Circulating hsa-miR-5096 predicts 18F-FDG PET/CT positivity and modulates somatostatin receptor 2 expression: a novel miR-based assay for pancreatic neuroendocrine tumors

Circulating non-coding RNA biomarkers of endocrine tumours

Circulating non-coding RNA (ncRNA) molecules are being investigated as biomarkers of malignancy, prognosis and follow-up in several neoplasms, including endocrine tumours of the pituitary, parathyroid, pancreas and adrenal glands. Most of these tumours are classified as neuroendocrine neoplasms (comprised of neuroendocrine tumours and neuroendocrine carcinomas) and include tumours of variable aggressivity. We consider them together here in this Review owing to similarities in their clinical presentation, pathomechanism and genetic background. No preoperative biomarkers of malignancy are available for several forms of these endocrine tumours. Moreover, biomarkers are also needed for the follow-up of tumour progression (especially in hormonally inactive tumours), prognosis and treatment efficacy monitoring. Circulating blood-borne ncRNAs show promising utility as biomarkers. These ncRNAs, including microRNAs, long non-coding RNAs and circular RNAs, are involved in several aspects of gene expression regulation, and their stability and tissue-specific expression could make them ideal biomarkers. However, no circulating ncRNA biomarkers have yet been introduced into routine clinical practice, which is mostly owing to methodological and standardization problems. In this Review, following a brief synopsis of these endocrine tumours and the biology of ncRNAs, the major research findings, pathomechanisms and methodological questions are discussed along with an outlook for future studies.

Elucidating sleep disorders: a comprehensive bioinformatics analysis of functional gene sets and hub genes

Background

Sleep disorders (SD) are known to have a profound impact on human health and quality of life although their exact pathogenic mechanisms remain poorly understood.

Methods

The study first accessed SD datasets from the GEO and identified DEGs. These DEGs were then subjected to gene set enrichment analysis. Several advanced techniques, including the RF, SVM-RFE, PPI networks, and LASSO methodologies, were utilized to identify hub genes closely associated with SD. Additionally, the ssGSEA approach was employed to analyze immune cell infiltration and functional gene set scores in SD. DEGs were also scrutinized in relation to miRNA, and the DGIdb database was used to explore potential pharmacological treatments for SD. Furthermore, in an SD murine model, the expression levels of these hub genes were confirmed through RT-qPCR and Western Blot analyses.

Results

The findings of the study indicate that DEGs are significantly enriched in functions and pathways related to immune cell activity, stress response, and neural system regulation. The analysis of immunoinfiltration demonstrated a marked elevation in the levels of Activated CD4+ T cells and CD8+ T cells in the SD cohort, accompanied by a notable rise in Central memory CD4 T cells, Central memory CD8 T cells, and Natural killer T cells. Using machine learning algorithms, the study also identified hub genes closely associated with SD, including IPO9, RAP2A, DDX17, MBNL2, PIK3AP1, and ZNF385A. Based on these genes, an SD diagnostic model was constructed and its efficacy validated across multiple datasets. In the SD murine model, the mRNA and protein expressions of these 6 hub genes were found to be consistent with the results of the bioinformatics analysis.

Conclusion

In conclusion, this study identified 6 genes closely linked to SD, which may play pivotal roles in neural system development, the immune microenvironment, and inflammatory responses. Additionally, the key gene-based SD diagnostic model constructed in this study, validated on multiple datasets showed a high degree of reliability and accuracy, predicting its wide potential for clinical applications. However, limited by the range of data sources and sample size, this may affect the generalizability of the results.

Two-dimensional segmentation fusion tool: an extensible, free-to-use, user-friendly tool for combining different bidimensional segmentations

Introduction: In several fields, the process of fusing multiple two-dimensional (2D) closed lines is an important step. For instance, this is fundamental in histology and oncology in general. The treatment of a tumor consists of numerous steps and activities. Among them, segmenting the cancer area, that is, the correct identification of its spatial location by the segmentation technique, is one of the most important and at the same time complex and delicate steps. The difficulty in deriving reliable segmentations stems from the lack of a standard for identifying the edges and surrounding tissues of the tumor area. For this reason, the entire process is affected by considerable subjectivity. Given a tumor image, different practitioners can associate different segmentations with it, and the diagnoses produced may differ. Moreover, experimental data show that the analysis of the same area by the same physician at two separate timepoints may result in different lines being produced. Accordingly, it is challenging to establish which contour line is the ground truth. Methods: Starting from multiple segmentations related to the same tumor, statistical metrics and computational procedures could be exploited to combine them for determining the most reliable contour line. In particular, numerous algorithms have been developed over time for this procedure, but none of them is validated yet. Accordingly, in this field, there is no ground truth, and research is still active. Results: In this work, we developed the Two-Dimensional Segmentation Fusion Tool (TDSFT), a user-friendly tool distributed as a free-to-use standalone application for MAC, Linux, and Windows, which offers a simple and extensible interface where numerous algorithms are proposed to "compute the mean" (i.e., the process to fuse, combine, and "average") multiple 2D lines. Conclusions: The TDSFT can support medical specialists, but it can also be used in other fields where it is required to combine 2D close lines. In addition, the TDSFT is designed to be easily extended with new algorithms thanks to a dedicated graphical interface for configuring new parameters. The TDSFT can be downloaded from the following link: https://sourceforge.net/p/tdsft.

The Quest for Circulating Biomarkers in Neuroendocrine Neoplasms: a Clinical Perspective

OPINION STATEMENT

Given the considerable heterogeneity in neuroendocrine neoplasms (NENs), it appears unlikely that a sole biomarker exists capable of fully capturing all useful clinical aspects of these tumors. This is reflected in the abundant number of biomarkers presently available for the diagnosis, prognosis, and monitoring of NEN patients. Although assessment of immunohistochemical and radiological markers remains paramount and often obligatory, there has been a notable surge of interest in circulating biomarkers over the years given the numerous benefits associated with liquid biopsies. Currently, the clinic primarily relies on single-analyte assays such as the chromogranin A assay, but these are far from ideal because of limitations such as compromised sensitivity and specificity as well as a lack of standardization. Consequently, the quest for NEN biomarkers continued with the exploration of multianalyte markers, exemplified by the development of the NETest and ctDNA-based analysis. Here, an extensive panel of markers is simultaneously evaluated to identify distinct signatures that could enhance the accuracy of patient diagnosis, prognosis determination, and response to therapy prediction and monitoring. Given the promising results, the development and implementation of these multianalyte markers are expected to usher in a new era of NEN biomarkers in the clinic. In this review, we will outline both clinically implemented and more experimental circulating markers to provide an update on developments in this rapidly evolving field.

Dual mechanism of Let-7i in tumor progression

Let-7i regulates tumors primarily by binding to the 3' untranslated region (3' UTR) of mRNA, which indirectly regulates post-transcriptional gene expression. Let-7i also has an epigenetic function via modulating DNA methylation to directly regulate gene expression. Let-7i performs a dual role by inducing both the promotion and inhibition of various malignancies, depending on its target. The mechanism of Let-7i action involves cancer cell proliferation, migration, invasion, apoptosis, epithelial-mesenchymal transition, EV transmission, angiogenesis, autophagy, and drug resistance sensitization. Let-7i is closely related to cancer, and hence, is a potential biomarker for the diagnosis and prognosis of various cancers. Therapeutically, it can be used to promote an anti-cancer immune response by modifying exosomes, thus exerting a tumor-suppressive effect.