Relationship Between ADAMTS8, ADAMTS18, and ADAMTS20 (A Disintegrin and Metalloproteinase with Thrombospondin Motifs) Expressions and Tumor Molecular Classification, Clinical Pathological Parameters, and Prognosis in Breast Invasive Ductal Carcinoma

Transcriptome Sequencing of Gingival Tissues from Impacted Third Molars Patients Reveals the Alterations of Gene Expression

OBJECTIVE

The removal of impacted third molars by surgery may occur with a series of complications, whereas limited information about the postoperative pathogenesis is available. The objective of this study is to identify changes in gene expression after flap surgical removal of impacted third molars and provide potential information to reduce postoperative complications.

METHODS

The gingival tissues of twenty patients with flap surgical removal of impacted third molars and twenty healthy volunteers were collected for gene expression testing. The collected gingival tissues were used RNA sequencing technology and quantitative real-time PCR validation was performed. DEG was mapped to protein databases such as GO and KEGG for functional annotation and, based on annotation information, for mining of differential expression genes in patients with mpacted third molars.

RESULTS

A total of 555 genes were differentially expressed. Among the top up-regulated genes, HLA-DRB4, CCL20, and CXCL8 were strongly associated with immune response and signal transduction. Among the top down-regulated genes, SPRR2B, CLDN17, LCE3D and LCE3E were related to keratinocyte differentiation, IFITM5, and BGLAP were related to bone mineralization, UGT2B17 is associated with susceptibility to osteoporosis. KEGG results showed that the DEGs were related to multiple disease-related pathways.

CONCLUSION

This first transcriptome analysis of gingival tissues from patients with surgical removal of impacted third molars provides new insights into postoperative genetic changes. The results may establish a basis for future research on minimizing the incidence of complications after flap-treated third molars.

Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach

Although systemic chemotherapy remains the standard of care for TNBC, even combination chemotherapy is often ineffective. The identification of biomarkers for differential chemotherapy response would allow for the selection of responsive patients, thus maximizing efficacy and minimizing toxicities. Here, we leverage TNBC PDXs to identify biomarkers of response. To demonstrate their ability to function as a preclinical cohort, PDXs were characterized using DNA sequencing, transcriptomics, and proteomics to show consistency with clinical samples. We then developed a network-based approach (CTD/WGCNA) to identify biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (c, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). CTD/WGCNA multigene biomarkers are predictive in PDX datasets (RNAseq and Affymetrix) for both taxane- (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating cross-expression platform and cross-drug class robustness. These biomarkers were also predictive in clinical datasets, thus demonstrating translational potential.

In silico study of cancer stage-specific DNA methylation pattern in White breast cancer patients based on TCGA dataset

BACKGROUND

Breast cancer is one of the most common types of cancer among women. As current breast cancer treatments are still ineffective, we assess the methylation pattern of White breast cancer patients across cancer stage based on The Cancer Genome Atlas (TCGA) dataset. Significant hypermethylation and hypomethylation can regulate the gene expression, thus becoming potential biomarkers in breast cancer tumorigenesis.

METHODS

DNA methylation data was downloaded using TCGA Assembler 2 based on race-specific metadata of TCGA - Breast Invasive Carcinoma (TCGA-BRCA) project from Genomic Data Commons (GDC) Data Portal. After the data was divided into each cancer stage, duplicated data of each patient was removed using OMICSBind, while differentially-expressed probes were identified using edgeR. The resulting probes were validated based on correlation and regression analysis with the gene expression, ANOVA between cancer stages, ROC curve per stage, as well as databases.

RESULTS

Based on the White dataset, we found 66 significant hypermethylated genes with logFC > 1.8 between Stage I-III. From this number, three epigenetic-regulated, stage-specific genes are proposed to be the detection biomarkers of breast cancer due to significant aberrant gene expression and/or low mutation ratio among breast cancer patients: ABCC9 (Stage III), SHISA3 (Stage II), and POU4F1 (Stage I-II).

CONCLUSIONS

Our study shows that ABCC9, SHISA3, and POU4F1 are potential stage-specific detection biomarkers of breast cancer for White individuals, whereas their roles in other races need to be studied further.

A six-gene-based signature for breast cancer radiotherapy sensitivity estimation

Breast cancer (BRCA) represents the most common malignancy among women worldwide with high mortality. Radiotherapy is a prevalent therapeutic for BRCA that with heterogeneous effectiveness among patients. Here, we proposed to develop a gene expression-based signature for BRCA radiotherapy sensitivity estimation. Gene expression profiles of BRCA samples from the Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) were obtained and used as training and independent testing dataset, respectively. Differential expression genes (DEGs) in BRCA samples compared with their paracancerous samples in the training set were identified by using the edgeR Bioconductor package. Univariate Cox regression analysis and LASSO Cox regression method were applied to screen optimal genes for constructing a radiotherapy sensitivity estimation signature. Nomogram combining independent prognostic factors was used to predict 1-, 3-, and 5-year OS of radiation-treated BRCA patients. Relative proportions of tumor infiltrating immune cells (TIICs) calculated by CIBERSORT and mRNA levels of key immune checkpoint receptors was adopted to explore the relation between the signature and tumor immune response. As a result, 603 DEGs were obtained in BRCA tumor samples, six of which were retained and used to construct the radiotherapy sensitivity prediction model. The signature was proved to be robust in both training and testing sets. In addition, the signature was closely related to the immune microenvironment of BRCA in the context of TIICs and immune checkpoint receptors’ mRNA levels. In conclusion, the present study obtained a radiotherapy sensitivity estimation signature for BRCA, which should shed new light in clinical and experimental research.

High ADAMTS18 expression is associated with poor prognosis in stomach adenocarcinoma

Stomach adenocarcinoma (STAD) is the most pathological type of gastric cancer. ADAM metallopeptidase with thrombospondin type 1 motif 18 (ADAMTS18) plays an essential role in organ development and tumorigenesis; however, its function in STAD, and its impact on clinical outcome remain unclear. Thus, the present study aimed to investigate the association between ADAMTS18 expression and the prognosis of patients with STAD. Data from 300 patients with STAD in The Cancer Genome Atlas (TCGA) database were analyzed, and the median survival time and overall survival (OS) rate of these patients were assessed. Subsequently, 40 paired tumor and non-tumor tissue samples from patients with STAD were collected, and the relative ADAMTS18 mRNA expression levels were determined. Results from TCGA database demonstrated that high tumor ADAMTS18 expression was associated with a poorer prognosis in patients with STAD. Similarly, results from the assessed patient cohort indicated that ADAMTS18 expression was significantly higher in STAD tissues compared with non-tumor tissues. Furthermore, ADAMTS18 expression was significantly associated with tumor differentiation, lymph node metastasis and tumor node metastasis stage. Taken together, these results suggest that ADAMTS18 is highly expressed in STAD tissues, and thus may act as a potential indicator of poor prognosis in patients with STAD.

Bioinformatics Identified 17 Immune Genes as Prognostic Biomarkers for Breast Cancer: Application Study Based on Artificial Intelligence Algorithms

An increasing body of evidence supports the association of immune genes with tumorigenesis and prognosis of breast cancer (BC). This research aims at exploring potential regulatory mechanisms and identifying immunogenic prognostic markers for BC, which were used to construct a prognostic signature for disease-free survival (DFS) of BC based on artificial intelligence algorithms. Differentially expressed immune genes were identified between normal tissues and tumor tissues. Univariate Cox regression identified potential prognostic immune genes. Thirty-four transcription factors and 34 immune genes were used to develop an immune regulatory network. The artificial intelligence survival prediction system was developed based on three artificial intelligence algorithms. Multivariate Cox analyses determined 17 immune genes (ADAMTS8, IFNG, XG, APOA5, SIAH2, C2CD2, STAR, CAMP, CDH19, NTSR1, PCDHA1, AMELX, FREM1, CLEC10A, CD1B, CD6, and LTA) as prognostic biomarkers for BC. A prognostic nomogram was constructed on these prognostic genes. Concordance indexes were 0.782, 0.734, and 0.735 for 1-, 3-, and 5- year DFS. The DFS in high-risk group was significantly worse than that in low-risk group. Artificial intelligence survival prediction system provided three individual mortality risk predictive curves based on three artificial intelligence algorithms. In conclusion, comprehensive bioinformatics identified 17 immune genes as potential prognostic biomarkers, which might be potential candidates of immunotherapy targets in BC patients. The current study depicted regulatory network between transcription factors and immune genes, which was helpful to deepen the understanding of immune regulatory mechanisms for BC cancer. Two artificial intelligence survival predictive systems are available at https://zhangzhiqiao7.shinyapps.io/Smart_Cancer_Survival_Predictive_System_16_BC_C1005/ and https://zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_16_BC_C1005/. These novel artificial intelligence survival predictive systems will be helpful to improve individualized treatment decision-making.

ADAMTS8 Promotes the Development of Pulmonary Arterial Hypertension and Right Ventricular Failure: A Possible Novel Therapeutic Target

RATIONALE

Pulmonary arterial hypertension (PAH) is characterized by pulmonary vascular remodeling with aberrant pulmonary artery smooth muscle cells (PASMCs) proliferation, endothelial dysfunction, and extracellular matrix remodeling.

OBJECTIVE

Right ventricular (RV) failure is an important prognostic factor in PAH. Thus, we need to elucidate a novel therapeutic target in both PAH and RV failure.

METHODS AND RESULTS

We performed microarray analysis in PASMCs from patients with PAH (PAH-PASMCs) and controls. We found a ADAMTS8 (disintegrin and metalloproteinase with thrombospondin motifs 8), a secreted protein specifically expressed in the lung and the heart, was upregulated in PAH-PASMCs and the lung in hypoxia-induced pulmonary hypertension (PH) in mice. To elucidate the role of ADAMTS8 in PH, we used vascular smooth muscle cell-specific ADAMTS8-knockout mice (ADAMTS^ΔSM22). Hypoxia-induced PH was attenuated in ADAMTS^ΔSM22 mice compared with controls. ADAMTS8 overexpression increased PASMC proliferation with downregulation of AMPK (AMP-activated protein kinase). In contrast, deletion of ADAMTS8 reduced PASMC proliferation with AMPK upregulation. Moreover, deletion of ADAMTS8 reduced mitochondrial fragmentation under hypoxia in vivo and in vitro. Indeed, PASMCs harvested from ADAMTS^ΔSM22 mice demonstrated that phosphorylated DRP-1 (dynamin-related protein 1) at Ser637 was significantly upregulated with higher expression of profusion genes (Mfn1 and Mfn2) and improved mitochondrial function. Moreover, recombinant ADAMTS8 induced endothelial dysfunction and matrix metalloproteinase activation in an autocrine/paracrine manner. Next, to elucidate the role of ADAMTS8 in RV function, we developed a cardiomyocyte-specific ADAMTS8 knockout mice (ADAMTS8^ΔαMHC). ADAMTS8^ΔαMHC mice showed ameliorated RV failure in response to chronic hypoxia. In addition, ADAMTS8^ΔαMHC mice showed enhanced angiogenesis and reduced RV ischemia and fibrosis. Finally, high-throughput screening revealed that mebendazole, which is used for treatment of parasite infections, reduced ADAMTS8 expression and cell proliferation in PAH-PASMCs and ameliorated PH and RV failure in PH rodent models.

CONCLUSIONS

These results indicate that ADAMTS8 is a novel therapeutic target in PAH.

Distinct Diagnostic and Prognostic Values of Kinesin Family Member Genes Expression in Patients with Breast Cancer

BACKGROUND This study investigated the diagnostic and prognostic values of kinesin superfamily proteins (KIFs) in breast cancer (BC) patients. MATERIAL AND METHODS All data were obtained from the Cancer Genome Atlas. DESeq was run to test for differentially expressed KIF genes. Patients were divided into high- and low-expression groups according to the median expression values of each KIF genes. Survival data were calculated using the Cox proportional hazard model. Comprehensive survival analysis was performed to evaluate the prognostic value of the prognostic signature. Gene set enrichment analysis (GSEA) was conducted to identify associated gene ontology and KEGG pathways. RESULTS Bioinformatics analysis showed that all KIF genes were significantly enriched during DNA replication and the cell cycle, and co-expressed with each other. Thirteen KIF genes were differentially expressed in cancer and adjacent tissues, and high levels of KIF15, KIF20A, KIF23, KIF2C and KIF4A genes were significantly correlated with poor overall survival (OS). GSEA showed that BC patients with high expression of KIF15, KIF20A, KIF23, KIF2C and KIF4A were enriched in the cell cycle process, P53 regulation pathway and mismatch repair. Combinations of low expression of KIF15, KIF20A, KIF23, KIF2C and KIF4A were more highly correlated with favorable OS. Nomograms showed that the KIF4A risk score provided the maximum number of risk points (range 0-100), whereas other genes made a lower contribution. CONCLUSIONS We conclude that 13 KIF genes are differentially expressed in BC tumor tissues, and KIF15, KIF20A, KIF23, KIF2C and KIF4A are associated with prognostic factors in BC.

ADAMTS8 targets ERK to suppress cell proliferation, invasion, and metastasis of hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system. A disintegrin and metallopeptidase with thrombospondin motif (ADAMTS) has been identified as a secreted metalloproteinase that participates in the inhibition of tumor cell growth and invasion. The aims of the present study were to investigate the clinical significance of ADAMTS8 in patients with HCC and to determine the effect of ADAMTS8 on HCC cell biological activity in vitro and in vivo.

Methods

The tumor tissues and matched adjacent non-tumor tissues were collected from 61 patients with HCC, and ADAMTS8 expression was detected with immunohistochemistry. Flow cytometry and MTT assays were used to assess cell apoptosis and cell viability, respectively, and ERK, p-ERK, Stat3, p-Stat3, Akt, and p-Akt protein expressions were measured by Western blot.

Results

The results showed that ADAMTS8 expression was significantly lower in HCC tissues than that in adjacent non-tumor tissues. Moreover, ADAMTS8 expression was inversely associated with clinical stages and metastasis in patients with HCC. Furthermore, we found that transfection with exogenous ADAMTS8 inhibited proliferation and migration and induced apoptosis in HepG2 cells. In the in vivo study, tumor growth of upregulated HepG2 cells in nude mice was significantly slower. Moreover, decreased ERK activity was detected after transfection with ADAMTS8.

Conclusion

These results indicate that low ADAMTS8 expression is a predictor of a poor prognosis in patients with HCC and that ADAMTS8 plays an important role in regulating HCC growth, invasion, and apoptosis by modulating the ERK signaling pathway. ADAMTS8 maybe a new target in HCC treatment.