Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma.

BACKGROUND: Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers. METHODS: 10 machine-learning algorithms and their combinations were applied in this work. A stable Tstr-related score (TCs) was constructed to predict the outcomes and PD-1 blockade treatment response in ccRCC patients. A nomogram based on TCs for personalized prediction of patient prognosis was constructed. Functional enrichment analysis and TimiGP algorithm were used to explore the underlying role of Tstr in ccRCC. The key TCs-related gene was identified by comprehensive analysis, and the bioinformatics results were verified by immunohistochemistry using a tissue microarray. RESULTS: A robust TCs was constructed and validated in four independent cohorts. TCs accurately predicted the prognosis and PD-1 blockade treatment response in ccRCC patients. The novel nomogram was able to precisely predict the outcomes of ccRCC patients. The underlying biological process of Tstr was related to acute inflammatory response and acute-phase response. Mast cells were identified to be involved in the role of Tstr as a protective factor in ccRCC. TNFS13B was shown to be the key TCs-related gene, which was an independent predictor of unfavorable prognosis. The protein expression analysis of TNFSF13B was consistent with the mRNA analysis results. High expression of TNFSF13B was associated with poor response to PD-1 blockade treatment. CONCLUSIONS: This study provides a Tstr cell-related score for predicting outcomes and PD-1 blockade therapy response in ccRCC. Tstr cells may exert their pro-tumoral role in ccRCC, acting against mast cells, in the acute inflammatory tumor microenvironment. TNFSF13B could serve as a key biomarker related to TCs.

Bladder-sparing treatment using tislelizumab combined with gemcitabine/cisplatin in selected patients with muscle-invasive bladder cancer: a real-world study.

PURPOSE: To retrospectively evaluate the tislelizumab-based chemoimmunotherapy combined with gemcitabine/cisplatin for bladder-sparing in patients with muscle-invasive bladder cancer (MIBC). METHODS: Forty-five patients who received bladder-sparing treatment or radical cystectomy (RC) for MIBC (cT2-T4a, NxM0) were retrospectively enrolled. All patients received maximal transurethral resection of bladder tumor (mTURBT), followed by four cycles of chemo-immunotherapy with tislelizumab (PD-L1 inhibitor), gemcitabine, and cisplatin. Clinical efficacy was evaluated to compare the benefit of bladder-sparing treatment on clinical CR (cCR) and RC for non-cCR patients. The primary outcomes were bladder intact disease-free survival (BIDFS) and overall survival (OS), and the secondary outcomes were adverse effects. The PD-L1 status and molecular subtypes of tumors were analyzed. RESULTS: The overall survival rate was 88.8% (95%CI: 79.6%, 98.0%) at 12 months, 85.7% (95%CI: 74.9%, 96.5%) at 18 months, and 66.6% (95%CI: 45.2%, 88.0%) at 24 months. Twenty-nine patients (64.4%) achieved cCR and their OS rate was 96.6% (95%CI: 89.9%, 100%). Sixteen patients were in the non-cCR group, and their OS rate was 75.0% (95%CI: 53.8%, 96.2%) at 12 months, 65.6% (95%CI: 40.3%, 90.9%) at 18 months, and 52.5% (95%CI: 21.9%, 83.1%) at 24 months. The BIDFS rate for patients who received bladder-sparing treatment was 96.0% (95%CI: 88.4%, 100%) from 12 to 24 months. Four patients (8.8%) were PD-L1 positive and 41 patients (91.2%) were PD-L1 negative. CONCLUSIONS: Our retrospective study of patients with MIBC suggests that tislelizumab-based neoadjuvant therapy was a safe and effective bladder-sparing treatment.

FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to the HIF2α blockade by facilitating LDHA phosphorylation.

Renal cell carcinoma (RCC) is one of the three major malignant tumors of the urinary system and originates from proximal tubular epithelial cells. Clear cell renal cell carcinoma (ccRCC) accounts for approximately 80% of RCC cases and is recognized as a metabolic disease driven by genetic mutations and epigenetic alterations. Through bioinformatic analysis, we found that FK506 binding protein 10 (FKBP10) may play an essential role in hypoxia and glycolysis pathways in ccRCC progression. Functionally, FKBP10 promotes the proliferation and metastasis of ccRCC in vivo and in vitro depending on its peptidyl-prolyl cis-trans isomerase (PPIase) domains. Mechanistically, FKBP10 binds directly to lactate dehydrogenase A (LDHA) through its C-terminal region, the key regulator of glycolysis, and enhances the LDHA-Y10 phosphorylation, which results in a hyperactive Warburg effect and the accumulation of histone lactylation. Moreover, HIFα negatively regulates the expression of FKBP10, and inhibition of FKBP10 enhances the antitumor effect of the HIF2α inhibitor PT2385. Therefore, our study demonstrates that FKBP10 promotes clear cell renal cell carcinoma progression and regulates sensitivity to HIF2α blockade by facilitating LDHA phosphorylation, which may be exploited for anticancer therapy.

Metformin escape in prostate cancer by activating the PTGR1 transcriptional program through a novel super-enhancer.

The therapeutic efficacy of metformin in prostate cancer (PCa) appears uncertain based on various clinical trials. Metformin treatment failure may be attributed to the high frequency of transcriptional dysregulation, which leads to drug resistance. However, the underlying mechanism is still unclear. In this study, we found evidences that metformin resistance in PCa cells may be linked to cell cycle reactivation. Super-enhancers (SEs), crucial regulatory elements, have been shown to be associated with drug resistance in various cancers. Our analysis of SEs in metformin-resistant (MetR) PCa cells revealed a correlation with Prostaglandin Reductase 1 (PTGR1) expression, which was identified as significantly increased in a cluster of cells with metformin resistance through single-cell transcriptome sequencing. Our functional experiments showed that PTGR1 overexpression accelerated cell cycle progression by promoting progression from the G0/G1 to the S and G2/M phases, resulting in reduced sensitivity to metformin. Additionally, we identified key transcription factors that significantly increase PTGR1 expression, such as SRF and RUNX3, providing potential new targets to address metformin resistance in PCa. In conclusion, our study sheds new light on the cellular mechanism underlying metformin resistance and the regulation of the SE-TFs-PTGR1 axis, offering potential avenues to enhance metformin's therapeutic efficacy in PCa.

SpreadRank: A Novel Approach for Identifying Influential Spreaders in Complex Networks.

Identifying influential spreaders in complex networks is critical for information spread and malware diffusion suppression. In this paper, we propose a novel influential spreader identification method, called SpreadRank, which considers the path reachability in information spreading and uses its quantitative index as a measure of node spread centrality to obtain the spread influence of a single node. To avoid the overlapping of the influence range of the node spread, this method establishes a dynamic influential node set selection mechanism based on the spread centrality value and the principle of minimizing the maximum connected branch after network segmentation, and it selects a group of nodes with the greatest overall spread influence. Experiments based on the SIR model demonstrate that, compared to other existing methods, the selected influential spreaders of SpreadRank can quickly diffuse or suppress information more effectively.

EID3 Promotes Cancer Stem Cell-Like Phenotypes in Osteosarcoma through the Activation of PI3K-AKT Signaling Pathway.

The aim of this study is to elucidate molecular mechanism by which E1A-like inhibitor of differentiation 3 (EID3) promotes cancer stem cell-like phenotypes in osteosarcoma. Overexpression of EID3 in osteosarcoma cells generated more spherical clones, enhanced the expression of stemness-associated genes, and promoted chemoresistance, invasion, and metastasis. Furthermore, osteosarcoma cells overexpressing EID3 had increased ability to grow in suspension as osteospheres with high expression of Sox2 and stem cell marker CD133. In addition, knockdown of EID3 reduced sphere formation and inhibited osteosarcoma cell migration and invasion. RNA sequencing and bioinformatics analysis revealed that PI3K-Akt signaling pathway and MAPK pathway-related genes were enriched in osteosarcoma cells with high expression of EID3. Taken together, EID3 promotes osteosarcoma, and EID3-PI3K-Akt axis is a potential therapeutic target for osteosarcoma treatment.

Differential Expression of E2F Transcription Factors and Their Functional and Prognostic Roles in Human Prostate Cancer.

Given the tumor heterogeneity, most of the current prognostic indicators cannot accurately evaluate the prognosis of patients with prostate cancer, and thus, the best opportunity to intervene in the progression of this disease is missed. E2F transcription factors (E2Fs) have been reported to be involved in the growth of various cancers. Accumulating studies indicate that prostate cancer (PCa) carcinogenesis is attributed to aberrant E2F expression or E2F alteration. However, the expression patterns and prognostic value of the eight E2Fs in prostate cancer have yet to be explored. In this study, The Cancer Genome Atlas (TCGA), Kaplan-Meier Plotter, Metascape, the Kyoto Encyclopedia of Genes and Genomes (KEGG), CIBERSORT, and cBioPortal and bioinformatic analysis were used to investigate E2Fs in patients with PCa. Our results showed that the expression of E2F1-3, E2F5, and E2F6 was higher in prostate cancer tissues than in benign tissues. Furthermore, elevated E2F1-3 and E2F5 expression levels were associated with a higher Gleason score (GS), advanced tumor stage, and metastasis. Survival analysis suggested that high transcription levels of E2F1-3, E2F5, E2F6, and E2F8 were associated with a higher risk of biochemical recurrence. In addition, we developed a prognostic model combining E2F1, E2F6, Gleason score, and the clinical stage that may accurately predict a biochemical recurrence-free survival. Functional enrichment analysis revealed that the E2F family members and their neighboring genes were mainly enriched in cell cycle-related pathways. Somatic mutations in different subgroups were also investigated, and immune components were predicted. Further experiments are warranted to clarify the biological associations between Pca-related E2F family genes, which may influence prognosis via the cell cycle pathway.

Tumor Suppressor Role and Clinical Significance of the FEV Gene in Prostate Cancer.

Background: In our previous research, we developed a 32-gene risk index model that may be utilized as a robust prognostic method for predicting prostate cancer (PCa) recurrence after surgery. Among the 32 genes, the Fifth Ewing Variant (FEV) gene was one of the top downregulated genes in relapsed PCa. However, current understanding of the FEV gene and its involvement in PCa is limited. Methods: FEV mRNA expression was analyzed and correlated to clinical outcomes in PCa patients who underwent prostatectomy at the Massachusetts General Hospital. Specimens from tissue microarray (TMA) including 102 prostate cancer patients were analysis for the expression of FEV. Meanwhile, FEV expression profiles were also assessed in PCa cell lines and in BPH-1 prostate epithelial cells using western blotting and quantitative reverse transcription-PCR (qRT-PCR). Furthermore, we transfected LNCaP and PC-3 cells with either an empty vector or full-length FEV gene and performed in vitro cell functional assays. The part FEV plays in tumor xenograft growth was also assessed in vivo. Results: Of the 191 patients included in this study base on the DASL dataset, 77 (40.3%) and 24 (13.6%), respectively, developed prostate-specific antigen (PSA) relapse and metastasis postradical prostatectomy. Significant FEV downregulation was observed in PCa patients showing PSA failure and metastasis. The protein expression of FEV was significantly negatively correlated with the Gleason score and pathological stage in prostate cancer tissues. Similarly, FEV expression significantly decreased in all PCa cell lines relative to BPH-1 (all P < 0.05). Functional assays revealed that FEV expression markedly inhibited PCa cell growth, migration, and invasion, which in turn significantly repressed the growth of tumor xenografts in vivo. Conclusion: The results of this study suggest an association between downregulated FEV expression and PSA relapse in PCa patients. In addition, FEV may act as a tumor suppressor in PCa.

The prognostic roles of CYP19A1 expression in bladder cancer patients of different genders.

BACKGROUND: The incidence of bladder cancer (BCa) in male is approximately three to four times higher than in female, but the oncological outcomes in female patients with BCa are significantly worse than in male patients. Although many biomarkers have been identified in recent decades to predict the prognosis of BCa patients, few of them are able to distinguish the prognosis of BCa patients with gender difference. Aromatase encoded by the CYP19A1 gene catalyzes the conversion of androgens to estrogens. In this study, we investigate the prognosis significance of CYP19A1 expression considering the gender difference in BCa patients from four available public databases. METHODS: Four available public databases of BCa, including GSE13507, TCGA-BLCA, E-MTAB-4321, and E-MTAB-1803, were utilized in this analysis. The overall survival (OS) and progression-free survival (PFS) in different stages and genders were evaluated using the Kaplan-Meier analysis based on the optimal cut-off values of CYP19A1 expression. Then, Gene Set Enrichment Analysis (GSEA) were further performed to explore the potential biologic pathways by altering CYP19A1 expression in BCa patients. RESULTS: The results showed that patients with high CYP19A1 expression had a poorer outcome compared with those with low expression in both BCa cohorts in general. Higher CYP19A1 expression in male patients were significantly associated with shorter survival for either non-muscle-invasive bladder cancer (NMIBC) or muscle-invasive bladder cancer (MIBC). However, female NMIBC patients with high CYP19A1 expression were identified to have a better prognosis, whereas high CYP19A1 expression in female MIBC patients were significantly associated with poorer survival. The result of the GSEA showed that different outcomes in female and male patients with NMIBC were related to the interaction of CYP19A1 and the cell-cycle-related pathways. CONCLUSIONS: These findings demonstrated that CYP19A1 expression might have a potential role in distinguishing the prognosis of female BCa patients dependent on tumor stage. Our results provide new insights for aromatase-mediated BCa therapy.

Malware propagation model for cluster-based wireless sensor networks using epidemiological theory.

Due to limited resources, wireless sensor network (WSN) nodes generally possess weak defense capabilities and are often the target of malware attacks. Attackers can capture or infect specific sensor nodes and propagate malware to other sensor nodes in WSNs through node communication. This can eventually infect an entire network system and even cause paralysis. Based on epidemiological theory, the present study proposes a malware propagation model suitable for cluster-based WSNs to analyze the propagation dynamic of malware. The model focuses on the data-transmission characteristics between different nodes in a cluster-based network and considers the actual application parameters of WSNs, such as node communication radius, node distributed density, and node death rate. In addition, an attack and defense game between malware and defending systems is also established, and the infection and recovery rates of malware propagation under the mixed strategy Nash equilibrium condition are given. In particular, the basic reproductive number, equilibrium point, and stability of the model are derived. These studies revealed that a basic reproductive number of less than 1 leads to eventual disappearance of malware, which provides significant insight into the design of defense strategies against malware threats. Numerical experiments were conducted to validate the theory proposed, and the influence of WSN parameters on malware propagation was examined.

Identification and Validation of a PPP1R12A-Related Five-Gene Signature Associated With Metabolism to Predict the Prognosis of Patients With Prostate Cancer.

BACKGROUND: Prostate cancer (PCa) is the most common malignant male neoplasm in the American male population. Our prior studies have demonstrated that protein phosphatase 1 regulatory subunit 12A (PPP1R12A) could be an efficient prognostic factor in patients with PCa, promoting further investigation. The present study attempted to construct a gene signature based on PPP1R12A and metabolism-related genes to predict the prognosis of PCa patients. METHODS: The mRNA expression profiles of 499 tumor and 52 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. We selected differentially expressed PPP1R12A-related genes among these mRNAs. Tandem affinity purification-mass spectrometry was used to identify the proteins that directly interact with PPP1R12A. Gene set enrichment analysis (GSEA) was used to extract metabolism-related genes. Univariate Cox regression analysis and a random survival forest algorithm were used to confirm optimal genes to build a prognostic risk model. RESULTS: We identified a five-gene signature (PPP1R12A, PTGS2, GGCT, AOX1, and NT5E) that was associated with PPP1R12A and metabolism in PCa, which effectively predicted disease-free survival (DFS) and biochemical relapse-free survival (BRFS). Moreover, the signature was validated by two internal datasets from TCGA and one external dataset from the Gene Expression Omnibus (GEO). CONCLUSION: The five-gene signature is an effective potential factor to predict the prognosis of PCa, classifying PCa patients into high- and low-risk groups, which might provide potential novel treatment strategies for these patients.

Corrigendum: TFEB Promotes Prostate Cancer Progression via Regulating ABCA2-Dependent Lysosomal Biogenesis.

[This corrects the article DOI: 10.3389/fonc.2021.632524.].

A HIF1α-GPD1 feedforward loop inhibits the progression of renal clear cell carcinoma via mitochondrial function and lipid metabolism.

BACKGROUND: Hypoxia signaling, especially the hypoxia inducible factor (HIF) pathway, is a major player in clear cell renal cell carcinoma (ccRCC), which is characterized by disorders in lipid and glycogen metabolism. However, the interaction between hypoxia and lipid metabolism in ccRCC progression is still poorly understood. METHODS: We used bioinformatic analysis and discovered that glycerol-3-phosphate dehydrogenase 1 (GPD1) may play a key role in hypoxia and lipid metabolism pathways in ccRCC. Tissue microarray, IHC staining, and survival analysis were performed to evaluate clinical function. In vitro and in vivo assays showed the biological effects of GPD1 in ccRCC progression. RESULTS: We found that the expression of GPD1 was downregulated in ccRCC tissues, and overexpression of GPD1 inhibited the progression of ccRCC both in vivo and in vitro. Furthermore, we demonstrated that hypoxia inducible factor-1α (HIF1α) directly regulates GPD1 at the transcriptional level, which leads to the inhibition of mitochondrial function and lipid metabolism. Additionally, GPD1 was shown to inhibit prolyl hydroxylase 3 (PHD3), which blocks prolyl-hydroxylation of HIF1α and subsequent proteasomal degradation, and thus reinforces the inhibition of mitochondrial function and phosphorylation of AMPK via suppressing glycerol-3-phosphate dehydrogenase 2 (GPD2). CONCLUSIONS: This study not only demonstrated that HIF1α-GPD1 forms a positive feedforward loop inhibiting mitochondrial function and lipid metabolism in ccRCC, but also discovered a new mechanism for the molecular basis of HIF1α to inhibit tumor activity, thus providing novel insights into hypoxia-lipid-mediated ccRCC therapy.

Malware homology determination using visualized images and feature fusion.

The family homology determination of malware has become a research hotspot as the number of malware variants are on the rise. However, existing studies on malware visualization only determines homology based on the global structure features of executable, which leads creators of some malware variants with the same structure intentionally set to misclassify them as the same family. We sought to develop a homology determination method using the fusion of global structure features and local fine-grained features based on malware visualization. Specifically, the global structural information of the malware executable file was converted into a bytecode image, and the opcode semantic information of the code segment was extracted by the n-gram feature model to generate an opcode image. We also propose a dual-branch convolutional neural network, which features the opcode image and bytecode image as the final family classification basis. Our results demonstrate that the accuracy and F-measure of family homology classification based on the proposed scheme are 99.05% and 98.52% accurate, respectively, which is better than the results from a single image feature or other major schemes.

TFEB Promotes Prostate Cancer Progression via Regulating ABCA2-Dependent Lysosomal Biogenesis.

Transcription factor EB (TFEB), a member of the MiT family, is dysregulated in different cancers and exerts specific biological functions within the tumor microenvironment. Downregulation of TFEB induces macrophage polarization in the TME and promotes tumor progression. However, the biological role and clinical significance of TFEB in prostate cancer (PCa) remain unknown. This study aimed to identify the role of TFEB in PCa and its potential clinical value. We explored TFEB expression in PCa using public databases and verified its prognostic value using immunohistochemistry in PCa tissue samples. The results revealed that TFEB expression was up-regulated in PCa tissues and was associated with cancer metastasis. Next, overexpression of TFEB promoted PCa cell malignant behavior in in vivo and in vitro experiments. RNA-sequencing and bioinformatics analysis showed high expression of TFEB promoted lysosomal biogenesis and knockdown of TFEB expression decreased the number of lysosomes. Furthermore, the ATP-binding cassette transporter A2 (ABCA2) was identified as a target gene of TFEB, which was verified using the cleavage under targets and release using nuclease (CUT&RUN) assay and qRT-PCR. Silencing of ABCA2 reduced lysosomal biogenesis and decreased matrix metalloproteinases expression, which reduced PCa cell invasion and migration in the tumor microenvironment. Our study suggests that TFEB promotes PCa progression by regulating ABCA2 through lysosomal biogenesis and may serve as a prognostic factor or as a potential therapeutic target of PCa.

Down-regulation of ACACA suppresses the malignant progression of Prostate Cancer through inhibiting mitochondrial potential.

Background and aim: Silencing the expression of ACACA inhibits cell proliferation and induces apoptosis in prostate cancer LNCaP cells. However, the role of ACACA in other prostate cancer cells is not fully understood. Also, the effect of knocking down ACACA gene on mitochondria remains unclear. This study aimed to discover the specific role of ACACA gene in prostate cancer (PCa) DU145 and PC3 cells as well as its effects on mitochondrial potential. Methods: The expression of ACACA gene was detected in human prostate cancer tissue microarrays and assessed in different clinical stages. Then, prostate cancer cell lines with low expression of ACACA were constructed to evaluate the changes in their cell cycle, proliferation, and metabolites. The effect of ACACA on tumor formation in vivo was analyzed. Also, mito-ATP production, mitochondrial staining, and mtDNA, nicotinamide adenine dinucleotide (NAD+/NADH), and reactive oxygen species (ROS) levels were detected. Results: ACACA was expressed more strongly in prostate cancer tissues. The expression level of ACACA was higher in patients with advanced PCa than in patients with lower grades. The proliferation ability reduced in ACACA-knockdown cells. In in vivo tests, the tumor volume and weight were lower in the experimental group than in the control group. Mito-ATP production decreased significantly after ACACA suppression, mtDNA levels and MitoTracker staining decreased in the experimental group. The ratio of NAD+/NADH and ROS levels were upregulated in the experimental group. Conclusion: Targeting ACACA gene and mitochondria might serve as a novel therapy for prostate cancer treatment.

Aberrant Expression of Citrate Synthase is Linked to Disease Progression and Clinical Outcome in Prostate Cancer.

PURPOSE: Citrate synthase (CS) is a rate-limiting enzyme in the citrate cycle and is capable of catalyzing oxaloacetate and acetyl-CoA to citrate. CS has been uncovered to be upregulated in a variety of cancers, and its expression and clinical significance in prostate cancer (PCa) remain unknown. METHODS: In this study, we examined the association between CS expression level and clinicopathological features of prostate cancer patients in a TMA cohort and the public cancer database (The Cancer Genome Atlas-Prostate Adenocarcinoma, TCGA-PRAD). The CS knockdown cell lines were constructed to study the effects of CS downregulation on proliferation, colony formation, migration, invasion, and cell cycle of prostate cancer cells in vitro. And the effect of CS downregulation on tumor growth in mice was studied in vivo. In addition, the metabolomics and mitochondrial function were detected in the CS knockdown cell lines. RESULTS: CS expression level in PCa tissues was higher than that in normal tissues (P < 0.05). CS upregulation was significantly associated with high Gleason score (P < 0.05), advanced pathological stage (P < 0.001), and biochemical recurrence (P < 0.001). Functionally, decreased expression of CS inhibited PCa cell proliferation, colony formation, migration, invasion and cell cycle in vitro, and inhibited tumor growth in vivo. In addition, CS downregulation exerted potential inhibitory effects on the lipid metabolism and mitochondrial function of PCa cells. CONCLUSION: In conclusion, these findings suggested that CS upregulation may contribute to the aggressive progression and poor prognosis of PCa patients, which might be partially associated with its influences on the cell lipid metabolism and mitochondrial function.

GPD1 Enhances the Anticancer Effects of Metformin by Synergistically Increasing Total Cellular Glycerol-3-Phosphate.

Metformin is an oral drug widely used for the treatment of type 2 diabetes mellitus. Numerous studies have demonstrated the value of metformin in cancer treatment. However, for metformin to elicit effects on cancer often requires a high dosage, and any underlying mechanism for how to improve its inhibitory effects remains unknown. Here, we found that low mRNA expression of glycerol-3-phosphate dehydrogenase 1 (GPD1) may predict a poor response to metformin treatment in 15 cancer cell lines. In vitro and in vivo, metformin treatment alone significantly suppressed cancer cell proliferation, a phenotype enhanced by GPD1 overexpression. Total cellular glycerol-3-phosphate concentration was significantly increased by the combination of GPD1 overexpression and metformin treatment, which suppressed cancer growth via inhibition of mitochondrial function. Eventually, increased reactive oxygen species and mitochondrial structural damage was observed in GPD1-overexpressing cell lines treated with metformin, which may contribute to cell death. In summary, this study demonstrates that GPD1 overexpression enhances the anticancer activity of metformin and that patients with increased GPD1 expression in tumor cells may respond better to metformin therapy. SIGNIFICANCE: GPD1 overexpression enhances the anticancer effect of metformin through synergistic inhibition of mitochondrial function, thereby providing new insight into metformin-mediated cancer therapy.

lncRNA NR_038323 Suppresses Renal Fibrosis in Diabetic Nephropathy by Targeting the miR-324-3p/DUSP1 Axis.

Several studies have suggested that long intergenic noncoding RNAs are involved in the progression of diabetic nephropathy (DN). However, the exact role and regulatory mechanism of long noncoding RNA (lncRNA) NR_038323 in diabetic nephropathy (DN) remain largely unclear. In the present study, we found that lncRNA NR_038323 overexpression ameliorated the high glucose (HG)-induced expression levels of collagen I, collagen IV, and fibronectin, whereas lncRNA NR_038323 knockdown exerted the opposite effects. Moreover, the results of bioinformatic prediction, luciferase assay, and fluorescence in situ hybridization (FISH) demonstrated that lncRNA NR_038323 directly interacted with miR-324-3p. Additionally, miR-324-3p mimic aggravated the HG-induced expression levels of collagen I, collagen IV, and fibronectin by dual-specificity protein phosphatase-1 (DUSP1) expression to activate p38 mitogen-activated protein kinase (MAPK) and ERK1/2 pathways. In contrast, overexpression of DUSP1 attenuated the HG-induced expression levels of collagen I, collagen IV, and fibronectin via inactivation of p38 MAPK and ERK1/2 pathways. In addition, lncRNA NR_038323 knockdown increased the expression levels of collagen I, collagen IV, and fibronectin by upregulating DUSP1 expression during HG treatment, which were markedly reversed by miR-324-3p inhibitor. Furthermore, these molecular changes were verified in the human kidney samples of DN patients. Finally, overexpression of lncRNA NR_038323 ameliorated the interstitial fibrosis in STZ-induced diabetic nephrology (DN) rat via miR-324-3p/DUSP1/p38MAPK and ERK1/2 axis. In conclusion, our data indicate that overexpression of lncRNA NR_038323 may suppress HG-induced renal fibrosis via the miR-324-3p/DUSP1/p38MAPK and ERK1/2 axis, which provides new insights into the pathogenesis of DN.

lncRNA ZEB1-AS1 Was Suppressed by p53 for Renal Fibrosis in Diabetic Nephropathy.

The role of p53 in renal fibrosis is still controversial, and its underlying mechanisms remain not clear. Here, we showed that the pharmacological inhibition and genetic deletion of p53 in proximal tubular cells can attenuate renal dysfunction, tubular epithelial disruption, and interstitial fibrosis in db/db and STZ-induced diabetic nephrology (DN) mice. In human renal proximal tubule (human kidney 2 [HK-2]) cells, inhibition of p53 by PIF reduced the high glucose (HG)-induced extracellular matrix (ECM) accumulation and reversed the inhibitory effect of HG on mRNA expression levels of lncRNA zinc finger E-box binding homeobox1-antisense RNA 1 (ZEB1-AS1) and ZEB1. Interestingly, our results demonstrated that both lncRNA ZEB1-AS1 and ZEB1 exhibited an anti-fibrotic role, while ZEB1 is positively regulated by lncRNA ZEB1-AS1 during HG treatment. Mechanistically, lnc ZEB1-AS1 bound directly to H3K4 methyltransferase myeloid and lymphoid or mixed-lineage leukemia 1 (MLL1) and promoted H3K4me3 histone modification on ZEB1 promoter, which was reduced by HG treatment. ChIP analysis indicated the binding of p53 to the promoter region of lnc ZEB1-AS1. Furthermore, the findings were verified by the kidney biopsy samples from patients with DN. Taken all together, our results suggest that p53 may be a therapeutic target for renal fibrosis in DN.