tion of the targeted messenger RNA (mRNA) almost completely. 19,25 This regulation ensures accuracy and robustness by repressing the expression of mRNAs that linger from previous cell states or the products of leaky transcription. 25

Objectives Investigate the feasibility of saliva sampling as a noninvasive and safer tool to detect SARS-CoV-2 and to compare its reproducibility and sensitivity with nasopharyngeal swab samples (NPS). The use of sample pools was also investigated. Methods 2107 paired samples were collected from asymptomatic health care 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. 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 shows a significantly higher concentration of both total RNA and viral copies than NPS. Comparison of our results with those of the other two laboratories shows 100% and 97% concordance. Saliva samples are stable without the use of any preservative, 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 Our 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.

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. The GATA3-AS1 Q10 transcript 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 RT-qPCR Q11 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%, a specificity of 75.0%, and an area under the curve of approximately 0.90, as measured by receiver operating characteristic curve analysis. The statistical model was based on luminal B-like patients and adjusted by menopausal status and phenotype (odds ratio, 37.49; 95% CI, 6.74e208.42; P Z 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. Q12

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.

Given their tumor-specific and stage-specific gene expression, long non-coding RNAs (lncRNAs) have demonstrated to be potential molecular biomarkers for diagnosis, prognosis, and treatment response. Particularly, the lncRNAs DSCAM-AS1 and GATA3-AS1 serve as examples of this because of their high subtype-specific expression profile in luminal B-like breast cancer. This makes them candidates to use as molecular biomarkers in clinical practice. However, lncRNA studies in breast cancer are limited in sample size and are restricted to the determination of their biological function, which represents an obstacle for its inclusion as molecular biomarkers of clinical utility. Nevertheless, due to their expression specificity among diseases, such as cancer, and their stability in body fluids, lncRNAs are promising molecular biomarkers that could improve the reliability, sensitivity, and specificity of molecular techniques used in clinical diagnosis. The development of lncRNA-based diagnostics and lncRNA-based therapeutics will be useful in routine medical practice to improve patient clinical management and quality of life.

Un holobionte es considerado una entidad biológica asociada en simbiosis con microorganismos que complementan sus vías metabólicas, sus funciones fisiológicas y su variación genética. El término hologenoma se refiere a todo el contenido genético del holobionte, es decir, a la suma del genoma del hospedero, sus organelos junto con los genomas del microbioma que lo componen. En la actualidad se ha establecido que existe una relación entre el desarrollo de enfermedades y el microbioma de los humanos, por lo que en esta revisión se describirá el papel del hologenoma en el cáncer y las técnicas de secuenciación masiva en paralelo aplicadas en la hologenómica. El estudio de la hologenómica junto con las tecnologías en secuenciación y bionformática proporcionará información relevante para el desarrollo de nuevas herramientas diagnósticas y su posterior aplicación en la práctica clínica.

Between 70-80 % of human genome is transcribed, nevertheless it contains only 1.5% of protein-coding sequences while non-coding genome comprises almost 99%. Within the non-coding transcripts, a group of regulatory non-coding RNAs (ncRNAs) stands out in number: the long non-coding RNAs (lncRNAs), which are transcripts lacking coding potential and longer than 200 nucleotides. These transcripts are involved in different regulatory processes. In this study, our aim is to identify new lncRNAs involved in regulation of chromosomal instability (CIN) in a cell model of prostate cancer (PCa). Using RNA-seq data from two prostate cell lines: LNCaP (neoplastic, exhibits CIN) and PrEC (non-neoplastic, does not exhibit CIN) we have identified a lncRNA adjacent to the protein-coding gene RFC4, a gene involved in CIN in human cancers. This transcript, which we have provisionally named lncRNA-RFC4, exhibits differential expression between PrEC and LNCaP as seen in expression analyses from RNA-seq data. Afterwards, we performed qPCR experiments and found similar results as those seen in RNA-seq data analyses, lncRNA-RFC4 is downregulated in LNCaP, whereas the adjacent coding gene RFC4 is upregulated; the opposite is found in PrEC cell line. Western blot experiments confirmed that RFC4 protein abundance is higher in LNCaP. Our findings suggest that this transcript could have a possible repressor role on RFC4. In order to explore the regulatory mechanism, we performed cell fractionation and measured the abundance of lncRNA-RFC4 in each fraction using qPCR, we found that this transcript accumulates in the nucleus, specifically in the chromatin fraction, the nucleoplasm and cytoplasm fraction are not enriched with this lncRNA. In order to predict possible RNA-protein interactions we used an in-silico tool and found predicted interactions between lncRNA-RFC4 and two repressor proteins, CBX7 and SUZ12, part of the polycomb repressive complex 1 and 2 respectively, these interactions are yet to be confirmed experimentally. In conclusion, we have identified a chromatin-enriched lncRNA adjacent to RFC4, a CIN related gene, this ncRNA could play a repressive role on the adjacent gene though its interaction with the repressor proteins CBX7 and SUZ12, consequently, this transcript could be involved in a network controlling CIN in this cell model of PCa. Further experiments are needed to prove cis regulation of RFC4 by lncRNA-RFC4 and the molecular mechanism underlying this regulatory network. Citation Format: Rogelio Montiel Manriquez, Cristian Arriaga Canon, Laura Contreras Espinosa, Paula Alarcón Zendejas, Luis Alonso Herrera Montalvo. Identification of a regulatory long non-coding RNA adjacent to RFC4, a gene related to chromosomal instability, in a cell model of prostate cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3698.