor activation in the endometrium; therefore, a putative AOP network was considered. An uncertainty analysis and a probabilistic quantification of the weight of evidence have been carried out via expert knowledge elicitation for each set of MIEs/KEs/KERs included in individual AOPs. The collected data on the AOP network were evaluated qualitatively, whereas a quantitative uncertainty analysis for weight of the AOP network certainty has not been performed. Recommendations are provided, including exploring further the uncertainties identified in the AOPs and putative AOP network; further methodological developments for quantifying the certainty of the KERs and of the overall AOPs and AOP network; and investigating of NAMs applications in the context of some of the MIEs/KEs currently part of the putative AOP network developed.

MSF-UBRW: An Improved Unbalanced Bi-Random Walk Method to Infer Human lncRNA-Disease Associations

Long-non-coding RNA (lncRNA) is a transcription product that exerts its biological functions through a variety of mechanisms. The occurrence and development of a series of human diseases are closely related to abnormal expression levels of lncRNAs. Scientists have developed many computational models to identify the lncRNA-disease associations (LDAs). However, many potential LDAs are still unknown. In this paper, a novel method, namely MSF-UBRW (multiple similarities fusion based on unbalanced bi-random walk), is designed to explore new LDAs. First, two similarities (functional similarity and Gaussian Interaction Profile kernel similarity) of lncRNAs are calculated and fused linearly, also for disease data. Then, the known association matrix is preprocessed. Next, the linear neighbor similarities of lncRNAs and diseases are calculated, respectively. After that, the potential associations are predicted based on unbalanced bi-random walk. The fusion of multiple similarities improves the prediction performance of MSF-UBRW to a large extent. Finally, the prediction ability of the MSF-UBRW algorithm is measured by two statistical methods, leave-one-out cross-validation (LOOCV) and 5-fold cross-validation (5-fold CV). The AUCs of 0.9391 in LOOCV and 0.9183 (±0.0054) in 5-fold CV confirmed the reliable prediction ability of the MSF-UBRW method. Case studies of three common diseases also show that the MSF-UBRW method can infer new LDAs effectively.

Precise Immunodetection of PTEN Protein in Human Neoplasia

PTEN is a major tumor-suppressor protein whose expression and biological activity are frequently diminished in sporadic or inherited cancers. PTEN gene deletion or loss-of-function mutations favor tumor cell growth and are commonly found in clinical practice. In addition, diminished PTEN protein expression is also frequently observed in tumor samples from cancer patients in the absence of PTEN gene alterations. This makes PTEN protein levels a potential biomarker parameter in clinical oncology, which can guide therapeutic decisions. The specific detection of PTEN protein can be achieved by using highly defined anti-PTEN monoclonal antibodies (mAbs), characterized with precision in terms of sensitivity for the detection technique, specificity for PTEN binding, and constraints of epitope recognition. This is especially relevant taking into consideration that PTEN is highly targeted by mutations and posttranslational modifications, and different PTEN protein isoforms exist. The precise characterization of anti-PTEN mAb reactivity is an important step in the validation of these reagents as diagnostic and prognostic tools in clinical oncology, including their routine use in analytical immunohistochemistry (IHC). Here, we review the current status on the use of well-defined anti-PTEN mAbs for PTEN immunodetection in the clinical context and discuss their potential usefulness and limitations for a more precise cancer diagnosis and patient benefit.

Precise definition of PTEN C-terminal epitopes and its implications in clinical oncology

Anti-PTEN monoclonal antibodies (mAb) are arising as important tools for immunohistochemistry (IHC) and protein quantification routine analysis in clinical oncology. Although an effort has been made to document the reliability of tumor tissue section immunostaining by anti-PTEN mAb, and to standardize their IHC use in research and in the clinical practice, the precise topological and biochemical definition of the epitope recognized by each mAb has been conventionally overlooked. In this study, six commercial anti-PTEN mAb have been validated and characterized for sensitivity and specificity by IHC and FISH, using a set of prostate and urothelial bladder tumor specimens, and by immunoblot, using PTEN positive and PTEN negative human cell lines. Immunoblot precise epitope mapping, performed using recombinant PTEN variants and mutations, revealed that all mAb recognized linear epitopes of 6–11 amino acid length at the PTEN C-terminus. Tumor-associated or disease-associated mutations at the PTEN C-terminus did not affect subcellular localization or PIP3 phosphatase activity of PTEN in cells, although resulted in specific loss of reactivity for some mAb. Furthermore, specific mimicking-phosphorylation mutations at the PTEN C-terminal region also abolished binding of specific mAb. Our study adds new evidence on the relevance of a precise epitope mapping in the validation of anti-PTEN mAb for their use in the clinics. This will be substantial to provide a more accurate diagnosis in clinical oncology based on PTEN protein expression in tumors and biological fluids.

Modeling Endometrial Cancer: Past, Present, and Future

Endometrial cancer is the most common type of cancer of the female reproductive tract. Although prognosis is generally good for patients with low-grade and early-stage diseases, the outcomes for high-grade and metastatic/recurrent cases remain poor, since traditional chemotherapy regimens based on platinum and taxanes have limited effects. No targeted agents have been approved so far, although several new drugs have been tested without striking results in clinical trials. Over the last decades, many efforts have been made towards the establishment and development of preclinical models, aiming at recapitulating the structural and molecular determinants of the disease. Here, we present an overview of the most commonly used in vitro and in vivo models and discuss their peculiar features, describing their main applications and the value in the advancement of both fundamental and translational endometrial cancer research.

Endometrial Carcinoma: Specific Targeted Pathways

Endometrial cancer (EC) is the most common gynecologic malignancy in the western world with more than 280,000 cases per year worldwide. Prognosis for EC at early stages, when primary surgical resection is the most common initial treatment, is excellent. Five-year survival rate is around 70 %.Several molecular alterations have been described in the different types of EC. They occur in genes involved in important signaling pathways. In this chapter, we will review the most relevant altered pathways in EC, including PI3K/AKT/mTOR, RAS-RAF-MEK-ERK, Tyrosine kinase, WNT/β-Catenin, cell cycle, and TGF-β signaling pathways. At the end of the chapter, the most significant clinical trials will be briefly discussed.This information is important to identify specific targets for therapy.

Role of MicroRNAs in carcinogenesis that potential for biomarker of endometrial cancer

The non-invasive diagnostic tool for early detection of endometrial cancer still limited. The etiology of this disease is believed to be associated with disharmony hormone production. One predominant factor that regulate hormone production is microRNA (miRNAs). Some studies reported that miRNAs play a significant role in the process carcinogenesis. We have identified 12 of miRNAs that potentially have a role in controlling endometrial carcinogenesis pathways. Further analysis suggested that these miRNA targeted genes that regulate the early development of endometrial cancer. These genes cluster into several functional groups involving a process of angiogenesis, apoptosis, cell cycle, cell proliferation and p53 pathways. Some of the genes are PTEN, GSK3b, and TP53, which are a tumor suppressor that control the process of growth arrest, DNA Repair, and Apoptosis. Upregulation of the miRNA may obstruct the cell ability to control the cell cycle. This study was found three miRNA that plays a role in the development of endometrial cancer. The hsa-miR-495 and hsa-miR-152 were repressed in endometrial cancer compared to normal tissue. The microRNA regulate genes that control proliferation and cell survival. Moreover, hsa-miR-181d was upregulated to control expression a tumor suppressor gene, PTEN to protect the cancer cell from apoptosis. Further investigation to validate the function of the miRNA is a warrant for developing biomarkers of endometrial carcinoma.

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Three miRNA may controlled genes that regulate early development of endometrial cancer.

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PTEN is central gene of endometrial cancer that targeted by the miRNA.

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The miRNA and PTEN are potential for a biomarker of early detection of endometrial cancer.