Background Coronavirus disease 2019 (COVID-19) is a systemic disease that can rapidly progress into acute respiratory failure and death. Timely identification of these patients is crucial for a proper administration of health-care resources. Objective To develop a predictive score that estimates the risk of invasive mechanical ventilation (IMV) among patients with COVID-19. Study design Retrospective cohort study of 401 COVID-19 patients diagnosed from March 12, to August 10, 2020. The score development cohort comprised 211 patients (52.62% of total sample) whereas the validation cohort included 190 patients (47.38% of total sample). We divided participants according to the need of invasive mechanical ventilation (IMV) and looked for potential predictive variables. Results We developed two predictive scores, one based on Interleukin-6 (IL-6) and the other one on the Neutrophil/Lymphocyte ratio (NLR), using the following variables: respiratory rate, SpO2/FiO2 ratio and lactic dehydrogenase (LDH). The area under the curve (AUC) in the development cohort was 0.877 (0.823–0.931) using the NLR based score and 0.891 (0.843–0.939) using the IL-6 based score. When compared with other similar scores developed for the prediction of adverse outcomes in COVID-19, the COVID-IRS scores proved to be superior in the prediction of IMV. Conclusion The COVID-IRS scores accurately predict the need for mechanical ventilation in COVID-19 patients using readily available variables taken upon admission. More studies testing the applicability of COVID-IRS in other centers and populations, as well as its performance as a triage tool for COVID-19 patients are needed.

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.

Background.Androgen receptor (AR) is widely expressed in different breast cancer subtypes. AR plays an important role in promoting the growth of HER2 +  breast cancer through cross-talk with HER2 signaling, including WNT7B upregulation, beta-catenin activation, stimulation of HER3 gene transcription, and promotion of HER2/HER3 heterodimerization. Preclinical data have shown that inhibiting AR with enzalutamide results in decreased HER2 phosphorylation and activation of ERK and AKT, without affecting HER2 and HER3 expression; however, the role that inhibiting HER2 with anti-HER2 therapy plays in AR expression and regulation is still unknown. In this study, we sought to identify the influence of anti-HER2 therapy on AR and estrogen receptor (ER) expression after neoadjuvant treatment in patients with locally advanced HER2+ breast cancer. Methods.We retrospectively collected data from 68 patients with locally advanced HER2+ breast cancer who received neoadjuvant treatment with trastuzumab and chemotherapy. AR and ER levels were determined by immunohistochemistry in available initial biopsy specimens and in surgical specimens of all patients with residual disease after neoadjuvant therapy. AR was assessed by Immunohistochemistry (IHC) staining using AR441 antibody from DAKO. Expression in >10% of cells was considered positive. Pathological complete response (pCR) was defined as ypT0/is, ypN0. ROC curve analysis was performed to identify the correlation between AR score and pCR. Results.Twenty-five patients had pretreatment tissue available. Eighteen (72%) were positive for AR staining and 20 (80%) for ER staining. Of the 25 cases, 10 (40%) achieved a pCR and 15 (60%) did not. The median AR score for those with a pCR was higher, 20 (range 0, 80) vs 10 (range 0, 70). The area under the ROC curve was 0.59 (95% confidence interval 0.35, 0.83); we found no statistically significant relationship between AR score and pCR (p = 0.47). All nine cases positive for AR before neoadjuvant therapy who had residual tissue for staining after therapy had negative AR staining after neoadjuvant anti-HER2 therapy. Of 18 cases positive for ER before neoadjuvant therapy who had residual tissue for staining after therapy, only 6 (33%) had negative ER staining after neoadjuvant anti-HER2 therapy. Further, all patients initially positive for AR and ER remained ER positive but were AR negative after therapy. Conclusions. We found that in 100% of cases AR positivity disappeared after anti-HER2 neoadjuvant therapy in patients with residual disease, whereas ER positivity disappeared in only 33% of cases, suggesting that blocking HER2 may inhibit positive feedback with AR; however, both AR and ER receptors have independent biological interactions with HER2 that need to be explored. We plan to confirm our results with a larger sample size, and we will continue to monitor our patients to determine the influence of AR negativity after neoadjuvant anti-HER2 therapy on disease-free and overall survival. Citation Format: Jose Rodrigo Espinosa Fernandez, Aysegul A. Sahin, Kenneth R. Hess, Raul Gerardo Ramirez Medina, Paula Anel Cabrera Galeana, Alejandro Javier España Ferrufino, Nereida Esparza Arias, Juan Enrique Bargallo Rocha, José Antonio García Gordillo, Gerardo Emmanuel Lopez Muñiz, Naoto T Ueno. Loss of androgen receptor after neoadjuvant anti-HER2 therapy in patients with locally advanced HER2-positive breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-22.