Expression and function of the TL1A/DR3 axis in chronic lymphocytic leukemia

Super-Enhancer–Associated nine-gene prognostic score model for prediction of survival in chronic lymphocytic leukemia patients

Chronic lymphocytic leukemia (CLL) is a type of highly heterogeneous mature B-cell malignancy with various disease courses. Although a multitude of prognostic markers in CLL have been reported, insights into the role of super-enhancer (SE)–related risk indicators in the occurrence and development of CLL are still lacking. A super-enhancer (SE) is a cluster of enhancers involved in cell differentiation and tumorigenesis, and is one of the promising therapeutic targets for cancer therapy in recent years. In our study, the CLL-related super-enhancers in the training database were processed by LASSO-penalized Cox regression analysis to screen a nine-gene prognostic model including TCF7, VEGFA, MNT, GMIP, SLAMF1, TNFRSF25, GRWD1, SLC6AC, and LAG3. The SE-related risk score was further constructed and it was found that the predictive performance with overall survival and time-to-treatment (TTT) was satisfactory. Moreover, a high correlation was found between the risk score and already known prognostic markers of CLL. In the meantime, we noticed that the expressions of TCF7, GMIP, SLAMF1, TNFRSF25, and LAG3 in CLL were different from those of healthy donors (p < 0.01). Moreover, the risk score and LAG3 level of matched pairs before and after treatment samples varied significantly. Finally, an interactive nomogram consisting of the nine-gene risk group and four clinical traits was established. The inhibitors of mTOR and cyclin-dependent kinases (CDKs) were considered effective in patients in the high-risk group according to the pRRophetic algorithm. Collectively, the SE-associated nine-gene prognostic model developed here may be used to predict the prognosis and assist in the risk stratification and treatment of CLL patients in the future.

Investigation of Biomarkers Associated with Low Platelet Counts in Normal Karyotype Acute Myeloid Leukemia

Acute myeloid leukemia (AML) patients are at risk of bleeding due to disease-related lack of platelets and systemic coagulopathy. Platelets play a role in hemostasis. Leukemic blasts have been shown to alter platelet activation in vitro. Here we investigated biomarkers associated with thrombocytopenia in normal karyotype AML (NK-AML). From The Cancer Genome Atlas database, case-control study was performed between normal karyotype (NK) platelet-decreased AML (PD-AML, platelet count < 100 × 109/L, n = 24) and NK platelet-not-decreased AML (PND-AML, with platelet count ≥ 100 × 109/L, n = 13). Differentially expressed gene analysis, pathway analysis and modelling for predicting platelet decrease in AML were performed. DEG analysis and pathway analysis revealed 157 genes and eight pathways specific for PD-AML, respectively. Most of the eight pathways were significantly involved in G-protein-coupled receptor-related pathway, cytokine-related pathway, and bone remodeling pathway. Among the key genes involved in at least one pathway, three genes including CSF1R, TNFSF15 and CLEC10A were selected as promising biomarkers for predicting PD-AML (0.847 of AUC in support vector machine model). This is the first study that identified biomarkers using RNA expression data analysis and could help understand the pathophysiology in AML with low platelet count.

Nonylphenol regulates TL1A through the AhR/HDAC2/HNF4α pathway in endothelial cells to promote the angiogenesis of colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most malignant cancers worldwide. Nonylphenol (NP) is an endocrine-disruptor chemical and plays an important role in the development of cancers. However, the effects of NP on CRC remain unclear. In this study, we aimed to investigate the potential mechanisms of NP in the pathogenesis of CRC.

METHODS

The levels of AhR, TL1A and HDAC2 in CRC tissues and endothelial cells were assessed by RT-qPCR or western blot. CHIP and dual luciferase reporter assays were used to confirm the interaction between AhR and HDAC2, or HNF4α and TL1A. The CCK8, would healing and tube formation assays were conducted to evaluate the proliferation, migration and angiogenesis of HUVECs. Western blot determined HNF4α protein and HNF4α acetylation levels. The secreted TL1A protein was detected by ELISA. The angiogenesis-related factor CD31 was tested by IHC.

RESULTS

The expression level of AhR was significantly up-regulated in CRC tissues and endothelial cells. Moreover, NP activated the AhR pathway mediated colorectal endothelial cell angiogenesis and proliferation, while TL1A overexpression resisted these effects caused by NP. Besides, NP was found to modulate HNF4α deacetylation through AhR/HDAC2 to inhibit TL1A. Furthermore, in vivo experiments proved that NP regulated CRC growth and angiogenesis via AhR/HDAC2/HNF4α/TL1A axis.

CONCLUSION

This study revealed that NP promoted CRC growth and angiogenesis through AhR/HDAC2/HNF4α/TL1A pathway and could be a new therapeutic target for CRC treatment.

Identification and Validation of the lncRNA BACE1-AS as Immune-Related Influencing Factor in Tumorigenesis following Pan-Carcinoma Analysis

BACKGROUND

The lncRNA BACE1-AS was identified as a plasma molecular marker in the early diagnosis of Alzheimer's disease, but its role in tumors remains poorly defined.

METHODS

The expression patterns, genomic mutation, and prognostic significance of BACE1-AS in pan-cancers were compared by analyzing 32 types of tumors from The Cancer Genome Atlas and cBioPortal databases. The relationships between BACE1-AS expression levels and the degree of immune cell infiltration, immune components, and immune-related genes were explored. The possible molecular mechanisms of BACE1-AS in tumors were explored using gene set enrichment analysis (GSEA). Finally, the role of BACE1-AS in hepatocellular carcinoma was confirmed via quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

BACE1-AS expression levels were significantly upregulated in LIHC, GBM, KIRC, CHOL, STAD, KICH, COAD, and PRAD. Higher expression levels of BACE1-AS were associated with worse overall survival in patients with HNSC and LIHC, while the opposite was found in PCPG and THCA. The overall mutation rate of BACE1-AS in pan-cancer was only approximately 0.9%, and it occurred mainly in uveal melanoma and uterine carcinoma. Generally, BACE1-AS expression was negatively correlated with the immune microenvironment. BACE1-AS expression was mainly related to naïve B cells, activated memory CD4 T cells, monocytes, M1 macrophages, M2 macrophages, and resting mast cells. The potential mechanisms of BACE1-AS in tumors were mainly via regulating the activities of B cell-mediated immunity, immune response regulating cell surface receptor signaling, RNA binding in posttranscriptional gene silencing, B cell receptor signaling pathways, and immune receptor activity. Finally, the qRT-PCR results confirmed that the expression levels of BACE1-AS in hepatocellular carcinoma cell lines were upregulated.

CONCLUSIONS

Overall, our results suggest that BACE1-AS is associated with the expression, prognosis, and rate of immune cell infiltration of most tumors. Thus, BACE1-AS may be a potential target for immunotherapies aimed at improving cancer patient outcomes.

A novel 10-gene immune-related lncRNA signature model for the prognosis of colorectal cancer

BACKGROUND

The tumor immune microenvironment of colorectal cancer (CRC) affects tumor development, prognosis and immunotherapy strategies. Recently, immune-related lncRNA were shown to play vital roles in the tumor immune microenvironment. The objective of this study was to identify lncRNAs involved in the immune response, tumorigenesis and progression of CRC and to establish an immune-related lncRNA signature for predicting the prognosis of CRC.

METHODS

We used data retrieved from the cancer genome atlas (TCGA) dataset to construct a 10-gene immune-related lncRNA pair (IRLP) signature model using a method based on the ranking and comparison of paired gene expression in CRC. The clinical prognosis, immune checkpoints and lncRNA-protein networks were analyzed to evaluate the signature.

RESULTS

The signature was closely associated with overall survival of CRC patients (p < 0.001 in both of the training and validating cohorts) and the 3-year AUC values for the training and validating cohorts were 0.884 and 0.739, respectively. And, there were positive correlations between the signature and age (p = 0.048), clinical stage (p < 0.01), T stage (p < 0.01), N stage (p < 0.001) and M stage (p < 0.01). In addition, the signature model appeared to be highly relevant to some checkpoints, including CD160, TNFSF15, HHLA2, IDO2 and KIR3DL1. Further, molecular functional analysis and lncRNA-protein networks were applied to understand the molecular mechanisms underlying the carcinogenic effect and progression.

CONCLUSION

The 10-gene IRLP signature model is an independent prognostic factor for CRC patient and can be utilized for the development of immunotherapy.

TNF-like ligand 1A is associated with progression and prognosis of human gastric cancer

Purpose

This study aimed to investigate the function of TNF-like ligand 1A (TL1A) in the tumorigenesis and progression of gastric cancer (GC).

Methods

RNA-seq gene expression and clinical information for GC patients were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) between GC tissue samples and normal controls were screened with the edgeR package. Identification of gene co-expression and functional enrichment analyses were performed with Pearson’s correlation analysis and gene set enrichment analysis (GSEA), respectively. Lastly, survival analysis was performed using the Kaplan-Meier method with the log rank test.

Results

TL1A expression in GC tissue samples were significantly higher than that in normal controls (LogFC=1.07 and P=8.90E-07). Moreover, 215 genes, co-expressed with TL1A, and 21 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were obtained. Next, the miRNA-lncRNA/mRNA network, comprising 7 miRNAs, 27 lncRNAs, and 21 mRNAs, was constructed based on key genes from intersections between co-expression analysis and GSEA. In addition, survival analysis results demonstrated that TL1A (P=2.6e−07) was significantly associated with the overall survival (OS) of GC patients.

Conclusion

TL1A was involved in the tumorigenesis and progression of GC, and was significantly associated with the OS of GC patients.

TNFSF15 promoter polymorphisms increase the susceptibility to small cell lung cancer: a case-control study

BACKGROUND

Tumor necrosis factor superfamily member 15 (TNFSF15) is closely related to tumorigenesis and development. This study aimed to investigate the correlations between TNFSF15 polymorphisms and genetic susceptibility to lung cancer.

METHODS

This case-control study included 209 small cell lung cancer patients (SCLC), 340 non- small cell lung cancer patients (NSCLC) and 460 health controls. TNFSF15-638 A > G and - 358 T > C polymorphisms were genotyped by polymerase chain reaction-restrictive fragment length polymorphism (PCR-RFLP) analysis. Odds ratio (OR) and 95% confidence interval (95% CI) were estimated by unconditional logistic regression.

RESULTS

Our results showed that subjects carrying the TNFSF15-638GG genotype or -358CC genotype were more likely to develop SCLC (-638GG, OR = 1.84, 95%CI = 1.13-2.99; -358CC, OR = 2.44, 95%CI = 1.46-4.06), but not NSCLC (P > 0.05). In stratified analysis, -638GG genotype was related to SCLC among males (OR = 1.95, 95%CI = 1.09-3.45, P = 0.023) and older patients (OR = 2.93, 95%CI = 1.44-8.68, P = 0.006). However, -358CC genotype was associated with SCLC among females (OR = 8.42, 95%CI = 2.22-31.89, P = 0.002) and older subjects with OR (95%CI) of 11.04 (3.57-34.15) (P < 0.001). Moreover, TNFSF15 -358CC was linked with a higher risk of SCLC among non-smokers (OR = 2.54, 95%CI = 1.20-5.35, P = 0.015) but not among smokers (OR = 1.88, 95%CI = 0.92-3.84, P = 0.086).

CONCLUSION

These findings highlight the importance of TNFSF15 polymorphisms in the development of SCLC.

Systematic tracking of altered modules identifies the key biomarkers involved in chronic lymphocytic leukemia

Key genes in chronic lymphocytic leukemia (CLL) were investigated through systematically tracking the dysregulated modules from protein-protein interaction (PPI) networks. Microarray data of normal subjects and CLL patients recruited from ArrayExpress database were applied to extract differentially expressed genes (DEGs). Additionally, we re-weighted the PPI network of normal and CLL conditions by means of Pearsons correlation coefficient (PCC). Furthermore, clique-merging method was applied to extract the modules and then the altered modules were screened out. The intersection genes were selected from miss and add genes in the altered modules. The common genes were screened from the intersection genes and DEGs in CLL. A total of 734 DEGs were screened by statistical analysis. In this investigation, there were 1,805 and 703 modules in normal as well as disease PPI network. In addition, 875 altered modules were obtained which included 145 miss genes, 353 add genes and 85 intersection genes. Finally, in-depth analysis revealed 9 mutual genes between the intersection genes and DEGs in CLL. Our analysis revealed several key genes associated with CLL by systematically tracking the dysregulated modules, which might be candidate targets for diagnosis and management of CLL.