Transfer RNA-derived small RNA(tsRNA) is a type of non-coding tRNA undergoing cleavage by specific nucleases such as Dicer. TsRNAs comprise of tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs). Based on the splicing site within the tRNA, tRFs can be classified into tRF-1, tRF-2, tRF-3, tRF-5, and i-tRF. TiRNAs can be classified into 5′-tiRNA and 3′-tiRNA. Both tRFs and tiRNAs have important roles in carcinogenesis, especially cancer of digestive system. TRFs and tiRNAs can promote cell proliferation and cell cycle progression by regulating the expression of oncogenes, combining with RNA binding proteins such as Y-box binding protein 1 (YBX1) to prevent transcription. Despite many reviews on the basic biological function of tRFs and tiRNAs, few have described their correlation with tumors especially gastrointestinal tumor. This review focused on the relationship of tRFs and tiRNAs with the biological behavior, clinicopathological characteristics, diagnosis, treatment and prognosis of digestive system tumors, and would provide novel insights for the early detection and treatment of digestive system tumors.

Background: Single-nucleotide polymorphisms (SNPs) in lncRNAs could be biomarkers for susceptibility to colorectal cancer (CRC), but the association of PCAT1 polymorphisms and CRC susceptibility is yet to be studied. Methods: Five tagSNPs covering the PCAT1 gene were detected through Kompetitive Allele-Specific PCR among 436 CRC patients and 510 controls. An expression quantitative trait locus (eQTL) bioinformatic analysis was then performed. Results: In the present study, PCAT1 rs2632159 polymorphism increased CRC risk by 1.37-fold and 2.19-fold in the dominant and recessive models, respectively (P=0.040 and 0.041). When the CRC cases were divided into colon cancer and rectal cancer, we found that this polymorphism affected colon cancer risk under the dominant model (P=0.022, OR = 1.51) and affected rectal cancer susceptibility under the recessive model (P=0.009, OR = 3.03). A more pronounced effect was observed in the male subgroup in that PCAT1 rs2632159 SNP increased rectal cancer risk by 3.97-fold (P=0.017). When PCAT1 rs2632159 was present, epistatic effects were observed with rs1902432 and rs785005 (P=0.011 and 0.008, respectively). eQTL analysis showed that rs2632159 could influence binding with the transcription factors EBF, LUN-1, and TCF12. Conclusion:PCAT1 rs2632159 SNP could be a biomarker for CRC risk. And the rs1902432 SNP might only have potential to be a biomarker for colon cancer risk.

Cellular senescence is widely acknowledged as having strong associations with cancer. However, the intricate relationships between cellular senescence-related (CSR) genes and cancer risk remain poorly explored, with insights on causality remaining elusive. In this study, Mendelian Randomization (MR) analyses were used to draw causal inferences from 866 CSR genes as exposures and summary statistics for 18 common cancers as outcomes. We focused on genetic variants affecting gene expression, DNA methylation, and protein expression quantitative trait loci (cis-eQTL, cis-mQTL, and cis-pQTL, respectively), which were strongly linked to CSR genes alterations. Variants were selected as instrumental variables (IVs) and analyzed for causality with cancer using both summary-data-based MR (SMR) and two-sample MR (TSMR) approaches. Bayesian colocalization was used to unravel potential regulatory mechanisms underpinning risk variants in cancer, and further validate the robustness of MR results. We identified five CSR genes (CNOT6, DNMT3B, MAP2K1, TBPL1, and SREBF1), 18 DNA methylation genes, and LAYN protein expression which were all causally associated with different cancer types. Beyond causality, a comprehensive analysis of gene function, pathways, and druggability values was also conducted. These findings provide a robust foundation for unravelling CSR genes molecular mechanisms and promoting clinical drug development for cancer.

Gastric cancer (GC) is a malignant tumour with high morbidity and mortality worldwide, and there is an urgent need for early diagnosis and precision treatment. In recent years, the role of microbiota in the occurrence and development of GC has drawn extensive attention. Particularly, the in‐depth study of GC‐related microbiota by 16S rRNA sequencing technology has offered valuable tools and new perspectives for exploring the microbial characteristics of GC patients. This review systematically summarises the microbial diversity and composition of GC and non‐GC samples based on 16S rRNA data, outlines the progress in identifying GC‐related microbial biomarkers, explores the potential mechanisms by which diagnostic microbial biomarkers influence the development of GC, and reflects on the limitations of present studies. By integrating the current evidence, this review intends to offer a new theoretical foundation and further direction for the clinical translation of microbiota research in the diagnosis and treatment of GC.

Background: Recently, the incidence of cholangiocarcinoma (CCA) has gradually increased. As CCA has a poor prognosis, the ideal survival rate is scarce for patients. The abnormal expressed tsRNAs may regulate the progression of a variety of tumors, and tsRNAs is expected to become a new diagnostic biomarker of cancer. However, the expression of tsRNAs is obscure and should be elucidated in CCA. Methods: High‐throughput RNA sequencing technology (RNA‐seq) was utilized to determine the overall expression profiles of tsRNAs in three pairs CCA and adjacent normal tissues and to screen the tsRNAs that were differentially expressed. The target genes of dysregulated tsRNAs were predicted and the biological effects and potential signaling pathways of these target genes were explored by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Quantitative real‐time polymerase chain reaction (qRT‐PCR) was used to validate 11 differentially expressed tRFs with 12 pairs CCA and adjacent normal tissues. Results: High‐throughput RNA‐seq totally demonstrated 535 dysregulated tsRNAs, of which 241 tsRNAs were upregulated, such as tRF‐21‐YLKZKWE5D，tRF‐16‐9NF5W8B，tRF‐27‐78YLKZKWE52，tRF‐19‐RLXN48KP，tRF‐33‐IK9NJ4S2I7L7DV，tRF‐19‐F8DHXYIV, and 294 tsRNAs were downregulated (tRF‐20‐739P8WQ0, tRF‐34‐JJ6RRNLIK898HR, tRF‐17‐VL8RPY5, tRF‐23‐YP9LON4VDP, tRF‐39‐EH623K76IR3DR2I2, tRF‐17‐18YKISM, tRF‐19‐Q1Q89PJZ, etc.) in CCA compared with adjacent normal tissues (|log2 [fold change] | ≥ 1 and p value <0.05). GO and KEGG enrichment analyses indicated that the target genes of dysregulated tRFs (tRF‐34‐JJ6RRNLIK898HR, tRF‐38‐0668K87SERM492V, and tRF‐39‐0668K87SERM492E2) were mainly enriched in the Notch signaling pathway, Hippo signaling pathway, cAMP signaling pathway and in growth hormone synthesis, secretion and action, etc. qRT‐PCR result showed that tRF‐34‐JJ6RRNLIK898HR/tRF‐38‐0668K87SERM492V/tRF‐39‐0668K87SERM492E2 was downregulated ( p = 0.021), and tRF‐20‐LE2WMK81 was upregulated in CCA ( p = 0.033). Conclusion: Differentially expressed tRFs in CCA are enriched in many pathways associated with neoplasms, which may impact the tumor progression and have potential to be diagnostic biomarkers and therapeutic targets of CCA.

Objectives: A bibliometric analysis for non-coding RNA and hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) was performed to describe international research status and visualize the research scope and emerging trends over the last two decades on this topic.Materials and methods: Research data of non-coding RNA and HBV-related HCC were retrieved and extracted from the Web of Science Core Collection (WoSCC) database from 1 January 2003 to 13 June 2022 and then analyzed by means of bibliometric methods. A total of 1,036 articles published in this field were assessed for specific characteristics, including the year of publication, journal, author, institution, country/region, references, and keywords. VOSviewer was employed to perform co-authorship, co-occurrence, and co-citation analyses accompanied by constructing a visual network.Results: Overall, 1,036 reports on non-coding RNA and HBV-related HCC from 2003 to 2022 were retrieved from WoSCC. The publication has gradually increased during the last two decades with 324 journals involved. Most research records (748 publications and 23,184 citations) were concentrated in China. A co-occurrence cluster analysis for the top 100 keywords was performed and four clusters were generated: (1) non-coding RNA as a molecular marker for the diagnosis and prognosis of HBV-related HCC; (2) dysregulation of non-coding RNA by hepatitis B virus X protein (HBx); (3) non-coding RNA affecting the biological behaviors of HBV-related HCC; and (4) epidemiological study for the effects of non-coding RNA on the risk of HBV-related HCC.Conclusion: The publications and citations involved in non-coding RNA and HBV-related HCC have increased over the last two decades associated with many countries, institutions, and authors. Our study revealed current development trends, global cooperation models, basic knowledge, research hotspots, and emerging frontiers in this field.