Role of MTHFR, IRF6, PAX7 and TP63 SNPs in susceptibility to non-syndromic orofacial cleft, a candidate gene study in a Portuguese population.

BACKGROUND: Non-syndromic orofacial cleft (NSOC) is a complex phenotype, involving multiple genetic and environmental factors. Association studies exploring the genetic susceptibility to this prevalent oral malformation show variability of results in different populations. Using a candidate gene approach, we aimed to verify the role of four single-nucleotide polymorphisms (SNPs) in the susceptibility to NSOC in Portuguese patients. METHODS: A total of 254 non-consanguineous individuals of Portuguese were recruited, including 120 patients with NSOC and 134 controls. About 92% of these patients had non-syndromic cleft lip with or without cleft palate (NSCL/P) and 8% had only non-syndromic cleft palate (NSCP). SNPs in the MTHFR (rs1801133), IRF6 (rs642961), PAX7 (rs742071) and TP63 (rs9332461) genes were studied, using a real-time approach with TaqMan probes. Allelic, genotypic, dominant, recessive and over-dominant models were explored using a chi-squared test. Adjusted p-value was calculated for multiple comparisons using the Benjamini-Hochberg false discovery rate (FDR). RESULTS: All SNPs were in Hardy-Weinberg equilibrium. For MTHFR, IRF6, and PAX7 SNPs, no statistically significant difference was highlighted for any of the evaluated models. For TP63 SNP, data fitted an over-dominant model, with a protective effect for heterozygotes (OR 1.897; CI 95% [1.144-3.147]; p < .016, when comparing controls vs. cases), but significance was lost when applying adjusted p-value for multiple comparisons (4 × 5 tests). CONCLUSION: In this Portuguese population, there was no evidence of an association between the evaluated SNPs and NSOC. For TP63 SNP, the possibility of a protective effect of heterozygotes should be further investigated.

Two Different Immune Profiles Are Identified in Sentinel Lymph Nodes of Early-Stage Breast Cancer.

In the management of early-stage breast cancer (BC), lymph nodes (LNs) are typically characterised using the One-Step Nucleic Acid Amplification (OSNA) assay, a standard procedure for assessing subclinical metastasis in sentinel LNs (SLNs). The pivotal role of LNs in coordinating the immune response against BC is often overlooked. Our aim was to improve prognostic information provided by the OSNA assay and explore immune-related gene signatures in SLNs. The expression of an immune gene panel was analysed in SLNs from 32 patients with Luminal A early-stage BC (cT1-T2 N0). Using an unsupervised approach based on these expression values, this study identified two clusters, regardless of the SLN invasion: one evidencing an adaptive anti-tumoral immune response, characterised by an increase in naive B cells, follicular T helper cells, and activated NK cells; and another with a more undifferentiated response, with an increase in the activated-to-resting dendritic cells (DCs) ratio. Through a protein-protein interaction (PPI) network, we identified seven immunoregulatory hub genes: CD80, CD40, TNF, FCGR3A, CD163, FCGR3B, and CCR2. This study shows that, in Luminal A early-stage BC, SLNs gene expression studies enable the identification of distinct immune profiles that may influence prognosis stratification and highlight key genes that could serve as potential targets for immunotherapy.

One Step Nucleic Acid Amplification (OSNA) Lysate Samples Are Suitable to Establish a Transcriptional Metastatic Signature in Patients with Early Stage Hormone Receptors-Positive Breast Cancer.

The One Step Nucleic Acid Amplification (OSNA) is being adopted worldwide for sentinel lymph nodes (SLNs) staging in breast cancer (BC). As major disadvantage, OSNA precludes prognostic information based on structural evaluation of SLNs. Our aim is to identify biomarkers related to tumor-microenvironment interplay exploring gene expression data from the OSNA remaining lysate. This study included 32 patients with early stage hormone receptors-positive BC. Remaining OSNA lysates were prepared for targeted RNA-sequencing analysis. Identification of differentially expressed genes (DEGs) was performed by DESeq2 in R and data analysis in STATA. The results show that, in metastatic SLNs, several genes were upregulated: KRT7, VTCN1, CD44, GATA3, ALOX15B, RORC, NECTIN2, LRG1, CD276, FOXM1 and IGF1R. Hierarchical clustering analysis revealed three different clusters. The identified DEGs codify proteins mainly involved in cancer aggressiveness and with impact in immune response. The overexpression of the immune suppressive genes VTCN1 and CD276 may explain that no direct evidence of activation of immune response in metastatic SLNs was found. We show that OSNA results may be improved incorporating microenvironment-related biomarkers that may be useful in the future for prognosis stratification and immunotherapy selection. As OSNA assay is being implemented for SLNs staging in other cancers, this approach could also have a wider utility.