Long noncoding RNA PURPL promotes cell proliferation in liver cancer by regulating p53

Developing an RNA Signature for Radiation Injury Using a Human Liver-on-a-Chip Model

Radiation exposure in a therapeutic setting or during a mass casualty event requires improved medical triaging, where the time to delivery and quantity of medical countermeasures are critical to survival. Radiation-induced liver injury (RILI) and fibrosis can lead to death, but clinical symptoms manifest late in disease pathogenesis and there is no simple diagnostic test to determine RILI. Because animal models do not completely recapitulate clinical symptoms, we used a human liver-on-a-chip model to identify biomarkers of RILI. The goals of this study were: 1. to establish a microfluidic liver-on-a-chip device as a physiologically relevant model for studying radiation-induced tissue damage; and 2. to determine acute changes in RNA expression and biological pathway regulation that identify potential biomarkers and mechanisms of RILI. To model functional human liver tissue, we used the Emulate organ-on-a-chip system to establish a co-culture of human liver sinusoidal endothelial cells (LSECs) and hepatocytes. The chips were subject to 0 Gy (sham), 1 Gy, 4 Gy, or 10 Gy irradiation and cells were collected at 6 h, 24 h, or 7 days postirradiation for RNA isolation. To identify significant expression changes in messenger RNA (mRNA) and long non-coding RNA (lncRNA), we performed RNA sequencing (RNASeq) to conduct whole transcriptome analysis. We found distinct differences in expression patterns by time, dose, and cell type, with higher doses of radiation resulting in the most pronounced expression changes, as anticipated. Ingenuity Pathway Analysis indicated significant inhibition of the cell viability pathway 24 h after 10 Gy exposure in LSECs but activation of this pathway in hepatocytes, highlighting differences between cell types despite receiving the same radiation dose. Overall, hepatocytes showed fewer gene expression changes in response to radiation, with only 3 statistically significant differentially expressed genes at 7 days: APOBEC3H, PTCHD4, and GDNF. We further highlight lncRNA of interest including DINO and PURPL in hepatocytes and TMPO-AS1 and PRC-AS1 in LSECs, identifying potential biomarkers of RILI. We demonstrated the potential utility of a human liver-on-a-chip model with primary cells to model organ-specific radiation injury, establishing a model for radiation medical countermeasure development and further biomarker validation. Furthermore, we identified biomarkers that differentiate radiation dose and defined cell-specific targets for potential radiation mitigation therapies.

A comparative analysis of transcriptomics of newly diagnosed multiple myeloma: exploring drug repurposing

Multiple myeloma (MM) is an incurable malignant plasma cell disorder characterized by the infiltration of clonal plasma cells in the bone marrow compartment. Gene Expression Profiling (GEP) has emerged as a powerful investigation tool in modern myeloma research enabling the dissection of the molecular background of MM and allowing the identification of gene products that could potentially serve as targets for therapeutic intervention. In this study we investigated shared transcriptomic abnormalities across newly diagnosed multiple myeloma (NDMM) patient cohorts. In total, publicly available transcriptomic data of 7 studies from CD138+ cells from 281 NDMM patients and 44 healthy individuals were integrated and analyzed. Overall, we identified 28 genes that were consistently differentially expressed (DE) between NDMM patients and healthy donors (HD) across various studies. Of those, 9 genes were over/under-expressed in more than 75% of NDMM patients. In addition, we identified 4 genes (MT1F, PURPL, LINC01239 and LINC01480) that were not previously considered to participate in MM pathogenesis. Meanwhile, by mining three drug databases (ChEMBL, IUPHAR/BPS and DrugBank) we identified 31 FDA-approved and 144 experimental drugs that target 8 of these 28 over/under-expressed MM genes. Taken together, our study offers new insights in MM pathogenesis and importantly, it reveals potential new treatment options that need to be further investigated in future studies.

Novel Long Noncoding RNAs, LINC01093 and MYLK-AS1, Serve as Potential Diagnostic and Prognostic Biomarkers or Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most fatal human malignancies worldwide. In this research, we aimed to identify long noncoding RNAs (lncRNAs) as biomarkers for HCC diagnosis and prognosis. lncRNA expression profiles were obtained from Gene Expression Omnibus and The Cancer Genome Atlas databases. The differentially expressed lncRNAs between HCC and adjacent tissues were analyzed with bioinformatic tools. Four lncRNAs with area under the curve of the receiver operating characteristic curve >0.9 were selected from both datasets. Univariate and Kaplan-Meier analyses were performed to obtain LINC01093, MYLK-AS1, and MCM3AP-AS1 as the optimal diagnostic and prognostic biomarkers. Finally, qPCR confirmed that LINC01093 and MYLK-AS1 were significantly differentially expressed in HCC and adjacent normal tissues. In general, we demonstrated that novel lncRNAs, LINC01093 and MYLK-AS1, could be used as potential diagnostic and prognostic biomarkers for HCC.

Context-Dependent Function of Long Noncoding RNA PURPL in Transcriptome Regulation during p53 Activation

PURPL is a p53-induced lncRNA that suppresses basal p53 levels. Here, we investigated PURPL upon p53 activation in liver cancer cells, where it is expressed at significantly higher levels than other cell types. Using isoform sequencing, we discovered novel PURPL transcripts that have a retained intron and/or previously unannotated exons. To determine PURPL function upon p53 activation, we performed transcriptome sequencing (RNA-Seq) after depleting PURPL using CRISPR interference (CRISPRi), followed by Nutlin treatment to induce p53. Strikingly, although loss of PURPL in untreated cells altered the expression of only 7 genes, loss of PURPL resulted in altered expression of ~800 genes upon p53 activation, revealing a context-dependent function of PURPL. Pathway analysis suggested that PURPL is important for fine-tuning the expression of specific genes required for mitosis. Consistent with these results, we observed a significant decrease in the percentage of mitotic cells upon PURPL depletion. Collectively, these data identify novel transcripts from the PURPL locus and suggest that PURPL delicately moderates the expression of mitotic genes in the context of p53 activation to control cell cycle arrest.

Knockdown of the long noncoding RNA PURPL induces apoptosis and sensitizes liver cancer cells to doxorubicin

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer with increasing incidence in western countries. Most HCC patients have advanced cancer at the time of diagnosis due to the asymptomatic nature of early-stage HCC and do not qualify for potentially curative surgical treatment, thus, highlighting the need for new therapeutic strategies. Long noncoding RNAs (lncRNAs) comprise a large and heterogeneous group of non-protein coding transcripts that play important regulatory roles in numerous biological processes in cancer. In this study, we performed RNA sequencing of liver biopsies from ten HCC, ten hepatitis C virus-associated HCC, and four normal livers to identify dysregulated lncRNAs in HCC. We show that the lncRNA p53-upregulated-regulator-of-p53-levels (PURPL) is upregulated in HCC biopsies and that its expression is p53-dependent in liver cancer cell lines. In addition, antisense oligonucleotide-mediated knockdown of PURPL inhibited cell proliferation, induced apoptosis, and sensitized HepG2 human HCC cells to treatment with the chemotherapeutic agent doxorubicin. In summary, our findings suggest that PURPL could serve as a new therapeutic target for reversing doxorubicin resistance in HCC.

Non-Coding RNAs in Hepatocellular Carcinoma

Liver cancer ranks as the fourth leading cause of cancer-related deaths. Despite extensive research efforts aiming to evaluate the biological mechanisms underlying hepatocellular carcinoma (HCC) development, little has been translated towards new diagnostic and treatment options for HCC patients. Historically, the focus has been centered on coding RNAs and their respective proteins. However, significant advances in sequencing and RNA detection technologies have shifted the research focus towards non-coding RNAs (ncRNA), as well as their impact on HCC development and progression. A number of studies reported complex post-transcriptional interactions between various ncRNA and coding RNA molecules. These interactions offer insights into the role of ncRNAs in both the known pathways leading to oncogenesis, such as dysregulation of p53, and lesser-known mechanisms, such as small nucleolar RNA methylation. Studies investigating these mechanisms have identified prevalent ncRNA changes in microRNAs, snoRNAs, and long non-coding RNAs that can both pre- and post-translationally regulate key factors in HCC progression. In this review, we present relevant publications describing ncRNAs to summarize the impact of different ncRNA species on liver cancer development and progression and to evaluate recent attempts at clinical translation.

Four-copy number alteration (CNA)-related lncRNA prognostic signature for liver cancer

The objective of this study was to identify CNA-related lncRNAs that can better evaluate the prognosis of patients with liver cancer. Prognostic molecular subtypes were identified, followed by tumor mutation and differential expression analyses. Genomic copy number anomalies and their association with lncRNAs were also evaluated. A risk model was built based on lncRNAs, as well as a nomogram, and the differences in the tumor immune microenvironment and drug sensitivity between the High_ and Low_risk groups were compared. Weighted gene co-expression network analysis was used to identify modules with significant enrichment in prognostic-related lncRNAs. In total, two subtypes were identified, TP53 and CTNNB1 were common high-frequency mutated genes in the two subtypes. A total of 8,372 differentially expressed (DE) mRNAs and 798 DElncRNAs were identified between cluster1 and cluster2. In addition, a four-lncRNA signature was constructed, and statistically significant differences between the Low_ and High_risk groups were found in terms of CD8 T cells, resting memory CD4 T cells, etc. Enrichment analysis showed that prognostic-related lncRNAs were involved in the cell cycle, p53 signaling pathway, non-alcoholic fatty liver disease, etc. A prognostic prediction signature, based on four-CNA-related lncRNAs, could contribute to a more accurate prognosis of patients with liver cancer.

Reduced RBPMS Levels Promote Cell Proliferation and Decrease Cisplatin Sensitivity in Ovarian Cancer Cells

Worldwide, the number of cancer-related deaths continues to increase due to the ability of cancer cells to become chemotherapy-resistant and metastasize. For women with ovarian cancer, a staggering 70% will become resistant to the front-line therapy, cisplatin. Although many mechanisms of cisplatin resistance have been proposed, the key mechanisms of such resistance remain elusive. The RNA binding protein with multiple splicing (RBPMS) binds to nascent RNA transcripts and regulates splicing, transport, localization, and stability. Evidence indicates that RBPMS also binds to protein members of the AP-1 transcription factor complex repressing its activity. Until now, little has been known about the biological function of RBPMS in ovarian cancer. Accordingly, we interrogated available Internet databases and found that ovarian cancer patients with high RBPMS levels live longer compared to patients with low RBPMS levels. Similarly, immunohistochemical (IHC) analysis in a tissue array of ovarian cancer patient samples showed that serous ovarian cancer tissues showed weaker RBPMS staining when compared with normal ovarian tissues. We generated clustered regularly interspaced short palindromic repeats (CRISPR)-mediated RBPMS knockout vectors that were stably transfected in the high-grade serous ovarian cancer cell line, OVCAR3. The knockout of RBPMS in these cells was confirmed via bioinformatics analysis, real-time PCR, and Western blot analysis. We found that the RBPMS knockout clones grew faster and had increased invasiveness than the control CRISPR clones. RBPMS knockout also reduced the sensitivity of the OVCAR3 cells to cisplatin treatment. Moreover, β-galactosidase (β-Gal) measurements showed that RBPMS knockdown induced senescence in ovarian cancer cells. We performed RNAseq in the RBPMS knockout clones and identified several downstream-RBPMS transcripts, including non-coding RNAs (ncRNAs) and protein-coding genes associated with alteration of the tumor microenvironment as well as those with oncogenic or tumor suppressor capabilities. Moreover, proteomic studies confirmed that RBPMS regulates the expression of proteins involved in cell detoxification, RNA processing, and cytoskeleton network and cell integrity. Interrogation of the Kaplan-Meier (KM) plotter database identified multiple downstream-RBPMS effectors that could be used as prognostic and response-to-therapy biomarkers in ovarian cancer. These studies suggest that RBPMS acts as a tumor suppressor gene and that lower levels of RBPMS promote the cisplatin resistance of ovarian cancer cells.

Effect of tumor-associated macrophages on lncRNA PURPL/miR-363/PDZD2 axis in osteosarcoma cells

Tumor-associated macrophages (TAMs) are known to participate in osteosarcoma (OS) progression. As demonstrated in our previous research, miR-363 played a tumor inhibitory effect in OS cells via lowering the PDZ domain containing 2 (PDZD2) expression. The regulatory roles of TAMs on miR-363/PDZD2 and the internal mechanism relating to long noncoding RNA p53 upregulated regulator of P53 levels (lncRNA PURPL) are examined in this study. TAM-like macrophages were formed by inducing CD14⁺ peripheral blood mononuclear cells (PBMCs). The TAMs migration was detected after MG-63 cells transfected with miR-363 mimics or inhibitors. We then analyzed the regulatory activity of PURPL on miR-363 expression. We also tested the influences of PURPL overexpression/knockdown on MG-63 cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), as well as TAMs migration. Silence in PDZD2 expression was used to confirm the effects of PURPL on MG-63 cells. We successfully induced TAM-like macrophages. MG-63 cells transfecting miR-363 mimics suppressed TAMs migration while transfecting a converse effect was seen in miR-363 inhibitor. TAMs raised PURPL expression in MG-63 cells, which was an upstream regulator of miR-363. Along with TAMs migration, PURPL overexpression promoted MG-63 cell proliferation, migration, invasion, and EMT. An opposite influence was seen due to the PURPL knockdown. The silence of PDZD2 weakened the influences of PURPL overexpression on MG-63 cells and TAMs migration. On modulating the PURPL/miR-363/PDZD2 axis, TAMs-promoted OS development might be achieved.

Disregulations of PURPL and MiR-338-3p Could Serve As Prognosis Biomarkers for Epithelial Ovarian Cancer

Objective: The present study aimed to explore the expressions of long noncoding RNA (lncRNA) p53 upregulated regulator of p53 levels (PURPL) in different ovarian tissues, and to evaluate the significance of disregulations of PURPL and microRNA-338-3p (miR-338-3p) in epithelial ovarian cancer (EOC).

Methods: The expressions of PURPL in ovarian cancer, the relations between PURPL and the prognosis of ovarian cancer, and the relation between PURPL and miR-338-3p were queried in multiple biomedical databases. Real-time PCR was performed to detect the expressions of PURPL in different ovarian tissues. Logistic regression analysis was used to analyze the risk factors of recurrence and death. Kaplan-Meier analysis was implemented to evaluate the relations between PURPL and miR-338-3p expressions and the survival of ovarian cancer.

Results: PURPL could target miR-338-3p, PURPL were upregulated in ovarian cancer tissues, upregulation of PURPL in ovarian cancer was negatively related with the recurrence free survival (RFS) and overall survival (OS), which were indicated by biomedical databases query. Our data showed upregulations of PURPL were noted in ovarian cancer tissues. Higher expressions of PURPL were associated with more advanced FIGO stage and developed lymph node metastasis in epithelial ovarian cancer. Upregulation of PURPL was related with the recurrence (P=0.002, OR=21.482, 95%CI: 3.457~94.251) and death (P=0.004, OR=35.643, 95%CI: 2.453~84.359) of ovarian cancer patient. PURPL expressions were negatively correlated to miR-338-3p expressions in different ovarian tissues (r = -0.968, P<0.0001). Poor RFS (χ²=19.410, P=0.0002) and OS (χ²=17.600, P=0.0005) were found in patients with high level PURPL and low level miR-338-3p expressions.

Conclusions: Upregulation of PURPL and downregulation of miR-338-3p were related with the poor RFS and OS of ovarian cancer, which indicated disregulations of PURPL and miR-338-3p could serve as prognosis biomarkers for epithelial ovarian cancer.

Construction and analysis of competing endogenous RNA network of MCF-7 breast cancer cells based on the inhibitory effect of 6-thioguanine on cell proliferation

Previous research has proven that 6-thioguanine (6-TG) inhibits the growth of MCF-7 breast cancer cells. Accumulating evidence indicates that long non-coding (lnc)RNAs are involved in the development of various cancer types as competitive endogenous (ce)RNA molecules. The present study was conducted to investigate the regulatory mechanism underlying the function of lncRNAs as ceRNA molecules in MCF-7 cells and to identify more effective prognostic biomarkers for breast cancer treatment. The expression profiles of lncRNAs in untreated MCF-7 cells and 6-TG-treated MCF-7 cells were compared by RNA-seq. The regulatory associations among lncRNAs, micro (mi)RNAs and mRNAs were analyzed and verified by the TargetScan, miRDB and miRTarBas databases. The ceRNA networks were constructed by Cytoscape. The expression levels of two lncRNAs and two miRNAs in the ceRNA network were measured by reverse transcription-quantitative PCR. The OncoLnc and Kaplan-Meier plotter network databases were utilized to determine the effects of lncRNA and miRNA expression on the survival of patients with breast cancer. A ceRNA network was constructed for MCF-7 breast cancer cells treated with 6-TG, and this network may provide valuable information for further research elucidating the molecular mechanism underlying the effects of 6-TG on breast cancer. Moreover, LINC00324, MIR22HG, miR-370-3p and miR-424-5p were identified as potential prognostic and therapeutic biomarkers for breast cancer.

Deciphering the Mounting Complexity of the p53 Regulatory Network in Correlation to Long Non-Coding RNAs (lncRNAs) in Ovarian Cancer

Amongst the various gynecological malignancies affecting female health globally, ovarian cancer is one of the predominant and lethal among all. The identification and functional characterization of long non-coding RNAs (lncRNAs) are made possible with the advent of RNA-seq and the advancement of computational logarithm in understanding human disease biology. LncRNAs can interact with deoxyribonucleic acid (DNA), ribonucleic acid (RNA), proteins and their combinations. Moreover, lncRNAs regulate orchestra of diverse functions including chromatin organization and transcriptional and post-transcriptional regulation. LncRNAs have conferred their critical role in key biological processes in human cancer including tumor initiation, proliferation, cell cycle, apoptosis, necroptosis, autophagy, and metastasis. The interwoven function of tumor-suppressor protein p53-linked lncRNAs in the ovarian cancer paradigm is of paramount importance. Several lncRNAs operate as p53 regulators or effectors and modulates a diverse array of functions either by participating in various signaling cascades or via interaction with different proteins. This review highlights the recent progress made in the identification of p53 associated lncRNAs while elucidating their molecular mechanisms behind the altered expression in ovarian cancer tumorigenesis. Moreover, the development of novel clinical and therapeutic strategies for targeting lncRNAs in human cancers harbors great promise.