Integrating high-throughput microRNA and mRNA expression data to identify risk mRNA signature for pancreatic cancer prognosis

Identifying and characterizing drug sensitivity-related lncRNA-TF-gene regulatory triplets

Recently, many studies have shown that lncRNA can mediate the regulation of TF-gene in drug sensitivity. However, there is still a lack of systematic identification of lncRNA-TF-gene regulatory triplets for drug sensitivity. In this study, we propose a novel analytic approach to systematically identify the lncRNA-TF-gene regulatory triplets related to the drug sensitivity by integrating transcriptome data and drug sensitivity data. Totally, 1570 drug sensitivity-related lncRNA-TF-gene triplets were identified, and 16 307 relationships were formed between drugs and triplets. Then, a comprehensive characterization was performed. Drug sensitivity-related triplets affect a variety of biological functions including drug response-related pathways. Phenotypic similarity analysis showed that the drugs with many shared triplets had high similarity in their two-dimensional structures and indications. In addition, Network analysis revealed the diverse regulation mechanism of lncRNAs in different drugs. Also, survival analysis indicated that lncRNA-TF-gene triplets related to the drug sensitivity could be candidate prognostic biomarkers for clinical applications. Next, using the random walk algorithm, the results of which we screen therapeutic drugs for patients across three cancer types showed high accuracy in the drug-cell line heterogeneity network based on the identified triplets. Besides, we developed a user-friendly web interface-DrugSETs (http://bio-bigdata.hrbmu.edu.cn/DrugSETs/) available to explore 1570 lncRNA-TF-gene triplets relevant with 282 drugs. It can also submit a patient’s expression profile to predict therapeutic drugs conveniently. In summary, our research may promote the study of lncRNAs in the drug resistance mechanism and improve the effectiveness of treatment.

Riluzole regulates pancreatic cancer cell metabolism by suppressing the Wnt-β-catenin pathway

Most cancer cells rely on aerobic glycolysis to support uncontrolled proliferation and evade apoptosis. However, pancreatic cancer cells switch to glutamine metabolism to survive under hypoxic conditions. Activation of the Wnt/β-catenin pathway induces aerobic glycolysis by activating enzymes required for glucose metabolism and regulating the expression of glutamate transporter and glutamine synthetase. The results demonstrate that riluzole inhibits pancreatic cancer cell growth and has no effect on human pancreatic normal ductal epithelial cells. RNA-seq experiments identified the involvement of Wnt and metabolic pathways by riluzole. Inhibition of Wnt-β-catenin/TCF-LEF pathway by riluzole suppresses the expression of PDK, MCT1, cMyc, AXIN, and CyclinD1. Riluzole inhibits glucose transporter 2 expression, glucose uptake, lactate dehydrogenase A expression, and NAD + level. Furthermore, riluzole inhibits glutamate release and glutathione levels, and elevates reactive oxygen species. Riluzole disrupts mitochondrial homeostasis by inhibiting Bcl-2 and upregulating Bax expression, resulting in a drop of mitochondrial membrane potential. Finally, riluzole inhibits pancreatic cancer growth in KPC (Pdx1-Cre, LSL-Trp53R172H, and LSL-KrasG12D) mice. In conclusion, riluzole can inhibit pancreatic cancer growth by regulating glucose and glutamine metabolisms and can be used to treat pancreatic cancer.

Establishment of a 4-miRNA Prognostic Model for Risk Stratification of Patients With Pancreatic Adenocarcinoma

Pancreatic adenocarcinomas (PAADs) often remain undiagnosed until later stages, limiting treatment options and leading to poor survival. The lack of robust biomarkers complicates PAAD prognosis, and patient risk stratification remains a major challenge. To address this issue, we established a panel constructed by four miRNAs (miR-4444-2, miR-934, miR-1301 and miR-3655) based on The Cancer Genome Atlas (TCGA) and Human Cancer Metastasis Database (HCMDB) to predicted the prognosis of PAAD patients. Then, a risk prediction model of these four miRNAs was constructed by using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) regression analysis. This model stratified TCGA PAAD cohort into the low-risk and high-risk groups based on the panel-based risk score, which was significantly associated with 1-, 2-, 3-year OS (AUC=0.836, AUC=0.844, AUC=0.952, respectively). The nomogram was then established with a robust performance signature for predicting prognosis compared to clinical characteristics of pancreatic cancer (PC) patients, including age, gender and clinical stage. Moreover, two GSE data were validated the expressions of 4 miRNAs with prognosis/survival outcome in PC. In the external clinical sample validation, the high-risk group with the upregulated expressions of miR-934/miR-4444-2 and downregulated expressions of miR-1301/miR-3655 were indicated a poor prognosis. Furthermore, the cell counting kit-8 (CCK-8) assay, clone formation, transwell and wound healing assay also confirmed the promoting effect of miR-934/miR-4444-2 and the inhibiting effect of miR-1301/miR-3655 in PC cell proliferation and migration. Taken together, we identified a new 4-miRNA risk stratification model could be used in predicting prognosis in PAAD.

PRSS1 Upregulation Predicts Platinum Resistance in Ovarian Cancer Patients

Ovarian cancer is the most frequent cause of death among gynecologic malignancies. A total of 80% of patients who have completed platinum-based chemotherapy suffer from relapse and develop resistance within 2 years. In the present study, we obtained patients' complete platinum (cisplatin and carboplatin) medication information from The Cancer Genome Atlas database and then divided them into two categories: resistance and sensitivity. Difference analysis was performed to screen differentially expressed genes (DEgenes) related to platinum response. Subsequently, we annotated DEgenes into the protein–protein interaction network as seed nodes and analyzed them by random walk. Finally, second-ranking protease serine 1 gene (PRSS1) was selected as a candidate gene for verification analysis. PRSS1's expression pattern was continuously studied in Oncomine and cBio Cancer Genomic Portal databases, revealing the key roles of PRSS1 in ovarian cancer formation. Hereafter, we conducted in-depth explorations on PRSS1's platinum response to ovarian cancer through tissue and cytological experiments. Quantitative real-time polymerase chain reaction and Western blot assay results indicated that PRSS1 expression levels in platinum-resistant samples (tissue/cell) were significantly higher than in samples sensitive to platinum. By cell transfection assay, we observed that knockdown of PRSS1 reduced the resistance of ovarian cancer cells to cisplatin. Meanwhile, overexpression of PRSS1 increased the resistance to cisplatin. In conclusion, we identified a novel risk gene PRSS1 related to ovarian cancer platinum response and confirmed its key roles using multiple levels of low-throughput experiments, revealing a new treatment strategy based on a novel target factor for overcoming cisplatin resistance in ovarian cancer.

miR-573 suppresses pancreatic cancer cell proliferation, migration, and invasion through targeting TSPAN1

PURPOSE

To explore whether miR-573 can suppress pancreatic cancer cell proliferation, migration, and invasion by targeting TSPAN1.

METHODS

The expression of miR-573 and TSPAN1 in pancreatic cancer tissues and cells lines was analyzed using RT-qPCR. The human pancreatic cancer cell line PANC‑1 was transfected with miR-573 mimic, pcDNA3.1-TSPAN1, or genOFFTM st-h-TSPAN1. The effects of miR-573 and TSPAN1 on cell proliferation, colony formation, migration, and invasion were analyzed by CCK‑8, colony formation, transwell migration, and invasion assay, respectively. Target genes of miR-573 were screened using bioinformatics tools and confirmed by dual-luciferase reporter assay and real-time PCR. The effects of miR-573 in vivo were observed using tumor xenografts.

RESULTS

We found that miR-573 is downregulated and TSPAN1 is upregulated in pancreatic cancer tissues and cells lines. Function assays demonstrated that overexpression of miR-573 inhibited cell proliferation, colony formation, migration, and invasion of pancreatic cancer cells, as well as suppressing tumor growth in vivo. Target genes of miR-573 were predicted using bioinformatics tools and confirmed by dual-luciferase reporter assay and RT-qPCR or western blotting. Downregulation of TSPAN1 also inhibited cell proliferation, colony formation, migration, and invasion of pancreatic cancer cells. Furthermore, overexpression of TSPAN1 attenuated miR-573-induced inhibition of pancreatic cancer cell proliferation and migration.

CONCLUSION

Our findings indicated that miR-573 suppresses pancreatic cancer cell proliferation, migration, and invasion through targeting TSPAN1. TSPAN1 targeted by miR-573 might be a potential therapeutic target for clinical treatment of pancreatic cancer.

The identification of six risk genes for ovarian cancer platinum response based on global network algorithm and verification analysis

Ovarian cancer is the most lethal gynaecological cancer, and resistance of platinum‐based chemotherapy is the main reason for treatment failure. The aim of the present study was to identify candidate genes involved in ovarian cancer platinum response by analysing genes from homologous recombination and Fanconi anaemia pathways. Associations between these two functional genes were explored in the study, and we performed a random walk algorithm based on reconstructed gene‐gene network, including protein‐protein interaction and co‐expression relations. Following the random walk, all genes were ranked and GSEA analysis showed that the biological functions focused primarily on autophagy, histone modification and gluconeogenesis. Based on three types of seed nodes, the top two genes were utilized as examples. We selected a total of six candidate genes (FANCA, FANCG, POLD1, KDM1A, BLM and BRCA1) for subsequent verification. The validation results of the six candidate genes have significance in three independent ovarian cancer data sets with platinum‐resistant and platinum‐sensitive information. To explore the correlation between biomarkers and clinical prognostic factors, we performed differential analysis and multivariate clinical subgroup analysis for six candidate genes at both mRNA and protein levels. And each of the six candidate genes and their neighbouring genes with a mutation rate greater than 10% were also analysed by network construction and functional enrichment analysis. In the meanwhile, the survival analysis for platinum‐treated patients was performed in the current study. Finally, the RT‐qPCR assay was used to determine the performance of candidate genes in ovarian cancer platinum response. Taken together, this research demonstrated that comprehensive bioinformatics methods could help to understand the molecular mechanism of platinum response and provide new strategies for overcoming platinum resistance in ovarian cancer treatment.

IGFBP3 as an indicator of lymph node metastasis and unfavorable prognosis for papillary thyroid carcinoma

Lymph node metastasis (LNM) is a usual event in papillary thyroid carcinoma (PTC) patients, which usually leads to poor prognosis. However, the molecular mechanisms of LNM remain unclear. Thus, we aimed to screen the possible key genes in the progression of LNM in PTC patients and further validate their roles. The study involved two phases: a discovery phase and a validation one. In the former phase, the candidate genes were screened by using bioinformatics methods. In the latter one, the genes were firstly assessed in a cohort from the cancer genome atlas (TCGA) to evaluate the associations of their expressions with clinical features and the prognostic values, and then, they were assessed at protein levels by using an immunohistochemical assay. Consequently, IGHBP3 was selected as the candidate gene, which might be enriched in several metabolism-related pathways and cancer progression-related pathways. High expressions of IGHBP3 have an association with gender, advanced clinical stages, high T stages, and the presence of LNM. Survival analysis indicated that IGHBP3 may affect the prognosis of PTC patients. The use of a tissue chip confirmed the view that IGHBP3 might play a crucial role in the LNM of PTC. In conclusion, IGHBP3 might be involved in the development of LNM in PTC patients. IGHBP3 over-expression might be a novel indicator and a potential target for PTC therapy.

Genome-wide analysis of prognostic-related lncRNAs, miRNAs and mRNAs forming a competing endogenous RNA network in lung squamous cell carcinoma

PURPOSE

As a type of cancer with the highest morbidity and mortality, lung squamous cell carcinoma (LUSC) has a very poor prognosis. Long-non-coding RNA (lncRNA) has recently attracted attentions because it can play the role of competing endogenous RNA (ceRNA) to inhibit microRNA (miRNA) functions. In this study, we aimed to find prognosis-related lncRNAs, miRNAs and mRNAs and construct a prognosis-related ceRNA network.

METHODS

The original LUSC RNA-sequencing data and miRNA profiles data were downloaded from the cancer genome atlas (TCGA) database. Differentially expressed lncRNAs, miRNAs and mRNAs were then identified between patients with lymph node metastasis and no lymph node metastasis. Univariate Cox regression analysis was performed to find the survival-associated lncRNAs, miRNAs and mRNAs. Subsequently, prognostic-related ceRNA network was established. By multivariate Cox regression analysis, three lncRNA signatures and three mRNA signatures were developed and used for predicting LUSC patients' survival.

RESULTS

A total of 224 lncRNAs, 160 miRNAs, 913 mRNAs were identified between samples with lymph node metastasis and no lymph node metastasis. Univariate Cox regression analysis showed that, among them, 28 lncRNAs, 8 miRNAs, 105 mRNAs were significantly associated with patients' overall survival time. Further pathway and enrichment analysis suggested that these mRNAs were associated with the regulation of transmembrane transport, regulation of blood circulation, plasma lipoprotein particle organization. Then we constructed a survival-related ceRNA network including 9 lncRNAs, 8 miRNAs and 23 mRNAs. Additionally, a multivariate Cox regression analysis demonstrated that three lncRNAs (AL161431.1, LINC02389, APCDD1L.DT) and three mRNAs (KLK6, SLITRK5, CCDC177) had a significant prognostic value. Risk score indicated that lncRNA signature and mRNA signature could independently predict overall survival in LUSC patients.

CONCLUSION

The current study provided a better understanding of the ceRNA network in the progression of LUSC and laid a theoretical foundation for LUSC prognosis.