Background The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests. Methods In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aim to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID-19 patients and influenza patients based on clinical variables alone. Results We discovered several novel associations between clinical variables, including correlations between being male and having higher levels of serum lymphocytes and neutrophils. We found that COVID-19 patients could be clustered into subtypes based on serum levels of immune cells, gender, and reported symptoms. Finally, we trained an XGBoost model to achieve a sensitivity of 92.5% and a specificity of 97.9% in discriminating COVID-19 patients from influenza patients. Conclusions We demonstrated that computational methods trained on large clinical datasets could yield ever more accurate COVID-19 diagnostic models to mitigate the impact of lack of testing. We also presented previously unknown COVID-19 clinical variable correlations and clinical subgroups.

Head and neck squamous cell carcinoma persists as one of the most common and deadly malignancies, with early detection and effective treatment still posing formidable challenges. To expand our currently sparse knowledge of the noncoding alterations involved in the disease and identify potential biomarkers and therapeutic targets, we globally profiled the dysregulation of small nucleolar and long noncoding RNAs in head and neck tumors. Using next-generation RNA-sequencing data from 40 pairs of tumor and matched normal tissues, we found 2808 long noncoding RNA (lncRNA) transcripts significantly differentially expressed by a fold change magnitude ≥2. Meanwhile, RNA-sequencing analysis of 31 tumor-normal pairs yielded 33 significantly dysregulated small nucleolar RNAs (snoRNA). In particular, we identified two dramatically downregulated lncRNAs and one down-regulated snoRNA whose expression levels correlated significantly with overall patient survival, suggesting their functional significance and clinical relevance in head and neck cancer pathogenesis. We confirmed the dysregulation of these noncoding RNAs in head and neck cancer cell lines derived from different anatomic sites, and determined that ectopic expression of the two lncRNAs inhibited key EMT and stem cell genes and reduced cellular proliferation and migration. As a whole, noncoding RNAs are pervasively dysregulated in head and squamous cell carcinoma. The precise molecular roles of the three transcripts identified warrants further characterization, but our data suggest that they are likely to play substantial roles in head and neck cancer pathogenesis and are significantly associated with patient survival.

Members of the EGFR/ErbB family of tyrosine kinases are found to be highly expressed and deregulated in many cancers, including head and neck squamous cell carcinoma (HNSCC). The ErbB family, including EGFR, has been demonstrated to play key roles in metastasis, tumorigenesis, cell proliferation, and drug resistance. Recently, these characteristics have been linked to a small subpopulation of cells classified as cancer stem cells (CSCs) which are believed to be responsible for tumor initiation and maintenance. In this study, we investigated the possible role of EGFR as a regulator of “stemness” in HNSCC cells. Activation of EGFR by the addition of EGF ligand or ectopic expression of EGFR in two established HNSCC cell lines (UMSCC-22B and HN-1) resulted in the induction of CD44, BMI-1, Oct-4, NANOG, CXCR4, and SDF-1. Activation of EGFR also resulted in increased tumorsphere formation, a characteristic ability of cancer stem cells. Conversely, treatment with the EGFR kinase inhibitor, Gefinitib (Iressa), resulted in decreased expression of the aforementioned genes, and loss of tumorsphere-forming ability. Similar trends were observed in a 99.9% CD44 positive stem cell culture derived from a fresh HNSCC tumor, confirming our findings for the cell lines. Additionally, we found that these putative cancer stem cells, when treated with Gefitinib, possessed a lower capacity to invade and became more sensitive to cisplatin-induced death in vitro. These results suggest that EGFR plays critical roles in the survival, maintenance, and function of cancer stem cells. Drugs that target EGFR, perhaps administered in combination with conventional chemotherapy, might be an effective treatment for HNSCC.

Background Low medication adherence is known to contribute to worse health outcomes in the general population. Aim We aimed to evaluate the medication regimen and determine the adherence levels among patients with end-stage liver disease. Methods We measured adherence in patients awaiting liver transplantation at a single center using the 8-item Morisky Medication Adherence Scale (MMAS-8), with a score <8 classified as low-adherence. Medication regimen complexity was assessed using the Medication Complexity Regimen tool (MRCI). Factors associated with low-adherence were identified by logistic regression. Results Of 181 patients, 33% were female, median age was 62, and Model for end-stage liver disease (MELD) score was 13. The median (IQR) number of medications was 10 (7–13) and the MRCI was 19 (13–27). 54 (30%) were high adherers, and 127 (70%) were low-adherers. 42% reported sometimes forgetting to take their medication and 22% reported intermittent adherence within the past 2 weeks. The most common reasons for low-adherence were: forgetfulness (27%), and side effects (14%). Compared to high adherence, low-adherence was associated with higher number of medications, medication complexity, and diabetes, but lower rates of hepatocellular carcinoma and self-perceived health. In univariable logistic regression, total medication number (OR 1.08), MRCI (OR 1.04), diabetes (OR 2.38), HCC (OR 0.38) and lower self-perceived health (OR 1.37), were statistically significant factors associated with non-adherence. In multivariate analysis, only medication number without supplements (OR 1.14) remained significantly associated with medication non-adherence. Conclusion A majority of patients awaiting liver transplantation demonstrate low medication adherence. Total number of medications and regimen complexity were strong correlates of adherence. Our data underscore the need for chronic liver disease management programs to improve medication adherence in this vulnerable population.

BackgroundAlcohol consumption is a well-established risk factor for head and neck squamous cell carcinoma (HNSCC); however, the molecular mechanisms by which alcohol promotes HNSCC pathogenesis and progression remain poorly understood. Our study sought to identify microRNAs that are dysregulated in alcohol-associated HNSCC and investigate their contribution to the malignant phenotype.MethodUsing RNA-sequencing data from 136 HNSCC patients, we compared the expression levels of 1,046 microRNAs between drinking and non-drinking cohorts. Dysregulated microRNAs were verified by qRT-PCR in normal oral keratinocytes treated with biologically relevant doses of ethanol and acetaldehyde. The most promising microRNA candidates were investigated for their effects on cellular proliferation and invasion, sensitivity to cisplatin, and expression of cancer stem cell genes. Finally, putative target genes were identified and evaluated in vitro to further establish roles for these miRNAs in alcohol-associated HNSCC.ResultsFrom RNA-sequencing analysis we identified 8 miRNAs to be significantly upregulated in alcohol-associated HNSCCs. qRT-PCR experiments determined that among these candidates, miR-30a and miR-934 were the most highly upregulated in vitro by alcohol and acetaldehyde. Overexpression of miR-30a and miR-934 in normal and HNSCC cell lines produced up to a 2-fold increase in cellular proliferation, as well as induction of the anti-apoptotic gene BCL-2. Upon inhibition of these miRNAs, HNSCC cell lines exhibited increased sensitivity to cisplatin and reduced matrigel invasion. miRNA knockdown also indicated direct targeting of several tumor suppressor genes by miR-30a and miR-934.ConclusionsAlcohol induces the dysregulation of miR-30a and miR-934, which may play crucial roles in HNSCC pathogenesis and progression. Future investigation of the alcohol-mediated pathways effecting these transformations will prove valuable for furthering the understanding and treatment of alcohol-associated HNSCC.Electronic supplementary materialThe online version of this article (doi:10.1186/s12943-015-0452-8) contains supplementary material, which is available to authorized users.