Telomere Length Maintenance and Its Transcriptional Regulation in Lynch Syndrome and Sporadic Colorectal Carcinoma

DUSP5 regulated by YTHDF1-mediated m6A modification promotes epithelial-mesenchymal transition and EGFR-TKI resistance via the TGF-β/Smad signaling pathway in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) patients have a dismal survival rate because of cancer metastasis and drug resistance. The study aims to identify the genes that concurrently modulate EMT, metastasis and EGFR-TKI resistance, and to investigate the underlying regulatory mechanisms.

METHODS

Cox regression and Kaplan-Meier analyses were applied to identify prognostic oncogenes in LUAD. Gene set enrichment analysis (GSEA) was used to indicate the biological functions of the gene. Wound-healing and Transwell assays were used to detect migratory and invasive ability. EGFR-TKI sensitivity was evaluated by assessing the proliferation, clonogenic survival and metastatic capability of cancer cells with treatment with gefitinib. Methylated RNA immunoprecipitation (MeRIP) and RNA immunoprecipitation (RIP) analyses established the level of m6A modification present on the target gene and the protein's capability to interact with RNA, respectively. Single-sample gene set enrichment (ssGSEA) algorithm used to investigate levels of immune cell infiltration.

RESULTS

Our study identified dual-specificity phosphatase 5 (DUSP5) as a novel and powerful predictor of adverse outcomes for LUAD by using public datasets. Functional enrichment analysis found that DUSP5 was positively enriched in EMT and transforming growth factor-beta (TGF-β) signaling pathway, a prevailing pathway involved in the induction of EMT. As expected, DUSP5 knockdown suppressed EMT via inhibiting the canonical TGF-β/Smad signaling pathway in in vitro experiments. Consistently, knockdown of DUSP5 was first found to inhibit migratory ability and invasiveness of LUAD cells in in vitro and prevent lung metastasis in in vivo. DUSP5 knockdown re-sensitized gefitinib-resistant LUAD cells to gefitinib, accompanying reversion of EMT progress. In LUAD tissue samples, we found 14 cytosine-phosphate-guanine (CpG) sites of DUSP5 that were negatively associated with DUSP5 gene expression. Importantly, 5'Azacytidine (AZA), an FDA-approved DNA methyltransferase inhibitor, restored DUSP5 expression. Moreover, RIP experiments confirmed that YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), a m6A reader protein, could bind DUSP5 mRNA. YTHDF1 promoted DUSP5 expression and the malignant phenotype of LUAD cells. In addition, the DUSP5-derived genomic model revealed the two clusters with distinguishable immune features and tumor mutational burden (TMB).

CONCLUSIONS

Briefly, our study discovered DUSP5 which was regulated by epigenetic modification, might be a potential therapeutic target, especially in LUAD patients with acquired EGFR-TKI resistance.

Association of Relative Telomere Length and LINE-1 Methylation with Autism but not with Severity

Autism is associated with genomic instability, which is regulated by telomere length (TL) and index of global methylation (LINE-1). This study will determine relative TL (RTL) and LINE-1 methylation percentage for 69 patients and 33 control subjects to evaluate their potential role as biomarkers for autism. The results displayed a significant decrease of both RTL and LINE-1 methylation in autistic cases relative to controls (P < 0.001). Analysis of receiver operating characteristics curve revealed that both of RTL and LINE-1 methylation percentage have the ability to serve as autism biomarkers (area under the curve = 0.817 and 0.889, respectively). The statistical analysis revealed positive correlation between the two biomarkers (correlation coefficient = 0.439 and P < 0.001).

Pan-cancer analysis of telomere maintenance mechanisms

Telomeres, protective caps at chromosome ends, maintain genomic stability and control cell lifespan. Dysregulated telomere maintenance mechanisms (TMMs) are cancer hallmarks, enabling unchecked cell proliferation. We conducted a pan-cancer evaluation of TMM using RNA sequencing data from The Cancer Genome Atlas for 33 different cancer types and analyzed the activities of telomerase-dependent (TEL) and alternative lengthening of telomeres (ALT) TMM pathways in detail. To further characterize the TMM profiles, we categorized the tumors based on their ALT and TEL TMM pathway activities into five major phenotypes: ALT high TEL low, ALT low TEL low, ALT middle TEL middle, ALT high TEL high, and ALT low TEL high. These phenotypes refer to variations in telomere maintenance strategies, shedding light on the heterogeneous nature of telomere regulation in cancer. Moreover, we investigated the clinical implications of TMM phenotypes by examining their associations with clinical characteristics and patient outcomes. Specific TMM profiles were linked to specific survival patterns, emphasizing the potential of TMM profiling as a prognostic indicator and aiding in personalized cancer treatment strategies. Gene ontology analysis of the TMM phenotypes unveiled enriched biological processes associated with cell cycle regulation (both TEL and ALT), DNA replication (TEL), and chromosome dynamics (ALT) showing that telomere maintenance is tightly intertwined with cellular processes governing proliferation and genomic stability. Overall, our study provides an overview of the complexity of transcriptional regulation of telomere maintenance mechanisms in cancer.

Integrated Bioinformatic Analysis of Differentially Expressed Genes Associated with Wound Healing

OBJECTIVE

Wound healing is a complex process involving the coordinated interaction of various genes and molecular
pathways. The study aimed to uncover novel therapeutic targets, biomarkers and candidate genes for drug development
to improve successful wound repair interventions.
Materials and Methods: This study is a network-meta analysis study. Nine wound healing microarray datasets obtained
from the Gene Expression Omnibus (GEO) database were used for this study. Differentially expressed genes (DEGs)
were described using the Limma package and shared genes were used as input for weighted gene co-expression
network analysis. The Gene Ontology analysis was performed using the EnrichR web server, and construction of a
protein-protein interaction (PPI) network was achieved by the STRING and Cytoscape.
Results: A total of 424 DEGs were determined. A co-expression network was constructed using 7692 shared genes
between nine data sets, resulting in the identification of seven modules. Among these modules, those with the top 20
genes of up and down-regulation were selected. The top down-regulated genes, including TJP1, SEC61A1, PLEK,
ATP5B, PDIA6, PIK3R1, SRGN, SDC2, and RBBP7, and the top up-regulated genes including RPS27A, EEF1A1,
HNRNPA1, CTNNB1, POLR2A, CFL1, CSNk1E, HSPD1, FN1, and AURKB, which can potentially serve as therapeutic
targets were identified. The KEGG pathway analysis found that the majority of the genes are enriched in the "Wnt
signaling pathway".
Conclusion: In our study of nine wound healing microarray datasets, we identified DEGs and co-expressed modules
using WGCNA. These genes are involved in important cellular processes such as transcription, translation, and posttranslational
modifications. We found nine down-regulated genes and ten up-regulated genes, which could serve as
potential therapeutic targets for further experimental validation. Targeting pathways related to protein synthesis and cell
adhesion and migration may enhance wound healing, but additional experimental validation is needed to confirm the
effectiveness and safety of targeted interventions.

Unedited allogeneic iNKT cells show extended persistence in MHC-mismatched canine recipients

Allogeneic invariant natural killer T cells (allo-iNKTs) induce clinical remission in patients with otherwise incurable cancers and COVID-19-related acute respiratory failure. However, their functionality is inconsistent among individuals, and they become rapidly undetectable after infusion, raising concerns over rejection and limited therapeutic potential. We validate a strategy to promote allo-iNKT persistence in dogs, an established large-animal model for novel cellular therapies. We identify donor-specific iNKT biomarkers of survival and sustained functionality, conserved in dogs and humans and retained upon chimeric antigen receptor engineering. We reason that infusing optimal allo-iNKTs enriched in these biomarkers will prolong their persistence without requiring MHC ablation, high-intensity chemotherapy, or cytokine supplementation. Optimal allo-iNKTs transferred into MHC-mismatched dogs remain detectable for at least 78 days, exhibiting sustained immunomodulatory effects. Our canine model will accelerate biomarker discovery of optimal allo-iNKT products, furthering application of MHC-unedited allo-iNKTs as a readily accessible universal platform to treat incurable conditions worldwide.

PSF toolkit: an R package for pathway curation and topology-aware analysis

Most high throughput genomic data analysis pipelines currently rely on over-representation or gene set enrichment analysis (ORA/GSEA) approaches for functional analysis. In contrast, topology-based pathway analysis methods, which offer a more biologically informed perspective by incorporating interaction and topology information, have remained underutilized and inaccessible due to various limiting factors. These methods heavily rely on the quality of pathway topologies and often utilize predefined topologies from databases without assessing their correctness. To address these issues and make topology-aware pathway analysis more accessible and flexible, we introduce the PSF (Pathway Signal Flow) toolkit R package. Our toolkit integrates pathway curation and topology-based analysis, providing interactive and command-line tools that facilitate pathway importation, correction, and modification from diverse sources. This enables users to perform topology-based pathway signal flow analysis in both interactive and command-line modes. To showcase the toolkit's usability, we curated 36 KEGG signaling pathways and conducted several use-case studies, comparing our method with ORA and the topology-based signaling pathway impact analysis (SPIA) method. The results demonstrate that the algorithm can effectively identify ORA enriched pathways while providing more detailed branch-level information. Moreover, in contrast to the SPIA method, it offers the advantage of being cut-off free and less susceptible to the variability caused by selection thresholds. By combining pathway curation and topology-based analysis, the PSF toolkit enhances the quality, flexibility, and accessibility of topology-aware pathway analysis. Researchers can now easily import pathways from various sources, correct and modify them as needed, and perform detailed topology-based pathway signal flow analysis. In summary, our PSF toolkit offers an integrated solution that addresses the limitations of current topology-based pathway analysis methods. By providing interactive and command-line tools for pathway curation and topology-based analysis, we empower researchers to conduct comprehensive pathway analyses across a wide range of applications.

Transcriptomic Maps of Colorectal Liver Metastasis: Machine Learning of Gene Activation Patterns and Epigenetic Trajectories in Support of Precision Medicine

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Specific Blood Plasma Circulating miRs Are Associated with the Physiological Impact of Total Fish Meal Replacement with Soybean Meal in Diets for Rainbow Trout (Oncorhynchus mykiss)

High dietary SBM content is known to induce important physiological alterations, hampering its use as a major FM alternative. Rainbow trout (Oncorhynchus mykiss) juveniles were fed two experimental diets during 9 weeks: (i) a FM diet containing 12% FM; and (ii) a vegetable meal (VM) diet totally devoid of FM and based on SBM (26%). Fish fed the VM diet did not show reduced growth performance when compared with fish fed the FM diet. Nevertheless, fish fed the VM diet had an increased viscerosomatic index, lower apparent fat digestibility, higher aminopeptidase enzyme activity and number of villi fusions, and lower α-amylase enzyme activity and brush border integrity. Small RNA-Seq analysis identified six miRs (omy-miR-730a-5p, omy-miR-135c-5p, omy-miR-93a-3p, omy-miR-152-5p, omy-miR-133a-5p, and omy-miR-196a-3p) with higher expression in blood plasma from fish fed the VM diet. Bioinformatic prediction of target mRNAs identified several overrepresented biological processes known to be associated with high dietary SBM content (e.g., lipid metabolism, epithelial integrity disruption, and bile acid status). The present research work increases our understanding of how SBM dietary content has a physiological impact in farmed fish and suggests circulating miRs might be suitable, integrative, and less invasive biomarkers in fish.

Association of longer telomere length in cancer cells and cancer-associated fibroblasts with worse prognosis

BACKGROUND

Telomere dysfunction has been reported to be directly involved in carcinogenesis owing to chromosomal instability and immortalization; however, the clinicopathological significance of telomeres remains controversial. We have shown that telomere shortening occurs in normal-appearing duct cells at initiation and then continues during the progression of pancreatic cancer. In this study, we determined the clinicopathological and prognostic value of telomere length (TL) in cancer progression.

METHODS

TL in both cancer cells and cancer-associated fibroblasts (CAFs) was analyzed by high-throughput quantitative fluorescence in situ hybridization using a previously reported cohort comprising 1434 cases of adenocarcinoma (ADC), squamous cell carcinoma (SCC), adenosquamous carcinoma, hepatocellular carcinoma, and renal cell carcinoma (RCC), which are known cancers with a statistically significantly low incidence of alternative lengthening of telomeres. Cases were divided into 2 groups as follows: longer and shorter telomeres, according to the median TL of cancer cells and CAFs. The statistical significance of TL in cancer cells and CAFs on clinicopathological characteristics and prognosis was analyzed.

RESULTS

There was a close association between TL in cancer cells and CAFs. Longer telomeres in cancer cells and CAFs were associated with aggressive features such as advanced stage, high mitosis score and nuclear score, poorly differentiated cancer, and desmoplastic stroma in ADC. Furthermore, a longer TL was an independent prognostic factor for ADC, SCC, and RCC.

CONCLUSIONS

Longer telomeres are associated with worse prognosis in ADC, SCC, and RCC. Thus, TL is a novel biomarker for the diagnosis of aggressive cancers with poor prognoses.

Integrative multiomics evaluation reveals the importance of pseudouridine synthases in hepatocellular carcinoma

Background: The pseudouridine synthases (PUSs) have been reported to be associated with cancers. However, their involvement in hepatocellular carcinoma (HCC) has not been well documented. Here, we assess the roles of PUSs in HCC. Methods: RNA sequencing data of TCGA-LIHC and LIRI-JP were downloaded from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), respectively. GSE36376 gene expression microarray was downloaded from the Gene Expression Omnibus (GEO). Proteomics data for an HBV-related HCC cohort was obtained from the CPTAC Data Portal. The RT-qPCR assay was performed to measure the relative mRNA expression of genes in clinical tissues and cell lines. Diagnostic efficiency was evaluated by the ROC curve. Prognostic value was assessed using the Kaplan-Meier curve, Cox regression model, and time-dependent ROC curve. Copy number variation (CNV) was analyzed using the GSCA database. Functional analysis was carried out with GSEA, GSVA, and clusterProfiler package. The tumor microenvironment (TME) related analysis was performed using ssGSEA and the ESTIMATE algorithm. Results: We identified 7 PUSs that were significantly upregulated in HCC, and 5 of them (DKC1, PUS1, PUS7, PUSL1, and RPUSD3) were independent risk factors for patients' OS. Meanwhile, the protein expression of DKC1, PUS1, and PUS7 was also upregulated and related to poor survival. Both mRNA and protein of these PUSs were highly diagnostic of HCC. Moreover, the CNV of PUS1, PUS7, PUS7L, and RPUSD2 was also associated with prognosis. Further functional analysis revealed that PUSs were mainly involved in pathways such as genetic information processing, substance metabolism, cell cycle, and immune regulation. Conclusion: PUSs may play crucial roles in HCC and could be used as potential biomarkers for the diagnosis and prognosis of patients.

Translational Regulation by eIFs and RNA Modifications in Cancer

Translation is a fundamental process in all living organisms that involves the decoding of genetic information in mRNA by ribosomes and translation factors. The dysregulation of mRNA translation is a common feature of tumorigenesis. Protein expression reflects the total outcome of multiple regulatory mechanisms that change the metabolism of mRNA pathways from synthesis to degradation. Accumulated evidence has clarified the role of an increasing amount of mRNA modifications at each phase of the pathway, resulting in translational output. Translation machinery is directly affected by mRNA modifications, influencing translation initiation, elongation, and termination or altering mRNA abundance and subcellular localization. In this review, we focus on the translation initiation factors associated with cancer as well as several important RNA modifications, for which we describe their association with cancer.

Single Cell Analysis of Gastric Cancer Reveals Non-Defined Telomere Maintenance Mechanism

Telomere maintenance mechanisms (TMMs) are important for cell survival and homeostasis. However, most related cancer research studies have used heterogenous bulk tumor tissue, which consists of various single cells, and the cell type properties cannot be precisely recognized. In particular, cells exhibiting non-defined TMM (NDTMM) indicate a poorer prognosis than those exhibiting alternative lengthening of telomere (ALT)-like mechanisms. In this study, we used bioinformatics to classify TMMs by cell type in gastric cancer (GC) in single cells and compared the biological processes of each TMM. We elucidated the pharmacological vulnerabilities of NDTMM type cells, which are associated with poor prognosis, based on molecular mechanisms. We analyzed differentially expressed genes in cells exhibiting different TMMs in two single-cell GC cohorts and the pathways enriched in single cells. NDTMM type cells showed high stemness, epithelial-mesenchymal transition, cancer hallmark activity, and metabolic reprogramming with mitochondrial abnormalities. Nuclear receptor subfamily 4 group A member 1 (NR4A1) activated parkin-dependent mitophagy in association with tumor necrosis factor-alpha (TNFA) to maintain cellular homeostasis without TMM. NR4A1 overexpression affected TNFA-induced GC cell apoptosis by inhibiting Jun N-terminal kinase/parkin-dependent mitophagy. Our findings also revealed that NR4A1 is involved in cell cycle mediation, inflammation, and apoptosis to maintain cell homeostasis, and is a novel potential therapeutic target in recalcitrant GC.

Relative Telomere Length Change in Colorectal Carcinoma and Its Association with Tumor Characteristics, Gene Expression and Microsatellite Instability

We compared tumor and adjacent normal tissue samples from 165 colorectal carcinoma (CRC) patients to study change in relative telomere length (RTL) and its association with different histological and molecular features. To measure RTL, we used a Luminex-based assay. We observed shorter RTL in the CRC tissue compared to paired normal tissue (RTL 0.722 ± SD 0.277 vs. 0.809 ± SD 0.242, p = 0.00012). This magnitude of RTL shortening (by ~0.08) in tumor tissue is equivalent to RTL shortening seen in human leukocytes over 10 years of aging measured by the same assay. RTL was shorter in cancer tissue, irrespective of age group, gender, tumor pathology, location and microsatellite instability (MSI) status. RTL shortening was more prominent in low-grade CRC and in the presence of microsatellite instability (MSI). In a subset of patients, we also examined differential gene expression of (a) telomere-related genes, (b) genes in selected cancer-related pathways and (c) genes at the genome-wide level in CRC tissues to determine the association between gene expression and RTL changes. RTL shortening in CRC was associated with (a) upregulation of DNA replication genes, cyclin dependent-kinase genes (anti-tumor suppressor) and (b) downregulation of "caspase executor", reducing apoptosis.

Tumor Microenvironment Profiling Identifies Prognostic Signatures and Suggests Immunotherapeutic Benefits in Neuroblastoma

The tumor microenvironment (TME) influences disease initiation and progression. Cross-talks of cells within TME can affect the efficacy of immunotherapies. However, a precise, concise, and comprehensive TME landscape in neuroblastoma (NB) has not been established. Here, we profiled the TME landscape of 498 NB-related patients on a self-curated gene list and identified three prognostic TMEsubgroups. The differentially expressed genes in these three TMEsubgroups were used to construct a genetic signature of the TME landscape and characterize three GeneSubgroups. The subgroup with the worst overall survival prognosis, the TMEsubgroup/GeneSubgroup3, lacked immune cell infiltration and received the highest scores of MYCN- and ALK-related signatures and lowest scores of immune pathways. Additionally, we found that the GeneSubgroup3 might be benefited from anti-GD2 instead of anti-PD-1 therapy. We further created a 48-gene signature, the TMEscore, to infer prognosis and validated it in three independent NB cohorts and a pan-cancer cohort of 9,460 patients. We did RNA-seq on 16 samples and verified that TMEscore was higher in patients with stage 3/4 than stage 1/2 diseases. The TMEscore could also predict responses for several immunotherapies. After adding clinical features, we found that the nomogram-based score system, the TMEIndex, surpassed the current risk system at predicting survivals. Our analysis explained TME at the transcriptome level and paved the way for immunotherapies in NB.

Telomere maintenance mechanism dysregulation serves as an early predictor of adjuvant therapy response and a potential therapeutic target in human cancers

Telomere maintenance mechanisms (TMMs) rescue cells from telomere crisis, endow cells immortal property, stabilize genomic integrity. However, TMM-associated molecular profiles and their clinical outcomes in cancer remain elusive. Here, we performed a pan-cancer and integrated analysis of TMM gene expression profiles from 10,107 unique samples with clinicopathological, molecular and outcome features across 7 malignancies from the same microarray platform (Affymetrix GPL570 platform). This resource was divided into Case-Control datasets for obtaining dysregulated TMM genes and Survival datasets for evaluating clinical outcomes. Multidimensional data from The Cancer Genome Atlas (TCGA) were used to elucidate associations between TMM dysregulation and survival, genomic instability. Our results demonstrated that TMMs had a consistent dysregulation spectrum across cancers, based on which we developed the TMM-dysregulation signature TMScore that was positively associated with various tumor adverse features. Two opposite prognostic patterns of TMScore independent of clinicopathological and molecular characteristics were identified, which might be explained by genomic instability: breast and lung cancer patients with elevated TMScore had inferior outcomes, suggesting TMScore-related genes as potential therapeutic targets, on the contrary, colon and stomach cancer patients had superior outcomes. Most important, the prognostic value of TMScore was still significant regardless of whether patients had received adjuvant therapy, which was valuable for discriminating non-responders from responders, and could predict the effectiveness of adjuvant therapy. In summary, our resources delineate TMMs dysregulated landscape across cancers, shed light on the impact of TMMs dysregulation on patient outcomes and adjuvant therapy, and provide novel therapeutic opportunities for cancer treatment.

The Transcriptome and Methylome of the Developing and Aging Brain and Their Relations to Gliomas and Psychological Disorders

Mutually linked expression and methylation dynamics in the brain govern genome regulation over the whole lifetime with an impact on cognition, psychological disorders, and cancer. We performed a joint study of gene expression and DNA methylation of brain tissue originating from the human prefrontal cortex of individuals across the lifespan to describe changes in cellular programs and their regulation by epigenetic mechanisms. The analysis considers previous knowledge in terms of functional gene signatures and chromatin states derived from independent studies, aging profiles of a battery of chromatin modifying enzymes, and data of gliomas and neuropsychological disorders for a holistic view on the development and aging of the brain. Expression and methylation changes from babies to elderly adults decompose into different modes associated with the serial activation of (brain) developmental, learning, metabolic and inflammatory functions, where methylation in gene promoters mostly represses transcription. Expression of genes encoding methylome modifying enzymes is very diverse reflecting complex regulations during lifetime which also associates with the marked remodeling of chromatin between permissive and restrictive states. Data of brain cancer and psychotic disorders reveal footprints of pathophysiologies related to brain development and aging. Comparison of aging brains with gliomas supports the view that glioblastoma-like and astrocytoma-like tumors exhibit higher cellular plasticity activated in the developing healthy brain while oligodendrogliomas have a more stable differentiation hierarchy more resembling the aged brain. The balance and specific shifts between volatile and stable and between more irreversible and more plastic epigenomic networks govern the development and aging of healthy and diseased brain.

Pan-Cancer Analysis of Clinical Relevance via Telomere Maintenance Mechanism

Understanding the telomere maintenance mechanism (TMM) in immortal cancer cells is vital for TMM-targeted therapies in clinical settings. In this study, we classified four telomere maintenance mechanisms into telomerase, ALT, telomerase + ALT, and non-defined telomere maintenance mechanism (NDTMM) across 31 cancer types using 10,704 transcriptomic datasets from The Cancer Genome Atlas. Our results demonstrated that approximately 50% of the total cohort displayed ALT activity with high telomerase activity in most cancer types. We confirmed significant patient prognoses according to distinct TMMs in six cancer types: adrenocortical carcinoma (ACC), PAAD, HNSC, SARC, GBM, and metastatic cancer. Patients with metastasis had a poor prognosis in the ALT group (p < 0.006) subjected to RAS protein signal transduction. Glioblastoma patients had poor prognosis in NDTMM (p < 0.0043) and showed high levels of myeloid leukocyte activation. Pancreatic adenocarcinoma (p < 0.04) and head and neck squamous cell carcinoma (p < 0.046) patients had a good prognosis in the ALT group with high immune cell activation. Furthermore, we showed that master transcriptional regulators might affect the selection of the TMM pathway and explained why different telomere maintenance mechanisms exist. Furthermore, they can be used to segregate patients and predict responders to different TMM-targeted therapeutics.

High-Resolution Cartography of the Transcriptome and Methylome Landscapes of Diffuse Gliomas

Molecular mechanisms of lower-grade (II-III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendroglioma-like (IDH-O) tumors both carrying mutations(s) at the isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma resemblance. We generated detailed maps of the transcriptomes and DNA methylomes, revealing that cell functions divided into three major archetypic hallmarks: (i) increased proliferation in IDH-wt and, to a lesser degree, IDH-O; (ii) increased inflammation in IDH-A and IDH-wt; and (iii) the loss of synaptic transmission in all subtypes. Immunogenic properties of IDH-A are diverse, partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We analyzed details of coregulation between gene expression and DNA methylation and of the immunogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby, molecular cartography provides a graphical coordinate system that links gene-level information with glioma subtypes, their phenotypes, and clinical context.

A genetic variant in telomerase reverse transcriptase (TERT) modifies cancer risk in Lynch syndrome patients harbouring pathogenic MSH2 variants

Individuals with Lynch syndrome (LS), have an increased risk of developing cancer. Common genetic variants of telomerase reverse transcriptase (TERT) have been associated with a wide range of cancers, including colorectal cancer (CRC) in LS. We combined genotype data from 1881 LS patients, carrying pathogenic variants in MLH1, MSH2 or MSH6, for rs2075786 (G>A, intronic variant), 1207 LS patients for rs2736108 (C>T, upstream variant) and 1201 LS patients for rs7705526 (C>A, intronic variant). The risk of cancer was estimated by heterozygous/homozygous odds ratio (OR) with mixed-effects logistic regression to adjust for gene/gender/country of sample origin considering family identity. The AA genotype of SNP rs2075786 is associated with 85% higher odds at developing cancer compared to GG genotype in MSH2 pathogenic variant carriers (p = 0.0160). Kaplan-Meier analysis also shows an association for rs2075786; the AA allele for MSH2 variant carriers confers risk for earlier diagnosis of LS cancer (log-rank p = 0.0011). We report a polymorphism in TERT to be a possible modifier of disease risk in MSH2 pathogenic variant carriers. The rs2075786 SNP in TERT is associated with a differential risk of developing cancer for MSH2 pathogenic variant carriers. Use of this information has the potential to personalise screening protocols for LS patients.

Telomere Maintenance Pathway Activity Analysis Enables Tissue- and Gene-Level Inferences

Telomere maintenance is one of the mechanisms ensuring indefinite divisions of cancer and stem cells. Good understanding of telomere maintenance mechanisms (TMM) is important for studying cancers and designing therapies. However, molecular factors triggering selective activation of either the telomerase dependent (TEL) or the alternative lengthening of telomeres (ALT) pathway are poorly understood. In addition, more accurate and easy-to-use methodologies are required for TMM phenotyping. In this study, we have performed literature based reconstruction of signaling pathways for the ALT and TEL TMMs. Gene expression data were used for computational assessment of TMM pathway activities and compared with experimental assays for TEL and ALT. Explicit consideration of pathway topology makes bioinformatics analysis more informative compared to computational methods based on simple summary measures of gene expression. Application to healthy human tissues showed high ALT and TEL pathway activities in testis, and identified genes and pathways that may trigger TMM activation. Our approach offers a novel option for systematic investigation of TMM activation patterns across cancers and healthy tissues for dissecting pathway-based molecular markers with diagnostic impact.

The role of m6A, m5C and Ψ RNA modifications in cancer: Novel therapeutic opportunities

RNA modifications have recently emerged as critical posttranscriptional regulators of gene expression programmes. Significant advances have been made in understanding the functional role of RNA modifications in regulating coding and non-coding RNA processing and function, which in turn thoroughly shape distinct gene expression programmes. They affect diverse biological processes, and the correct deposition of many of these modifications is required for normal development. Alterations of their deposition are implicated in several diseases, including cancer. In this Review, we focus on the occurrence of N⁶-methyladenosine (m⁶A), 5-methylcytosine (m⁵C) and pseudouridine (Ψ) in coding and non-coding RNAs and describe their physiopathological role in cancer. We will highlight the latest insights into the mechanisms of how these posttranscriptional modifications influence tumour development, maintenance, and progression. Finally, we will summarize the latest advances on the development of small molecule inhibitors that target specific writers or erasers to rewind the epitranscriptome of a cancer cell and their therapeutic potential.

Clinicopathological Characteristics of TZAP Expression in Colorectal Cancers

Purpose

The zinc finger protein, ZBTB48, is a telomere-associated protein. It was renamed as telomeric zinc finger-associated protein (TZAP) binding to elongated telomeres. However, its expression level was not measured in cancers.

Patients and Methods

We analyzed TZAP mRNA levels in 60 colorectal cancers (CRC) and its correlation with telomere length and TERT was studied.

Results

TZAP mRNA in CRC was higher statistically than that in paired non-cancerous tissues (p = 0.033). Higher TZAP was found in carcinoembryonic antigen (CEA)-positive CRCs (>5 ng/mL) (p = 0.012). Shorter telomere was found in CRCs with high TZAP expression than that with low TZAP expression (p = 0.010). According to quantitative correlation analysis, TZAP has a correlation with age (r = −0.349, p = 0.007), TERT (r = 0.279, p = 0.041) and telomere length (r = −0.305, p = 0.021). TZAP expression did not harbor prognostic value in CRC. Inhibition of TZAP expression by siRNA suppresses cell growth in HT29 cells; however, it resulted in increased cell viability in HCT116 cells. TZAP inhibition induces a decrease in mRNA levels of TERT in both HT29 and HCT116 cells. TCGA data analysis showed higher expression of TZAP showed poorer overall survival in colon cancer (p = 0.001); however, it did not have a significance in rectal cancer (p = 0.951).

Conclusion

We suggested that TZAP may be a possible biomarker for CRC.

Telomere Instability in Lynch Syndrome Families Leads to Some Shorter Telomeres in MSH2+/- Carriers

Lynch syndrome (LS) is an inherited predisposition to early onset of various cancers, caused by mutation in a DNA mismatch repair (MMR) gene. In heterozygous MMR^+/− carriers, somatic mutation, loss or silencing of the wild type allele increases the mutation rate, facilitating the initiation of MMR-defective cancers. These cancers are characterized by instability at short tandem repeats (STRs) and in telomeric DNA. We have investigated telomere length in saliva DNA from LS and control families, using single telomere analysis at XpYp and 12q and by qPCR to measure total telomeric DNA. Single telomere analysis showed a trend for shorter XpYp telomeres in MSH2^+/− carriers compared to MLH1^+/− carriers or controls, but this was masked in the comparative analysis of total telomeric DNA. Comparison of age-adjusted telomere length within families showed that neither MSH2^+/− or MLH1^+/− children had consistently shorter or longer telomeres than their MMR^+/− parent, indicating the absence of an inter-generational effect on telomere length. Unexpectedly however, wildtype children in families with MSH2 mutations, had significantly longer XpYp telomeres than their MMR^+/− parent. Altogether our data suggest that MMR insufficiency, particularly in MSH2^+/− carriers, increases telomere instability and somatic cell turnover during the lifetime of LS mutation carriers but has minimal consequences for telomere length in the germline.

The Human Blood Transcriptome in a Large Population Cohort and Its Relation to Aging and Health

Background: The blood transcriptome is expected to provide a detailed picture of an organism's physiological state with potential outcomes for applications in medical diagnostics and molecular and epidemiological research. We here present the analysis of blood specimens of 3,388 adult individuals, together with phenotype characteristics such as disease history, medication status, lifestyle factors, and body mass index (BMI). The size and heterogeneity of this data challenges analytics in terms of dimension reduction, knowledge mining, feature extraction, and data integration.

Methods: Self-organizing maps (SOM)-machine learning was applied to study transcriptional states on a population-wide scale. This method permits a detailed description and visualization of the molecular heterogeneity of transcriptomes and of their association with different phenotypic features.

Results: The diversity of transcriptomes is described by personalized SOM-portraits, which specify the samples in terms of modules of co-expressed genes of different functional context. We identified two major blood transcriptome types where type 1 was found more in men, the elderly, and overweight people and it upregulated genes associated with inflammation and increased heme metabolism, while type 2 was predominantly found in women, younger, and normal weight participants and it was associated with activated immune responses, transcriptional, ribosomal, mitochondrial, and telomere-maintenance cell-functions. We find a striking overlap of signatures shared by multiple diseases, aging, and obesity driven by an underlying common pattern, which was associated with the immune response and the increase of inflammatory processes.

Conclusions: Machine learning applications for large and heterogeneous omics data provide a holistic view on the diversity of the human blood transcriptome. It provides a tool for comparative analyses of transcriptional signatures and of associated phenotypes in population studies and medical applications.

Pan-Cancer Analysis of Alternative Lengthening of Telomere Activity

Alternative lengthening of telomeres (ALT) is a telomerase-independent mechanism that extends telomeres in cancer cells. It influences tumorigenesis and patient survival. Despite the clinical significance of ALT in tumors, the manner in which ALT is activated and influences prognostic outcomes in distinct cancer types is unclear. In this work, we profiled distinct telomere maintenance mechanisms (TMMs) using 8953 transcriptomes of 31 different cancer types from The Cancer Genome Atlas (TCGA). Our results demonstrated that approximately 29% of cancer types display high ALT activity with low telomerase activity in the telomere-lengthening group. Among the distinct ALT mechanisms, homologous recombination was frequently observed in sarcoma, adrenocortical carcinoma, and kidney chromophobe. Five cancer types showed a significant difference in survival in the presence of high ALT activity. Sarcoma patients with elevated ALT had unfavorable risks (p < 0.038) coupled with a high expression of TOP2A, suggesting this as a potential drug target. On the contrary, glioblastoma patients had favorable risks (p < 0.02), and showed low levels of antigen-presenting cells. Together, our analyses highlight cancer type-dependent TMM activities and ALT-associated genes as potential therapeutic targets.

TCGA Pan-Cancer Genomic Analysis of Alternative Lengthening of Telomeres (ALT) Related Genes

Telomere maintenance mechanisms (TMM) are used by cancer cells to avoid apoptosis, 85–90% reactivate telomerase, while 10–15% use the alternative lengthening of telomeres (ALT). Due to anti-telomerase-based treatments, some tumors switch from a telomerase-dependent mechanism to ALT; in fact, the co-existence between both mechanisms has been observed in some cancers. Although different elements in the ALT pathway are uncovered, some molecular mechanisms are still poorly understood. Therefore, with the aim to identify potential molecular markers for the study of ALT, we combined in silico approaches in a 411 telomere maintenance gene set. As a consequence, we conducted a genomic analysis of these genes in 31 Pan-Cancer Atlas studies from The Cancer Genome Atlas and found 325,936 genomic alterations; from which, we identified 20 genes highly mutated in the cancer studies. Finally, we made a protein-protein interaction network and enrichment analysis to observe the main pathways of these genes and discuss their role in ALT-related processes, like homologous recombination and homology directed repair. Overall, due to the lack of understanding of the molecular mechanisms of ALT cancers, we proposed a group of genes, which after ex vivo validations, could represent new potential therapeutic markers in the study of ALT.

LncRNA MEG3 inhibits non-small cell lung cancer via interaction with DKC1 protein

Long non-coding RNA (lncRNA) MEG3 is a key biomarker and therapeutic target in lung cancer; however, its underlying molecular mechanism in lung cancer progression remains unclear. The present study demonstrated a novel regulatory axis in lung cancer, lncRNA MEG3/dyskeratosis congenita 1 (DKC1), and further investigated the effects and molecular mechanism of lncRNA MEG3/DKC1 in lung cancer. RT-qPCR and western blot analysis were performed to determine gene and protein expression levels. The RNA immunoprecipitation assay was performed to verify binding between lncRNA MEG3 and DKC1. Flow cytometry analysis was performed to assess cell apoptosis, while the Cell Counting Kit-8 assay was performed to determine cell viability. Transwell and wound healing assays were performed to assess cell invasion and migration, respectively. Telomerase activity was measured using the quantitative TeloTAGGG Telomerase PCR-ELISA kit. The results demonstrated that lncRNA MEG3 was downregulated, while its binding protein, DKC1, was upregulated in lung cancer cells. Furthermore, lncRNA MEG3 inhibited cell proliferation, migration, invasion and telomerase activity in A549 cells by downregulating DKC1. lncRNA MEG3 inhibited non-small cell lung cancer progression by inhibiting telomere function, cell proliferation, telomerase activity, cell migration and invasion via regulation of the DKC1 protein expression. LncRNA MEG3/DKC1 was identified as a novel dual-directional regulatory axis in the present study, acting as a promising target for the treatment of lung cancer.

Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma

Background

Tumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.

Methods

RNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.

Results

LUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein–protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.

Conclusion

mRNAsi-related hub genes could be a potential biomarker of LUSC.