LINC00665:A Promising Biomarker in Gastrointestinal Tumors.

An increasing volume of studies has reported that long non-codingRNAs (lncRNAs) are involved in the carcinogenesis of many different cancers. Especially in gastrointestinal tumors, lncRNAs are found to participate in various physiological and pathological processes. LncRNAs can regulate gene expression at multiple levels, including transcriptional, post-transcription, translational, and post-translational levels. Long intergenic non-protein coding RNA 665(LINC00665), a novel cancer-related lncRNA, is frequently dysregulated in multiple gastrointestinal tumors, including gastric and colorectal cancers, hepatocellular carcinoma, and so on. In this review, we analyzed the expression and prognostic value of LINC00665 in human gastrointestinal tumors, systematically summarized the current literature about the clinical significance of this lncRNA, and explored the regulatory mechanisms of LINC00665 as a competing endogenous RNA (ceRNA) in tumor progression. Consequently, we concluded that LINC00665 might act as a prognostic biomarker and a potential target for gastrointestinal tumor diagnosis and treatment.

DDX1 is a prognostic biomarker and correlates with immune infiltrations in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading lethal malignant tumors worldwide. DEAD-box (DDX) family helicases are implicated in numerous human cancers. However, the role of DDX1 in HCC has not yet been fully elucidated. We downloaded gene expression data and clinical information data of HCC from The Cancer Genome Atlas and International Cancer Genome Consortium (ICGC) database and conducted subsequent analyses using the R package and online portal. The results revealed that HCC tissues had higher DDX1 expression compared with either paired or unpaired normal tissues. The increased DDX1 expression was closely related to the advanced pathological grade and histologic grade of HCC. Further analysis suggested that patients with high DDX1 expression contributed to poor prognosis The Cox regression analysis revealed that the expression level of DDX1 was an independent prognostic factor for HCC. In addition, an ICGC cohort was used for external validation. The cBio-Portal, MethSurv, and UALCAN database were used for evaluating the genomic mechanism. Moreover, the Tumor Immune Estimation Resource dataset and QUANTISEQ algorithm revealed that DDX1 expression positively correlates with immune infiltrating cells. We also identified the DDX1-related differentially expressed genes (DEGs) and explored their biological functions by GO, KEGG, and GSEA analyses, which indicated that DDX1 may regulate the progression of HCC. In general, increased DDX1 expression predicts a poor prognosis and drives the progression of HCC.

Clinical Trials of Liposomes in Children's Anticancer Therapy: A Comprehensive Analysis of Trials Registered on ClinicalTrials.gov.

Objective: Clinical trials have become essential for driving the development of medicine. However, little is known about the current status of clinical trials on liposomes in children's anticancer therapy (LCAT). This study aimed to synthesize current finding from clinical trials of LCAT in ClinicalTrials.gov. Methods: A cross-sectional descriptive study of clinical trials on LCAT was conducted, using studies registered on ClinicalTrials.gov through December 30, 2021. Results: A total of 74 eligible trials were identified, accounting for 4.8% (74/1552) of all trials on liposomes for cancer therapy. Among these trials, 70 (94.6%) were interventional trials, and the remaining 4 (5.4%) were observational trials. Of the 70 interventional trials, 63 (90.0%) were for treatment, 48.6% were involving unlabeled allocations, 30.0% were randomized, 52.9% were single group assignment, 71.4% were without masking, 28.6% were Phase 3 trials, 30.0% were Phase 1 trials, and 24.3% were Phase 2 trials. Furthermore, 17 liposomal drugs for 123 types of cancer were investigated in the interventional trials, and these were mainly focused on organic chemicals (43/70, 61.4%). Of these cancers, the highest proportion was leukemia (15.4%), followed by lymphoma (9.8%) and ovarian cancer (8.9%). Conclusion: High quality, adequately powered, masked, appropriately sized, and randomized clinical trials represent the critical priorities for conducting a high-quality clinical trial. However, most of these trials for LCAT were non-randomized, single group assignment, and non-blinded interventional trials of small scale, with various eligibility criteria and outcome measures. Our analysis highlights the need for improvement in the completeness of study designs curated on clinicalTrials.gov. We urge for decision-makers to avoid adopting entrenched positions about the study design of cancer clinical trials to avoid this problem. As such, tackling the problematic challenges related to cancer and designing efficient trials for cancer requires developing and applying new approaches and multiple strategies.

The Pan-Cancer Crosstalk Between the EFNA Family and Tumor Microenvironment for Prognosis and Immunotherapy of Gastric Cancer.

Background: EFNA1-5 have important physiological functions in regulating tumorigenesis and metastasis. However, correlating EFNA genes in the tumor immune microenvironment (TIME), and the prognosis of patients with gastric cancer remains to be determined. Methods: Using public databases, the expression of EFNA1-5 in pan-cancer and gastric cancer was comprehensively analyzed using UCSC Xena, the Oncomine dataset and UALCAN. We further completed survival analysis by Kaplan-Meier plotter to evaluate the prognosis of the high and low expression groups of the EFNAs gene in patients with gastric cancer. The TIMER tool was used to reveal the correlation between immune cell infiltration and genes of interest. Spearman correlation was used to find an association between the EFNA genes and tumor stem cells, TIME, microsatellite instability (MSI) or tumor mutational burden (TMB). We also used cBioportal, GeneMANIA and STRINGS to explore the types of changes in these genes and the protein interactions. Finally, we described the TIME based on QUANTISEQ algorithm, predicted the relationship between the EFNA genes and half-maximal inhibitory concentration (IC50), and analyzed the relationship between the EFNA family genes and immune checkpoints. Results: The expression of EFNA1, EFNA3, EFNA4, and EFNA5 was elevated in pan-cancer. Compared with normal adjacent tissues, EFNA1, EFNA3, and EFNA4 were up-regulated in gastric cancer. In terms of the influence on the survival of patients, the expression of EFNA3 and EFNA4 were related to overall survival (OS) and disease-free survival (DFS) for patients with gastric cancer. High expression of EFNA5 often predicted poor OS and DFS. In gastric cancer, the expression of EFNA3 and EFNA4 showed a significant negative correlation with B cells. The higher the expression of EFNA5, the higher the abundance of B cells, CD4+T cells and macrophages. CD8+T cells, dendritic cells infiltration and EFNA1-4 expression were negatively correlated. The infiltration of CD4+T cells, macrophages and neutrophils was negatively correlated with the expression of EFNA1, EFNA3, and EFNA4. TMB and MSI were positively correlated with EFNA3/EFNA4 expression. In the tumor microenvironment and drug sensitivity, EFNA3/4/5 also showed a significant correlation. In addition, we explored the relationship between the EFNA family genes and the immune microenvironment (B cells, M2 macrophages, monocytes, CD8+ T cells, regulatory T cells, myeloid dendritic cells, natural killer cells, non-regulatory CD4+ T cells), immune checkpoint (PDCD1, PDCD1LG2, CD274, CTLA4), and IC50 of common chemotherapeutic drugs for gastric cancer (5-fluorouracil, cisplatin, docetaxel and gemcitabine). Conclusions: Our study provides new ideas for tumor treatment and prognosis from the perspective of TIME, and nominates EFNA1-5 to become potential therapeutic targets for gastric cancer.