Exploring G-quadruplex structure in PRCC-TFE3 fusion oncogene: Plausible use as anti cancer therapy for translocation Renal cell carcinoma (tRCC).

The TFE3 fusion gene, byproduct of Xp11.2 translocation, is the diagnostic marker for translocation renal cell carcinoma (tRCC). Absence of any clinically recognized therapy for tRCC, pressing a need to create novel and efficient therapeutic approaches. Previous studies shown that stabilization of the G-quadruplex structure in oncogenes suppresses their expression machinery. To combat the oncogenesis caused by fusion genes, our objective is to locate and stabilize the G-quadruplex structure within the PRCC-TFE3 fusion gene. Using the Quadruplex-forming G Rich Sequences (QGRS) mapper and the Non-B DNA motif search tool (nBMST) online server, we found putative G-quadruplex forming sequences (PQS) in the PRCC-TFE3 fusion gene. Circular dichroism demonstrating a parallel G-quadruplex in the targeted sequence. Fluorescence and UV-vis spectroscopy results suggest that pyridostatin binds to this newly discovered G-quadruplex. The PCR stop assay, as well as transcriptional or translational inhibition using real time PCR and Dual luciferase assay, revealed that stable G-quadruplex formation affects biological processes. Confocal microscopy of HEK293T cells transfected with the fusion transcript confirmed G-quadruplexes formation in cell. This investigation may shed light on G-quadruplex's functions in fusion genes and may help in the development of therapies specifically targeted against fusion oncogenes, which would enhance the capability of current tRCC therapy approach.

The influence of circadian rhythms on CD8+ T cell activation upon vaccination: A mathematical modeling perspective.

Circadian rhythms have been implicated in the modulation of many physiological processes, including those associated with the immune system. For example, these rhythms influence CD8+ T cell responses within the adaptive immune system. The mechanism underlying this immune-circadian interaction, however, remains unclear, particularly in the context of vaccination. Here, we devise a molecularly-explicit gene regulatory network model of early signaling in the naïve CD8+ T cell activation pathway, comprised of three axes (or subsystems) labeled ZAP70, LAT and CD28, to elucidate the molecular details of this immune-circadian mechanism and its relation to vaccination. This is done by coupling the model to a periodic forcing function to identify the molecular players targeted by circadian rhythms, and analyzing how these rhythms subsequently affect CD8+ T cell activation under differing levels of T cell receptor (TCR) phosphorylation, which we designate as vaccine load. By performing both bifurcation and parameter sensitivity analyses on the model at the single cell and ensemble levels, we find that applying periodic forcing on molecular targets within the ZAP70 axis is sufficient to create a day-night discrepancy in CD8+ T cell activation in a manner that is dependent on the bistable switch inherent in CD8+ T cell early signaling. We also demonstrate that the resulting CD8+ T cell activation is dependent on the strength of the periodic coupling as well as on the level of TCR phosphorylation. Our results show that this day-night discrepancy is not transmitted to certain downstream molecules within the LAT subsystem, such as mTORC1, suggesting a secondary, independent circadian regulation on that protein complex. We also corroborate experimental results by showing that the circadian regulation of CD8+ T cell primarily acts at a baseline, pre-vaccination state, playing a facilitating role in priming CD8+ T cells to vaccine inputs according to the time of day. By applying an ensemble level analysis using bifurcation theory and by including several hypothesized molecular targets of this circadian rhythm, we further demonstrate an increased variability between CD8+ T cells (due to heterogeneity) induced by its circadian regulation, which may allow an ensemble of CD8+ T cells to activate at a lower vaccine load, improving its sensitivity. This modeling study thus provides insights into the immune targets of the circadian clock, and proposes an interaction between vaccine load and the influence of circadian rhythms on CD8+ T cell activation.

Papillary renal neoplasm with reverse polarity: an observational study of histology, immunophenotypes, and molecular variation.

Background: Papillary renal neoplasm with reverse polarity (PRNRP) is a novel entity with unique clinicopathological characteristics, and only a small number of patients with PRNRP have been described. Methods: We retrospectively analyzed the data for nine patients with PRNRP and evaluated differences in the clinical, histomorphological, immunohistochemical, and molecular features; prognosis; and differential diagnosis of PRNRP from other renal tumors with papillary structure. Results: There were six males and three females aged 36 to 74 years (mean: 62.33 years; median: 68 years). All the tumors were solitary and ranged from 1 to 3.7 cm (mean: 2.17 cm; median: 2 cm), with three and six tumors arose in the left and right renal tract, respectively. Pathologically, PRNRP is a small, well-circumscribed neoplasm with predominant papillary formations. The lining epithelium is composed of a monolayer of cuboidal to low-columnar cells with low-grade nuclei arranged against the apical pole of the tumor cells. Edema, mucinous degeneration, and hyaline degeneration are found in the fibrovascular cores. Foamy macrophages, psammoma bodies, hemosiderin deposition, and infiltrative tumor boundaries were present in some patients. Immunohistochemically, all tumors showed diffuse positive staining for GATA3. Sanger sequencing confirmed the presence of KRAS mutation in seven patients. All patients had a good prognosis after surgery and were relapse free. Positive staining for GATA3 and negative staining for vimentin were the most significant markers for differentiating PRNRP from other renal tumors with analogous structure. Conclusions: These findings suggested that PRNRP is a distinctive subtype of renal tumor with specific pathological features and indolent behaviors that should be distinguished from other renal tumors, especially papillary renal cell carcinoma. A monolayer of tumor cells with an inverted nuclear pattern, positive staining for GATA3, and KRAS mutation are essential for pathological diagnosis. Owing to its satisfactory prognosis, the surveillance and follow-up of patients with PRNRP should be additionally formulated.

Biphasic papillary (biphasic squamoid alveolar) renal cell carcinoma: a clinicopathologic and molecular study of 17 renal cell carcinomas including 10 papillary adenomas.

Biphasic papillary renal cell carcinoma (synonymous with biphasic squamoid alveolar renal cell carcinoma) is considered within the spectrum of papillary renal cell carcinoma (PRCC). With < 70 reported cases of biphasic PRCC, there is limited data on the pathologic spectrum and clinical course. Seventeen biphasic PRCC cases and 10 papillary adenomas with similar biphasic morphology were assessed. The mean age of the biphasic PRCC patients was 62 years (male to female ratio of 1.8:1), from 10 partial nephrectomies, 6 radical nephrectomies, and 1 biopsy. The mean tumor size was 3.6 cm (range 1.6-8 cm), with 24% showing multifocality. Fifteen out of 17 cases were limited to the kidney (one of which was staged as pT2a but had lung metastases at diagnosis) and 2/17 cases were staged as T3a. All tumors showed typical biphasic morphology with an extent of squamoid foci widely variable from 10 to 95%. Emperipolesis was identified in 88% of cases. All biphasic PRCC tested exhibited positivity for PAX8 (16/16), keratin 7 (17/17), EMA (15/15), AMACR (17/17), and vimentin (12/12) in both large and small cells; cyclin D1 was only expressed in the large cells (16/16). The 10 papillary adenomas showed a similar immunoprofile to biphasic PRCC. NGS testing performed on 13 biphasic PRCC revealed 4 (31%) harboring MET SNVs. In 1/5 (20%) papillary adenomas, a pathogenic MET SNV was identified. Biphasic PRCC is rare with a generally similar immunoprofile to "type 1" PRCC but with notable strong positivity for cyclin D1 in the large cell component. Although most of the biphasic PRCC cases were of small size, low stage, and with an indolent behavior, one patient had metastatic disease and one patient died of the disease.

Establishment and Characterization of a TFE3-rearranged Renal Cell Carcinoma Cell Line (FU-UR-2) With the PRCC-TFE3 Fusion Transcript.

BACKGROUND/AIM: Xp11.2-RCC was classified into molecularly defined renal carcinomas and named TFE3-rearranged renal cell carcinoma (TFE3-rRCC) in the 2022 World Health Organization classification of renal tumors. MATERIALS AND METHODS: In this study, we established and characterized a TFE3-rRCC cell line from a right-sided renal tumor of a 35-year-old female patient and named it FU-UR-2. FU-UR-2 had been initially diagnosed as a papillary RCC because the patient was 35 years old, a routine immunohistochemical staining for TFE3 was negative, and its morphology was papillary. The G-band analysis revealed an X-chromosome aberration, thus we performed immunohistochemical re-staining for TFE3 and examined the aberration in the TFE3 gene by reverse-transcriptase polymerase chain reaction and fluorescence in situ hybridization. RESULTS: FU-UR-2 was confirmed as a TFE3-rRCC with a PRCC-TFE3 fusion transcript. CONCLUSION: Cultured FU-UR-2 cells continuously propagated over 90 passages and may provide a new permanent culture model to study pathogenetic mechanisms, investigate biological behavior, and develop new treatments such as molecular-targeting antitumor agents or immunological drugs for TFE3-rRCCs.

Identification and validation of ubiquitin-proteasome system related genes as a prognostic signature for papillary renal cell carcinoma.

Dysregulation of the ubiquitin-proteasome system (UPS) pathway greatly affects uncontrolled proliferation, genomic instability, and carcinogenesis, particularly in those with renal papillary cell carcinoma (PRCC). However, there is little information at the molecular level about the full link between changes in the genes involved in ubiquitin-mediated proteolysis and PRCC. METHODS: The Cancer Genome Atlas (TCGA) and GeneCards databases were utilized to find the clinical data and gene expression patterns of patients with PRCC. Univariate Cox regression analysis and absolute shrinkage and selection operator (LASSO) analyses identified a risk signature formed by ten optimal UPS genes. The predictive value of the risk signature in TCGA-PRCC cohorts was evaluated using Kaplan-Meier analysis and receiver operating characteristic (ROC) curves. By utilizing GO enrichment and the KEGG pathway, the interactions of differentially expressed genes connected to ubiquitin-mediated proteolysis were functionally examined. The protein expression of the hub genes was affirmed using the Human Protein Atlas (HPA) database. The effectiveness of particular CDC20 and UBE2C in vitro was confirmed by experimental research. RESULTS: Ten of the best ubiquitin-mediated proteolysis genes (UBE2C, DDB2, CBLC, BIRC3, PRKN, UBE2O, SIAH1, SKP2, UBC, and CDC20) were detected to create a risk signature. The high-risk score group stratified was associated with advanced tumor status and poor survival of PRCC patients. 10 genes were also found to be associated with the cell cycle pathway and ubiquitin-mediated proteolysis to GO and KEGG analysis. Of these 10 genes, CDC20 and UBE2C are highly expressed in tumor tissue and correlated with cancer immunity founded on the analyses of the expression of human protein atlas and TISIDB. The downregulation of UBE2C facilitated tumor inhibition and the anti-immune effect was confirmed by in vitro experiments. CONCLUSION: Our results indicate that the risk model created from the ubiquitin-mediated proteolysis genes can be reliably and accurately predict the prognosis of PRCC patients, highlighting its targeted value for PRCC treatment. Particularly, the expression of UBE2C may be crucial for the prognosis and immunological treatment of renal cancer.

Impact of MET status on treatment outcomes in papillary renal cell carcinoma: A pooled analysis of historical data.

BACKGROUND: Papillary renal cell carcinoma (PRCC) represents 15% of RCCs but has no indicated therapies, with limited biomarker-based data to inform targeted treatment. MET alterations may be key; > 80% of PRCC tumours show MET upregulation. The objective of this study was to assess MET status in PRCC and its impact on clinical outcomes. METHODS: This retrospective, observational study included patients with locally advanced/metastatic PRCC from three international registries. MET status was determined retrospectively by next generation sequencing (NGS) of archival tissue. MET-driven was defined as MET and/or hepatocyte growth factor amplification, chromosome 7 gain, and/or MET kinase domain mutations. Objectives included progression-free survival (PFS) and overall survival (OS) by MET status using a Cox proportional hazards model. RESULTS: Of 308 patients, 305 received first-line treatment; most commonly sunitinib (n = 208; 68%), then everolimus (n = 40; 13%). Of 179 patients with valid NGS results, 38% had MET-driven and 49% MET-independent tumours (13% unevaluable). In the MET-driven versus MET-independent subgroups, respectively, of sunitinib-treated patients, median PFS was numerically longer, though not statistically significantly; PFS: 9.2 months (95% confidence interval [CI]: 5.4-13.2) versus 5.7 months (95% CI: 4.3-7.4), hazard ratio (HR) = 0.67; 95% CI: 0.41-1.08. There was no difference between the OS of each subgroup. CONCLUSIONS: MET-driven PRCC may respond to targeted agents. However, the presence of MET alterations did not appear to be predictive for outcomes in response to current therapies, which are not biomarker-driven, compared with MET-independent tumours.

A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis.

COVID-19 had been declared a public health emergency by the World Health Organization in the early 2020. Since then, this deadly virus has claimed millions of lives worldwide. Amidst its chaotic spread, several other diseases have faced negligence in terms of treatment and care, of which one such chronic disease is Tuberculosis. Due to huge rise in COVID-19 cases, there had been a drastic decrease in notification of TB cases which resulted in reversal of global TB target progress. Apart from these due to the earlier co-infections of TB with SARS and MERS-CoV viruses, the TB-COVID-19 co-infection posed a severe threat in the spread of the disease. All these factors backed to be major motivation factor in development of this model. Leading with this concern, a TB - COVID-19 co-infection model is developed in this study, considering possibility of waning immunity of both diseases. Considering different epidemiological traits, an epidemiological model with 11 compartments is developed and the co-dynamics is analysed. A detailed stability and bifurcation analysis is performed for the TB only sub-model, COVID-19 only sub-model and the complete TB - COVID-19 model. Impact of key parameters namely, infection rate, waning immunity, and face mask efficacy on disease prevalence is discussed in detail. Sensitivity analysis by means of normalized forward sensitivity index of the basic reproduction number and LHS-PRCC approach is carried to provide a thorough understanding of significance of various parameters in accelerating as well as controlling the disease spread. Optimal control analysis is presented extensively, incorporating controls related to timely and improved TB treatment, and enhanced COVID-19 tests and isolation facilities to curb the spread of these infectious diseases. The simulation results obtained from each of these analyses stress on the importance of different control measures in mitigation of the diseases and are illustrated accordingly. The study suggests that in the times of a pandemic, other disease treatment and care must not be neglected, and adequate care must be taken so that mortality due to co-infection and unavailability of timely treatment can be avoided.

Modeling nosocomial infection of COVID-19 transmission dynamics.

COVID-19 epidemic has posed an unprecedented threat to global public health. The disease has alarmed the healthcare system with the harm of nosocomial infection. Nosocomial spread of COVID-19 has been discovered and reported globally in different healthcare facilities. Asymptomatic patients and super-spreaders are sough to be among of the source of these infections. Thus, this study contributes to the subject by formulating a S E I H R mathematical model to gain the insight into nosocomial infection for COVID-19 transmission dynamics. The role of personal protective equipment θ is studied in the proposed model. Benefiting the next generation matrix method, R 0 was computed. Routh-Hurwitz criterion and stable Metzler matrix theory revealed that COVID-19-free equilibrium point is locally and globally asymptotically stable whenever R 0 < 1 . Lyapunov function depicted that the endemic equilibrium point is globally asymptotically stable when R 0 > 1 . Further, the dynamics behavior of R 0 was explored when varying θ . In the absence of θ , the value of R 0 was 8.4584 which implies the expansion of the disease. When θ is introduced in the model, R 0 was 0.4229, indicating the decrease of the disease in the community. Numerical solutions were simulated by using Runge-Kutta fourth-order method. Global sensitivity analysis is performed to present the most significant parameter. The numerical results illustrated mathematically that personal protective equipment can minimizes nosocomial infections of COVID-19.

Targeting chemoresistance in Xp11.2 translocation renal cell carcinoma using a novel polyamide-chlorambucil conjugate.

Renal cell carcinoma with Xp11.2 translocation involving the TFE3 gene (TFE3-RCC) is a recently identified subset of RCC with unique morphology and clinical presentation. The chimeric PRCC-TFE3 protein produced by Xp11.2 translocation has been shown to transcriptionally activate its downstream target genes that play important roles in carcinogenesis and tumor development of TFE3-RCC. However, the underlying molecular mechanisms remain poorly understood. Here we show that in TFE3-RCC cells, PRCC-TFE3 controls heme oxygenase 1 (HMOX1) expression to confer chemoresistance. Inhibition of HMOX1 sensitized the PRCC-TFE3 expressing cells to genotoxic reagents. We screened for a novel chlorambucil-polyamide conjugate (Chb) to target PRCC-TFE3-dependent transcription, and identified Chb16 as a PRCC-TFE3-dependent transcriptional inhibitor of HMOX1 expression. Treatment of the patient-derived cancer cells with Chb16 exhibited senescence and growth arrest, and increased sensitivity of the TFE3-RCC cells to the genotoxic reagent etoposide. Thus, our data showed that the TFE3-RCC cells acquired chemoresistance through HMOX1 expression and that inhibition of HMOX1 by Chb16 may be an effective therapeutic strategy for TFE3-RCC.

Fumarate inhibits PTEN to promote tumorigenesis and therapeutic resistance of type2 papillary renal cell carcinoma.

Fumarate is an oncometabolite. However, the mechanism underlying fumarate-exerted tumorigenesis remains unclear. Here, utilizing human type2 papillary renal cell carcinoma (PRCC2) as a model, we show that fumarate accumulates in cells deficient in fumarate hydratase (FH) and inhibits PTEN to activate PI3K/AKT signaling. Mechanistically, fumarate directly reacts with PTEN at cysteine 211 (C211) to form S-(2-succino)-cysteine. Succinated C211 occludes tethering of PTEN with the cellular membrane, thereby diminishing its inhibitory effect on the PI3K/AKT pathway. Functionally, re-expressing wild-type FH or PTEN C211S phenocopies an AKT inhibitor in suppressing tumor growth and sensitizing PRCC2 to sunitinib. Analysis of clinical specimens indicates that PTEN C211 succination levels are positively correlated with AKT activation in PRCC2. Collectively, these findings elucidate a non-metabolic, oncogenic role of fumarate in PRCC2 via direct post-translational modification of PTEN and further reveal potential stratification strategies for patients with FH loss by combinatorial AKTi and sunitinib therapy.

Investigating the transmission dynamics of SARS-CoV-2 in Nigeria: A SEIR modelling approach.

This study was designed to investigate the transmission dynamics of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to inform policy advisory vital for managing the spread of the virus in Nigeria. We applied the Susceptible-Exposed-Infectious-Recovered (SEIR)-type predictive model to discern the transmission dynamics of SARS-CoV-2 at different stages of the pandemic; incidence, during and after the lockdown from 27th March 2020 to 22nd September 2020 in Nigeria. Our model was calibrated with the COVID-19 data (obtained from the Nigeria Centre for Disease Control) using the "lsqcurvefit" package in MATLAB to fit the "cumulative active cases" and "cumulative death" data. We adopted the Latin hypercube sampling with a partial rank correlation coefficient index to determine the measure of uncertainty in our parameter estimation at a 99% confidence interval (CI). At the incidence of SARS-CoV-2 in Nigeria, the basic reproduction number (R0 ) was 6.860; 99%CI [6.003, 7.882]. R0 decreased by half (3.566; 99%CI [3.503, 3.613]) during the lockdown, and R0 was 1.238; 99%CI [1.215, 1.262] after easing the lockdown. If all parameters are maintained (as in after easing the lockdown), our model forecasted a gradual and perpetual surge through the next 12 months or more. In the light of our results and available data, evidence of human-to-human transmission at higher rates is still very likely. A timely, proactive, and well-articulated effort should help mitigate the transmission of SARS-CoV-2 in Nigeria.

A Novel Ferroptosis-Related lncRNA Signature for Prognosis Prediction in Patients with Papillary Renal Cell Carcinoma.

PURPOSE: Papillary renal cell carcinoma (PRCC) is a common renal cell carcinoma. Recent studies have reported that ferroptosis is involved in the occurrence and development of tumors. Long non-coding RNAs can be used as independent biomarkers for the diagnosis and prognosis of a variety of tumors. METHODS: Gene expression profile and clinical information of patients with PRCC were obtained from The Cancer Genome Atlas (TCGA) database. Lasso penalized Cox regression and univariate Cox regression analysis were utilized for model construction. The Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Immune cell infiltration and immune function were compared between the high-risk and low-risk groups. Chemotherapy sensitivity analysis was also performed. RESULTS: We constructed a prognostic signature consisting of 15 ferroptosis-related lncRNAs. The K-M curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the lncRNA signature was 0.930, exhibiting robust prognostic capacity. The high-risk group had a greater degree of immune cell infiltration than the low-risk group. Significant differences in inflammation promotion, parainflammation, and type I IFN response were noted between the low-risk and high-risk groups (p < 0.01). The expression levels of immune checkpoints including CD80, IDO1, and LAG3 were significantly higher in the high-risk group than in the low-risk group (p < 0.05). Chemotherapy sensitivity analysis showed that MNX1-AS1, ZFAS1, MIR4435-2HG, and ADAMTS9-AS1 were significantly correlated with the sensitivity of some chemotherapy drugs (p < 0.05). CONCLUSION: We demonstrated that a ferroptosis-related lncRNA prognostic signature could be a novel biomarker for PRCC.

Automated Classification of Papillary Renal Cell Carcinoma and Chromophobe Renal Cell Carcinoma Based on a Small Computed Tomography Imaging Dataset Using Deep Learning.

OBJECTIVES: This study was conducted in order to design and develop a framework utilizing deep learning (DL) to differentiate papillary renal cell carcinoma (PRCC) from chromophobe renal cell carcinoma (ChRCC) using convolutional neural networks (CNNs) on a small set of computed tomography (CT) images and provide a feasible method that can be applied to light devices. METHODS: Training and validation datasets were established based on radiological, clinical, and pathological data exported from the radiology, urology, and pathology departments. As the gold standard, reports were reviewed to determine the pathological subtype. Six CNN-based models were trained and validated to differentiate the two subtypes. A special test dataset generated with six new cases and four cases from The Cancer Imaging Archive (TCIA) was applied to validate the efficiency of the best model and of the manual processing by abdominal radiologists. Objective evaluation indexes [accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and area under the curve (AUC)] were calculated to assess model performance. RESULTS: The CT image sequences of 70 patients were segmented and validated by two experienced abdominal radiologists. The best model achieved 96.8640% accuracy (99.3794% sensitivity and 94.0271% specificity) in the validation set and 100% (case accuracy) and 93.3333% (image accuracy) in the test set. The manual classification achieved 85% accuracy (100% sensitivity and 70% specificity) in the test set. CONCLUSIONS: This framework demonstrates that DL models could help reliably predict the subtypes of PRCC and ChRCC.

Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver.

The predictive accuracy of mathematical models representing anything ranging from the meteorological to the biological system profoundly depends on the quality of model parameters derived from experimental data. Hence, robust sensitivity analysis (SA) of these critical model parameters aids in sifting the influential from the negligible out of typically vast parameter regimes, thus illuminating key components of the system under study. We here move beyond traditional local sensitivity analysis to the adoption of global SA techniques. Partial rank correlation coefficient (PRCC) based on Latin hypercube sampling is compared with the variance-based Sobol method. We selected for this SA investigation an infection model for the hepatitis-B virus (HBV) that describes infection dynamics and clearance of HBV in the liver [Murray & Goyal, 2015]. The model tracks viral particles such as the tenacious and nearly ineradicable covalently closed circular DNA (cccDNA) embedded in infected nuclei and an HBV protein known as p36. Our application of these SA methods to the HBV model illuminates, especially over time, the quantitative relationships between cccDNA synthesis rate and p36 synthesis and export. Our results reinforce previous observations that the viral protein, p36, is by far the most influential factor for cccDNA replication. Moreover, both methods are capable of finding crucial parameters of the model. Though the Sobol method is independent of model structure (e.g., linearity and monotonicity) and well suited for SA, our results ensure that LHS-PRCC suffices for SA of a non-linear model if it is monotonic.

PRCC reduces the sensitivity of cancer cells to DNA damage by inhibiting JNK and ATM/ATR pathways and results in a poor prognosis in hepatocellular carcinoma.

BACKGROUND AND AIM: The proline rich mitotic checkpoint control factor (PRCC) is involved in the splicing process of pre-mRNA. This study aims to elucidate PRCC molecular function, regulatory mechanism and diagnostic value in hepatocellular carcinoma (HCC). METHODS: The tissue microarray and serum samples from HCC patients were used to investigate the clinical value of PRCC. The biological function and molecular mechanism of PRCC were demonstrated by cell biology, biochemical and animal experiments. The relationship between PRCC and intratumoral heterogeneity (ITH) was analyzed by bioinformatics. RESULTS: PRCC was highly expressed in HCC tissues and related to the poor prognosis of HCC patients, its contents were elevated in the preoperative sera of HCC patients. PRCC exhibited high application potential as a substitute or adjuvant of alpha-fetoprotein (AFP) for clinical diagnosis of HCC. It had no significant effect on the proliferation of cancer cells, but could inhibit spheroid formation and metastasis of HCC cells in vitro and in vivo. The high ectopic expression of PRCC made cancer cells insensitive to DNA damage, and enhanced the heterogeneity of HCC cells by inhibiting the JNK/ATM/ATR/ATF2 axis. The HCC patients with high PRCC expression had high ITH, which corresponded to a short overall survival in patients. CONCLUSIONS: PRCC has high application potential as a substitute or adjuvant of AFP for clinical diagnosis of HCC. The high ectopic expression of PRCC not only caused HCC cells to resist to cell death induced by DNA damage, but also endowed cancer cells with numerous DNA mutations to become increasingly heterogeneous, finally leading to a poor prognosis in HCC patients. These data suggested PRCC could be a promising therapeutic target in HCC patients.

A construction and comprehensive analysis of ceRNA networks and infiltrating immune cells in papillary renal cell carcinoma.

BACKGROUND: As the second most common malignancy in adults, papillary renal cell carcinoma (PRCC) has shown an increasing trend in both incidence and mortality. Effective treatment for advanced metastatic PRCC is still lacking. In this study, we aimed to establish competitive endogenous RNA (ceRNA) networks related to PRCC tumorigenesis, and analyze the specific role of differentially expressed ceRNA components and infiltrating immune cells in tumorigenesis. METHODS: CeRNA networks were established to identify the key ceRNAs related to PRCC tumorigenesis based on the 318 samples from The Cancer Genome Atlas database (TCGA), including 285 PRCC and 33 normal control samples. The R package, "CIBERSORT," was used to evaluate the infiltration of 22 types of immune cells. Then we identified the significant ceRNAs and immune cells, based on which two nomograms were obtained for predicting the prognosis in PRCC patients. Finally, we investigated the co-expression of PRCC-specific immune cells and core ceRNAs via Pearson correlation test. RESULTS: COL1A1, H19, ITPKB, LDLR, TCF4, and WNK3 were identified as hub genes in ceRNA networks. Four prognostic-related tumor-infiltrating immune cells, including T cells CD4 memory resting, Macrophages M1, and Macrophages M2 were revealed. Pearson correlation test indicated that Macrophage M1 was negatively related with COL1A1 (p < 0.01) and LDLR (p < 0.01), while Macrophage M2 was positively related with COL1A1 (p < 0.01), TCF4 (p < 0.01), and H19 (p = 0.032). Two nomograms were conducted with favorable accuracies (area under curve of 1-year survival: 0.935 and 0.877; 3-year survival: 0.849 and 0.841; and 5-year survival: 0.818 and 0.775, respectively). CONCLUSION: The study constructed two nomograms suited for PRCC prognosis predicting. Moreover, we concluded that H19-miR-29c-3p-COL1A1 axis might promote the polarization of M2 macrophages and inhibit M1 macrophage activation through Wnt signaling pathway, collaborating to promote PRCC tumorigenesis and lead to poor overall survival of PRCC patients.

Limited Association Between Ascorbate Concentrations and Vitamin C Transporters in Renal Cell Carcinoma Cells and Clinical Samples.

BACKGROUND/AIMS: Maintenance of whole-body ascorbate levels and distribution is mediated via sodium-dependent vitamin C transporters (SVCTs). The kidney is one of a few organs that express both SVCT1 and SVCT2. Recent evidence suggests that accumulation of ascorbate may be different in tumour compared to normal tissue, but data on SVCT levels in tumours is sparse. METHODS: The role of the two SVCT isoforms in ascorbate uptake in renal cell carcinoma (RCC) was investigated in vitro and in clinical samples. In three human RCC cell lines, we investigated SVCT protein levels and cellular location in response to ascorbate supplementation and withdrawal. In clinical RCC samples (n=114), SVCT patterns of staining and protein levels were analysed and compared to ascorbate levels. RESULTS: In cell culture, transporter levels and cellular location were not modified by ascorbate availability at any time up to 8h, although basal SVCT2 levels governed maximal ascorbate accumulation. In clinical samples, SVCT1 protein levels in papillary RCC (pRCC) were similar to matched normal renal cortex, but were increased in clear-cell RCC (ccRCC). Native SVCT2 (72 kDa) was significantly decreased in both pRCC and ccRCC tissues compared to cortex (p<0.01), whereas a modified form of SVCT2 (100 kDa) was significantly increased (p<0.001). There was no association between the transporters (SVCT1, native or modified SVCT2) and ascorbate concentrations in either normal or tumour tissues. SVCT1 and SVCT2 displayed diffuse cytoplasmic staining in both pRCC and ccRCC tumour cells, with cortex showing distinct membrane staining for SVCT1. CONCLUSION: We observed a re-distribution of ascorbate transporters in tumour tissue compared to normal cortex and a shift from native to modified SVCT2 in cell culture and clinical samples. Data presented here show that SVCT protein levels do not appear to predict intracellular ascorbate accumulation in RCC.

Whether histologic subtyping affect the oncological outcomes of patients with papillary renal cell carcinoma: evidence from a systematic review and meta-analysis.

BACKGROUND: Whether the histologic subtype (type 1 and type 2) of papillary renal cell carcinoma (pRCC) is a tool to predict the prognosis is of great debate. This study is aimed to evaluate the prognostic significance of histologic subtype in patients with pRCC after surgery through a systematic review and meta-analysis. METHODS: We searched PubMed, the Web of Science, Cochrane library and EMBASE databases to identify studies published until January 20, 2021 according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were deemed eligible if they compared the overall survival (OS), cancer specific survival (CSS), recurrence-free survival (RFS) or disease-free survival (DFS) between patients with type 1 or type 2 pRCC. And the corresponding hazard ratios (HRs) and 95% conference intervals (CIs) were collected for meta-analysis and further subgroup analysis. RESULTS: Overall 22 studies with a total of 4,494 patients were considered eligible and included for the systematic review and meta-analysis. The pooled results showed that type 2 pRCC was associated with a worse OS (pooled HR 1.61, 95% CI: 1.10-2.36, P=0.02) and CSS (pooled HR 1.59, 95% CI: 1.00-2.51, P=0.05). However, the subgroup analysis yielded the same result as the initial analysis only when the HRs were extracted from univariate analysis. In studies with multivariate analysis, type 2 pRCC was not statistically associated with a worse OS (pooled HR 1.22, 95% CI: 0.97-1.53, P=0.27), CSS (pooled HR 1.16, 95% CI: 0.67-2.00, P=0.60), and DFS (pooled HR 1.33, 95% CI: 0.93-1.91, P=0.12) compared to type 1 pRCC. DISCUSSION: Histologic subtype is not an independent prognostic factor for patients with pRCC, although the result needs to be taken with caution. And studies with retrospective study design, larger sample size and longer follow-up period are required to verify these results.