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Telomere maintenance via telomerase reactivation is a nearly universal hallmark of cancer cells which enables replicative immortality. In contrast, telomerase activity is silenced in most adult somatic cells. Thus, telomerase represents an attractive target for highly selective cancer therapeutics. However, development of telomerase inhibitors has been challenging and thus far there are no clinically approved strategies exploiting this cancer target. The discovery of prevalent mutations in the TERT promoter region in many cancers and recent advances in telomerase biology has led to a renewed interest in targeting this enzyme. Here we discuss recent efforts targeting telomerase, including immunotherapies and direct telomerase inhibitors, as well as emerging approaches such as targeting TERT gene expression driven by TERT promoter mutations. We also address some of the challenges to telomerase-directed therapies including potential therapeutic resistance and considerations for future therapeutic applications and translation into the clinical setting. Although much work remains to be done, effective strategies targeting telomerase will have a transformative impact for cancer therapy and the prospect of clinically effective drugs is boosted by recent advances in structural models of human telomerase.

BackgroundPapillary thyroid carcinoma (PTC) is characterized by frequent metastases to cervical lymph nodes (CLNs), and the presence of lymph node metastasis at diagnosis has a significant impact on the surgical approach. Therefore, we established a radiomic signature to predict the CLN status of PTC patients using preoperative thyroid ultrasound, and investigated the association between the radiomic features and underlying molecular characteristics of PTC tumors.MethodsIn total, 270 patients were enrolled in this prospective study, and radiomic features were extracted according to multiple guidelines. A radiomic signature was built with selected features in the training cohort and validated in the validation cohort. The total protein extracted from tumor samples was analyzed with LC/MS and iTRAQ technology. Gene modules acquired by clustering were chosen for their diagnostic significance. A radiogenomic map linking radiomic features to gene modules was constructed with the Spearman correlation matrix. Genes in modules related to metastasis were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a protein-protein interaction (PPI) network was built to identify the hub genes in the modules. Finally, the screened hub genes were validated by immunohistochemistry analysis.ResultsThe radiomic signature showed good performance for predicting CLN status in training and validation cohorts, with area under curve of 0.873 and 0.831 respectively. A radiogenomic map was created with nine significant correlations between radiomic features and gene modules, and two of them had higher correlation coefficient. Among these, MEmeganta representing the upregulation of telomere maintenance via telomerase and cell-cell adhesion was correlated with ‘Rectlike’ and ‘deviation ratio of tumor tissue and normal thyroid gland’ which reflect the margin and the internal echogenicity of the tumor, respectively. MEblue capturing cell-cell adhesion and glycolysis was associated with feature ‘minimum calcification area’ which measures the punctate calcification. The hub genes of the two modules were identified by protein-protein interaction network. Immunohistochemistry validated that LAMC1 and THBS1 were differently expressed in metastatic and non-metastatic tissues (p=0.003; p=0.002). And LAMC1 was associated with feature ‘Rectlike’ and ‘deviation ratio of tumor and normal thyroid gland’ (pConclusionsThe radiomic signature proposed here has the potential to noninvasively predict the CLN status in PTC patients. Merging imaging phenotypes with genomic data could allow noninvasive identification of the molecular properties of PTC tumors, which might support clinical decision making and personalized management.

Temozolomide (TMZ) is considered a standard chemotherapeutic agent for glioblastoma (GBM). Characterizing the biological molecules and signaling pathways involved in TMZ sensitivity would be helpful for selecting therapeutic schemes and evaluating prognosis for GBM. Thus, in the present study, we selected 34 glioma cell lines paired with specific IC50 values of TMZ obtained from CancerRxGene and RNA-seq data downloaded from the Cancer Cell Line Encyclopedia to identify genes related to TMZ sensitivity. The results showed that 1,373 genes were related to the response of GBM cells to TMZ. Biological function analysis indicated that epithelial-mesenchymal transition, Wnt signaling, and immune response were the most significantly activated functions in TMZ-resistant cell lines. Additionally, negative regulation of telomere maintenance via telomerase was enriched in TMZ-sensitive glioma cell lines. We also preliminarily observed a synergistic effect of combination treatment comprising TMZ and a telomerase inhibitor in vitro. We identified six genes (MROH8, BET1, PTPRN2, STC1, NKX3-1, and ARMC10) using the random survival forests variable hunting algorithm based on the minimum error rate of the gene combination and constructed a gene expression signature. The signature was strongly related to GBM clinical characteristics and exhibited good prognosis accuracy for both The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) datasets. Patients in the high score group had a shorter survival time than those in the low score group (11.2 vs. 22.2 months, hazard ratio = 7.31, p = 4.59e-11) of the TCGA dataset. The CGGA dataset was selected as a validation group with 40 patients in the high score set and 43 patients in the low score set (12.5 vs. 28.8 months, hazard ratio = 3.42, p = 8.61e-5). Moreover, the signature showed a better prognostic value than MGMT promoter methylation in both datasets. We also developed a nomogram for clinical use that integrated the TMZ response signature and four other risk factors to individually predict patient survival after TMZ chemotherapy. Overall, our study provides promising therapeutic targets and potential guidance for adjuvant therapy of GBM.

Context: Telomere maintenance via telomerase activation and the alternative lengthening of telomeres (ALT) mechanism was assessed in medullary thyroid carcinoma. Setting and Design: In total, 42 medullary thyroid carcinomas (MTC) were studied including 24 rearranged during transfection (RET)- mutated cases. Relative telomerase reverse transcriptase (TERT) expression, splice forms, and telomere length were determined by PCR-based methods, and telomerase activity by ELISA. The ALT mechanism was detected by Southern blot analysis and immunofluorescence. Results: TERT expression and telomerase activity were detected in 21/42 tumors (50%), and was independent of the common somatic M918T RET mutation. Mean telomere length was shorter in MTCs compared with thyroids. Telomerase activation was associated with large tumor size (P = .027), advanced clinical stage (P = .0001), and short survival (P = .0001). Full-length TERT and the α− and β−-deletion forms were revealed, and the full-length form was associated with short survival (P = .04). A subset of cases without telomerase activation showed involvement of the ALT mechanism, which was associated with a low MIB-1 proliferation index (P = .024). Conclusions: Stabilization of telomeres by telomerase activation occurs in half of the MTCs and by the ALT mechanism in a subset of cases. Telomerase activation may be used as an additional prognostic marker in medullary thyroid carcinoma.

Aims The aim of the study was to identify key miRNAs related to hepatocellular carcinoma (HCC) and then to explore their potential function and clinical significance. Materials and methods The miRNA expression profiles of 387 HCC and 62 normal liver tissues were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. GEO2R tool and edgeR package in R/Bioconductor were used to screen out HCC-related miRNAs. VennDiagram package was used to identify key miRNAs related to HCC. The miRWalk tool and multiple R packages, such as pROC and survival, were used to explore potential function and clinical significance of these key miRNAs. Key findings A total of 17 and 300 HCC-related human miRNAs were identified in GEO dataset and TCGA, respectively. Thereinto seven miRNAs including hsa-miR-199a-3p, hsa-miR-199b-3p, hsa-miR-139-5p, hsa-miR-139-3p, hsa-miR-424-3p, hsa-miR-1269b and hsa-miR-1269a were key miRNAs related to HCC. Functional enrichment analysis showed that these key miRNAs were involved in multiple biological processes, such as telomere maintenance via telomerase, protein sumoylation, histone mRNA metabolic process and angiotensin maturation. Cox regression analysis indicated that hsa-miR-139-5p expression was associated with the prognosis of HCC patients. ROC curve analysis suggested that survival prediction model developed based on tumor stage and hsa-miR-139-5p exhibited good performance in predicting 3-year overall survival of HCC patients. Significance The present study identified several HCC-related miRNAs, which might serve as new diagnostic markers and therapeutic targets for HCC. In addition, hsa-miR-139-5p might act as a promising prognostic indicator for HCC patients.