A placental model of SARS-CoV-2 infection reveals ACE2-dependent susceptibility and differentiation impairment in syncytiotrophoblasts.

SARS-CoV-2 infection causes COVID-19. Several clinical reports have linked COVID-19 during pregnancy to negative birth outcomes and placentitis. However, the pathophysiological mechanisms underpinning SARS-CoV-2 infection during placentation and early pregnancy are not clear. Here, to shed light on this, we used induced trophoblast stem cells to generate an in vitro early placenta infection model. We identified that syncytiotrophoblasts could be infected through angiotensin-converting enzyme 2 (ACE2). Using a co-culture model of vertical transmission, we confirmed the ability of the virus to infect syncytiotrophoblasts through a previous endometrial cell infection. We further demonstrated transcriptional changes in infected syncytiotrophoblasts that led to impairment of cellular processes, reduced secretion of HCG hormone and morphological changes vital for syncytiotrophoblast function. Furthermore, different antibody strategies and antiviral drugs restore these impairments. In summary, we have established a scalable and tractable platform to study early placental cell types and highlighted its use in studying strategies to protect the placenta.

Siglec-10 expression is up-regulated in activated human CD4+ T cells.

Most sialic acid-binding immunoglobulin-like lectins (Siglecs) suppress immune cell function but are expressed at low levels on human T cells. We found that soluble CD52 inhibited T cell signalling by ligating Siglec-10, but the presence of Siglec-10 on human T cells has been questioned. To address this concern, we examined the expression of Siglec-10 at the RNA and protein level in human CD4+ T cells. Analysis by RNAseq, qPCR and flow cytometry demonstrated that, in contrast to other Siglecs, after activation of CD4+ T cells Siglec-10 was selectively upregulated in a subset of cells also high for CD52 expression. This observation is consistent with a homeostatic role for Siglec-10 in human CD4+ T cells.

MicroRNAs expression profile in solid and unicystic ameloblastomas.

OBJECTIVES: Odontogenic tumors (OT) represent a specific pathological category that includes some lesions with unpredictable biological behavior. Although most of these lesions are benign, some, such as the ameloblastoma, exhibit local aggressiveness and high recurrence rates. The most common types of ameloblastoma are the solid/multicystic (SA) and the unicystic ameloblastoma (UA); the latter considered a much less aggressive entity as compared to the SA. The microRNA system regulates the expression of many human genes while its deregulation has been associated with neoplastic development. The aim of the current study was to determine the expression profiles of microRNAs present in the two most common types of ameloblastomas. MATERIAL & METHODS: MicroRNA expression profiles were assessed using TaqMan® Low Density Arrays (TLDAs) in 24 samples (8 SA, 8 UA and 8 control samples). The findings were validated using quantitative RTqPCR in an independent cohort of 19 SA, 8 UA and 19 dentigerous cysts as controls. RESULTS: We identified 40 microRNAs differentially regulated in ameloblastomas, which are related to neoplastic development and differentiation, and with the osteogenic process. Further validation of the top ranked microRNAs revealed significant differences in the expression of 6 of them in relation to UA, 7 in relation to SA and 1 (miR-489) that was related to both types. CONCLUSION: We identified a new microRNA signature for the ameloblastoma and for its main types, which may be useful to better understand the etiopathogenesis of this neoplasm. In addition, we identified a microRNA (miR-489) that is suggestive of differentiating among solid from unicystic ameloblastoma.

Genomewide miRNA profiling of oral lichenoid disorders and oral squamous cell carcinoma.

OBJECTIVE: To dissect the aberrant microRNA profile of oral lichenoid disorders (OLD) by analyzing the larger set of OLD samples tested so far. MATERIALS AND METHODS: MicroRNA expression profiles were assessed using TLDA card in 32 samples (16 OLD, 8 OSCC, and 8 control). The findings were validated using RT-qPCR in an independent cohort of 91 samples. RESULTS: We identified 20 differentially expressed microRNAs in OLD, of which several are functionally related to cell proliferation, response to organic substances, or immune processes. Further validation of the top-ranked microRNAs revealed that they were all aberrantly expressed in OLD. CONCLUSION: We have identified a new microRNA signature associated with OLD that may provide a meaningful basis for better understanding the physiopathology of the disease. In addition, we validated seven microRNAs whose expression was shown to be higher in OLD tissue in comparison with the control and OSCC tissues.

Associations between STR autosomal markers and longevity.

Life span is a complex and multifactorial trait, which is shaped by genetic, epigenetic, environmental, and stochastic factors. The possibility that highly hypervariable short tandem repeats (STRs) associated with longevity has been largely explored by comparing the genotypic pools of long lived and younger individuals, but results so far have been contradictory. In view of these contradictory findings, the present study aims to investigate whether HUMTHO1 and HUMCSF1PO STRs, previously associated with longevity, exert a role as a modulator of life expectancy, as well as to assess the extent to which other autosomal STR markers are associated with human longevity in population from northern Spain. To that end, 21 autosomal microsatellite markers have been studied in 304 nonagenarian individuals (more than 90 years old) and 516 younger controls of European descent. Our results do not confirm the association found in previous studies between longevity and THO1 and CSF1PO loci. However, significant association between longevity and autosomal STR markers D12S391, D22S1045, and DS441 was observed. Even more, when we compared allelic frequency distribution of the 21 STR markers between cases and controls, we found that 6 out of the 21 STRs studied showed different allelic frequencies, thus suggesting that the genomic portrait of the human longevity is far complex and probably shaped by a high number of genomic loci.

Global DNA methylation: uncommon event in oral lichenoid disease.

OBJECTIVES: Accumulating evidence indicates that aberrant DNA methylation is closely related to oral carcinogenesis, and it has been shown that methylation changes might be used as prognostic biomarker in oral squamous cell carcinoma. Oral lichenoid disease (OLD) is the most common oral potentially malignant disorder in our region. The aim of this study was to perform the first wide DNA methylation study in OLD in order to investigate the relevance of DNA methylation changes in this premalignant disorder. MATERIALS AND METHODS: Two different Illumina microarray platforms, namely the GoldenGate Cancer Panel I and the HumanMethylation27 DNA Analysis BeadChip, were utilized in the discovery phase to interrogate the methylation profile of 59 OLD cases and 9 healthy individuals. Top-ranked genes were further validated by pyrosequencing in a second sample set consisting of 160 OLD and 65 controls. RESULTS: Our results show that the frequency of aberrant DNA methylation is rare in OLD, and this finding was further corroborated by pyrosequencing in the biological validation. CONCLUSIONS: These findings reinforce the notion that molecular alterations associated with oral carcinogenesis do not seem to be common events in OLD, which in turn might explain the low rate of malignization of this disorder.

A microRNA-based prediction algorithm for diagnosis of non-small lung cell carcinoma in minimal biopsy material.

BACKGROUND: Diagnosis is jeopardised when limited biopsy material is available or histological quality compromised. Here we developed and validated a prediction algorithm based on microRNA (miRNA) expression that can assist clinical diagnosis of lung cancer in minimal biopsy material to improve clinical management. METHODS: Discovery utilised Taqman Low Density Arrays (754 miRNAs) in 20 non-small cell lung cancer (NSCLC) tumour/normal pairs. In an independent set of 40 NSCLC patients, 28 miRNA targets were validated using qRT-PCR. A prediction algorithm based on eight miRNA targets was validated blindly in a third independent set of 47 NSCLC patients. The panel was also tested in formalin-fixed paraffin-embedded (FFPE) specimens from 20 NSCLC patients. The genomic methylation status of highly deregulated miRNAs was investigated by pyrosequencing. RESULTS: In the final, frozen validation set the panel had very high sensitivity (97.5%), specificity (96.3%) and ROC-AUC (0.99, P=10(-15)). The panel provided 100% sensitivity and 95% specificity in FFPE tissue (ROC-AUC=0.97 (P=10(-6))). DNA methylation abnormalities contribute little to the deregulation of the miRNAs tested. CONCLUSION: The developed prediction algorithm is a valuable potential biomarker for assisting lung cancer diagnosis in minimal biopsy material. A prospective validation is required to measure the enhancement of diagnostic accuracy of our current clinical practice.