LATS2 is De-methylated and Overexpressed in Nasopharyngeal Carcinoma and Predicts Poor Prognosis

<p>Abstract</p> <p>Background</p> <p>LATS2, which encodes a novel serine/threonine kinase, is known to be important in centrosome duplication and in the maintenance of genomic stability. Recently, a potential role for LATS2 in cancer has been reported. In breast cancer and acute lymphoblastic leukemia (ALL), LATS2 mRNA is downregulated and has been suggested to be a tumor suppressor. However, the role of LATS2 in nasopharyngeal carcinoma has not been investigated. In this study, we aimed to investigate the expression pattern of LATS2 and its clinicopathological involvement in nasopharyngeal carcinoma to understand its effect on cell survival.</p> <p>Methods</p> <p>Using quantitative real time PCR and immunoblotting, the expression of LATS2 was detected in nasopharyngeal carcinoma cell lines and in the immortalized nasopharyngeal epithelial cell line NP69. Using immunohistochemistry, we analyzed LATS2 protein expression in 220 nasopharyngeal carcinoma cases. The association of LATS2 protein expression with the clinicopathological characteristics and the prognosis of nasopharyngeal carcinoma were subsequently assessed. Using methylation specific PCR, we detected the methylation status of the LATS2 promoter. RNA interference was performed by transfecting siRNA to specifically knock down LATS2 expression in 5-8F and CNE2.</p> <p>Results</p> <p>LATS2 protein was detected in 178 of 220 (80.91%) cases of nasopharyngeal carcinoma. LATS2 overexpression was a significant, independent prognosis predictor (<it>P </it>= 0.037) in nasopharyngeal carcinoma patients. Methylation specific PCR revealed that 36.7% (11/30) of nasopharyngeal carcinoma tissues and all of the chronic nasopharyngeal inflammation samples were methylated. Functional studies showed that the suppression of LATS2 expression in nasopharyngeal carcinoma (5-8F and CNE2) cell lines by using specific small interfering (siRNA) resulted in the inhibition of growth, induction of apoptosis and S-phase cell cycle increase. Overexpression of LATS2 in NP69 stimulated cell proliferation.</p> <p>Conclusions</p> <p>Our results indicate that LATS2 might play a role in the tumorigenesis of nasopharyngeal carcinoma by promoting the growth of nasopharyngeal carcinoma cells. Transfection with specific siRNA might be feasible for the inhibition of growth, induction of apoptosis and S phase increase in nasopharyngeal carcinoma.</p

The polymorphism L412F in TLR3 inhibits autophagy and is a marker of severe COVID-19 in males

The polymorphism L412F in TLR3 has been associated with several infectious diseases. However, the mechanism underlying this association is still unexplored. Here, we show that the L412F polymorphism in TLR3 is a marker of severity in COVID-19. This association increases in the sub-cohort of males. Impaired macroautophagy/autophagy and reduced TNF/TNFα production was demonstrated in HEK293 cells transfected with TLR3L412F-encoding plasmid and stimulated with specific agonist poly(I:C). A statistically significant reduced survival at 28 days was shown in L412F COVID-19 patients treated with the autophagy-inhibitor hydroxychloroquine (p = 0.038). An increased frequency of autoimmune disorders such as co-morbidity was found in L412F COVID-19 males with specific class II HLA haplotypes prone to autoantigen presentation. Our analyses indicate that L412F polymorphism makes males at risk of severe COVID-19 and provides a rationale for reinterpreting clinical trials considering autophagy pathways. Abbreviations: AP: autophagosome; AUC: area under the curve; BafA1: bafilomycin A1; COVID-19: coronavirus disease-2019; HCQ: hydroxychloroquine; RAP: rapamycin; ROC: receiver operating characteristic; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; TLR: toll like receptor; TNF/TNF-α: tumor necrosis factor

Biased-corrected richness estimates for the Amazonian tree flora

Amazonian forests are extraordinarily diverse, but the estimated species richness is very much debated. Here, we apply an ensemble of parametric estimators and a novel technique that includes conspecific spatial aggregation to an extended database of forest plots with up-to-date taxonomy. We show that the species abundance distribution of Amazonia is best approximated by a logseries with aggregated individuals, where aggregation increases with rarity. By averaging several methods to estimate total richness, we confirm that over 15,000 tree species are expected to occur in Amazonia. We also show that using ten times the number of plots would result in an increase to just ~50% of those 15,000 estimated species. To get a more complete sample of all tree species, rigorous field campaigns may be needed but the number of trees in Amazonia will remain an estimate for years to come