DNAJB4 identified as a potential breast cancer marker: evidence from bioinformatics analysis and basic experiments

Sodium Butyrate Inhibits the Malignant Proliferation of Colon Cancer Cells via the miR-183/DNAJB4 Axis

Colorectal carcinoma (CRC) is one of the most common malignant tumors in the digestive tract. It was found that butyric acid could inhibit the expression of miR-183 to slow down malignant progression of CRC in the early stage. However, its regulatory mechanism remains unclear. This study screened the IC50 value of butyrate on inhibition of CRC cells malignant progression. Its inhibitory effects were detected by MTT assay, colony formation experiment, Transwell migration experiment, and apoptosis evaluation by flow cytometry. Next, the expressions of miR-183 and DNAJB4 were, respectively, determined in butyrate treated and miR-183 analog or si-DNAJB4-transfected CRC cells to further detect the role of upregulated miR-183 or silencing DNAJB4 in CRC cells malignant progression. Subsequently, the targeted regulatory relationship between miR-183 and si-DNAJB4 was confirmed by bioinformatic prediction tools and double luciferase report genes analysis method. The regulatory mechanism of butyrate on miR-183/DNAJB4 axis signal pathway was evaluated in molecular level, and verified in nude mouse xerograft tumor model and immunohistochemical analysis tests of Ki67 positive rates. The results displayed that butyrate with increased concentration can hinder the proliferation and improve apoptosis of CRC cells by decreasing the expression of miR-183. Thus, butyrate reduces miR-183 expression and increases DNAJB4 expression via the miR-183/DNAJB4 axis, ultimately inhibiting the malignant progression and increasing apoptosis of CRC. While over expression of miR-183 downregulate the expression of DNAJB4, which can reverse the inhibitory effect of butyrate.

Robust Identification of Differential Gene Expression Patterns from Multiple Transcriptomics Datasets for Early Diagnosis, Prognosis, and Therapies for Breast Cancer

Background and Objectives: Breast cancer (BC) is one of the major causes of cancer-related death in women globally. Proper identification of BC-causing hub genes (HubGs) for prognosis, diagnosis, and therapies at an earlier stage may reduce such death rates. However, most of the previous studies detected HubGs through non-robust statistical approaches that are sensitive to outlying observations. Therefore, the main objectives of this study were to explore BC-causing potential HubGs from robustness viewpoints, highlighting their early prognostic, diagnostic, and therapeutic performance. Materials and Methods: Integrated robust statistics and bioinformatics methods and databases were used to obtain the required results. Results: We robustly identified 46 common differentially expressed genes (cDEGs) between BC and control samples from three microarrays (GSE26910, GSE42568, and GSE65194) and one scRNA-seq (GSE235168) dataset. Then, we identified eight cDEGs (COL11A1, COL10A1, CD36, ACACB, CD24, PLK1, UBE2C, and PDK4) as the BC-causing HubGs by the protein-protein interaction (PPI) network analysis of cDEGs. The performance of BC and survival probability prediction models with the expressions of HubGs from two independent datasets (GSE45827 and GSE54002) and the TCGA (The Cancer Genome Atlas) database showed that our proposed HubGs might be considered as diagnostic and prognostic biomarkers, where two genes, COL11A1 and CD24, exhibit better performance. The expression analysis of HubGs by Box plots with the TCGA database in different stages of BC progression indicated their early diagnosis and prognosis ability. The HubGs set enrichment analysis with GO (Gene ontology) terms and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways disclosed some BC-causing biological processes, molecular functions, and pathways. Finally, we suggested the top-ranked six drug molecules (Suramin, Rifaximin, Telmisartan, Tukysa Tucatinib, Lynparza Olaparib, and TG.02) for the treatment of BC by molecular docking analysis with the proposed HubGs-mediated receptors. Molecular docking analysis results also showed that these drug molecules may inhibit cancer-related post-translational modification (PTM) sites (Succinylation, phosphorylation, and ubiquitination) of hub proteins. Conclusions: This study's findings might be valuable resources for diagnosis, prognosis, and therapies at an earlier stage of BC.

DNAJB4 suppresses breast cancer progression and promotes tumor immunity by regulating the Hippo signaling pathway

PURPOSE

Breast cancer is the most common cancer worldwide. Low DNAJB4 expression levels are strongly correlated with poor prognosis in breast cancer patients. However, the molecular mechanism by which DNAJB4 regulates breast cancer progression is unclear.

METHODS

The expression of DNAJB4 was validated in human breast cancer tissues, normal human breast tissues, and breast cancer cell lines. CCK-8, colony-forming, and wound healing assays were used to assess the biological effect of DNAJB4 overexpression on cell proliferation and migration in MCF-7 cell lines. Bioinformatic analysis was used to identify the DNAJB4 related pathways in breast cancer. Epithelial-mesenchymal transition (EMT)-related biomarkers and Hippo pathway components were quantified by Western blots. Luciferase and Western blot assays were used to validate which miRNA regulates DNAJB4. In addition, the effects of DNAJB4 on in vivo tumor growth were assessed in xenograft models.

RESULTS

DNAJB4 was expressed at low levels in human breast cancer tissues and breast cancer cell lines and correlated with poor prognosis. DNAJB4 overexpression significantly inhibited cell proliferation and migration in vitro by activating the Hippo pathway. The dual-luciferase assay showed that hsa-miR-183-5p targeted DNAJB4. Moreover, the effects of DNAJB4 could be reversed by miR-183-5p. In addition, the expression of DNAJB4 was strongly correlated with immune infiltration levels. Notably, DNAJB4 overexpression markedly enhanced CD4 + and CD8 + T cells and reduced PD-L1 levels in 4T1 tumors via the Hippo pathway, which retarded tumor growth in a subcutaneous xenograft tumor mouse model of 4T1 cells.

CONCLUSIONS

The present study demonstrated that DNAJB4 overexpression inhibited the malignant biological behavior of breast cancer by regulating the Hippo pathway and tumor immunosuppressive environment.

Human Endogenous Retrovirus-H-Derived miR-4454 Inhibits the Expression of DNAJB4 and SASH1 in Non-Muscle-Invasive Bladder Cancer

Although most human endogenous retroviruses (HERVs) have been silenced and lost their ability to translocate because of accumulated mutations during evolution, they still play important roles in human biology. Several studies have demonstrated that HERVs play pathological roles in numerous human diseases, especially cancer. A few studies have revealed that long non-coding RNAs that are transcribed from HERV sequences affect cancer progression. However, there is no study on microRNAs derived from HERVs related to cancer. In this study, we identified 29 microRNAs (miRNAs) derived from HERV sequences in the human genome. In particular, we discovered that miR-4454, which is HERV-H-derived miRNA, was upregulated in non-muscle-invasive bladder cancer (NMIBC) cells. To figure out the effects of upregulated miR-4454 in NMIBC, genes whose expression was downregulated in NMIBC, as well as tumor suppressor genes, were selected as putative target genes of miR-4454. The dual-luciferase assay was used to determine the negative relationship between miR-4454 and its target genes, DNAJB4 and SASH1, and they were confirmed to be promising target genes of miR-4454. Taken together, this study suggests that the upregulation of miR-4454 derived from HERV-H in NMIBC reduces the expression of the tumor suppressor genes, DNAJB4 and SASH1, to promote NMIBC progression.

DNAJB4 promotes triple-negative breast cancer cell apoptosis via activation of the Hippo signaling pathway

INTRODUCTION

Triple-negative breast cancer (TNBC) is currently the most malignant subtype of breast cancer without effective targeted therapies. DNAJB4 (Dnaj heat shock protein family (Hsp40) member B4) is a member of the human heat shock protein family (Hsp40). The clinical significance of DNAJB4 in breast cancer has been reported in our previous study. However, the biological function of DNAJB4 in TNBC cell apoptosis remains unclear to date.

METHODS

The expression of DNAJB4 in normal breast cells, breast cancer cells, four-paired TNBC tissues, and adjacent noncancerous tissues was quantified by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot assay. The role of DNAJB4 in TNBC cell apoptosis was investigated using a number of gain- and loss-of-function in vitro and in vivo assays. The underlying molecular mechanisms in TNBC cell apoptosis were elucidated via Western blot assay.

RESULTS

DNAJB4 expression was significantly downregulated in TNBC tissues and cell lines. DNAJB4 knockdown inhibited TNBC cell apoptosis and promoted tumorigenicity in vitro and in vivo, but DNAJB4 overexpression resulted in the opposite. Mechanically, DNAJB4 knockdown inhibited TNBC cell apoptosis through suppression of the Hippo signaling pathway, and the result was reversed after DNAJB4 overexpression.

CONCLUSIONS

DNAJB4 promotes TNBC cell apoptosis by activating the Hippo signaling pathway. Therefore, DNAJB4 may act as a prognostic biomarker and therapeutic target for TNBC.

The Impact of YRNAs on HNSCC and HPV Infection

HPV infection is one of the most important risk factors for head and neck squamous cell carcinoma among younger patients. YRNAs are short non-coding RNAs involved in DNA replication. YRNAs have been found to be dysregulated in many cancers, including head and neck squamous cell carcinoma (HNSCC). In this study, we investigated the role of YRNAs in HPV-positive HNSCC using publicly available gene expression datasets from HNSCC tissue, where expression patterns of YRNAs in HPV(+) and HPV(−) HNSCC samples significantly differed. Additionally, HNSCC cell lines were treated with YRNA1-overexpressing plasmid and RNA derived from these cell lines was used to perform a NGS analysis. Additionally, a deconvolution analysis was performed to determine YRNA1’s impact on immune cells. YRNA expression levels varied according to cancer pathological and clinical stages, and correlated with more aggressive subtypes. YRNAs were mostly associated with more advanced cancer stages in the HPV(+) group, and YRNA3 and YRNA1 expression levels were found to be correlated with more advanced clinical stages despite HPV infection status, showing that they may function as potential biomarkers of more advanced stages of the disease. YRNA5 was associated with less-advanced cancer stages in the HPV(−) group. Overall survival and progression-free survival analyses showed opposite results between the HPV groups. The expression of YRNAs, especially YRNA1, correlated with a vast number of proteins and cellular processes associated with viral infections and immunologic responses to viruses. HNSCC-derived cell lines overexpressing YRNA1 were then used to determine the correlation of YRNA1 and the expression of genes associated with HPV infections. Taken together, our results highlight the potential of YRNAs as possible HNSCC biomarkers and new molecular targets.

Predicting multipotency of human adult stem cells derived from various donors through deep learning

Adult stem cell-based therapeutic approaches have great potential in regenerative medicine because of their immunoregulatory properties and multidifferentiation capacity. Nevertheless, the outcomes of stem cell‑based therapies to date have shown inconsistent efficacy owing to donor variation, thwarting the expectation of clinical effects. However, such donor dependency has been elucidated by biological consequences that current research could not predict. Here, we introduce cellular morphology-based prediction to determine the multipotency rate of human nasal turbinate stem cells (hNTSCs), aiming to predict the differentiation rate of keratocyte progenitors. We characterized the overall genes and morphologies of hNTSCs from five donors and compared stemness-related properties, including multipotency and specific lineages, using mRNA sequencing. It was demonstrated that transformation factors affecting the principal components were highly related to cell morphology. We then performed a convolutional neural network-based analysis, which enabled us to assess the multipotency level of each cell group based on their morphologies with 85.98% accuracy. Surprisingly, the trend in expression levels after ex vivo differentiation matched well with the deep learning prediction. These results suggest that AI‑assisted cellular behavioral prediction can be utilized to perform quantitative, non-invasive, single-cell, and multimarker characterizations of live stem cells for improved quality control in clinical cell therapies.

Identification of a novel signature based on unfolded protein response-related gene for predicting prognosis in bladder cancer

BACKGROUND

The unfolded protein response (UPR) served as a vital role in the progression of tumors, but the molecule mechanisms of UPR in bladder cancer (BLCA) have been not fully investigated.

METHODS

We identified differentially expressed unfolded protein response-related genes (UPRRGs) between BLCA samples and normal bladder samples in the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis and the least absolute shrinkage and selection operator penalized Cox regression analysis were used to construct a prognostic signature in the TCGA set. We implemented the validation of the prognostic signature in GSE13507 from the Gene Expression Omnibus database. The ESTIMATE, CIBERSORT, and ssGSEA algorithms were used to explore the correlation between the prognostic signature and immune cells infiltration as well as key immune checkpoints (PD-1, PD-L1, CTLA-4, and HAVCR2). GDSC database analyses were conducted to investigate the chemotherapy sensitivity among different groups. GSEA analysis was used to explore the potential mechanisms of UPR-based signature.

RESULTS

A prognostic signature comprising of seven genes (CALR, CRYAB, DNAJB4, KDELR3, CREB3L3, HSPB6, and FBXO6) was constructed to predict the outcome of BLCA. Based on the UPRRGs signature, the patients with BLCA could be classified into low-risk groups and high-risk groups. Patients with BLCA in the low-risk groups showed the more favorable outcomes than those in the high-risk groups, which was verified in GSE13507 set. This signature could serve as an autocephalous prognostic factor in BLCA. A nomogram based on risk score and clinical characteristics was established to predict the over survival of BLCA patients. Furthermore, the signature was closely related to immune checkpoints (PD-L1, CTLA-4, and HAVCR2) and immune cells infiltration including CD8⁺ T cells, follicular helper T cells, activated dendritic cells, and M2 macrophages. GSEA analysis indicated that immune and carcinogenic pathways were enriched in high-risk group.

CONCLUSIONS

We identified a novel unfolded protein response-related gene signature which could predict the over survival, immune microenvironment, and chemotherapy response of patients with bladder cancer.