Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells.

While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations (p-value ≤ 0.05, gene abundance percentage ≥ 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants (p = 0.0055). Among these findings were previously reported regulatory variants including rs60464856-RUVBL1 (multiome p-value = 0.0099 in BPH1) and rs7247241-SPINT2 (multiome p-value = 0.0002- 0.0004 in 22Rv1). We also functionally validated a new regulatory SNP and its target gene rs2474694-VPS53 (multiome p-value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.

NOX4 promotes tumor progression through the MAPK-MEK1/2-ERK1/2 axis in colorectal cancer.

BACKGROUND: Metabolic reprogramming plays a key role in cancer progression and clinical outcomes; however, the patterns and primary regulators of metabolic reprogramming in colorectal cancer (CRC) are not well understood. AIM: To explore the role of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) in promoting progression of CRC. METHODS: We evaluated the expression and function of dysregulated and survival-related metabolic genes using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Consensus clustering was used to cluster CRC based on dysregulated metabolic genes. A prediction model was constructed based on survival-related metabolic genes. Sphere formation, migration, invasion, proliferation, apoptosis and clone formation was used to evaluate the biological function of NOX4 in CRC. mRNA sequencing was utilized to explore the alterations of gene expression NOX4 over-expression tumor cells. In vivo subcutaneous and lung metastasis mouse tumor model was used to explore the effect of NOX4 on tumor growth. RESULTS: We comprehensively analyzed 3341 metabolic genes in CRC and identified three clusters based on dysregulated metabolic genes. Among these genes, NOX4 was highly expressed in tumor tissues and correlated with worse survival. In vitro, NOX4 overexpression induced clone formation, migration, invasion, and stemness in CRC cells. Furthermore, RNA-sequencing analysis revealed that NOX4 overexpression activated the mitogen-activated protein kinase-MEK1/2-ERK1/2 signaling pathway. Trametinib, a MEK1/2 inhibitor, abolished the NOX4-mediated tumor progression. In vivo, NOX4 overexpression promoted subcutaneous tumor growth and lung metastasis, whereas trametinib treatment can reversed the metastasis. CONCLUSION: Our study comprehensively analyzed metabolic gene expression and highlighted the importance of NOX4 in promoting CRC metastasis, suggesting that trametinib could be a potential therapeutic drugs of CRC clinical therapy targeting NOX4.

Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma.

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

Androgen drives melanoma invasiveness and metastatic spread by inducing tumorigenic fucosylation.

Melanoma incidence and mortality rates are historically higher for men than women. Although emerging studies have highlighted tumorigenic roles for the male sex hormone androgen and its receptor (AR) in melanoma, cellular and molecular mechanisms underlying these sex-associated discrepancies are poorly defined. Here, we delineate a previously undisclosed mechanism by which androgen-activated AR transcriptionally upregulates fucosyltransferase 4 (FUT4) expression, which drives melanoma invasiveness by interfering with adherens junctions (AJs). Global phosphoproteomic and fucoproteomic profiling, coupled with in vitro and in vivo functional validation, further reveal that AR-induced FUT4 fucosylates L1 cell adhesion molecule (L1CAM), which is required for FUT4-increased metastatic capacity. Tumor microarray and gene expression analyses demonstrate that AR-FUT4-L1CAM-AJs signaling correlates with pathological staging in melanoma patients. By delineating key androgen-triggered signaling that enhances metastatic aggressiveness, our findings help explain sex-associated clinical outcome disparities and highlight AR/FUT4 and its effectors as potential prognostic biomarkers and therapeutic targets in melanoma.

Novel model of pyroptosis-related molecular signatures for prognosis prediction of clear cell renal cell carcinoma patients.

Background: Pyroptosis is a programmed death mode of inflammatory cells, which is closely related to tumor progression and tumor immunity. Clear cell renal cell carcinoma (ccRCC) is the major pathological type of renal cell carcinoma (RCC) with poor prognosis. Many theories have tried to clarify the mechanism in the development of ccRCC, but the role of pyroptosis in ccRCC has not been well described. The main purpose of this study is to explore the role of pyroptosis in ccRCC and establish a novel prognosis prediction model of pyroptosis-related molecular signatures for ccRCC. Methods: In the present study, we made a systematical analysis of the association between ccRCC RNA transcriptome sequencing data from The Cancer Genome Atlas (TCGA) database [which included 529 ccRCC patients who were randomized in a training cohort (n=265) and an internal validation cohort (n=264)] and 40 pyroptosis-related genes (PRGs), from which four genes (CASP9, GSDME, IL1B and TIRAP) were selected to construct a molecular prediction model of PRGs for ccRCC. In addition, a cohort of 114 ccRCC patients from Shanghai Eastern Hepatobiliary Surgery Hospital (EHSH) was used as external data to verify the effectiveness of the model by immunohistochemistry. Moreover, the biological functions of the four PRGs were also verified in ccRCC 786-O and 769-P cells by Western blot (WB), CCK-8 cell proliferation, and Transwell invasion assays. Results: The model was able to differentiate high-risk patients from low-risk patients, and this differentiation was consistent with their clinical survival outcomes. In addition, the four PRGs also affected the ability of cell proliferation and invasion in ccRCC. Conclusion: The prediction model of pyroptosis-related molecular markers developed in this study may prove to be a novel understanding for ccRCC.

Integration analysis of PLAUR as a sunitinib resistance and macrophage related biomarker in ccRCC, an in silicon and experimental study.

Sunitinib remains the preferred systemic treatment option for specific patients with advanced RCC who are ineligible for immune therapy. However, it's essential to recognize that Sunitinib fails to elicit a favourable response in all patients. Moreover, most patients eventually develop resistance to Sunitinib. Therefore, identifying new targets associated with Sunitinib resistance is crucial. Utilizing multiple datasets from public cohorts, we conducted an exhaustive analysis and identified a total of 8 microRNAs and 112 mRNAs displaying significant expression differences between Sunitinib responsive and resistant groups. A particular set of six genes, specifically NIPSNAP1, STK40, SDC4, NEU1, TBC1D9, and PLAUR, were identified as highly significant via WGCNA. To delve deeper into the resistance mechanisms, we performed additional investigations using cell, molecular, and flow cytometry tests. These studies confirmed PLAUR's pivotal role in fostering Sunitinib resistance, both in vitro and in vivo. Our findings suggest that PLAUR could be a promising therapeutic target across various cancer types. In conclusion, this investigation not only uncovers vital genes and microRNAs associated with Sunitinib resistance in RCC but also introduces PLAUR as a prospective therapeutic target for diverse cancers. The outcomes contribute to advancing personalized healthcare and developing superior therapeutic strategies.Communicated by Ramaswamy H. Sarma.

5-hydroxymethylcytosine sequencing in plasma cell-free DNA identifies unique epigenomic features in prostate cancer patients resistant to androgen deprivation therapy.

Background: Currently there are no biomarkers to identify resistance to androgen-deprivation therapy (ADT) in men with hormone-naive prostate cancer. 5-hydroxymethylcytosines (5hmC) in the gene body are associated with gene activation and are critical for epigenomic regulation of cancer progression. Objective: To evaluate whether 5hmC signature in cell-free DNA (cfDNA) predicts early ADT resistance. Design Setting and Participants: Serial plasma samples from 55 prostate cancer patients receiving ADT were collected at three timepoints including baseline (prior to initiating ADT, N=55), 3-month (after initiating ADT, N=55), and disease progression (N=15) within 24 months or 24-month if no progression was detected (N=14). 20 of the 55 patients showed disease progression during the 24-month follow-up. The remaining 35 patients showed no progression in the same follow-up period. Outcome Measurements and Statistical Analysis: cfDNA (5-10ng) was used for selective chemical labeling (hMe-Seal) sequencing to map 5hmC abundance across the genome. Read counts in gene bodies were normalized with DESeq2. Differential methylation and gene set enrichment analyses were performed to identify the 5hmC-enriched genes and biological processes that were associated with disease progression. Kaplan-Meir analysis was utilized to determine the association of 5hmC signatures with progression-free survival. Results and Limitations: 5hmC-sequencing generated an average of 18.6 (range 6.03 to 42.43) million reads per sample with 98% (95-99%) mappable rate. Baseline sample comparisons identified significant 5hmC difference in 1,642 of 23,433 genes between 20 patients with progression and 35 patients without progression (false discovery rate, FDR<0.1). Patients with progression showed significant enrichments in multiple hallmark gene sets with androgen responses as the top enriched gene set (FDR=1.19E-13). Interestingly, this enrichment was driven by a subgroup of patients with disease progression featuring a significant 5hmC hypermethylation of the gene sets involving AR, FOXA1 and GRHL2. To quantify overall activities of these gene sets, we developed a gene set activity score algorithm using a mean value of log2 ratios of gene read counts in an entire gene set. We found that the activity scores in these gene sets were significantly higher in this subgroup of patients with progression than in the remaining patients regardless of the progression status. Furthermore, the high activity scores in these gene sets were associated with poor progression-free survival (p <0.05). Longitudinal analysis showed that activity scores in this subgroup with progression were significantly reduced after 3-month ADT but returned to high levels when the disease was progressed. Conclusions: 5hmC-sequencing in cfDNA identified a subgroup of prostate cancer patients with preexisting activation (5hmC hypermethylation) of gene sets involving AR, FOXA1 and GRHL2 before initiating ADT. Activity scores in these gene sets may serve as sensitive biomarkers to determine treatment resistance, monitor disease progression and potentially identify patients who would benefit from upfront treatment intensification. More studies are needed to validate this initial finding. Patient summary: There are no clinical tests to identify prostate cancer patients who will develop early resistance to androgen deprivation therapy within 24 months. In this study, we evaluated cell-free DNA epigenomic modification in blood and identified significant enrichment of 5-hydroxymethylation in androgen response genes in a subgroup of patients with treatment resistance. High level 5-hydroxylmethylation in these genes may serve as a discriminative biomarker to diagnose patients who are likely to experience early failure during androgen deprivation therapy.

N/O Co-doped hierarchical nanoporous biochar derived from waste polypropylene nonwoven for high-performance supercapacitors.

How to efficiently treat municipal solid waste (MSW) has become one of the critical solutions in response to the call for "carbon neutrality". Here, the waste polypropylene nonwoven fabric of waste diapers was converted into hierarchical nanoporous biochar (HPBC) through pre-carbonization and activation processes as an ideal precursor for supercapacitors (SCs) with excellent performance. The prepared HPBC-750-4 with an ultrahigh specific surface area (3838.04 m2 g-1) and abundant heteroatomic oxygen (13.25%) and nitrogen (1.16%) codoped porous biochar structure. Given its structural advantages, HPBC-750-4 achieved a specific capacitance of 340.9 F g-1 at a current density of 1 A g-1 in a three-electrode system. Its capacitance retention rate was above 99.2% after 10 000 cycles at a current density of 10 A g-1, which indicated an excellent rate capability and long-term cycling stability. Furthermore, the HPBC-750-4//HPBC-750-4 symmetric SC exhibited a superb energy density of 10.02 W h kg-1 with a power density of 96.15 W kg-1 in a 6 M KOH electrolyte. This work not only demonstrates the enormous potential of waste polypropylene nonwoven fabric in the SC industry but also provides an economically feasible means of managing MSW.

Glycolysis-related biomarker TCIRG1 participates in regulation of renal cell carcinoma progression and tumor immune microenvironment by affecting aerobic glycolysis and AKT/mTOR signaling pathway.

BACKGROUND: Renal cell carcinoma (RCC) is a hypermetabolic disease. Abnormal up-regulation of glycolytic signaling promotes tumor growth, and glycolytic metabolism is closely related to immunotherapy of renal cancer. The aim of the present study was to determine whether and how the glycolysis-related biomarker TCIRG1 affects aerobic glycolysis, the tumor microenvironment (TME) and malignant progression of clear cell renal cell carcinoma (ccRCC). METHODS: Based on The Cancer Genome Atlas (TCGA, n = 533) and the glycolysis-related gene set from MSigDB, we identified the glycolysis-related gene TCIRG1 by bioinformatics analysis, analyzed its immunological properties in ccRCC and observed how it affected the biological function and glycolytic metabolism using online databases such as TIMER 2.0, UALCAN, LinkedOmics and in vitro experiments. RESULTS: It was found that the expression of TCIRG1, was significantly increased in ccRCC tissue, and that high TCIRG1 expression was associated with poor overall survival (OS) and short progression-free interval (PFI). In addition, TCIRG1 expression was highly correlated with the infiltration immune cells, especially CD4+T cell Th1, CD8+T cell, NK cell, and M1 macrophage, and positively correlated with PDCD1, CTLA4 and other immunoinhibitors, CCL5, CXCR3 and other chemokines and chemokine receptors. More importantly, TCIRG1 may regulate aerobic glycolysis in ccRCC via the AKT/mTOR signaling pathway, thereby affecting the malignant progression of ccRCC cell lines. CONCLUSIONS: Our results demonstrate that the glycolysis-related biomarker TCIRG1 is a tumor-promoting factor by affecting aerobic glycolysis and tumor immune microenvironment in ccRCC, and this finding may provide a new idea for the treatment of ccRCC by combination of metabolic intervention and immunotherapy.

Combined CRISPRi and proteomics screening reveal a cohesin-CTCF-bound allele contributing to increased expression of RUVBL1 and prostate cancer progression.

Genome-wide association studies along with expression quantitative trait locus (eQTL) mapping have identified hundreds of single-nucleotide polymorphisms (SNPs) and their target genes in prostate cancer (PCa), yet functional characterization of these risk loci remains challenging. To screen for potential regulatory SNPs, we designed a CRISPRi library containing 9,133 guide RNAs (gRNAs) to cover 2,166 candidate SNP loci implicated in PCa and identified 117 SNPs that could regulate 90 genes for PCa cell growth advantage. Among these, rs60464856 was covered by multiple gRNAs significantly depleted in screening (FDR < 0.05). Pooled SNP association analysis in the PRACTICAL and FinnGen cohorts showed significantly higher PCa risk for the rs60464856 G allele (p value = 1.2 × 10-16 and 3.2 × 10-7, respectively). Subsequent eQTL analysis revealed that the G allele is associated with increased RUVBL1 expression in multiple datasets. Further CRISPRi and xCas9 base editing confirmed that the rs60464856 G allele leads to elevated RUVBL1 expression. Furthermore, SILAC-based proteomic analysis demonstrated allelic binding of cohesin subunits at the rs60464856 region, where the HiC dataset showed consistent chromatin interactions in prostate cell lines. RUVBL1 depletion inhibited PCa cell proliferation and tumor growth in a xenograft mouse model. Gene-set enrichment analysis suggested an association of RUVBL1 expression with cell-cycle-related pathways. Increased expression of RUVBL1 and activation of cell-cycle pathways were correlated with poor PCa survival in TCGA datasets. Our CRISPRi screening prioritized about one hundred regulatory SNPs essential for prostate cell proliferation. In combination with proteomics and functional studies, we characterized the mechanistic role of rs60464856 and RUVBL1 in PCa progression.

Construction and validation of a prognostic model for predicting clear cell renal cell carcinoma based on complement-related genes.

Background: Clear cell renal cell carcinoma (ccRCC) is a highly heterogeneous tumor and is the most common subtype of renal cell carcinoma (RCC). Surgery is used to cure most early ccRCC, but the 5-year overall survival (OS) of ccRCC patients is far from satisfactory. Thus, new prognostic features and therapeutic targets for ccRCC need to be identified. Since complement factors can influence tumor development, we aimed to develop a model to predict the prognosis of ccRCC through complement-related genes. Methods: Differentially expressed genes were screened from an International Cancer Genome Consortium (ICGC) data set, and the genes associated with prognosis were screened by univariate regression and least absolute shrinkage and selection operator-Cox regression, and column line plots were generated using the rms R package to predict OS. The C-index was used to show the accuracy of the survival prediction and the prediction effects were verified using a data set from The Cancer Genome Atlas (TCGA). An immuno-infiltration analysis was performed with CIBERSORT analysis, and a drug sensitivity analysis was performed using the Gene Set Cancer Analysis (GSCA) (http://bioinfo.life.hust.edu.cn/GSCA/#/) database. Results: We identified 5 complement-related genes (i.e., A2M, APOBEC3G, COL4A2, DOCK4, and NOTCH4) for risk-score modeling to predict OS at 1, 2, 3, and 5 years, and the C-index of the prediction mode was 0.795. In addition, the model was successfully validated in TCGA data set. The CIBERSORT analysis showed that M1 macrophages were downregulated in the high-risk group. The GSCA database analysis showed that DOCK4, COL4A2, and A2M were positively correlated with the half maximal inhibitory concentration (IC50) of 10 drugs and small molecules, and COL4A2, NOTCH4, A2M, and APOBEC3G were negatively correlated with the IC50 of dozens of different drugs and small molecules. Conclusions: We developed and validated a survival prognostic model based on 5 complement-related genes for ccRCC. We also elucidated the relationship with tumor immune status and developed a new predictive tool for clinical purposes. In addition, our results showed that A2M, APOBEC3G, COL4A2, DOCK4, and NOTCH4 may be potential targets for the treatment of ccRCC in the future.

Detectable Lipidomes and Metabolomes by Different Plasma Exosome Isolation Methods in Healthy Controls and Patients with Advanced Prostate and Lung Cancer.

Circulating exosomes in the blood are promising tools for biomarker discovery in cancer. Due to their heterogeneity, different isolation methods may enrich distinct exosome cargos generating different omic profiles. In this study, we evaluated the effects of plasma exosome isolation methods on detectable multi-omic profiles in patients with non-small cell lung cancer (NSCLC), castration-resistant prostate cancer (CRPC), and healthy controls, and developed an algorithm to quantify exosome enrichment. Plasma exosomes were isolated from CRPC (n = 10), NSCLC (n = 14), and healthy controls (n = 10) using three different methods: size exclusion chromatography (SEC), lectin binding, and T-cell immunoglobulin domain and mucin domain-containing protein 4 (TIM4) binding. Molecular profiles were determined by mass spectrometry of extracted exosome fractions. Enrichment analysis of uniquely detected molecules was performed for each method with MetaboAnalyst. The exosome enrichment index (EEI) scores methods based on top differential molecules between patient groups. The lipidomic analysis detected 949 lipids using exosomes from SEC, followed by 246 from lectin binding and 226 from TIM4 binding. The detectable metabolites showed SEC identifying 191 while lectin binding and TIM4 binding identified 100 and 107, respectively. When comparing uniquely detected molecules, different methods showed preferential enrichment of different sets of molecules with SEC enriching the greatest diversity. Compared to controls, SEC identified 28 lipids showing significant difference in NSCLC, while only 1 metabolite in NSCLC and 5 metabolites in CRPC were considered statistically significant (FDR < 0.1). Neither lectin-binding- nor TIM4-binding-derived exosome lipids or metabolites demonstrated significant differences between patient groups. We observed the highest EEI from SEC in lipids (NSCLC: 871.33) which was also noted in metabolites. These results support that the size exclusion method of exosome extraction implemented by SBI captures more heterogeneous exosome populations. In contrast, lectin-binding and TIM4-binding methods bind surface glycans or phosphatidylserine moieties of the exosomes. Overall, these findings suggest that specific isolation methods select subpopulations which may significantly impact cancer biomarker discovery.

Combined CRISPRi and proteomics screening reveal a cohesin-CTCF-bound allele contributing to increased expression of RUVBL1 and prostate cancer progression.

Genome-wide association studies along with expression quantitative trait loci (eQTL) mapping have identified hundreds of single nucleotide polymorphisms (SNPs) and their target genes in prostate cancer (PCa), yet functional characterization of these risk loci remains challenging. To screen for potential regulatory SNPs, we designed a CRISPRi library containing 9133 guide RNAs (gRNAs) to target 2,166 candidate SNP sites implicated in PCa and identified 117 SNPs that could regulate 90 genes for PCa cell growth advantage. Among these, rs60464856 was covered by multiple gRNAs significantly depleted in the screening (FDR<0.05). Pooled SNP association analysis in the PRACTICAL and FinnGen cohorts showed significantly higher PCa risk for the rs60464856 G allele (pvalue=1.2E-16 and 3.2E-7). Subsequent eQTL analysis revealed that the G allele is associated with increased RUVBL1 expression in multiple datasets. Further CRISPRi and xCas9 base editing proved the rs60464856 G allele leading to an elevated RUVBL1 expression. Furthermore, SILAC-based proteomic analysis demonstrated allelic binding of cohesin subunits at the rs60464856 region, where HiC dataset showed consistent chromatin interactions in prostate cell lines. RUVBL1 depletion inhibited PCa cell proliferation and tumor growth in xenograft mouse model. Gene set enrichment analysis suggested an association of RUVBL1 expression with cell-cycle-related pathways. An increased expression of RUVBL1 and activations of cell-cycle pathways were correlated with poor PCa survival in TCGA datasets. Together, our CRISPRi screening prioritized about one hundred regulatory SNPs essential for prostate cell proliferation. In combination with proteomics and functional studies, we characterized the mechanistic role of rs60464856 and RUVBL1 in PCa progression.

Combining expression of RNF43 and infiltration level of CD163+ tumor associated macrophage predicts prognosis of clear cell renal cell carcinoma.

Searching for reliable indicators for evaluating prognosis diagnosed with clear cell renal cell carcinoma (ccRCC) is crucial for improving clinical therapies. However, current researches have looked mainly at the prognostic value of a single intratumoral indicator, neglecting tumor-infiltrating immune cells (TIICs) in the microenvironment. This study examined whether the integration of Ring finger protein 43 (RNF43) expression and CD163+ tumor-associated macrophage (TAM) infiltration in combination with clinical indexes forecast ccRCC patient outcome with relatively high accuracy. Firstly, the expression of RNF43 and CD163 were detected with immunohistochemistry. Totally, 346 ccRCC patients were random separated evenly into training and validation datasets to make further analyses. We found that RNF43 expression was negatively correlated with infiltration level of CD163+ TAM in ccRCC, which was closely associated with the TNM stage and outcome of these patients. The multiple regression analysis demonstrated that RNF43, CD163, and TNM stage could function as independent risk factors in overall survival (OS) and progression-free survival (PFS) prediction of ccRCC. Furthermore, a better postoperative prognosis index for ccRCC patients was obtained by combining RNF43 and CD163+ TAMs, which assessed with time-dependent C-index analyses and a nomogram. Consequently, combining RNF43 and CD163+ TAMs along with TNM stage acquired robust accuracy in forecasting outcome of patients with ccRCC. In conclusion, combining intratumoral RNF43 expression, CD163+ TAM infiltration, and TNM stage could significantly enhance the veracity in forecasting postoperative outcomes.

Carbon Dot@MXene Nanozymes with Triple Enzyme-Mimic Activities for Mild NIR-II Photothermal-Amplified Nanocatalytic Therapy.

Nanozymes have shown promising potential in disease treatment owing to the advantages of low-cost, facile fabrication, and high stability. However, the highly complex tumor microenvironment (TME) and inherent low catalytic activity severely restrict the clinical applications of nanozymes. Herein, a novel mild hyperthermia-enhanced nanocatalytic therapy platform based on Z-scheme heterojunction nanozymes by depositing N-doped carbon dots (CDs) onto Nb2 C nanosheets is constructed. CD@Nb2 C nanozymes not only display outstanding photothermal effects in the safe and efficient NIR-II window but also possess triple enzyme-mimic activities to obtain amplified ROS levels. The triple enzyme-mimic activities and NIR-II photothermal properties of CD nanozymes are enhanced by the construction of Z-scheme heterojunctions owing to the accelerated carrier transfer process. More importantly, the introduction of mild hyperthermia can further improve the peroxidase-mimic and catalase-mimic activities as well as the glGSH depletion abilities of CD@Nb2 C nanozymes, thereby producing more ROS to efficiently inhibit tumor growth. The combined therapy effect of CD@Nb2 C nanozymes through mild NIR-II photothermal-enhanced nanocatalytic therapy can achieve complete tumor eradication. This work highlights the efficient tumor therapy potential of heterojunction nanozymes.

Extensive germline-somatic interplay contributes to prostate cancer progression through HNF1B co-option of TMPRSS2-ERG.

Genome-wide association studies have identified 270 loci conferring risk for prostate cancer (PCa), yet the underlying biology and clinical impact remain to be investigated. Here we observe an enrichment of transcription factor genes including HNF1B within PCa risk-associated regions. While focused on the 17q12/HNF1B locus, we find a strong eQTL for HNF1B and multiple potential causal variants involved in the regulation of HNF1B expression in PCa. An unbiased genome-wide co-expression analysis reveals PCa-specific somatic TMPRSS2-ERG fusion as a transcriptional mediator of this locus and the HNF1B eQTL signal is ERG fusion status dependent. We investigate the role of HNF1B and find its involvement in several pathways related to cell cycle progression and PCa severity. Furthermore, HNF1B interacts with TMPRSS2-ERG to co-occupy large proportion of genomic regions with a remarkable enrichment of additional PCa risk alleles. We finally show that HNF1B co-opts ERG fusion to mediate mechanistic and biological effects of the PCa risk-associated locus 17p13.3/VPS53/FAM57A/GEMIN4. Taken together, we report an extensive germline-somatic interaction between TMPRSS2-ERG fusion and genetic variations underpinning PCa risk association and progression.

GBP2 serves as a novel prognostic biomarker and potential immune microenvironment indicator in renal cell carcinoma.

Since the application of immune checkpoint therapy (ICT) has gradually become a new strategy for clear cell renal cell carcinoma (ccRCC) treatment, biomarkers that predict the individual response to ICT is needed. This study aimed to identify a new clinical indicator for postoperative surveillance of ccRCC and prediction of ICT response. We investigated the GBP2 expression and its relation with immune cell infiltration in tumor microenvironment using public databases, clinical specimens and ccRCC cell lines. Bioinformatic analysis using public database revealed that GBP2 expression is higher in cancer tissues than in adherent normal tissues among different cancer types including ccRCC, and the same results were acquired from clinical tissue samples tested by Western Blot and PCR. In ccRCC cell lines, CCk-8 proliferation assay and apoptosis assessment suggested GBP2 facilitates the malignancy of ccRCC. 286 ccRCC patients were randomly divided into a training or validation cohort, and immunohistochemistry (IHC) and Kaplan-Meier analysis revealed that higher GBP2 expression is related to worse prognosis. C-index analysis implied that integrating GBP2 expression with TNM stage improved the accuracy in predicting prognosis of ccRCC patients compared to the solitary use of either. Bioinformatic analysis implied a relation between GBP2 and immunity, and GBP2 expression is positively related with suppressive immune markers in ccRCC microenvironment. Taken together, our study demonstrated the potential of GBP2 to sever as a prognostic predictor of ccRCC, and an association between GBP2 and tumor-infiltrating lymphocytes in ccRCC was observed, making it a promising indicator of ICT response.

Vascular toxicity of multi-walled carbon nanotubes targeting vascular endothelial growth factor.

Multiwalled carbon nanotubes (MWCNTs) are currently widely used and are expected to be used as drug carriers and contrast agents in clinical practice. Previous studies mainly focused on their lung toxicity; therefore, their effects on the vascular endothelium are unclear. In this study, a human angiogenesis array was used to determine the effect of MWCNTs on the expression profile of angiogenic factors in endothelial cells and to clarify the role of vascular endothelial growth factor (VEGF) in MWCNT-induced endothelial cell injury at the cellular and animal levels. The results indicated that MWCNTs (20-30 nm and 30-50 nm) could enter endothelial cells and disrupt human umbilical vein endothelial cell (HUVECs) activity in a concentration-dependent manner. MWCNTs disrupted the tube formation ability and cell migration function of HUVECs. The results from a Matrigel Plug experiment in mice showed that angiogenesis in the MWCNT experimental group was significantly reduced. The results of a protein chip analysis indicated that VEGF expression in the MWCNT treatment group was decreased, a finding that was validated by ELISA results. The protein expression levels of AKT and eNOS in the MWCNT treatment group were significantly decreased; the administration of recombinant VEGF significantly alleviated the migration ability and tube formation ability of endothelial cells injured by MWCNTs, upregulated the protein expression of AKT and eNOS, and increased the number of neovascularization in mice in the MWCNT treatment group. This study demonstrated that MWCNTs affect angiogenesis via the VEGF-Akt-eNOS axis which can be rescued by VEGF endothelial treatment.

Proteogenomic, Epigenetic, and Clinical Implications of Recurrent Aberrant Splice Variants in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Alternative mRNA splicing can be dysregulated in cancer, resulting in the generation of aberrant splice variants (SVs). Given the paucity of actionable genomic mutations in clear cell renal cell carcinoma (ccRCC), aberrant SVs may be an avenue to novel mechanisms of pathogenesis. OBJECTIVE: To identify and characterize aberrant SVs enriched in ccRCC. DESIGN, SETTING, AND PARTICIPANTS: Using RNA-seq data from the Cancer Cell Line Encyclopedia, we identified neojunctions uniquely expressed in ccRCC. Candidate SVs were then checked for expression across normal tissue in the Genotype-Tissue Expression Project and primary tumor tissue from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and our institutional Total Cancer Care database. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Clinicopathologic, genomic, and survival data were available for all cohorts. Epigenetic data were available for the TCGA and CPTAC cohorts. Proteomic data were available for the CPTAC cohort. The association of aberrant SV expression with these variables was examined using the Kruskal-Wallis test, pairwise t test, Spearman correlation test, and Cox regression analysis. RESULTS AND LIMITATIONS: Our pipeline identified 16 ccRCC-enriched SVs. EGFR, HPCAL1-SV and RNASET2-SV expression was negatively correlated with gene-specific CpG methylation. We derived a survival risk score based primarily on the expression of five SVs (RNASET2, FGD1, PDZD2, COBLL1, and PTPN14), which was consistent and applicable across multiple cohorts on multivariate analysis. The splicing factor RBM4, which modulates splicing of HIF-1α, exhibited significantly lower expression at the protein level in the high-risk group, as defined by our SV-based score. CONCLUSIONS: We describe 16 aberrant SVs enriched in ccRCC, many of which are associated with disease biology and/or clinical outcomes. This study provides a novel strategy for identifying and characterizing disease-specific aberrant SVs. PATIENT SUMMARY: We describe a method to identify disease targets and biomarkers using transcriptomic analysis beyond somatic mutations or gene expression. Kidney tumors express unique splice variants that may provide additional prognostic information following surgery.

Novel role of prostate cancer risk variant rs7247241 on PPP1R14A isoform transition through allelic TF binding and CpG methylation.

Although previous studies identified numerous single nucleotide polymorphisms (SNPs) and their target genes predisposed to prostate cancer (PrCa) risks, SNP-related splicing associations are rarely reported. In this study, we applied distance-based sQTL analysis (sQTLseekeR) using RNA-seq and SNP genotype data from benign prostate tissue (n = 467) and identified significant associations in 3344 SNP-transcript pairs (P ≤ 0.05) at PrCa risk loci. We characterized a common SNP (rs7247241) and its target gene (PPP1R14A) located in chr19q13, an sQTL with risk allele T associated with upregulation of long isoform (P = 9.99E-7). We confirmed the associations in both TCGA (P = 2.42E-24) and GTEX prostate cohorts (P = 9.08E-78). To functionally characterize this SNP, we performed chromatin immunoprecipitation qPCR and confirmed stronger CTCF and PLAGL2 binding in rs7247241 C than T allele. We found that CTCF binding enrichment was negatively associated with methylation level at the SNP site in human cell lines (r = -0.58). Bisulfite sequencing showed consistent association of rs7247241-T allele with nearby sequence CpG hypermethylation in prostate cell lines and tissues. Moreover, the methylation level at CpG sites nearest to the CTCF binding and first exon splice-in (ψ) of PPP1R14A was significantly associated with aggressive phenotype in the TCGA PrCa cohort. Meanwhile, the long isoform of the gene also promoted cell proliferation. Taken together, with the most updated gene annotations, we reported a set of sQTL associated with multiple traits related to human prostate diseases and revealed a unique role of PrCa risk SNP rs7247241 on PPP1R14A isoform transition.