A four-gene signature predicts survival in clear-cell renal-cell carcinoma

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.

Multifaceted roles for BCL3 in cancer: a proto-oncogene comes of age

In the early 1990's a group of unrelated genes were identified from the sites of recurring translocations in B-cell lymphomas. Despite sharing the nomenclature 'Bcl', and an association with blood-borne cancer, these genes have unrelated functions. Of these genes, BCL2 is best known as a key cancer target involved in the regulation of caspases and other cell viability mechanisms. BCL3 on the other hand was originally identified as a non-canonical regulator of NF-kB transcription factor pathways - a signaling mechanism associated with important cell outcomes including many of the hallmarks of cancer. Most of the early investigations into BCL3 function have since focused on its role in NF-kB mediated cell proliferation, inflammation/immunity and cancer. However, recent evidence is coming to light that this protein directly interacts with and modulates a number of other signaling pathways including DNA damage repair, WNT/β-catenin, AKT, TGFβ/SMAD3 and STAT3 - all of which have key roles in cancer development, metastatic progression and treatment of solid tumours. Here we review the direct evidence demonstrating BCL3's central role in a transcriptional network of signaling pathways that modulate cancer biology and treatment response in a range of solid tumour types and propose common mechanisms of action of BCL3 which may be exploited in the future to target its oncogenic effects for patient benefit.

Targeting Class I-II-III PI3Ks in Cancer Therapy: Recent Advances in Tumor Biology and Preclinical Research

Phosphatidylinositol-3-kinase (PI3K) enzymes, producing signaling phosphoinositides at plasma and intracellular membranes, are key in intracellular signaling and vesicular trafficking pathways. PI3K is a family of eight enzymes divided into three classes with various functions in physiology and largely deregulated in cancer. Here, we will review the recent evidence obtained during the last 5 years on the roles of PI3K class I, II and III isoforms in tumor biology and on the anti-tumoral action of PI3K inhibitors in preclinical cancer models. The dependency of tumors to PI3K isoforms is dictated by both genetics and context (e.g., the microenvironment). The understanding of class II/III isoforms in cancer development and progression remains scarce. Nonetheless, the limited available data are consistent and reveal that there is an interdependency between the pathways controlled by all PI3K class members in their role to promote cancer cell proliferation, survival, growth, migration and metabolism. It is unknown whether this feature contributes to partial treatment failure with isoform-selective PI3K inhibitors. Hence, a better understanding of class II/III functions to efficiently inhibit their positive and negative interactions with class I PI3Ks is needed. This research will provide the proof-of-concept to develop combination treatment strategies targeting several PI3K isoforms simultaneously.

Prognostic Gene Expression-Based Signature in Clear-Cell Renal Cell Carcinoma

The inaccuracy of the current prognostic algorithms and the potential changes in the therapeutic management of localized ccRCC demands the development of an improved prognostic model for these patients. To this end, we analyzed whole-transcriptome profiling of 26 tissue samples from progressive and non-progressive ccRCCs using Illumina Hi-seq 4000. Differentially expressed genes (DEG) were intersected with the RNA-sequencing data from the TCGA. The overlapping genes were used for further analysis. A total of 132 genes were found to be prognosis-related genes. LASSO regression enabled the development of the best prognostic six-gene panel. Cox regression analyses were performed to identify independent clinical prognostic parameters to construct a combined nomogram which includes the expression of CERCAM, MIA2, HS6ST2, ONECUT2, SOX12, TMEM132A, pT stage, tumor size and ISUP grade. A risk score generated using this model effectively stratified patients at higher risk of disease progression (HR 10.79; p < 0.001) and cancer-specific death (HR 19.27; p < 0.001). It correlated with the clinicopathological variables, enabling us to discriminate a subset of patients at higher risk of progression within the Stage, Size, Grade and Necrosis score (SSIGN) risk groups, pT and ISUP grade. In summary, a gene expression-based prognostic signature was successfully developed providing a more precise assessment of the individual risk of progression.

A Novel Machine Learning 13-Gene Signature: Improving Risk Analysis and Survival Prediction for Clear Cell Renal Cell Carcinoma Patients

Simple Summary

Clear cell renal cell carcinoma is a type of kidney cancer which comprises the majority of all renal cell carcinomas. Many efforts have been made to identify biomarkers which could help healthcare professionals better treat this kind of cancer. With extensive public data available, we conducted a machine learning study to determine a gene signature that could indicate patient survival with high accuracy. Through the min-Redundancy and Max-Relevance algorithm we generated a signature of 13 genes highly correlated with patient outcomes. These findings reveal potential strategies for personalized medicine in the clinical practice.

Abstract

Patients with clear cell renal cell carcinoma (ccRCC) have poor survival outcomes, especially if it has metastasized. It is of paramount importance to identify biomarkers in genomic data that could help predict the aggressiveness of ccRCC and its resistance to drugs. Thus, we conducted a study with the aims of evaluating gene signatures and proposing a novel one with higher predictive power and generalization in comparison to the former signatures. Using ccRCC cohorts of the Cancer Genome Atlas (TCGA-KIRC) and International Cancer Genome Consortium (ICGC-RECA), we evaluated linear survival models of Cox regression with 14 signatures and six methods of feature selection, and performed functional analysis and differential gene expression approaches. In this study, we established a 13-gene signature (AR, AL353637.1, DPP6, FOXJ1, GNB3, HHLA2, IL4, LIMCH1, LINC01732, OTX1, SAA1, SEMA3G, ZIC2) whose expression levels are able to predict distinct outcomes of patients with ccRCC. Moreover, we performed a comparison between our signature and others from the literature. The best-performing gene signature was achieved using the ensemble method Min-Redundancy and Max-Relevance (mRMR). This signature comprises unique features in comparison to the others, such as generalization through different cohorts and being functionally enriched in significant pathways: Urothelial Carcinoma, Chronic Kidney disease, and Transitional cell carcinoma, Nephrolithiasis. From the 13 genes in our signature, eight are known to be correlated with ccRCC patient survival and four are immune-related. Our model showed a performance of 0.82 using the Receiver Operator Characteristic (ROC) Area Under Curve (AUC) metric and it generalized well between the cohorts. Our findings revealed two clusters of genes with high expression (SAA1, OTX1, ZIC2, LINC01732, GNB3 and IL4) and low expression (AL353637.1, AR, HHLA2, LIMCH1, SEMA3G, DPP6, and FOXJ1) which are both correlated with poor prognosis. This signature can potentially be used in clinical practice to support patient treatment care and follow-up.

The enhancer rare germline variation rs548071605 contributes to lung cancer development

Rare germline variations contribute to the missing heritability of human complex diseases including cancers. Given their very low frequency, discovering and testing disease-causing rare germline variations remains challenging. The tag-single nucleotide polymorphism rs17728461 in 22q12.2 is highly associated with lung cancer risk. Here, we identified a functional rare germline variation rs548071605 (A>G) in a p65-responsive enhancer located within 22q12.2. The enhancer significantly promoted lung cancer cell proliferation in vitro and in a xenograft mouse model by upregulating the leukemia inhibitory factor (LIF) gene via the formation of a chromatin loop. Differential expression of LIF and its significant correlation with first progression survival time of patients further supported the lung cancer-driving effects of the 22q-Enh enhancer. Importantly, the rare variation was harbored in the p65 binding sequence and dramatically increased the enhancer activity by increasing responsiveness of the enhancer to p65 and B-cell lymphoma 3 protein, an oncoprotein that assisted the p65 binding. Our study revealed a regulatory rare germline variation with a potential lung cancer-driving role in the 22q12.2 risk region, providing intriguing clues for investigating the "missing heritability" of cancers, and also offered a useful experimental model for identifying causal rare variations.

Biomarkers in renal cell carcinoma: Are we there yet?

Management of kidney cancer has undergone a paradigm shift with the approval of new therapies over the last two decades. Although these drugs have improved clinical outcomes in patients with kidney cancer, there are still a large number of patients who do not show objective responses. A multitude of investigators, including those for The Cancer Genome Atlas have biologically characterized and sub-classified kidney cancer. However, we have not been able to identify molecular targets to effectively treat patients with kidney cancer. As we familiarize ourselves with newer drugs for patients with kidney cancer, it is important to understand that these drugs may not work in every patient and instead may expose patients to unnecessary toxic effects along with burdening society with the financial impact. As we head toward the era of "precision medicine", validated biomarkers are being utilized to guide treatment choices and help identify pathways of resistance in other tumor types. The current review aims at evaluating the progress made so far in this realm for patients with kidney cancer.

Loss of RANBP3L leads to transformation of renal epithelial cells towards a renal clear cell carcinoma like phenotype

Background

Renal cell carcinomas (RCC) are characterized by the deregulation of several hundred hyperosmolality-responsive genes. High expression of a subset of these genes including the Ran binding protein 3 like (RANBP3L) is linked to a favorable prognostic outcome in RCC. However, the cellular function of RANBP3L remains largely unknown.

Methods

We used CRISPR/Cas9-mediated gene editing to generate functional deletions of the Ranbp3l and nuclear factor of activated T cells 5 (Nfat5) gene loci in a murine renal cell line. The NFAT5-KO cells were used to assess the regulation of Ranbp3l by NFAT5 using immunofluorescence, RNA-Seq and promoter assays. RANBP3L-deficient cells were analyzed for changes in cell morphology, proliferation, migration and colony-forming capacity using immunofluorescence and live cell imaging. RANPB3L-dependent changes in gene expression were identified by RNA-Seq.

Results

We show that NFAT5 directly regulates Ranpb3l under hyperosmotic conditions by binding its promoter. Functional analysis of RANBP3L-deficient cells revealed a loss of epithelial structure, an increased cell migration behavior and colony forming capacity, accompanied by massive alterations in gene expression, all of which are hallmarks for tumor cells. Strikingly, a RANBP3L dependent signature of 60 genes separated samples with clear cell carcinoma (KIRC) from papillary (KIRP), chromophobe renal carcinoma (KICH) and healthy tissue.

Conclusions

Loss of RANBP3L induces a tumor like phenotype resembles RCC, especially KIRC, on the morphological and gene expression level and might promote tumor development and progression. Therapeutic reconstitution or elevation of osmoregulated RANBP3L expression might represent a novel treatment strategy for RCC or KIRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-01982-y.

Review of Prognostic Expression Markers for Clear Cell Renal Cell Carcinoma

Context: The number of prognostic markers for clear cell renal cell carcinoma (ccRCC) has been increasing regularly over the last 15 years, without being integrated and compared.

Objective: Our goal was to perform a review of prognostic markers for ccRCC to lay the ground for their use in the clinics.

Evidence Acquisition: PubMed database was searched to identify RNA and protein markers whose expression level was reported as associated with survival of ccRCC patients. Relevant studies were selected through cross-reading by two readers.

Evidence Synthesis: We selected 249 studies reporting an association with prognostic of either single markers or multiple-marker models. Altogether, these studies were based on a total of 341 distinct markers and 13 multiple-marker models. Twenty percent of these markers were involved in four biological pathways altered in ccRCC: cell cycle, angiogenesis, hypoxia, and immune response. The main genes (VHL, PBRM1, BAP1, and SETD2) involved in ccRCC carcinogenesis are not the most relevant for assessing survival.

Conclusion: Among single markers, the most validated markers were KI67, BIRC5, TP53, CXCR4, and CA9. Of the multiple-marker models, the most famous model, ClearCode34, has been highly validated on several independent datasets, but its clinical utility has not yet been investigated.

Patient Summary: Over the years, the prognosis studies have evolved from single markers to multiple-marker models. Our review highlights the highly validated prognostic markers and multiple-marker models and discusses their clinical utility for better therapeutic care.

The role of B-Cell Lymphoma-3 (BCL-3) in enabling the hallmarks of cancer: implications for the treatment of colorectal carcinogenesis

With its identification as a proto-oncogene in chronic lymphocytic leukaemia and central role in regulating NF-κB signalling, it is perhaps not surprising that there have been an increasing number of studies in recent years investigating the role of BCL-3 (B-Cell Chronic Lymphocytic Leukaemia/Lymphoma-3) in a wide range of human cancers. Importantly, this work has begun to shed light on our mechanistic understanding of the function of BCL-3 in tumour promotion and progression. Here, we summarize the current understanding of BCL-3 function in relation to the characteristics or traits associated with tumourigenesis, termed ‘Hallmarks of Cancer’. With the focus on colorectal cancer, a major cause of cancer related mortality in the UK, we describe the evidence that potentially explains why increased BCL-3 expression is associated with poor prognosis in colorectal cancer. As well as promoting tumour cell proliferation, survival, invasion and metastasis, a key emerging function of this proto-oncogene is the regulation of the tumour response to inflammation. We suggest that BCL-3 represents an exciting new route for targeting the Hallmarks of Cancer; in particular by limiting the impact of the enabling hallmarks of tumour promoting inflammation and cell plasticity. As BCL-3 has been reported to promote the stem-like potential of cancer cells, we suggest that targeting BCL-3 could increase the tumour response to conventional treatment, reduce the chance of relapse and hence improve the prognosis for cancer patients.

Identification of a Glucose Metabolism-related Signature for prediction of Clinical Prognosis in Clear Cell Renal Cell Carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent and invasive histological subtypes among all renal cell carcinomas (RCC). Cancer cell metabolism, particularly glucose metabolism, has been reported as a hallmark of cancer. However, the characteristics of glucose metabolism-related gene sets in ccRCC have not been systematically profiled.

Methods: In this study, we downloaded a gene expression profile and glucose metabolism-related gene set from TCGA (The Cancer Genome Altas) and MSigDB, respectively, to analyze the characteristics of glucose metabolism-related gene sets in ccRCC. We used a multivariable Cox regression analysis to develop a risk signature, which divided patients into low- and high- risk groups. In addition, a nomogram that combined the risk signature and clinical characteristics was created for predicting the 3- and 5-year overall survival (OS) of ccRCC. The accuracy of the nomogram prediction was evaluated using the area under the receiver operating characteristic curve (AUC) and a calibration plot.

Results: A total of 231 glucose metabolism-related genes were found, and 68 differentially expressed genes (DEGs) were identified. After screening by univariate regression analysis, LASSO regression analysis and multivariable Cox regression analysis, six glucose metabolism-related DEGs (FBP1, GYG2, KAT2A, LGALS1, PFKP, and RGN) were selected to develop a risk signature. There were significant differences in the clinical features (Fuhrman nuclear grade and TNM stage) between the high- and low-risk groups. The multivariable Cox regression indicated that the risk score was independent of the prognostic factors (training set: HR=3.393, 95% CI [2.025, 5.685], p<0.001; validation set: HR=1.933, 95% CI [1.130, 3.308], p=0.016). The AUCs of the nomograms for the 3-year OS in the training and validation sets were 0.808 and 0.819, respectively, and 0.777 and 0.796, respectively, for the 5- year OS.

Conclusion: We demonstrated a novel glucose metabolism-related risk signature for predicting the prognosis of ccRCC. However, additional in vitro and in vivo research is required to validate our findings.

Genomic profiling in renal cell carcinoma

The treatment landscape of metastatic renal cell carcinoma (RCC) has been revolutionized over the past two decades, bringing forth an era in which more than a dozen therapeutic agents are now available to treat patients. As a consequence, personalized care has become a critical part of developing effective treatment guidelines and improving patient outcomes. One of the most important emerging aspects of precision medicine in cancer is matching patients and treatments based on the genomic characteristics of an individual and their tumour. Despite the lack of a single genomic predictor of treatment response or prognostication feature in RCC, emerging research suggests that the identification of such markers remains promising. Mutations in VHL and alterations in its downstream pathways are the mainstay of RCC development and progression. However, the predictive value of VHL mutations has been questioned. Further research has examined mutations in genes involved in chromosome remodelling (for example, PBRM1, BAP1 and SETD2), DNA methylation and DNA damage repair, all of which have been associated with clinical outcomes. Here, we provide a comprehensive overview of genomic evidence in the context of RCC and its potential predictive and prognostic value.

Significance of PI3K signalling pathway in clear cell renal cell carcinoma in relation to VHL and HIF status

Renal cell carcinoma (RCC) includes diverse tumour types characterised by various genetic abnormalities. The genetic changes, like mutations, deletions and epigenetic alterations, play a crucial role in the modification of signalling networks, tumour pathogenesis and prognosis. The most prevalent RCC type, clear cell RCC (ccRCC), is asymptomatic in the early stages and has a poorer prognosis compared with the papillary and the chromophobe types RCCs. Generally, ccRCC is refractory to chemotherapy and radiation therapy. Loss of von Hippel-Lindau (VHL) gene and upregulation of hypoxia-inducible factors (HIF), the signature of most sporadic ccRCC, promote multiple growth factors. Hence, VHL/HIF and a variety of pathways, including phosphatase and TEnsin homolog on chromosome 10/phosphatidylinositol-3-kinase (PI3K)/AKT, are closely connected and contribute to the ontogeny of ccRCC. In the recent decade, multiple targeting agents have been developed based on blocking major signalling pathways directly or indirectly involved in ccRCC tumour progression, metastasis, angiogenesis and survival. However, most of these drugs have limitations; either metastatic ccRCC develops resistance to these agents, or despite blocking receptors, tumour cells use alternate signalling pathways. This review compiles the state of knowledge about the PI3K/AKT signalling pathway confined to ccRCC and its cross-talks with VHL/HIF pathway.

A 17-Gene Signature Predicted Prognosis in Renal Cell Carcinoma

Renal cell carcinoma (RCC), which was one of the most common malignant tumors in urinary system, had gradually increased incidence and mortality in recent years. Although significant advances had been made in molecular and biology research on the pathogenesis of RCC, effective treatments and prognostic indicators were still lacking. In order to predict the prognosis of RCC better, we identified 17 genes that were associated with the overall survival (OS) of RCC patients from The Cancer Genome Atlas (TCGA) dataset and a 17-gene signature was developed. Through SurvExpress, we analyzed the expression differences of the 17 genes and their correlation with the survival of RCC patients in five datasets (ZHAO, TCGA, KIPAN, KIRC, and KIRP), and then evaluated the survival prognostic significance of the 17-gene signature for RCC. Our results showed that the 17-gene signature had a predictive prognostic value not only in single pathologic RCC, but also in multiple pathologic types of RCC. In conclusion, the 17-gene signature model was related to the survival of RCC patients and could help predict the prognosis with significant clinical implications.

Development and validation of a metastasis-associated prognostic signature based on single-cell RNA-seq in clear cell renal cell carcinoma

Single-cell RNA sequencing (scRNA-seq) was recently adopted for deciphering intratumoral heterogeneity across cell sub-populations, including clear cell renal cell carcinoma (ccRCC). Here, we characterized the single-cell expression profiling of 121 cell samples and found 44 metastasis-associated marker genes. Accordingly, we trained and validated 17 pivotal metastasis-associated genes (MAGs) in 626 patients incorporating internal and external cohorts to evaluate the model for predicting overall survival (OS) and progression-free survival (PFS). Correlation analysis revealed that the MAGs correlated significantly with several risk clinical characteristics. Moreover, we conducted Cox regression analysis integrating these independent clinical variables into a MAGs nomogram with superior accuracy in predicting progression events. We further revealed the differential landscape of somatic tumor mutation burden (TMB) between two nomogram-score groups and observed that TMB was also a prognostic biomarker; patients with high MAGs-nomogram scores suffered from a higher TMB, potentially leading to worse prognosis. Last, higher MAGs-nomogram scores correlated with the upregulation of oxidative phosphorylation, the Wnt signaling pathway, and MAPK signaling crosstalk in ccRCC. Overall, we constructed the robust MAGs through scRNA-seq and validated the model in a large patient population, which was valuable for prognostic stratification and providing potential targets against metastatic ccRCC.

LINC00511 promotes the malignant phenotype of clear cell renal cell carcinoma by sponging microRNA-625 and thereby increasing cyclin D1 expression

The expression pattern and detailed roles of long noncoding RNA LINC00511 in clear cell renal cell carcinoma (ccRCC) remain unknown. We measured LINC00511 expression in ccRCC. We clarified the clinical characteristics associated with LINC00511 in ccRCC. We examined the biological roles of LINC00511 in the progression of ccRCC, and we identified the potential mechanisms involved. LINC00511 was upregulated in ccRCC tissues and cell lines. High LINC00511 expression significantly correlated with TNM classification, lymph node metastasis, and short overall survival among patients with ccRCC. Additionally, LINC00511 knockdown restricted ccRCC cell proliferation, colony formation, and metastasis in vitro; accelerated cell cycle arrest at G0–G1 and apoptosis in vitro; and decreased tumor growth in vivo. Investigation of the mechanism revealed that LINC00511 directly interacted with microRNA-625 (miR-625), and the inhibitory effects of the LINC00511 knockdown on malignant characteristics were neutralized by miR-625 silencing. Furthermore, cyclin D1 (CCND1) was identified as a direct target of miR-625 in ccRCC cells. The tumor-suppressive activity of miR-625 upregulation on ccRCC cells was reversed by CCND1 reintroduction. In conclusion, LINC00511 serves as a competing endogenous RNA that regulates CCND1 expression by sponging miR-625 in ccRCC. Hence, the LINC00511/miR-625/CCND1 pathway might be a promising therapeutic target in ccRCC.

Identification of CTRP1 as a Prognostic Biomarker and Oncogene in Human Glioblastoma

Introduction

Glioblastoma (GBM) is the most frequent and malignant type of primary brain tumors in adults. The valuable prognostic biomarkers and therapeutic targets for GBM remain to be elucidated. The association of adipokines with cancer has been well documented. The C1q/TNF-related protein 1 (CTRP1), a novel adipokine, belongs to the CTRP family.

Methods

In the present study, the expression and potential roles of CTRP1 in GBM were explored based on in silico evaluation, including GEPIA, the Pathology Atlas of the Human Protein Atlas, cBioPortal, TIMER, and SurvExpress. The CCK8, transwell, and wound healing assays were used to detect cell proliferation and migration.

Results

It was found that mRNA expression levels of CTRP1 were significantly upregulated in GBM tissues compared with those in nontumor tissues according to the analysis on public dataset and immunohistochemical results of GBM tissues (P<0.05). CTRP1 was mainly localized in the cytoplasm and cell membrane of GBM cells. The genetic alterations of CTRP1 occurred at a low rate in GBM (2 of 591 sequenced cases/patients, 0.33%). The mRNA expression levels of CTRP1 were positively associated with the tumor-infiltrating macrophages and CCL2 in GBM (P<0.05, respectively). The higher mRNA expression levels of CTRP1 were significantly correlated with higher risk and shorter overall survival time in GBM (P<0.05). CTRP1 knockdown significantly inhibited the proliferation and migration in human GBM cells, suggesting the inhibition of CTRP1 on human GMB progression. Moreover, CTRP1 knockdown inhibited CCL2 expression, and CCL2 overexpression reversed the inhibition of cell proliferation and migration induced by CTRP1 knockdown, suggesting that CTRP1 promoted tumor progression by regulating CCL2 expression.

Conclusions

These findings suggest that CTRP1 potentially indicates poor prognosis in GBM and promotes the progression of human GBM.

Class II PI3Ks at the Intersection between Signal Transduction and Membrane Trafficking

Phosphorylation of inositol phospholipids by the family of phosphoinositide 3-kinases (PI3Ks) is crucial in controlling membrane lipid composition and regulating a wide range of intracellular processes, which include signal transduction and vesicular trafficking. In spite of the extensive knowledge on class I PI3Ks, recent advances in the study of the three class II PI3Ks (PIK3C2A, PIK3C2B and PIK3C2G) reveal their distinct and non-overlapping cellular roles and localizations. By finely tuning membrane lipid composition in time and space among different cellular compartments, this class of enzymes controls many cellular processes, such as proliferation, survival and migration. This review focuses on the recent developments regarding the coordination of membrane trafficking and intracellular signaling of class II PI3Ks through the confined phosphorylation of inositol phospholipids.

Comprehensive assessment gene signatures for clear cell renal cell carcinoma prognosis

There are many prognostic gene signature models in clear cell renal cell carcinoma (ccRCC). However, different results from various methods and samples are hard to contribute to clinical practice. It is necessary to develop a robust gene signature for improving clinical practice in ccRCC.A method was proposed to integrate least absolute shrinkage and selection operator and multiple Cox regression to obtain mRNA and microRNA signature from the cancer genomic atlas database for predicting prognosis of ccRCC. The gene signature model consisted by 5 mRNAs and 1 microRNA was identified. Prognosis index (PI) model was constructed from RNA expression and median value of PI is used to classified patients into high- and low-risk groups.The results showed that high-risk patients showed significantly decrease survival comparison with low-risk groups [hazard ratio (HR) =7.13, 95% confidence interval = 3.71-13.70, P < .001]. As the gene signature was mainly consisted by mRNA, the validation data can use transcriptomic data to verify. For comparison of the performance with previous works, other gene signature models and 4 datasets of ccRCC were retrieved from publications and public database. For estimating PI in each model, 3 indicators including HR, concordance index , and the area under the curve of receiver operating characteristic for 3 years were calculated across 4 independent datasets.The comparison results showed that the integrative model from our study was more robust than other models via comprehensive analysis. These findings provide some genes for further study their functions and mechanisms in ccRCC tumorigenesis and malignance, and may be useful for effective clinical decision making of ccRCC patients.

BCL3 Expression Is a Potential Prognostic and Predictive Biomarker in Acute Myeloid Leukemia of FAB Subtype M2

Although the implication of BCL3 has been disclosed in human chronic lymphocytic leukemia as well as other solid tumors, the diagnostic and prognostic of BCL3 expression in acute myeloid leukemia (AML) remains largely unclear. In this study, we isolated total RNA from bone marrow mononuclear cells collected from 101 de novo AML patients and 27 healthy donors. After reverse transcription, quantitative real-time PCR was performed to detect BCL3 expression level. BCL3 mRNA level was significantly down-regulated in BMMCs of AML patients compared with healthy controls (P = 0.0015). BCL3 was showed a higher level in AML patients with poor-risk karyotypes than that of in patients with favorable/intermediate-risk karyotypes (P = 0.014). ROC analysis demonstrated that BCL3 could effectively differentiate AML patients from normal controls. Among the French-American-British (FAB) subtypes, the frequency of low BCL3 expression in M2 subtypes is significantly higher than that of in the other subtypes M1/M4/M5/M6/M7 (P = 0.006), and mildly lower in myelomonocytic/monocytic subtypes M4/M5 (P = 0.064) than those in M1/M2/M6/M7 subtypes. Chromosome analysis revealed that BCL3^low patients had a remarkably higher frequency of t (8;21) abnormality (P = 0.0047) and lower frequency of normal karyotype (P = 0.0059) than BCL3^high patients. BCL3^high patients showed a significantly higher frequency of FLT3-ITD mutation (P = 0.028) and lower frequency of C-Kit mutation (P = 0.0232) than BCL3^low patients. Although there were no significant differences in complete remission and overall survival between BCL3^low and BCL3^high groups, patients with high BCL3 expression markedly shorter overall survival (OS, P = 0.049), relapse-free survival (RFS, P = 0.027) and disease-free survival (DFS, P = 0.042) in M2 AML than low BCL3 expression patients. Additionally, in AMLs of M2 subtype, high BCL3 expression patients had markedly lower complete remission (CR) rate (P = 0.0317) after the second induction treatment than patients with BCL3 low expression. Thus, these findings indicated that BCL3 appeared as a promising molecular biomarker of pediatric acute myeloid leukemia with unfavorable prognosis.

Development Of A Three-Gene Prognostic Signature For Hepatitis B Virus Associated Hepatocellular Carcinoma Based On Integrated Transcriptomic Analysis

Integration of public genome-wide gene expression data together with Cox regression analysis is a powerful weapon to identify new prognostic gene signatures for cancer diagnosis and prognosis. Hepatitis B virus (HBV) is a major cause of hepatocellular carcinoma (HCC), however, it remains largely unknown about the specific gene prognostic signature of HBV-associated HCC. Using Robust Rank Aggreg (RRA) method to integrate seven whole genome expression datasets, we identified 82 up-regulated genes and 577 down-regulated genes in HBV-associated HCC patients. Combination of several enrichment analysis, univariate and multivariate Cox proportional hazards regression analysis, we revealed that a three-gene (SPP2, CDC37L1, and ECHDC2) prognostic signature could act as an independent prognostic indicator for HBV-associated HCC in both the discovery cohort and the internal testing cohort. Gene set enrichment analysis showed that the high-risk group with lower expression levels of the three genes was enriched in bladder cancer and cell cycle pathway, whereas the low-risk group with higher expression levels of the three genes was enriched in drug metabolism-cytochrome P450, PPAR signaling pathway, fatty acid and histidine metabolisms. This indicates that patients of HBV-associated HCC with higher expression of these three genes may preserve relatively good hepatic cellular metabolism and function, which may also protect HCC patients from persistent drug toxicity in response to various medication. Our findings suggest a three-gene prognostic model that serves as a specific prognostic signature for HBV-associated HCC.

Current and Emerging Therapeutic Targets for Metastatic Renal Cell Carcinoma

PURPOSE OF REVIEW

The treatment of advanced renal cell carcinoma has evolved dramatically over recent years. In this review, we will summarize current and emerging therapies based on molecular targets and provide insight into treatment strategy for metastatic renal cell carcinoma.

RECENT FINDINGS

We have witnessed a paradigm shift in the therapeutic landscape as treatment was formerly reliant on cytokine-based agents which have now been replaced with therapies targeting angiogenesis, mammalian target of rapamycin pathways, and immune responses. These dramatic changes are primarily due to our improved understanding of the underlying mutations and molecular mechanisms leading to tumorigenesis and progression. We now have targeted agents in the form of small-molecule tyrosine kinase inhibitors, monoclonal antibodies, and mTOR inhibitors. Moreover, immunotherapy-targeting checkpoints of T-lymphocyte activity has provided increased overall survival and a new class of agents with potential to radically change the treatment options. With these agents and their combination, durable responses are increasingly seen even though treatment resistance remains a huge challenge. New treatment strategies are rapidly developing and the therapeutic landscape is expected for further evolution.

Prognostic and Predictive Factors for Renal Cell Carcinoma

Metastatic renal cell carcinoma (mRCC) is an incurable malignancy, characterized by its resistance to traditional chemotherapy, radiation, and hormonal therapy. Treatment perspectives and prognosis of patients with mRCC have been significantly improved by advances in the understanding of its molecular pathogenesis, which have led to the development of targeted therapeutics. Different molecular factors derived from the tumor or the host detected in both tissue or serum could be predictive of therapeutic benefit. Some of them suggest a rational selection of patients to be treated with certain therapies, though none have been validated for routine use. This article provides an overview of both clinical and molecular factors associated with predictive or prognostic value in mRCC and emphasizes that both should be considered in parallel to provide the most appropriate, individualized treatment and achieve the best outcomes in clinical practice.

MiR-216a exerts tumor-suppressing functions in renal cell carcinoma by targeting TLR4

MiR-216a, a tumor-related microRNA (miRNA), has been reported to be implicated in the tumorigenesis and progression of diverse types of human malignancies; however, its role in renal cell carcinoma (RCC) remains unclear. This study aimed to explore the biological role of miR-216a in RCC and clarify the potential mechanisms involved. In the present study, miR-216a was found to be significantly down-regulated in both RCC tissues and cell lines. Functional studies demonstrated that enhanced expression of miR-216a suppressed RCC cell proliferation, migration and invasion in vitro, inhibited tumor growth in vivo, and induced RCC cell cycle arrest and apoptosis. Moreover, the tumor-suppressing effects of miR-216a in RCC were abrogated by the miR-216a inhibitor treatment. Notably, toll-like receptor 4 (TLR4) was downregulated by miR-216a via direct binding to its 3' untranslated region in RCC cells. Furthermore, TLR4 expression was discovered to be markedly up-regulated and inversely correlated with miR-216a expression in RCC tissues. Mechanistic studies revealed that restoring the expression of TLR-4 alleviated miR-216a-induced inhibitory effects on proliferation, migration and invasion of RCC cells. Taken together, these findings suggest that miR-216a functions as a tumor suppressor in RCC by directly targeting TLR4 and that miR-216a might be a novel therapeutic target for RCC.

Measuring deaminated nucleotide surveillance enzyme ITPA activity with an ATP-releasing nucleotide chimera

Nucleotide quality surveillance enzymes play important roles in human health, by detecting damaged molecules in the nucleotide pool and deactivating them before they are incorporated into chromosomal DNA or adversely affect metabolism. In particular, deamination of adenine moiety in (deoxy)nucleoside triphosphates, resulting in formation of (d)ITP, can be deleterious, leading to DNA damage, mutagenesis and other harmful cellular effects. The 21.5 kDa human enzyme that mitigates this damage by conversion of (d)ITP to monophosphate, ITPA, has been proposed as a possible therapeutic and diagnostic target for multiple diseases. Measuring the activity of this enzyme is useful both in basic research and in clinical applications involving this pathway, but current methods are nonselective and are not applicable to measurement of the enzyme from cells or tissues. Here, we describe the design and synthesis of an ITPA-specific chimeric dinucleotide (DIAL) that replaces the pyrophosphate leaving group of the native substrate with adenosine triphosphate, enabling sensitive detection via luciferase luminescence signaling. The probe is shown to function sensitively and selectively to quantify enzyme activity in vitro, and can be used to measure the activity of ITPA in bacterial, yeast and human cell lysates.

Treatment of renal cell carcinoma: Current status and future directions

Answer questions and earn CME/CNE Over the past 12 years, medical treatment for renal cell carcinoma (RCC) has transitioned from a nonspecific immune approach (in the cytokine era), to targeted therapy against vascular endothelial growth factor (VEGF), and now to novel immunotherapy agents. Multiple agents-including molecules against vascular endothelial growth factor, platelet-derived growth factor, and related receptors; inhibitors of other targets, such as the mammalian target of rapamycin and the MET and AXL tyrosine-protein kinase receptors; and an immune-checkpoint inhibitor-have been approved based on significant activity in patients with advanced RCC. Despite these advances, important questions remain regarding biomarkers of efficacy, patient selection, and the optimal combination and sequencing of agents. The purpose of this review is to summarize present management and future directions in the treatment of metastatic RCC. CA Cancer J Clin 2017;67:507-524. © 2017 American Cancer Society.

PI3K Signaling in Tissue Hyper-Proliferation: From Overgrowth Syndromes to Kidney Cysts

The members of the PhosphoInositide-3 Kinase (PI3K) protein family are well-known regulators of proliferative signals. By the generation of lipid second messengers, they mediate the activation of AKT/PKB (AKT) and mammalian Target Of Rapamycin (mTOR) pathways. Although mutations in the PI3K/AKT/mTOR pathway are highly characterized in cancer, recent evidence indicates that alterations in the proliferative signals are major drivers of other diseases such as overgrowth disorders and polycystic kidney disease. In this review, we briefly summarize the role of the PI3K/AKT/mTOR pathway in cell proliferation by comparing the effect of alterations in PI3K enzymes in different tissues. In particular, we discuss the most recent findings on how the same pathway may lead to different biological effects, due to the convergence and cooperation of different signaling cascades.