Hot Spot TERT Promoter Mutations Are Rare in Sporadic Pancreatic Neuroendocrine Neoplasms and Associated with Telomere Length and Epigenetic Expression Patterns

Telomere length assessment and molecular characterization of TERT gene promoter in periampullary carcinomas

Genetic and epigenetic alterations of the telomere maintenance machinery like telomere length and telomerase reverse transcriptase (encoded by TERT gene) are reported in several human malignancies. However, there is limited knowledge on the status of the telomere machinery in periampullary carcinomas (PAC) which are rare and heterogeneous groups of cancers arising from different anatomic sites around the ampulla of Vater. In the current study, we investigated the relative telomere length (RTL) and the most frequent genetic and epigenetic alterations in the TERT promoter in PAC and compared it with tumor-adjacent nonpathological duodenum (NDu). We found shorter RTLs (1.27 vs 1.33, P = 0.01) and lower TERT protein expression (p = 0.04) in PAC tissues as compared to the NDu. Although we did not find any mutation at two reactivating hotspot mutation sites of the TERT promoter, we detected polymorphism in 45% (9/20) of the cases at rs2853669 (T > C). Also, we found a hypermethylated region in the TERT promoter of PACs consisting of four CpGs (cg10896616 with Δβ 7%; cg02545192 with Δβ 9%; cg03323598 with Δβ 19%; and cg07285213 with Δβ 15%). In conclusion, we identified shorter telomeres with DNA hypermethylation in the TERT promoter region and lower TERT protein expression in PAC tissues. These results could be used further to investigate molecular pathology and develop theranostics for PAC.

Role of telomere length in human carcinogenesis (Review)

Cancer is considered the most important clinical, social and economic issue regarding cause‑specific disability‑adjusted life years among all human pathologies. Exogenous, endogenous and individual factors, including genetic predisposition, participate in cancer triggering. Telomeres are specific DNA structures positioned at the end of chromosomes and consist of repetitive nucleotide sequences, which, together with shelterin proteins, facilitate the maintenance of chromosome stability, while protecting them from genomic erosion. Even though the connection between telomere status and carcinogenesis has been identified, the absence of a universal or even a cancer‑specific trend renders consent even more complex. It is indicative that both short and long telomere lengths have been associated with a high risk of cancer incidence. When evaluating risk associations between cancer and telomere length, a disparity appears to emerge. Even though shorter telomeres have been adopted as a marker of poorer health status and an older biological age, longer telomeres due to increased cell growth potential are associated with the acquirement of cancer‑initiating somatic mutations. Therefore, the present review aimed to comprehensively present the multifaceted pattern of telomere length and cancer incidence association.

Global mapping of cancers: The Cancer Genome Atlas and beyond

Cancer genomes have been explored from the early 2000s through massive exome sequencing efforts, leading to the publication of The Cancer Genome Atlas in 2013. Sequencing techniques have been developed alongside this project and have allowed scientists to bypass the limitation of costs for whole-genome sequencing (WGS) of single specimens by developing more accurate and extensive cancer sequencing projects, such as deep sequencing of whole genomes and transcriptomic analysis. The Pan-Cancer Analysis of Whole Genomes recently published WGS data from more than 2600 human cancers together with almost 1200 related transcriptomes. The application of WGS on a large database allowed, for the first time in history, a global analysis of features such as molecular signatures, large structural variations and noncoding regions of the genome, as well as the evaluation of RNA alterations in the absence of underlying DNA mutations. The vast amount of data generated still needs to be thoroughly deciphered, and the advent of machine-learning approaches will be the next step towards the generation of personalized approaches for cancer medicine. The present manuscript wants to give a broad perspective on some of the biological evidence derived from the largest sequencing attempts on human cancers so far, discussing advantages and limitations of this approach and its power in the era of machine learning.