Downregulation of Serotonergic System Components in an Experimentally Induced Cryptorchidism in Rabbits.

Cryptorchidism (CO) or undescended testes is defined as the failure of one or both testes to be positioned inside the scrotum. Typically, cryptorchidism is detected at birth or shortly thereafter, and in humans, it is considered to be part of the testicular dysgenesis syndrome (TDS), a complex pathology regarding the male reproductive system that apparently involves the interaction of both genetic and environmental harmful factors, mainly during embryonic development. Serotonin (5-HT) is an ancient molecule that participates in a broad range of body functions, and in recent years, its importance in reproduction has started to be elucidated. In male pathologies such as infertility, varicocele, erectile dysfunction, and primary carcinoid tumors, an increase in 5-HT concentration or its metabolites in the blood, semen, and urine has been directly related; nevertheless, the role of 5-HT in CO remains unknown. In the present work, our goal was to answer two important questions: (1) whether some serotonergic system components are present in adult male Oryctolagus cuniculus (chinchilla rabbit) and (2) if there are changes in their expression in an experimental model of CO. Using histological, molecular, and biochemical approaches, we found the presence of some serotonergic system components in the adult chinchilla rabbit, and we demonstrated that its expression is downregulated after CO was pharmacologically induced. Although we did not test the role of 5-HT in the etiology of CO, our results suggest that this indoleamine could be important for the regulation of steroidogenesis and spermatogenesis processes in the chinchilla rabbit during adulthood. Finally, in parallel experimental series, we found downregulation of kynurenine concentration in COI rabbits when compared to control ones, suggesting that CO could be affecting the kynurenine pathway and probably testicular immune privilege which in turn could lead to infertility/sterility conditions in this disorder.

Antisense Oligonucleotides as a Tool for Prolonged Knockdown of Nuclear lncRNAs in Human Cell Lines.

Long noncoding RNAs (lncRNAs) play key regulatory roles in gene expression at the transcriptional level. Experimental evidence has established that a substantial fraction of lncRNA preferentially accumulates in the nucleus. For analysis of the function of nuclear lncRNAs, it is important to achieve efficient knockdown of these transcripts inside the nucleus. In contrast to the use of RNA interference, a technology that depends on the cytoplasmic silencing machinery, an antisense oligonucleotide (ASO) technology can achieve RNA knockdown by recruiting RNase H to the RNA-DNA duplexes for nuclear RNA cleavage. Unlike the use of CRISPR-Cas tools for genome engineering, where possible alterations in the chromatin state can occur, ASOs allow the efficient knockdown of nuclear transcripts without modifying the genome. Nevertheless, one of the major obstacles to ASO-mediated knockdown is its transitory effect. For the study of long-lasting effects of lncRNA silencing, maintaining efficient knockdown for a long time is needed. In this study, a protocol was developed to achieve a knockdown effect for over 21 days. The purpose was to evaluate the cis-regulatory effects of lncRNA knockdown on the adjacent coding gene RFC4, which is related to chromosomal instability, a condition that is observed only through time and cell aging. Two different human cell lines were used: PrEC, normal primary prostate epithelial cells, and HCT116, an epithelial cell line isolated from colorectal carcinoma, achieving successful knockdown in the assayed cell lines.

Transcriptomics and RNA-Based Therapeutics as Potential Approaches to Manage SARS-CoV-2 Infection.

SARS-CoV-2 is a coronavirus family member that appeared in China in December 2019 and caused the disease called COVID-19, which was declared a pandemic in 2020 by the World Health Organization. In recent months, great efforts have been made in the field of basic and clinical research to understand the biology and infection processes of SARS-CoV-2. In particular, transcriptome analysis has contributed to generating new knowledge of the viral sequences and intracellular signaling pathways that regulate the infection and pathogenesis of SARS-CoV-2, generating new information about its biology. Furthermore, transcriptomics approaches including spatial transcriptomics, single-cell transcriptomics and direct RNA sequencing have been used for clinical applications in monitoring, detection, diagnosis, and treatment to generate new clinical predictive models for SARS-CoV-2. Consequently, RNA-based therapeutics and their relationship with SARS-CoV-2 have emerged as promising strategies to battle the SARS-CoV-2 pandemic with the assistance of novel approaches such as CRISPR-CAS, ASOs, and siRNA systems. Lastly, we discuss the importance of precision public health in the management of patients infected with SARS-CoV-2 and establish that the fusion of transcriptomics, RNA-based therapeutics, and precision public health will allow a linkage for developing health systems that facilitate the acquisition of relevant clinical strategies for rapid decision making to assist in the management and treatment of the SARS-CoV-2-infected population to combat this global public health problem.

The promising role of new molecular biomarkers in prostate cancer: from coding and non-coding genes to artificial intelligence approaches.

BACKGROUND: Risk stratification or progression in prostate cancer is performed with the support of clinical-pathological data such as the sum of the Gleason score and serum levels PSA. For several decades, methods aimed at the early detection of prostate cancer have included the determination of PSA serum levels. The aim of this systematic review is to provide an overview about recent advances in the discovery of new molecular biomarkers through transcriptomics, genomics and artificial intelligence that are expected to improve clinical management of the prostate cancer patient. METHODS: An exhaustive search was conducted by Pubmed, Google Scholar and Connected Papers using keywords relating to the genetics, genomics and artificial intelligence in prostate cancer, it includes "biomarkers", "non-coding RNAs", "lncRNAs", "microRNAs", "repetitive sequence", "prognosis", "prediction", "whole-genome sequencing", "RNA-Seq", "transcriptome", "machine learning", and "deep learning". RESULTS: New advances, including the search for changes in novel biomarkers such as mRNAs, microRNAs, lncRNAs, and repetitive sequences, are expected to contribute to an earlier and accurate diagnosis for each patient in the context of precision medicine, thus improving the prognosis and quality of life of patients. We analyze several aspects that are relevant for prostate cancer including its new molecular markers associated with diagnosis, prognosis, and prediction to therapy and how bioinformatic approaches such as machine learning and deep learning can contribute to clinic. Furthermore, we also include current techniques that will allow an earlier diagnosis, such as Spatial Transcriptomics, Exome Sequencing, and Whole-Genome Sequencing. CONCLUSION: Transcriptomic and genomic analysis have contributed to generate knowledge in the field of prostate carcinogenesis, new information about coding and non-coding genes as biomarkers has emerged. Synergies created by the implementation of artificial intelligence to analyze and understand sequencing data have allowed the development of clinical strategies that facilitate decision-making and improve personalized management in prostate cancer.

Transcriptome Analysis Identifies GATA3-AS1 as a Long Noncoding RNA Associated with Resistance to Neoadjuvant Chemotherapy in Locally Advanced Breast Cancer Patients.

Breast cancer is one of the leading causes of mortality in women worldwide, and neoadjuvant chemotherapy has emerged as an option for the management of locally advanced breast cancer. Extensive efforts have been made to identify new molecular markers to predict the response to neoadjuvant chemotherapy. Transcripts that do not encode proteins, termed long noncoding RNAs (lncRNAs), have been shown to display abnormal expression profiles in different types of cancer, but their role as biomarkers in response to neoadjuvant chemotherapy has not been extensively studied. Herein, lncRNA expression was profiled using RNA sequencing in biopsies from patients who subsequently showed either response or no response to treatment. GATA3-AS1 was overexpressed in the nonresponder group and was the most stable feature when performing selection in multiple random forest models. GATA3-AS1 was experimentally validated by quantitative RT-PCR in an extended group of 68 patients. Expression analysis confirmed that GATA3-AS1 is overexpressed primarily in patients who were nonresponsive to neoadjuvant chemotherapy, with a sensitivity of 92.9% and a specificity of 75.0%. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74-208.42; P = 0.001); GATA3-AS1 was established as an independent predictor of response. Thus, lncRNA GATA3-AS1 is proposed as a potential predictive biomarker of nonresponse to neoadjuvant chemotherapy.

Saliva is a reliable and accessible source for the detection of SARS-CoV-2.

OBJECTIVES: The aim of this study was to investigate the feasibility of saliva sampling as a non-invasive and safer tool to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and to compare its reproducibility and sensitivity with nasopharyngeal swab samples (NPS). The use of sample pools was also investigated. METHODS: A total of 2107 paired samples were collected from asymptomatic healthcare and office workers in Mexico City. Sixty of these samples were also analyzed in two other independent laboratories for concordance analysis. Sample processing and analysis of virus genetic material were performed according to standard protocols described elsewhere. A pooling analysis was performed by analyzing the saliva pool and the individual pool components. RESULTS: The concordance between NPS and saliva results was 95.2% (kappa 0.727, p = 0.0001) and 97.9% without considering inconclusive results (kappa 0.852, p = 0.0001). Saliva had a lower number of inconclusive results than NPS (0.9% vs 1.9%). Furthermore, saliva showed a significantly higher concentration of both total RNA and viral copies than NPS. Comparison of our results with those of the other two laboratories showed 100% and 97% concordance. Saliva samples are stable without the use of any preservative, and a positive SARS-CoV-2 sample can be detected 5, 10, and 15 days after collection when the sample is stored at 4 °C. CONCLUSIONS: The study results indicate that saliva is as effective as NPS for the identification of SARS-CoV-2-infected asymptomatic patients. Sample pooling facilitates the analysis of a larger number of samples, with the benefit of cost reduction.

The Promising Role of miR-21 as a Cancer Biomarker and Its Importance in RNA-Based Therapeutics.

MicroRNAs are small noncoding transcripts that posttranscriptionally regulate gene expression via base-pairing complementarity. Their role in cancer can be related to tumor suppression or oncogenic function. Moreover, they have been linked to processes recognized as hallmarks of cancer, such as apoptosis, invasion, metastasis, and proliferation. Particularly, one of the first oncomiRs found upregulated in a variety of cancers, such as gliomas, breast cancer, and colorectal cancer, was microRNA-21 (miR-21). Some of its target genes associated with cancer are PTEN (phosphatase and tensin homolog), PDCD4 (programmed cell death protein 4), RECK (reversion-inducing cysteine-rich protein with Kazal motifs), and STAT3 (signal transducer activator of transcription 3). As a result, miR-21 has been proposed as a plausible diagnostic and prognostic biomarker, as well as a therapeutic target for several types of cancer. Currently, research and clinical trials to inhibit miR-21 through anti-miR-21 oligonucleotides and ADM-21 are being conducted. As all of the evidence suggests, miR-21 is involved in carcinogenic processes; therefore, inhibiting it could have effects on more than one type of cancer. However, whether miR-21 can be used as a tissue-specific biomarker should be analyzed with caution. Consequently, the purpose of this review is to outline the available information and recent advances regarding miR-21 as a potential biomarker in the clinical setting and as a therapeutic target in cancer to highlight its importance in the era of precision medicine.

The use of long non-coding RNAs as prognostic biomarkers and therapeutic targets in prostate cancer.

Prostate cancer is the most common cancer in men and the second leading cause of cancer-related deaths. The most used biomarker to detect prostate cancer is Prostate Specific Antigen (PSA), whose levels are measured in serum. However, it has been recently established that molecular markers of cancer should not be based solely on genes and proteins but should also reflect other genomic traits; long non-coding RNAs (lncRNAs) serve this purpose. lncRNAs are transcripts of >200 bases that do not encode proteins and that have been shown to display abnormal expression profiles in different types of cancer. Experimental studies have highlighted lncRNAs as potential biomarkers for prognoses and treatments in patients with different types of cancer, including prostate cancer, where the PCA3 lncRNA is currently used as a diagnostic tool and management strategy. With the development of genomic technologies, particularly next-generation sequencing (NGS), several other lncRNAs have been linked to prostate cancer and are currently under validation for their medical use. In this review, we will discuss different strategies for the discovery of novel lncRNAs that can be evaluated as prognostic biomarkers, the clinical impact of these lncRNAs and how lncRNAs can be used as potential therapeutic targets.