A machine learning model based on MRI for the preoperative prediction of bladder cancer invasion depth.

OBJECTIVES: To construct and validate a prediction model based on full-sequence MRI for preoperatively evaluating the invasion depth of bladder cancer. METHODS: A total of 445 patients with bladder cancer were divided into a seven-to-three training set and test set for each group. The radiomic features of lesions were extracted automatically from the preoperative MRI images. Two feature selection methods were performed and compared, the key of which are the Least Absolute Shrinkage and Selection Operator (LASSO) and the Max Relevance Min Redundancy (mRMR). The classifier of the prediction model was selected from six advanced machine-learning techniques. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were applied to assess the efficiency of the models. RESULTS: The models with the best performance for pathological invasion prediction and muscular invasion prediction consisted of LASSO as the feature selection method and random forest as the classifier. In the training set, the AUC of the pathological invasion model and muscular invasion model were 0.808 and 0.828. Furthermore, with the mRMR as the feature selection method, the external invasion model based on random forest achieved excellent discrimination (AUC, 0.857). CONCLUSIONS: The full-sequence models demonstrated excellent accuracy for preoperatively predicting the bladder cancer invasion status. CLINICAL RELEVANCE STATEMENT: This study introduces a full-sequence MRI model for preoperative prediction of the depth of bladder cancer infiltration, which could help clinicians to recognise pathological features associated with tumour infiltration prior to invasive procedures. KEY POINTS: • Full-sequence MRI prediction model performed better than Vesicle Imaging-Reporting and Data System (VI-RADS) for preoperatively evaluating the invasion status of bladder cancer. • Machine learning methods can extract information from T1-weighted image (T1WI) sequences and benefit bladder cancer invasion prediction.

AF9 targets acetyl-modified STAT6 to diminish purine metabolism and accelerate cell apoptosis during metastasis.

Cell migration and invasion are two important steps for tumour metastasis, and involved the behaviors including metabolism remodeling and anti-apoptosis. However, it's still elusive that cancer cells how to antagonize apoptosis during tumour metastasis. In this study, we observed that super elongation complex (SEC) subunit AF9 depletion exacerbated cell migration and invasion but reduced the apoptosis during invasive migration. Mechanically, AF9 targeted acetyl (Ac)-STAT6 at lysine (K) 284 and blocked STAT6 transactivation on the promoter of such genes involved in regulating purine metabolism and metastasis, in turn induced apoptosis of suspended cells. Of note, AcSTAT6-K284 was not induced by IL4 signaling but decreased by limited nutrition which triggered SIRT6 to remove acetyl group at STAT6-K284. The functional experiments proved that AcSTAT6-K284 attenuated cell migration and invasion depending on AF9 expression level. Animal metastatic study further confirmed the AF9/AcSTAT6-K284 axis existed and blocked kidney renal clear cell carcinoma (KIRC) metastasis. In clinical, both AF9 expression and AcSTAT6-K284 were decreased accompanied by the advanced tumour grade and positively correlated with KIRC patients' survival. Conclusively, we explored an inhibitory axis which not only suppressed tumour metastasis but also could be utilized for drug development to hamper KIRC metastasis.

Competition between p53 and YY1 determines PHGDH expression and malignancy in bladder cancer.

PURPOSE: Serine metabolism is frequently dysregulated in many types of cancers and the tumor suppressor p53 is recently emerging as a key regulator of serine metabolism. However, the detailed mechanism remains unknown. Here, we investigate the role and underlying mechanisms of how p53 regulates the serine synthesis pathway (SSP) in bladder cancer (BLCA). METHODS: Two BLCA cell lines RT-4 (WT p53) and RT-112 (p53 R248Q) were manipulated by applying CRISPR/Cas9 to examine metabolic differences under WT and mutant p53 status. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) and non-targeted metabolomics analysis were adopted to identify metabolomes changes between WT and p53 mutant BLCA cells. Bioinformatics analysis using the cancer genome atlas and Gene Expression Omnibus datasets and immunohistochemistry (IHC) staining was used to investigate PHGDH expression. Loss-of-function of PHGDH and subcutaneous xenograft model was adopted to investigate the function of PHGDH in mice BLCA. Chromatin immunoprecipitation (Ch-IP) assay was performed to analyze the relationships between YY1, p53, SIRT1 and PHGDH expression. RESULTS: SSP is one of the most prominent dysregulated metabolic pathways by comparing the metabolomes changes between wild-type (WT) p53 and mutant p53 of BLCA cells. TP53 gene mutation shows a positive correlation with PHGDH expression in TCGA-BLCA database. PHGDH depletion disturbs the reactive oxygen species homeostasis and attenuates the xenograft growth in the mouse model. Further, we demonstrate WT p53 inhibits PHGDH expression by recruiting SIRT1 to the PHGDH promoter. Interestingly, the DNA binding motifs of YY1 and p53 in the PHGDH promoter are partially overlapped which causes competition between the two transcription factors. This competitive regulation of PHGDH is functionally linked to the xenograft growth in mice. CONCLUSION: YY1 drives PHGDH expression in the context of mutant p53 and promotes bladder tumorigenesis, which preliminarily explains the relationship between high-frequency mutations of p53 and dysfunctional serine metabolism in bladder cancer.

Leukemia inhibitory factor receptor homodimerization mediated by acetylation of extracellular lysine promotes prostate cancer progression through the PDPK1/AKT/GCN5 axis.

BACKGROUND: Prostate cancer (PCa), an inert tumour, has a long progression period, but valid biomarkers and methods for effectively and sensitively monitoring PCa progression are lacking, prompting us to identify new predictors for diagnosis and prognosis. Posttranslational modifications characterizing receptor activation are considered potentially strong indicators of disease progression. METHODS: The posttranscriptional regulation of leukaemia inhibitory factor receptor (LIFR) and its novel downstream signalling activity in PCa were studied using liquid mass spectrometry, genetically engineered mouse (GEM) models, organoid assays, lentivirus packaging, infection and stable cell line construction. RESULTS: In this study, the level of acetylated K620 on LIFR in its extracellular domain was shown to predict the progression and prognosis of PCa. In PCa cells, LIFR-K620 acetylation is reversibly mediated by GCN5 and SIRT2. GEM experiments and organoid assays confirmed that the loss of LIFR-K620 acetylation inhibits PCa progression. Mechanistically, K620 acetylation facilitates LIFR homodimerization and subsequently promotes LIFR-S1044 phosphorylation and activation, which further recruits PDPK1 to activate AKT signalling and sequentially enhances the GCN5 protein level to sustain the protumour level of LIFR-K620 acetylation by preventing GCN5 degradation via CRL4Cdt2 E3 ligase. CONCLUSIONS: Acetylation of extracellular K620 on LIFR reinforces its homodimerization and integrates the activities of PDPK1, AKT, GSK3ß and GCN5 to form a novel positive feedback loop in PCa; this modification is thus a promising biomarker for monitoring PCa progression.

A novel ferroptosis-related gene signature associated with cell cycle for prognosis prediction in patients with clear cell renal cell carcinoma.

BACKGROUND: It is of great urgency to explore useful prognostic markers for patients with clear cell renal cell carcinoma (ccRCC). Prognostic models based on ferroptosis-related gene (FRG) in ccRCC is poorly reported for now. METHODS: Comprehensive analysis of 22 FRGs were performed in 629 ccRCC samples from two independent patient cohorts. We carried out least absolute shrinkage and selection operator analysis to screen out prognosis-related FRGs and constructed prognosis model for patients with ccRCC. Weighted gene co-expression network analysis was also carried out for potential functional enrichment analysis. RESULTS: Based on the TCGA cohort, a total of 11 prognosis-associated FRGs were selected for the construction of the prognosis model. Significantly differential overall survival (hazard ratio = 3.61, 95% CI: 2.68-4.87, p < 0.0001) was observed between patients with high and low FRG score in the TCGA cohort, which was further verified in the CPTAC cohort with hazard ratio value of 5.13 (95% CI: 1.65-15.90, p = 0.019). Subgroup survival analysis revealed that our FRG score could significantly distinguish patients with high survival risk among different tumor stages and different tumor grades. Functional enrichment analysis illustrated that the process of cell cycle, including cell cycle-mitotic pathway, cytokinesis pathway and nuclear division pathway, might be involved in the regulation of ccRCC through ferroptosis. CONCLUSIONS: We developed and verified a FRG signature for the prognosis prediction of patients with ccRCC, which could act as a risk factor and help to update the tumor staging system when integrated with clinicopathological characteristics. Cell cycle-related pathways might be involved in the regulation of ccRCC through ferroptosis.

miR-145-5p: A Potential Biomarker in Predicting Gleason Upgrading of Prostate Biopsy Samples Scored 3+3=6.

BACKGROUND: The Gleason grading system is a major tool used for prediction of prostate cancer (PCa) behavior. Because of heterogeneity and sampling errors, prognosis is variable even among patients with the same Gleason score (GS). Therefore, more accurate biomarkers that complement the Gleason system are needed to improve the clinical management of PCa. METHODS: Formalin-fixed, paraffin embedded tissue samples were obtained from radical prostatectomy (RP) (patient set 1, n=53) and needle biopsy (patient set 2, n=107; patient set 3, n=119). Cancer tissues from pure regions of each Gleason pattern (GP) were separately collected using laser-captured microdissection, followed by Real-time-PCR to determine the relative expression of miRNAs, including miR-1-5p, miR-21-5p, miR-30d-5p, miR-100-5p, miR-145-5p, miR-224-5p, and miR-708-5p. miRNA's association with Gleason upgrading (GU) was evaluated using receiver operator characteristics (ROC) curve and multivariate logistic regression analysis. The integrated miRNA targets prediction and enrichment analyses were performed to determine the potential functions of miRNA. RESULTS: It was found that miR-145-5p in GP3 from radical prostatectomy (RP) were overexpressed in patients with GS6 PCa compared with GS7 patients, which was further confirmed in a larger biopsy cohort. ROC curve analysis revealed that miR-145-5p in biopsy was significantly associated with GU upon RP. In multivariate analyses, miR-145-5p was an independent predictor of GU. CONCLUSION: Our study indicated that differential expression of miRNAs existed in GP3 from pure GS6 and GS7 PCa, highlighting a path toward the clinical use of miRNAs in predicting GU and assisting in treatment modality selection.

Cytosolic GDH1 degradation restricts protein synthesis to sustain tumor cell survival following amino acid deprivation.

The mTORC1 pathway plays key roles in regulating various biological processes, including sensing amino acid deprivation and driving expression of ribosomal protein (RP)-coding genes. In this study, we observed that depletion of glutamate dehydrogenase 1 (GDH1), an enzyme that converts glutamate to α-ketoglutarate (αKG), confers resistance to amino acid deprivation on kidney renal clear cell carcinoma (KIRC) cells. Mechanistically, under conditions of adequate nutrition, GDH1 maintains RP gene expression in a manner dependent on its enzymatic activity. Following amino acid deprivation or mTORC1 inhibition, GDH1 translocates from mitochondria to the cytoplasm, where it becomes ubiquitinated and degraded via the E3 ligase RNF213. GDH1 degradation reduces intracellular αKG levels by more than half and decreases the activity of αKG-dependent lysine demethylases (KDMs). Reduced KDM activity in turn leads to increased histone H3 lysine 9 and 27 methylation, further suppressing RP gene expression and preserving nutrition to support cell survival. In summary, our study exemplifies an economical and efficient strategy of solid tumor cells for coping with amino acid deficiency, which might in the future be targeted to block renal carcinoma progression.

Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.

Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TCGA). We constructed and cross-verified automatic diagnosis and prognosis models by performing a machine learning algorithm based on pathomics data. Our study indicated that high diagnostic efficiency of the machine learning-based diagnosis model was observed in patients with BCa, with area under the curve (AUC) values of 96.3%, 89.2%, and 94.1% in the training cohort, test cohort, and external validation cohort, respectively. Our diagnosis model also performed well in distinguishing patients with BCa from patients with glandular cystitis, with an AUC value of 93.4% in the General cohort. Significant differences were found in overall survival in TCGA cohort (hazard ratio (HR) = 2.09, 95% confidence interval (CI): 1.56-2.81, P < .0001) and the General cohort (HR = 5.32, 95% CI: 2.95-9.59, P < .0001) comparing patients with BCa of high risk vs low risk stratified by risk score, which was proved to be an independent prognostic factor for BCa. The integration nomogram based on our risk score and clinicopathologic characters displayed higher prediction accuracy than current tumor stage/grade systems, with AUC values of 77.7%, 83.8%, and 81.3% for 1-, 3-, and 5-y overall survival prediction of patients with BCa. However, prospective studies are still needed for further verifications.

Cryopreserved skin epithelial cell sheet combined with acellular amniotic membrane as an off-the-shelf scaffold for urethral regeneration.

BACKGROUND: Autologous tissue transplantation for urethral repair is often limited and causes donor site complications. Here, a cryopreserved rabbit skin epithelial cell sheet (SEC) combined with an acellular amniotic membrane (AM) was used to repair rabbit urethral defects. METHODS: Abdominal skin was collected from 4-week-old New Zealand rabbits, and primary epithelial cells were extracted and cultured to form a cell sheet. Fresh SEC-AMs were constructed and cryopreserved. A cryopreservation system including optimized medium, two-pump perfusion, a programmed freezer and liquid nitrogen storage was established. Cell viability, mechanical strength, electron microscopy, and histological staining were performed in vitro after 1 month. Next, the sheets were transplanted subcutaneously for 2 weeks, and the graft was used to repair the rabbit urethral defect. Urinary function was measured and samples were collected for histological staining after 1 month. RESULTS: We confirmed that cryopreservation damage of SECs was reduced by composition with acellular AMs in terms of high cell activity. The SEC mechanical strength was also enhanced by AMs, which was convenient for the operation. In in vivo experiments, we transplanted sheets into the groin area for two weeks and found that cryopreservation reduced inflammatory cell infiltration and significantly improved vascular density. In the urethral repair experiment, the near-normal passive urine flow rate, smooth mucosa of the gross specimen, intact epithelialization and abundant neovascularization were confirmed in the cryopreserved-SEC-AM group compared with the other groups. CONCLUSIONS: Cryopreserved SEC-AMs demonstrated similar outcomes of rabbit urethral defect repair as fresh SEC-AMs, showing good clinical application prospects.

Biobanked human foreskin epithelial cell sheets reduce inflammation and promote wound healing in a nude mouse model.

BACKGROUND: Human epithelial cell sheets (ECSs) are used to clinically treat epithelial conditions such as burns, corneal blindness, middle ear cholesteatoma and vitiligo. As a widely used material in clinic, there is little information on the biobanking of ECSs and its repair effect after storage. RESULTS: Two methods for biobanking foreskin ECSs were compared in a short term (7 days): 4-degree storage and programmed cryopreservation. Cell sheet integrity, viability, apoptosis, immunogenicity, mechanical properties and function were evaluated. In vivo, ECSs were directly transplanted to skin defect models and histological examination was performed at 1 week postoperatively. We successfully extracted human foreskin-derived primary epithelial cells and fabricated them into ECSs. Compared with 4-degree storage, programmed cryopreservation preserved the ECS structural integrity, enhanced the mechanical properties, decreased HLA-I expression, and increased cell viability and survival. An increased proportion of melanocytes with proliferative capacity remained in the cryopreserved sheets, and the undifferentiated epithelial cells were comparable to those of the fresh sheets. In vivo, cryopreserved ECSs could reduce inflammatory cell infiltration and promote connective tissue remodeling, epithelial cell proliferation and vascular regeneration. CONCLUSIONS: Programmed cryopreservation of ECSs was superior and more feasible than 4-degree storage and the cryopreserved ECSs achieved satisfying skin wound healing in vivo. We anticipate that the off-the-shelf ECSs could be quickly used, such as, to repair human epithelial defect in future.

Clinical use of a machine learning histopathological image signature in diagnosis and survival prediction of clear cell renal cell carcinoma.

Due to the complicated histopathological characteristics of renal neoplasms, traditional distinguishing of clear cell renal cell carcinoma (ccRCC) by naked eyes of experienced pathologist remains labor intensive and time consuming. Here, we extracted quantitative features of hematoxylin-eosin-stained images using CellProfiler and performed machine learning method to develop and verify a novel computational recognition of digital pathology for diagnosis and prognosis of ccRCC patients in the training, test and external validation cohort. The diagnostic model based on digital pathology could accurately distinguish ccRCC from normal renal tissues, with area under the curve (AUC) of 96.0%, 94.5% and 87.6% in the training, test and external validation cohorts, respectively. It could also accurately distinguish ccRCC from other pathological types of renal cancer, with AUC values of 97.0% and 81.4% in the Cancer Genome Atlas (TCGA) cohort and General cohort. We next developed and verified a computational recognition prognosis model with risk score. There was a significant difference in disease-free survival comparing patients with high vs low risk score in training cohort (hazard ratio = 2.72, P < .0001) and validation cohort (hazard ratio = 9.50, P = .0091). The integrated nomogram based on our computational recognition risk score and clinicopathologic factors demonstrated excellent survival prediction for ccRCC patients, with increased accuracy by 6.6% in patients from Shanghai General Hospital and by 2.5% in patients from TCGA cohort when compared to current tumor stages/grade systems. These results indicate the potential clinical use of our machine learning histopathological image signature in diagnosis and survival prediction of ccRCC.

Ubiquitin ligase KLHL2 promotes the degradation and ubiquitination of ARHGEF7 protein to suppress renal cell carcinoma progression.

Recent studies have revealed that ARHGEF7 is upregulated in many malignant tumors, but the underlying molecular mechanisms to this response remain to be fully elucidated. In this study, we confirm that ARHGEF7 physically interacts with KLHL2, which was previously identified to be an E3 ubiquitin ligase. KLHL2 is capable of promoting ARHGEF7 degradation via the ubiquitin-proteasome pathway. We identify that the Kelch domain of KLHL2 is necessary for binding with ARHGEF7 and downstream activities. In addition, we find that ARHGEF7 is overexpressed in clear cell renal cell carcinoma (ccRCC) specimens, and that the level of expression negatively correlates with that of KLHL2. Moreover, we utilize knockdown loss-of-function assays to demonstrate that ARHGEF7 in 786-O and A498 cell lines can act as a regulator of cell proliferation, migration and invasion, and that these effects can be reversed by KLHL2 inactivation. Taken together, our data suggest that ARHGEF7 is a putative oncogene that functions via an interaction with KLHL2, and control of ARHGEF7 can be a potential future target to inhibit tumor progression.

CCR8 blockade primes anti-tumor immunity through intratumoral regulatory T cells destabilization in muscle-invasive bladder cancer.

Regulatory T cells (Tregs) play a major role in the development of an immunosuppressive tumor microenvironment. Systemic Treg depletion is not favored because of the critical role of Tregs in maintaining immune homeostasis and preventing the autoimmunity. Recently, CCR8 has been identified as an important chemokine receptor expressed on intratumoral Tregs and is known to be critical for CCR8+Treg-mediated immunosuppression. However, the inherent molecular mechanisms and clinical significance of intratumoral CCR8+Tregs remain poorly understood. In this study, a retrospective analysis of 259 muscle-invasive bladder cancer (MIBC) patients from two independent clinic centers was conducted to explore the prognostic merit of CCR8+Tregs via immunohistochemistry. Eighty-three fresh MIBC samples and data from the Cancer Genome Atlas were used to evaluate the proportion and function of immune cells via flow cytometry, ex vivo intervention experiments and bioinformatics analysis. It was found that the CCR8 expression by intratumoral Tregs maintained the stability and potentiated their suppressive function by upregulating the expression of transcript factors FOXO1 and c-MAF. High level of CCR8+Tregs was associated with the immune tolerance and predicted poor survival and inferior therapeutic responsiveness to chemotherapy. Moreover, it was revealed that CCR8 blockade could destabilize intratumoral Tregs into a fragile phenotype accompanied with reactivation of antitumor immunity and augment of anti-PD-1 therapeutic benefits in MIBC. In summary, those results suggested that CCR8+Tregs represented a stable Treg subtype and a promising therapeutic target in the immunotherapy of MIBC.

The study on copy number alteration of clear cell renal cancer in Chinese population.

Objectives: Copy number alteration (CNA) is one of the important genetic variations. Although there are many studies on renal cancer CNA, few studies are based on the Chinese population. In our study, our objective is to acquire the whole-genome CNA landscape in Chinese population and explore the tumor risk-associated functional genes in the CNA regions, by detecting whole-genome in the clear cell renal cancer (ccRCC) tissues. Methods: We enrolled 35 formalin fixed paraffin embedded samples, which were processed by Oncoscan assay, and then acquired the data of whole-genome CNA. Then genes annotation and enrichment analyzing were processed. Furthermore, the gene burden and the affected bp (base pair) per Mbp (million bp) regions in whole-genome were analyzed by comparison of different T stage affected by CNA. Results: We acquired the whole-genome CNA landscape by Oncoscan detection, and found out the high-frequency CNA regions which were not reported in previous studies, for example, 11P11, 22q11.23, 20q11.3 (PDRG1), and Xp22.33 so on. During the analyzing of genes annotation and enrichment, we found out some ccRCC functional genes in the CNA regions which might play a role in the biological process, for example, the copy number loss of DNA repair genes (TTC5、PARP2, etc.) and tumor suppressor genes (TADA3, VHL, BAP1, ERC2-IT1, etc.), the copy number gain of oncogenes (ABL2, MET, HUWE1, etc.) and Notch signal pathway genes (MDK, etc.). Besides, gene fusion (GSTTP and GSTTP2) was noticed at 22q11.23 which copy number loss occurred, and the frequency is 46%. And between the different T stage patients affected by CNA, the T2+T3 group carried more high-frequency CNA regions (P-value was 0.012). Conclusions: In this study, the whole-genome ccRCC CNA landscape in Chinese population was acquired, a few functional genes and fusion genes were found out. However, a larger scale of samples is still needed to validate our results.

A novel gene signature combination improves the prediction of overall survival in urinary bladder cancer.

Objectives: Bladder carcinoma is a clinical heterogeneous disease, which is with significant variability of the prognosis and high risk of death. This revealed prominently the need to identify high-efficiency cancer characteristics to predict clinical prognosis. Methods: Gene expression profiles of 93 bladder tumor patients from Gene Expression Omnibus data sets was performed in this study, along with 408 bladder tumor patients retrieved from The Cancer Genome Atlas database. The relationship of gene signature and overall survival was analyzed in the training cohort (n = 46). The validation for that was performed in an internal validation cohort (n = 47) and an external validation cohort (n = 408). Results: Four genes (TMPRSS11E, SCEL, KRT78, TMEM185A) were identified by univariable and multivariable Cox regression analysis. According to a risk score on the bases on the four-gene signature, we grouped these patients in high-risk group and low-risk group with significantly different overall survival in the training series and successfully validated it in both the internal and external validation cohorts. Subsequent studies demonstrated that the four-gene expression risk score was independent of radical cystectomy stage, chemotherapy and lymph node status. Higher rates of FAT4 mutation and MACF1 mutation in bladder tumors with high risk score were found compared with tumors with low risk score. Gene set enrichment analysis revealed high-risk score was associated with some tumor progression and recurrence associated pathways. Conclusions: This four-gene risk score might have potential clinical implications in the selection of high-risk urinary bladder cancer patients for aggressive therapy. The selected four genes might become potential therapeutic targets and diagnostic markers for urinary bladder cancer.

Identification of Cancer-Specific Methylation of Gene Combination for the Diagnosis of Bladder Cancer.

Here we conducted an evidence-based study in developing and validating a urinary biomarker combination of gene methylation assays in patients with hematuria. A number of 99 urine samples were obtained and detected from Chinese patients with hematuria. The Cancer Genome Atlas cohort with methylation (HM450) beta-values and clinical data of 412 bladder cancer and 21 matching normal tissue was included as a validation series. A risk score formula was then developed and calculated by the targeted genes, weighted by their estimated regression coefficients from the multivariable binary logistic regression analyses, and evaluated by receiver operating characteristic (ROC) curves analysis. The combination assay of HOXA9, ONECUT2, PCDH17, PENK, TWIST1, VIM and ZNF154 was singled out according to the results of multivariate logistic regression analysis. The higher probability of DNA methylation of all the selected 7 genes was found in bladder cancer group than the control group. Remarkable higher DNA methylation beta-values of all the selected 7 genes were also displayed in bladder cancer tissues compared with their matching normal bladder tissues. And the AUC value of our risk score model were 0.894 and 0.851 in respective cohort, revealing highlighted predictive value of our risk score model on bladder cancer diagnosis. In conclusions, a urinary combined methylation assay of HOXA9, ONECUT2, PCDH17, PENK, TWIST1, VIM and ZNF154 displayed accurate prediction of bladder cancer in hematuria patients, which provided the guidance for the patients at early stage tumor and during the follow-up after operation. Of course, prospective study based on a hematuria cohort with a large sample size should be conducted to validate these findings in the future.

Phosphorylation of LIFR promotes prostate cancer progression by activating the AKT pathway.

Prostate cancer (PCa) is the most common solid organ malignancy among men, outnumbering both lung and colorectal cancer, and it is the second leading cause of male tumor-related death in the United States due to high metastasis. Recently, leukemia inhibitory factor receptor (LIFR) has been found to play roles in multiple types of cancer. However, the roles of LIFR in the progression of PCa remain to be revealed. In this study, we found that LIFR plays an oncogenic role in PCa. The phosphorylation of LIFR at S1044 contributes to subsequent activation of the AKT pathway, inducing the expression of a series of proliferation and metastatic genes. Additionally, LIFR-S1044 is phosphorylated by ERK2 but not ERK1. The signal intensity of pLIFR-S1044 and pAKT S473 in PCa tissue displays a tight positive correlation. The ERK2/LIFR/AKT axis modulates PCa progression and offers a promising therapeutic and diagnostic target for PCa.

Multi-omics Perspective on the Tumor Microenvironment based on PD-L1 and CD8 T-Cell Infiltration in Urothelial Cancer.

Objectives: We carried out an integrated analysis based on multiple-dimensional types of data from cohorts of bladder cancer patients to identify multi-omics perspective (genomics and transcriptomics) on the tumor microenvironment on the bases of the programmed cell death 1 ligand (PD-L1) and CD8 T-cell infiltration in urothelial carcinoma. Methods: Multiple-dimensional types of data, including clinical, genomic and transcriptomic data of 408 bladder cancer patients were retrieved from the Cancer Genome Atlas database. Based on the median values of PD-L1 and CD8A, the tumor samples were grouped into four tumor microenvironment immune types (TMIT). The RNA sequencing profiles, somatic mutation and PD-L1 amplification data of bladder cancer were analyzed by different TMITs. Results: Our research demonstrated that 36.8% of the evaluated bladder cancer belonged to TMIT I (high PD-L1/high CD8A). TIMT subtypes were not significantly associated with overall survival or disease free survival in urothelial cancer. TMIT I facilitates CD8+ T-cell infiltration and activates T-effector and interferon gamma (IFN-γ) associated gene signature. The number of somatic mutations, cytolytic activity, IFN-γ mRNA expression and TIGIT mRNA expression in TMIT I was remarkably higher than those in other TMIT groups. Our results showed a high rate of C>T transversion and a high rate of transition/transversion (Ti/Tv) in TMIT I bladder tumors. The RB1 mutation was significantly associated with TMIT I bladder cancer and be significantly co-occurring with the TP53 mutation. However, FGFR3 mutation and TP53 mutation were mutually exclusive in TMIT II bladder tumors. More importantly, different amino acid changes by FGFR3/RB1 mutations were also found between TMIT I and TMIT II bladder cancer, such as amino acid changes in "Immunoglobulin I-set domain (260-356)"and "Protein tyrosine kinase (472-748)". We also detected 9 genes as significantly cancer-associated genes in TMIT I bladder cancer, of which, RAD51C has been reported to play an important role in DNA damage responses. Further analysis concentrated on the potential molecular mechanism found that TMIT I was significantly associated with anti-tumor immune-related signaling pathway, and kataegis was present on chromosome 21 in TMIT I bladder tumors. Conclusions: The classification of bladder cancer into four TMITs on the bases of the PD-L1 expression and the CD8+ CTLs statuses is an appropriate approach for bladder tumor immunotherapy. TMIT I (high PD-L1/high CD8A) is significantly correlated with more somatic mutation burden, and facilitates CD8+ T-cell infiltration and activates T-effector and IFN-γ associated gene signature. Alteration landscape for somatic variants was different between TMIT I and TMIT II (low PD-L1/low CD8A).

Derepression of LOXL4 inhibits liver cancer growth by reactivating compromised p53.

TP53 is the most frequently mutated gene in human cancer, whereas tumors with wild-type TP53 develop alternative strategies to survive. Identifying new regulators of p53 reactivation would greatly contribute to the development of cancer therapies. After screening the entire genome in liver cancer cells, we identified lysyl oxidase-like 4 (LOXL4) as a novel regulator for p53 activation. We found that 5-azacytidine (5-aza-CR) induces LOXL4 upregulation, with LOXL4 subsequently binding the basic domain of p53 via its low-isoelectric point region. The interaction between LOXL4 and p53 induces the reactivation of compromised p53, resulting in cell death. Furthermore, the nude mouse xenograft model showed that the 5-aza-CR-dependent LOXL4-p53 axis reduces tumor growth. A positive correlation between LOXL4 expression and overall survival in liver cancer patients with wild-type p53 tumors was observed. In conclusion, we found that 5-aza-CR-induced LOXL4 upregulation reactivates wild-type p53 and triggers cell death, which blocks liver cancer development.