Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

BACKGROUND: Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. METHODS: A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. RESULTS: Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. CONCLUSIONS: Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Bibliometric analysis of aptamer-conjugated nanoparticles for diagnosis in the last two decades.

Objective.Aptamer-conjugated nanoparticles for diagnosis have recently gained increasing attention. Here, we performed a bibliometric analysis to provide an overview of this field over the past two decades.Methods. The terms 'aptamer, nanoparticles and diagnosis' were used to search for relevant original articles published in English from 2003 to 2022 in the Web of Science database. VOSviewer and CiteSpace software were employed to analyze the development process, knowledge structure, research hotspots, and potential trends in the field of aptamer-conjugated nanoparticles for diagnosis.Results. A total of 1076 original articles were retrieved, with a rapid increase in the annual output and citation. The journal 'Biosensors and Bioelectronics' has contributed the most in this field, and the most influential researcher, institution and country were Weihong Tan, the Chinese Academy of Sciences, China, respectively. Gold nanoparticles and quantum dots were the most used, but in the past three years, research hotspots focused on carbon dots and graphene quantum dots. Diagnostic directions primarily focused on cancer. The most used strategy was label-free electrochemical detection, but in the past two years, colorimetric analysis and fluorescence imaging emerged as hot topics.Conclusion.The bibliometric analysis reveals a rapid increase in the research on aptamer-conjugated nanoparticles for diagnosis, major contributors at the levels of journals, authors, institutions, and countries, and research preferences in diagnostic objects, nanoparticle types, and detection methods, as well as the evolution of research hotspots and future trends.

Evolution and Trends of Aptamers in Cancer Research: A Bibliometric Analysis of the Literature over the Last Decade.

OBJECTIVE: Aptamers are increasingly applied in cancer research. Here, we have performed the first bibliometric analysis to demonstrate the evolution of aptamers in cancer research over the past decade and to reveal future trends. METHOD: Original articles and reviews on aptamers in cancer research published from 2013 to 2022 were retrieved from the Web of Science Core Collection database. VOSviewer, CiteSpace, and R software were used for bibliometric analysis of the literature and visualization of the results. RESULTS: A total of 1627 eligible publications were analyzed. Annual and cumulative publications have been found to be steadily increased. China was the most productive country (884 publications) and Hunan University was the most productive institution (97 publications). The United States had the highest level of international collaboration (betweenness centrality = 0.55). Wei-Hong Tan was the most productive author (68 publications) and Craig Tuerk was the most cited author (387 citations). Analytical Chemistry and Biosensors and Bioelectronics were the most influential journals in this field. Three major themes were identified: aptamer selection techniques, aptamer-targeted drug delivery, and aptasensors for cancer detection. The research hotspots have shifted from aptamer selection, targeted drug delivery, molecular imaging, and biomarker detection to electrochemical aptasensors and therapeutic applications. The future may focus on high specificity and affinity in aptamer selection, aptasensor fabrication, aptamer- targeted drug delivery, and therapeutic aptamer development. CONCLUSION: The field of aptamers in cancer research has been steadily developing over the past decade, and future research may focus on aptamer application in cancer detection and therapy and the improvement of aptamer selection.

The Index sAGP is Valuable for Distinguishing Atypical Hepatocellular Carcinoma from Atypical Benign Focal Hepatic Lesions.

Purpose: The differential diagnosis of atypical hepatocellular carcinoma (aHCC) and atypical benign focal hepatic lesions (aBFHL) usually depends on pathology. This study aimed to develop non-invasive approaches based on conventional blood indicators for the differential diagnosis of aHCC and aBFHL. Patients and Methods: Hospitalized patients with pathologically confirmed focal hepatic lesions and their clinical data were retrospectively collected, in which patients with HCC with serum alpha-fetoprotein (AFP) levels of ≤200 ng/mL and atypical imaging features were designated as the aHCC group (n = 224), and patients with benign focal hepatic lesions without typical imaging features were designated as the aBFHL group (n = 178). The performance of indexes (both previously reported and newly constructed) derived from conventional blood indicators by four mathematical operations in distinguishing aHCC and aBFHL was evaluated using the receiver operating characteristic (ROC) curve and diagnostic validity metrics. Results: Among ten previously reported derived indexes related to HCC, the index GPR, the ratio of γ-glutamyltransferase (GGT) to platelet (PLT), showed the best performance in distinguishing aHCC from aBFHL with the area under ROC curve (AUROC) of 0.853 (95% CI 0.814-0.892), but the other indexes were of little value (AUROCs from 0.531 to 0.700). A new derived index, sAGP [(standardized AFP + standardized GGT)/standardized PLT], was developed and exhibited AUROCs of 0.905, 0.894, 0.891, 0.925, and 0.862 in differentiating overall, BCLC stage 0/A, TNM stage I, small, and AFP-negative aHCC from aBFHL, respectively. Conclusion: The sAGP index is an efficient, simple, and practical metric for the non-invasive differentiation of aHCC from aBFHL.

Aspirin enhances the sensitivity of hepatocellular carcinoma side population cells to doxorubicin via miR-491/ABCG2.

Objective: To explore whether aspirin (ASA) enhances the sensitivity of hepatocellular carcinoma (HCC) side population (SP) cells to doxorubicin (Doxo) via miR-491/ATP-binding cassette sub-family G member 2 (ABCG2).Methods: Non-SP and SP cells were isolated from MHCC-97L cell line using flow cytometry analysis and fluorescence-activated cell sorting. Colony formation assay was performed to determine the colony-formation ability of cells. Cell viability of SP cells was determined with the MTT assay. Luciferase reporter assay was applied in confirming the binding between miR-491 and ABCG2.Results: Although the Doxo treatment lowered the colony-formation ability of both non-SP and SP cells, the colony-formation ability of SP cells was 2-fold higher than that of non-SP cells (P<0.05). Doxo slightly inhibited the cell viability of SP cells in a concentration-dependent manner; the addition of ASA dramatically enhanced the inhibitory effect of Doxo on SP cell viability in a concentration-dependent manner (P<0.05). Compared with non-SP cells, the miR-491 expression was significantly decreased in SP cells, which was significantly reversed by ASA (P<0.05). miR-491 directly controlled the ABCG2 expression. In the presence of Doxo, miR-491 inhibitor reduced the inhibitory effect of ASA on the cell viability of SP cells, which was significantly reversed by knockdown of ABCG2 (P<0.05).Conclusion: ASA enhanced the sensitivity of SP cells to Doxo via regulating the miR-491/ABCG2 signaling pathway.