Telomeric Repeat-containing RNA (TERRA) are long non-coding RNAs transcribed from telomeric DNA sequences from multiple chromosome ends. Major research efforts have been made to understand TERRA roles and functions in several physiological and pathological processes. We summarize herein available data regarding TERRA’s roles in human cells and we report the first investigation in cutaneous T-cells lymphomas (CTCL) using real-time PCR. Among the TERRA analysed, our data suggest a particular role for TERRA 16p downregulation and TERRA 11q upregulation in CTCL lymphomagenesis.

Background: Telomere shortening is linked to a range of different human diseases, hence reliable measurement methods are needed to uncover such associations. Among the plethora of telomere length measurement methods, qPCR is reported as easy to conduct and a cost‐effective approach to study samples with low DNA amounts.Methods: Cancer cells’ telomere length was evaluated by relative and absolute qPCR methods.Results: Robust and reproducible telomere length measurements were optimized taking into account a careful reference gene selection and by knowing the cancer cells ploidy. qPCR data were compared to “gold standard” measurement from terminal restriction fragment (TRF).Conclusions: Our study provides guidance and recommendations for accurate telomere length measurement by qPCR in cancer cells, taking advantage of our expertise in telomere homeostasis investigation in primary cutaneous T‐cell lymphomas. Furthermore, our data emphasize the requirement of samples with both, high DNA quality and high tumor cells representation.

Familial Mediterranean Fever (FMF) is a hereditary autoinflammatory disorder, particularly present in the Mediterranean populations, and associated with pathogenic variants in the MEFV gene. This study aims to investigate the distribution of MEFV variants in a large cohort of Lebanese patients, and to explore the genotype-phenotype correlation among affected individuals. A retrospective analysis was conducted on 3,167 patients referred for MEFV sequencing at the Medical Genetics and Genomics Center(CGGM) at Saint-Joseph University of Beirut-Lebanon, from 2006 to 2023. Sanger sequencing was used to detect MEFV variants, focusing initially on hot-spot exons. Among the 3,167 patients, 46.73% (N = 1,480) carried at least one MEFV variant. The most common variants detected were M694V and V726A, both found in 28.98% of cases, followed by E148Q(27.83%) and M694I(13.98%). Moreover, Shiites and Sunni Muslims, and individuals from South and North Lebanon exhibited the highest frequency of variants. Interestingly, family history was found to be significantly higher in patients having two MEFV variants than those with one variant (p = 0.0026). The most commonly reported symptoms were fever(78%), abdominal pain(88%), joint pain(65%), and thoracic pain(46%). The genotype-phenotype correlation analysis revealed a more severe phenotype in patients carrying the M694V or V726A mutations compared to those with the homozygous E148Q genotype. This study, the largest in Lebanon, highlights the high prevalence of MEFV variants, particularly M694V and V726A, in FMF patients. Our data provide valuable insights into the genetic landscape of FMF in Lebanon and emphasize the importance of early genetic screening for a better disease management and genetic counselling.

Cutaneous T‐cell lymphomas (CTCLs) are telomerase‐positive tumors expressing hTERT, although neither gene rearrangement/amplification nor promoter hotspot mutations could explain the hTERT re‐expression. As the hTERT promoter is rich in CpG, we investigated the contribution of epigenetic mechanisms in its re‐expression. We analyzed hTERT promoter methylation status in CTCL cells compared with healthy cells. Gene‐specific methylation analyses revealed a common methylation pattern exclusively in tumor cells. This methylation pattern encompassed a hypermethylated distal region from −650 to −150 bp and a hypomethylated proximal region from −150 to +150 bp. Interestingly, the hypermethylated region matches with the recently named TERT hypermethylated oncogenic region (THOR). THOR has been associated with telomerase reactivation in many cancers, but it has so far not been reported in cutaneous lymphomas. Additionally, we assessed the effect of THOR on two histone deacetylase inhibitors (HDACi), romidepsin and vorinostat, both approved for CTCL treatment and a DNA methyltransferase inhibitor (DNMTi) 5‐azacytidine, unapproved for CTCL. Contrary to our expectations, the findings reported herein revealed that THOR methylation is relatively stable under these epigenetic drugs' pressure, whereas these drugs reduced the hTERT gene expression.

Artificial intelligence (AI) has rapidly advanced in the past years, particularly in medicine for improved diagnostics. In clinical cytogenetics, AI is becoming crucial for analyzing chromosomal abnormalities and improving precision. However, existing software lack learning capabilities from experienced users. AI integration extends to genomic data analysis, personalized medicine and research, but ethical concerns arise. In this article, we discuss the challenges of the full automation in cytogenetic test interpretation and focus on its importance and benefits.