Prognostic value of DKK2 from the Dickkopf family in human breast cancer

Value of negatively correlated miR-205-5p/HMGB3 and miR-96-5p/FOXO1 on the diagnosis of breast cancer and benign breast diseases

Background

MicroRNA (miRNA) and mRNA levels in matching specimens were used to identify miRNA-mRNA interactions. We aimed to integrate transcriptome, immunophenotype, methylation, mutation, and survival data analyses to examine the profiles of miRNAs and target mRNAs and their associations with breast cancer (BC) diagnosis.

Methods

Based on the Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), differentially expressed miRNAs and targeted mRNAs were screened from experimentally verified miRNA-target interaction databases using Pearson's correlation analysis. We used real-time quantitative reverse transcription polymerase chain reaction to verify BC and benign disease samples, and logistic regression analysis was used to establish a diagnostic model based on miRNAs and target mRNAs. Receiver operating characteristic curve analysis was performed to test the ability to recognize the miRNA-mRNA pairs. Next, we investigated the complex interactions between miRNA-mRNA regulatory pairs and phenotypic hallmarks.

Results

We identified 27 and 359 dysregulated miRNAs and mRNAs, respectively, based on the GEO and TCGA databases. Using Pearson's correlation analysis, 10 negative miRNA-mRNA regulatory pairs were identified after screening both databases, and the related miRNA and target mRNA levels were assessed in 40 BC tissues and 40 benign breast disease tissues. Two key regulatory pairs (miR-205-5p/High mobility group box 3 (HMGB3) and miR-96-5p/Forkhead Box O1 (FOXO1)) were selected to establish the diagnostic model. They also had utility in survival and clinical analyses.

Conclusions

A diagnostic model including two miRNAs and their respective target mRNAs was established to distinguish between BC and benign breast diseases. These markers play essential roles in BC pathogenesis.

Promoter methylation analysis of DKK2 may be a potential biomarker for early detection of cervical cancer

Background

Dickkopf 2 (DKK2) plays an important role in multiple cancers. Its potential value in the clinical diagnosis of cervical cancer has remained unclear.

Objectives

To investigate the expression and promoter methylation levels of DKK2 in cervical cancer and their clinicopathological associations.

Methods

We used the Gene Expression Omnibus, Oncomine, Cancer Genome Atlas, and University of ALabama at Birmingham CANcer data analysis databases, reverse transcription-PCR, and methylation-specific PCR analysis to predict and examine the expression of DKK2 mRNA and DKK2 methylation levels in cell lines and cervical cancer tissues from 79 patients with cervical cancer and 63 with cervical precancerous lesions including 25 with low-grade squamous intraepithelial lesions (LSIL) and 38 patients with high-grade squamous intraepithelial lesions (HSIL).

Results

DKK2 mRNA expression was downregulated in all cancer cell lines and cervical cancer tissues, whereas hypermethylation of DKK2 was higher in cervical cancer tissue samples. DKK2 methylation in cervical cancer was significantly higher than that in HSIL (χ2 = 8.346, P = 0.004), whereas DKK2 methylation in HSIL was significantly higher than that in normal cervical samples (χ2 = 7.934, P = 0.005) and in LSIL samples (χ2 = 4.375, P = 0.037). DKK2 silencing caused by its promoter hypermethylation was confirmed by treatment with the methyltransferase inhibitor 5-Aza-dC in cell lines. Patients with lymph node metastasis exhibited increased promoter methylation frequency (χ2 = 5.239, P = 0.022) and low DKK2 mRNA expression (χ2 = 3.958, P = 0.047) compared with patients with no lymph node metastasis. Patients with high-risk human papillomavirus infection exhibited increased promoter methylation frequency (χ2 = 6.279, P = 0.015).

Conclusions

DKK2 epigenetic changes of DKK2 may play a key role in the development of cervical cancer, suggesting that DKK2 hypermethylation could be used as a triage test for screening, early diagnosis, or risk prediction of cervical cancer.

Identification of novel cell glycolysis related gene signature predicting survival in patients with breast cancer

One of the most frequently identified tumors and a contributing cause of death in women is breast cancer (BC). Many biomarkers associated with survival and prognosis were identified in previous studies through database mining. Nevertheless, the predictive capabilities of single-gene biomarkers are not accurate enough. Genetic signatures can be an enhanced prediction method. This research analyzed data from The Cancer Genome Atlas (TCGA) for the detection of a new genetic signature to predict BC prognosis. Profiling of mRNA expression was carried out in samples of patients with TCGA BC (n = 1222). Gene set enrichment research has been undertaken to classify gene sets that vary greatly between BC tissues and normal tissues. Cox models for additive hazards regression were used to classify genes that were strongly linked to overall survival. A subsequent Cox regression multivariate analysis was used to construct a predictive risk parameter model. Kaplan–Meier survival predictions and log-rank validation have been used to verify the value of risk prediction parameters. Seven genes (PGK1, CACNA1H, IL13RA1, SDC1, AK3, NUP43, SDC3) correlated with glycolysis were shown to be strongly linked to overall survival. Depending on the 7-gene-signature, 1222 BC patients were classified into subgroups of high/low-risk. Certain variables have not impaired the prognostic potential of the seven-gene signature. A seven-gene signature correlated with cellular glycolysis was developed to predict the survival of BC patients. The results include insight into cellular glycolysis mechanisms and the detection of patients with poor BC prognosis.

Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer

Background

Breast cancer (BC) is the most common malignant tumor in women. The immunophenotype of tumor microenvironment (TME) has shown great therapeutic potential in tumor.

Method

The transcriptome was obtained from TCGA and GEO data. Immune infiltration was analyzed by single-sample gene set enrichment (ssGSEA). The immune feature was constructed by Cox regression analysis. In addition, the coexpression of differential expression genes (DEGs) was identified. Through enrichment analysis, the function and pathway of module genes were identified. The somatic mutations related to immune characteristics were analyzed by Maftools. By using the consistency clustering algorithm, the molecular subtypes were constructed, and the overall survival time (OS) was predicted.

Results

Immune landscape can be divided into low immune infiltration and high immune infiltration. Cox regression analysis identified seven immune cells as protective factors of BC. In the coexpression modules for DEGs of high and low immune infiltration, module 1 was related to T cells and high immune infiltration. In particular, the area under the curve (AUC) value of hub gene SASH3 was the highest, and the correlation with T cells was stronger in the high immune infiltration. Enrichment analysis found that oxidative stress, T cell aggregation, and apoptosis were observed in high immune infiltration. In addition, TP53 was identified as the most important somatic gene mutation related to immune characteristics. Importantly, we also constructed seven immune cell-based breast cancer subtypes to predict OS.

Conclusion

We evaluated the immune landscape of BC and constructed the gene characteristics related to the immune landscape. The potential of T cells and SASH3 in immunotherapy of BC was revealed, which may guide the development of new clinical treatment strategies.

Identification of long-term survival-associated gene in breast cancer

Breast cancer patients at the same stage may show different clinical prognoses or different therapeutic effects of systemic therapy. Differentially expressed genes of breast cancer were identified from GSE42568. Through survival, receiver operating characteristic (ROC) curve, random forest, GSVA and a Cox regression model analyses, genes were identified that could be associated with survival time in breast cancer. The molecular mechanism was identified by enrichment, GSEA, methylation and SNV analyses. Then, the expression of a key gene was verified by the TCGA dataset and RT-qPCR, Western blot, and immunohistochemistry. We identified 784 genes related to the 5-year overall survival time of breast cancer. Through ROC curve and random forest analysis, 10 prognostic genes were screened. These were integrated into a complex by GSVA, and high expression of the complex significantly promoted the recurrence-free survival of patients. In addition, key genes were related to immune and metabolic-related functions. Importantly, we identified methylation of MEX3A and TBC1D 9 and mutations events. Finally, the expression of UGCG was verified by the TCGA dataset and by experimental methods in our own samples. These results indicate that 10 genes may be potential biomarkers and therapeutic targets for long-term survival in breast cancer, especially UGCG.

Dickkopf-2 (DKK2) as Context Dependent Factor in Patients with Esophageal Adenocarcinoma

Dickkopf-2 (DKK2) has been described as Wnt/beta-catenin pathway antagonist and its expression is mediated by micro RNA-221 (miRNA-221). So far, there is only limited data characterizing the role of DKK2 expression in esophageal cancer. A tissue micro array of 192 patients with esophageal adenocarcinoma was analyzed immunohistochemically for DKK2, miRNA-221 expression by RNA scope, and GATA6 amplification by fluorescence in-situ hybridization. The data was correlated with clinical, pathological and molecular data (TP53, HER2, c-myc, GATA6, PIK3CA, and KRAS amplifications). DKK2 expression was detectable in 21.7% and miRNA-221 expression in 33.5% of the patients. We observed no correlation between DKK2 or miRNA-221 expression and clinico-pathological data DKK2 expression was correlated with TP53 mutations and amplification of GATA6. We did not detect a survival difference in dependence of DKK2 for the total cohort, however, in patients without neoadjuvant treatment DKK2 expression correlated with a prolonged survival (median overall-survival 202 vs. 55 months, p = 0.012) which turned opposite in patients that underwent neoadjuvant treatment. High amounts of miRNA-221 were in trend associated with a prolonged overall-survival (p = 0.070). DKK2 as a Wnt antagonist is associated with prolonged survival in patients without neoadjuvant treatment and changes its prognostic value to the contrary in patients after neoadjuvant therapy. The modulatory effects of neoadjuvant treatment in connection with DKK2 expression are not fully understood, but when considering DKK2 as a tumor marker, it is necessary to see it in the context of neoadjuvant therapy.

Up-regulation of long non-coding RNA AWPPH inhibits proliferation and invasion of gastric cancer cells via miR-203a/DKK2 axis

AWPPH is a newly discovered long non-coding RNA (lncRNA). However, the expression and function of AWPPH in gastric cancer (GC) have not yet been clarified. This study tries to assess the expression and biological roles of AWPPH in GC and the underlying mechanism. The expression of lncRNA AWPPH was evaluated in GC tissues and adjacent normal tissues from 40 patients. Cell Counting Kit-8 (CCK8) and transwell assays were applied to assess cell proliferation and invasion capabilities. Bioinformatics tool was employed to predict AWPPH's sponging miRNA, while luciferase reporter assays were used to verify the target. LncRNA AWPPH was remarkably downregulated in GC and associated with metastasis. CCK8 and transwell assays proved that AWPPH inhibited cell proliferation and invasion in GC cells. MiR-203a was a predicted and further verified target of AWPPH. DKK2 was verified as a direct target of miR-203a. Upregulation of miR-203a attenuated the repressive effects of AWPPH on GC cell proliferation and invasion. AWPPH inhibited GC cell proliferation and invasion via miR-203a/DKK2 axis. This finding might provide new insight for the potential therapeutic strategies for GC in the future.