A systematic review of predictive and prognostic biomarkers for VEGF-targeted therapy in renal cell carcinoma

Personalized treatment using predictive biomarkers in solid organ malignancies: A review

In recent years, the influence of specific biomarkers in the diagnosis and prognosis of solid organ malignancies has been increasingly prominent. The relevance of the use of predictive biomarkers, which predict cancer response to specific forms of treatment provided, is playing a more significant role than ever before, as it affects diagnosis and initiation of treatment, monitoring for efficacy and side effects of treatment, and adjustment in treatment regimen in the long term. In the current review, we explored the use of predictive biomarkers in the treatment of solid organ malignancies, including common cancers such as colorectal cancer, breast cancer, lung cancer, prostate cancer, and cancers associated with high mortalities, such as pancreatic cancer, liver cancer, kidney cancer and cancers of the central nervous system. We additionally analyzed the goals and types of personalized treatment using predictive biomarkers, and the management of various types of solid organ malignancies using predictive biomarkers and their relative efficacies so far in the clinical settings.

Overexpression of Osteopontin-a and Osteopontin-c Splice Variants Are Worse Prognostic Features in Colorectal Cancer

Background: Osteopontin (OPN) is a glycoprotein involved in various physiological and pathological processes, and its aberrant expression in cancer cells is closely linked to tumor progression. In colorectal cancer (CRC), OPN is overexpressed, but the roles of its splice variants (OPN-SVs), OPNa, OPNb, and OPNc, are not well understood. This study aimed to characterize the expression patterns of OPN-SVs and their potential diagnostic and prognostic implications in CRC using transcriptomic data deposited in TSVdb and TCGA. Methods: The expression patterns of each OPN-SV were analyzed using transcriptomic data deposited in TSVdb and TCGA, which were correlated to patient data available at cBioPortal. Results: Bioinformatic analysis revealed that OPNa, OPNb, and OPNc are overexpressed in CRC samples compared to non-tumor samples. Notably, OPNa and OPNc are overexpressed in CRC stages (II, III, and IV) compared to stage I. Higher levels of OPNa and OPNc transcripts are associated with worse overall survival (OS) and shorter progression-free survival (PFS) in CRC patients. Additionally, the expression of OPNa, OPNb, and OPNc is correlated with BRAFV600E mutations in CRC samples. Conclusions: These findings suggest that OPNa and OPNc, in particular, have potential as diagnostic and prognostic biomarkers, paving the way for their further evaluation in CRC diagnosis and prognosis.

Osteopontin: A Key Multifaceted Regulator in Tumor Progression and Immunomodulation

The tumor microenvironment (TME) is composed of various cellular components such as tumor cells, stromal cells including fibroblasts, adipocytes, mast cells, lymphatic vascular cells and infiltrating immune cells, macrophages, dendritic cells and lymphocytes. The intricate interplay between these cells influences tumor growth, metastasis and therapy failure. Significant advancements in breast cancer therapy have resulted in a substantial decrease in mortality. However, existing cancer treatments frequently result in toxicity and nonspecific side effects. Therefore, improving targeted drug delivery and increasing the efficacy of drugs is crucial for enhancing treatment outcome and reducing the burden of toxicity. In this review, we have provided an overview of how tumor and stroma-derived osteopontin (OPN) plays a key role in regulating the oncogenic potential of various cancers including breast. Next, we dissected the signaling network by which OPN regulates tumor progression through interaction with selective integrins and CD44 receptors. This review addresses the latest advancements in the roles of splice variants of OPN in cancer progression and OPN-mediated tumor-stromal interaction, EMT, CSC enhancement, immunomodulation, metastasis, chemoresistance and metabolic reprogramming, and further suggests that OPN might be a potential therapeutic target and prognostic biomarker for the evolving landscape of cancer management.

Gold nanostructure-enhanced immunosensing: ultra-sensitive detection of VEGF tumor marker for early disease diagnosis

We present an advanced electrochemical immunosensor designed to detect the vascular endothelial growth factor (VEGF) precisely. The sensor is constructed on a modified porous gold electrode through a fabrication process involving the deposition of silver and gold on an FTO substrate. Employing thermal annealing and a de-alloying process, the silver is eliminated from the electrode, producing a reproducible porous gold substrate. Utilizing a well-defined protocol, we immobilize the heavy-chain (VHH) antibody against VEGF on the gold substrate, facilitating VEGF detection through various electrochemical methods. Remarkably, this immunosensor performs well, featuring an impressive detection limit of 0.05 pg/mL and an extensive linear range from 0.1 pg/mL to 0.1 µg/mL. This emphasizes it's to measure biomarkers across a wide concentration spectrum precisely. The robust fabrication methodology in this research underscores its potential for widespread application, offering enhanced precision, reproducibility, and remarkable detection capabilities for the developed immunosensor.

Integrative analysis and risk model construction for super‑enhancer‑related immune genes in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer associated with poor prognosis, and accounts for the majority of RCC-related deaths. The lack of comprehensive diagnostic and prognostic biomarkers has limited further understanding of the pathophysiology of ccRCC. Super-enhancers (SEs) are congregated enhancer clusters that have a key role in tumor processes such as epithelial-mesenchymal transition, metabolic reprogramming, immune escape and resistance to apoptosis. RCC may also be immunogenic and sensitive to immunotherapy. In the present study, an Arraystar human SE-long non-coding RNA (lncRNA) microarray was first employed to profile the differentially expressed SE-lncRNAs and mRNAs in 5 paired ccRCC and peritumoral tissues and to identify SE-related genes. The overlap of these genes with immune genes was then determined to identify SE-related immune genes. A model for predicting clinical prognosis and response to immunotherapy was built following the comprehensive analysis of a ccRCC gene expression dataset from The Cancer Genome Atlas (TCGA) database. The patients from TCGA were divided into high- and low-risk groups based on the median score derived from the risk model, and the Kaplan-Meier survival analysis showed that the low-risk group had a higher survival probability. In addition, according to the receiver operating characteristic curve analysis, the risk model had more advantages than other clinical factors in predicting the overall survival (OS) rate of patients with ccRCC. Using this model, it was demonstrated that the high-risk group had a more robust immune response. Furthermore, 61 potential drugs with half-maximal inhibitory concentration values that differed significantly between the two patient groups were screened to investigate potential drug treatment of ccRCC. In summary, the present study provided a novel index for predicting the survival probability of patients with ccRCC and may provide some insights into the mechanisms through which SE-related immune genes influence the diagnosis, prognosis and potential treatment drugs of ccRCC.

Osteopontin in cancer

Osteopontin (OPN) is a heavily post-translationally modified protein with a molecular weight of 44-70 kDa, depending on the degree of glycosylation. OPN is involved in various biological processes, including bone remodeling, immune response, cell adhesion, migration, and survival. It is essential for controlling osteoclast and osteoblast activity for maintaining bone mass and bone strength. Additionally, OPN has been linked to cardiovascular, inflammatory illnesses, as well as the onset and progression of cancer. OPN is a multifunctional protein that can interact with a variety of cell surface receptors, such as integrins, CD44, the urokinase-type plasminogen activator receptor (uPAR), as well as extracellular matrix (ECM) components (e.g. collagen and hydroxyapatite). These interactions contribute to its wide range of biological functions in general and has significant implications for bone biology, immunology and cancer, specifically. In this chapter, we summarize the structure of OPN with a focus on its molecular mechanisms of action in various cancers.

Development and validation of a kidney renal clear cell carcinoma prognostic model relying on pyroptosis-related LncRNAs-A multidimensional comprehensive bioinformatics exploration

BACKGROUND

Renal cell carcinoma (RCC) is a malignant tumour that may develop in the kidney. RCC is one of the most common kinds of tumours of this sort, and its most common pathological subtype is kidney renal clear cell carcinoma (KIRC). However, the aetiology and pathogenesis of RCC still need to be clarified. Exploring the internal mechanism of RCC contributes to diagnosing and treating this disease. Pyroptosis is a critical process related to cell death. Recent research has shown that pyroptosis is a critical factor in the initiation and progression of tumour formation. Thus far, researchers have progressively uncovered evidence of the regulatory influence that long noncoding RNAs (lncRNAs) have on pyroptosis.

METHODS

In this work, a comprehensive bioinformatics approach was used to produce a predictive model according to pyroptosis-interrelated lncRNAs for the purpose of predicting the overall survival and molecular immune specialties of patients diagnosed with KIRC. This model was verified from multiple perspectives.

RESULTS

First, we discovered pyroptosis-associated lncRNAs in KIRC patients using the TCGA database and a Sankey diagram. Then, we developed and validated a KIRC patient risk model based on pyroptosis-related lncRNAs. We demonstrated the grouping power of PLnRM through PCA and used PLnRM to assess the tumour immune microenvironment and response to immunotherapy. Immunological and molecular traits of diverse PLnRM subgroups were evaluated, as were clinical KIRC patient characteristics and predictive risk models. On this basis, a predictive nomogram was developed and analyzed, and novel PLnRM candidate compounds were identified. Finally, we investigated possible medications used by KIRC patients.

CONCLUSIONS

The results demonstrate that the model generated has significant value for KIRC in clinical practice.

Artificial Intelligence in Renal Cell Carcinoma Histopathology: Current Applications and Future Perspectives

Renal cell carcinoma (RCC) is characterized by its diverse histopathological features, which pose possible challenges to accurate diagnosis and prognosis. A comprehensive literature review was conducted to explore recent advancements in the field of artificial intelligence (AI) in RCC pathology. The aim of this paper is to assess whether these advancements hold promise in improving the precision, efficiency, and objectivity of histopathological analysis for RCC, while also reducing costs and interobserver variability and potentially alleviating the labor and time burden experienced by pathologists. The reviewed AI-powered approaches demonstrate effective identification and classification abilities regarding several histopathological features associated with RCC, facilitating accurate diagnosis, grading, and prognosis prediction and enabling precise and reliable assessments. Nevertheless, implementing AI in renal cell carcinoma generates challenges concerning standardization, generalizability, benchmarking performance, and integration of data into clinical workflows. Developing methodologies that enable pathologists to interpret AI decisions accurately is imperative. Moreover, establishing more robust and standardized validation workflows is crucial to instill confidence in AI-powered systems' outcomes. These efforts are vital for advancing current state-of-the-art practices and enhancing patient care in the future.

Sunitinib resistance in renal cell carcinoma: From molecular mechanisms to predictive biomarkers

Currently, renal cell carcinoma (RCC) is the most prevalent type of kidney cancer. Targeted therapy has replaced radiation therapy and chemotherapy as the main treatment option for RCC due to the lack of significant efficacy with these conventional therapeutic regimens. Sunitinib, a drug used to treat gastrointestinal tumors and renal cell carcinoma, inhibits the tyrosine kinase activity of a number of receptor tyrosine kinases, including vascular endothelial growth factor receptor (VEGFR), platelet-derived growth factor receptor (PDGFR), c-Kit, rearranged during transfection (RET) and fms-related receptor tyrosine kinase 3 (Flt3). Although sunitinib has been shown to be efficacious in the treatment of patients with advanced RCC, a significant number of patients have primary resistance to sunitinib or acquired drug resistance within the 6-15 months of therapy. Thus, in order to develop more efficacious and long-lasting treatment strategies for patients with advanced RCC, it will be crucial to ascertain how to overcome sunitinib resistance that is produced by various drug resistance mechanisms. In this review, we discuss: 1) molecular mechanisms of sunitinib resistance; 2) strategies to overcome sunitinib resistance and 3) potential predictive biomarkers of sunitinib resistance.

Exploration of the role of Cuproptosis genes and their related long non-coding RNA in clear cell renal cell carcinoma: a comprehensive bioinformatics study

Clear cell renal cell carcinoma is a common malignant tumor of the urinary system. The mechanism of its occurrence and development is unknown, and there is currently few effective comprehensive predictive markers for prognosis and treatment response. With the discovery of a new cell death process - cuproptosis drew the attention of researchers. We constructed a model for the prediction of clinical prognosis and immunotherapy response through integrative analysis of gene expression datasets from KIRC samples in The Cancer Genome Atlas (TCGA) database. During the course of the study, we found that cuproptosis genes are significantly differentially expressed between clear cell renal cell carcinoma samples and normal samples. Based on this, we put forward the prognostic model for cuproptosis gene related-long non-coding RNA. And through various statistic and external independent cohorts, we proved that the model is accurate and stable, worthy of clinical application and further exploration and validation.

Targeting FGL2 in glioma immunosuppression and malignant progression

Glioblastoma (GBM) is the most malignant type of glioma with the worst prognosis. Traditional therapies (surgery combined with radiotherapy and chemotherapy) have limited therapeutic effects. As a novel therapy emerging in recent years, immunotherapy is increasingly used in glioblastoma (GBM), so we expect to discover more effective immune targets. FGL2, a member of the thrombospondin family, plays an essential role in regulating the activity of immune cells and tumor cells in GBM. Elucidating the role of FGL2 in GBM can help improve immunotherapy efficacy and design treatment protocols. This review discusses the immunosuppressive role of FGL2 in the GBM tumor microenvironment and its ability to promote malignant tumor progression while considering FGL2-targeted therapeutic strategies. Also, we summarize the molecular mechanisms of FGL2 expression on various immune cell types and discuss the possibility of FGL2 and its related mechanisms as new GBM immunotherapy.

Construction of a Prognostic Model for KIRC and Identification of Drugs Sensitive to Therapies - A Comprehensive Biological Analysis Based on m6A-Related LncRNAs

As one of the common malignancies in the urinary system, kidney cancer has been receiving explorations with respect to its pathogenesis, treatment and prognosis due to its high morbidity, high mortality and low drug efficiency. Such epigenetic modifications for RNA molecules as N6-methyladenosine (m6A) usher in another perspective for the research on tumor mechanisms, and an increasing number of biological processes and prognostic markers have been revealed. In this study, the transcriptome data, clinical data and mutation spectrum data of KIRC in the TCGA database were adopted to construct an m6A-related lncRNA prognostic model. Besides, the predictive ability of this model for clinical prognosis was evaluated, and some compounds sensitive to therapies for KIRC were screened. The findings of this study demonstrate that this effective and stable model has certain clinical application value.

System analysis of VEGFA in renal cell carcinoma: The expression, prognosis, gene regulation network and regulation targets

BACKGROUND

VEGFA is one of the most important regulators of angiogenesis and plays a crucial role in cancer angiogenesis and progression. Recent studies have highlighted a relationship between VEGFA expression and renal cell carcinoma occurrence. However, the expression level, gene regulation network, prognostic value, and target prediction of VEGFA in renal cell carcinoma remain unclear. Therefore, system analysis of the expression, gene regulation network, prognostic value, and target prediction of VEGFA in patients with renal cell carcinoma is of great theoretical significance as there is a clinical demand for the discovery of new renal cell carcinoma treatment targets and strategies to further improve renal cell carcinoma treatment efficacy.

METHODS

This study used multiple free online databases, including cBioPortal, TRRUST, GeneMANIA, GEPIA, Metascape, UALCAN, LinkedOmics, Metascape, and TIMER for the abovementioned analysis.

RESULTS

VEGFA was upregulated in patients with kidney renal clear cell carcinoma (KIRC) and kidney chromophobe (KICH), and downregulated in patients with kidney renal papillary cell carcinoma (KIRP). Moreover, genetic alterations of VEGFA were found in patients with renal cell carcinoma as follows: 4% (KIRC), 8% (KICH), and 4% (KIRP). The promoter methylation of VEGFA was lower and higher in patients with clinical stages of KIRC and stage 1 KIRP, respectively. VEGFA expression significantly correlated with KIRC and KIRP pathological stages. Furthermore, patients with KICH and KIRP having low VEGFA expression levels had a longer survival than those having high VEGFA expression levels. VEGFA and its neighboring genes functioned in the regulation of protein methylation and glycosylation, as well as muscle fiber growth and differentiation in patients with renal cell carcinoma. Gene Ontology enrichment analysis revealed that the functions of VEGFA and its neighboring genes in patients with renal cell carcinoma are mainly related to cell adhesion molecule binding, catalytic activity, acting on RNA, ATPase activity, actin filament binding, protease binding, transcription coactivator activity, cysteine-type peptidase activity, and calmodulin binding. Transcription factor targets of VEGFA and its neighboring genes in patients with renal cell carcinoma were found: HIF1A, TFAP2A, and ESR1 in KIRC; STAT3, NFKB1, and HIPK2 in KICH; and FOXO3, TFAP2A, and ETS1 in KIRP. We further explored the VEGFA-associated kinase (ATM in KICH as well as CDK1 and AURKB in KIRP) and VEGFA-associated microRNA (miRNA) targets (MIR-21 in KICH as well as MIR-213, MIR-383, and MIR-492 in KIRP). Furthermore, the following genes had the strongest correlation with VEGFA expression in patients with renal cell carcinoma: NOTCH4, GPR4, and TRIB2 in KIRC; CKMT2, RRAGD, and PPARGC1A in KICH; and FLT1, C6orf223, and ESM1 in KIRP. VEGFA expression in patients with renal cell carcinoma was positively associated with immune cell infiltration, including CD8+T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells.

CONCLUSIONS

This study revealed VEGFA expression and potential gene regulatory network in patients with renal cell carcinoma, thereby laying a foundation for further research on the role of VEGFA in renal cell carcinoma occurrence. Moreover, the study provides new renal cell carcinoma therapeutic targets and prognostic biomarkers as a reference for fundamental and clinical research.

Expression of BAG1 is associated with prognosis in kidney renal clear cell carcinoma based on bioinformatics

Background

BCL2 associated Athano-Gene 1 (BAG1) has been described to be involved in the development and progression of cancer. But the role of BAG1 in kidney renal clear cell carcinoma (KIRC) has remained largely unknown.

Methods

We performed bioinformatic analysis of data from TCGA and GEO dataset. The role of BAG1 in KIRC was explored by Logistic and Cox regression model. The molecular mechanisms of BAG1 was revealed by GSEA.

Results

The current study found that the KIRC tumor samples have a low level of BAG1 mRNA expression compared to the matched normal tissues based on TCGA data and GEO databases. Low expression of BAG1 in KIRC was significantly associated with Sex, clinical pathological stage, tumor-node-metastasis (TNM) stage, hemoglobin levels, cancer status and history of neoadjuvant treatment. Kaplan-Meier survival analysis indicated that KIRC patients with BAG1 high expression have a longer survival time than those with BAG1 low expression (p < 0.000). Cox regression analysis showed that BAG1 remained independently associated with overall survival, with a hazard ratio (HR) of 1.75(CI:1.05–2.90; p = 0.029). GSEA indicated that the signaling pathways including fatty acid metabolism and oxidative phosphorylation were differentially enriched in high BAG1 expression phenotype.

Conclusions

These findings suggested that BAG1 expression may act as a potential favorable prognostic marker and challenging therapeutic target.

Expression of vascular endothelial growth factor C in renal cell carcinoma and its correlation with pathological parameters and prognosis

BACKGROUND

Renal cell carcinoma (RCC) is a common malignant tumor of the urinary system. This study aimed to analyze the expression of vascular endothelial growth factor C (VEGF-C) in RCC and its relationship with pathological parameters and prognosis.

METHODS

The clinical data of 68 patients who underwent surgical treatment and confirmed to be RCC by pathology from February 2012 to January 2014 were collected. The specimens of carcinoma tissues of the 68 patients were collected, among which 20 patients were collected from normal tissue specimens adjacent to the cancer more than 5 cm away from the tumor as controls. The VEGF-C expression level was detected by immunohistochemistry, and the relationship between VEGF-C expression and clinical pathological parameters and prognosis of RCC was analyzed.

RESULTS

The positive expression rate of VEGF-C in cancer tissues of RCC patients was significantly higher than the adjacent tissues (85.29% vs. 15.00%) (P<0.05). The positive expression rate of VEGF-C in cancer tissues of RCC patients with low-to- moderate differentiation, stage III-IV, and lymph node metastasis was higher than that of RCC patients with high differentiation, stage I-II, and no lymph node metastasis (P<0.05). The survival rates of RCC patients at 1-, 3- and 5-year follow-up were 82.35% (56/68), 54.41% (37/68), and 32.35% (22/68), and the survival time of patients with positive VEGF-C expression was shorter than patients with negative expression (P<0.05). There was no significant difference in the 5-year survival rate among RCC patients according to sex or presence of muscular infiltration (P>0.05). Meanwhile, the 5-year survival rate was higher in patients with tumor diameter <5 cm, high differentiation, stage I-II, no lymph node metastasis, VEGF-C-negative expression, and aged <55 years old (P<0.05). The Cox regression model analysis showed that differentiation degree, clinical stage, lymph node metastasis, and VEGF-C expression were all independent risk factors affecting the prognosis of RCC patients (P<0.05).

CONCLUSIONS

VEGF-C is highly expressed in cancer tissues of RCC patients, and is related to clinical stage, pathological differentiation, and lymph node metastasis, which maybe an effective factor of prognosis prediction.

Overexpression of SNHG12 regulates the viability and invasion of renal cell carcinoma cells through modulation of HIF1α

Background

Cumulative evidences demonstrated the aberrant overexpression of Small Nucleolar RNA Host Gene 12 (SNHG12) in diverse human cancer. However, the expression status and involvement of SNHG12 in renal cell carcinoma is still elusive.

Methods

The expression of SNHG12 was determined by q-PCR. The transcriptional regulation was interrogated by luciferase reporter assay. Cell viability was measured with CCK-8 kit. The anchorage-independent was evaluated by soft agar assay. Cell apoptosis was analyzed by Annexin V/7-AAD double staining. The migration and invasion were determined by trans-well assay and wound scratch closure. The in vivo tumor growth was monitored in xenograft mice model. Protein expression was quantified by immunoblotting.

Results

SNHG12 was aberrantly up-regulated in renal carcinoma both in vivo and in vitro. High expression of SNHG12 associated with poor prognosis. Deficiency of SNHG12 significantly suppressed cell viability, anchorage-independent growth and induced apoptosis. In addition, SNHG12 silencing inhibited migrative and invasive in vitro and xenograft tumor growth in vivo. Mechanistically, SNHG12 modulated HIF1α expression via competing with miR-199a-5p, which consequently contributed to its oncogenic potential. MiR-199a-5p inhibition severely compromised SNHG12 silencing-elicited tumor repressive effects.

Conclusion

Our data uncovered a crucial role of SNHG12-miR-199a-5p-HIF1α axis in human renal cancer.

The role of osteopontin in kidney diseases

BACKGROUND

Osteopontin (OPN) is a pleiotropic glycoprotein expressed in various cell types in animals and in humans, including bone, immune, smooth muscle, epithelial and endothelial cells. Moreover, OPN is found in kidneys (in the thick ascending limbs of the loop of Henle and in distal nephrons) and urine. The protein plays an important role in mineralization and bone resorption. In addition, OPN is involved in the regulation of immunity and inflammation, angiogenesis and apoptosis. It was demonstrated that OPN and some OPN gene polymorphic variants are associated with the pathogenesis and progression of multiple disorders, such as cancer, autoimmune, neurodegenerative and cardiovascular diseases. Moreover, recent studies suggested that OPN is associated with the pathogenesis of renal failure.

METHODS

In this review, I briefly discussed the role of OPN and its gene polymorphisms in kidney physiology, as well as in various kidney diseases.

FINDINGS AND CONCLUSION

Most studies reported that OPN expression is elevated in urolithiasis, and also in acute and chronic kidney diseases, and in renal allograft dysfunction. Moreover, it was demonstrated that polymorphic variants of the OPN gene may be associated with renal failure. However, some reports suggested that OPN is essential for tubulogenesis, and that it inhibits calcium oxalate crystal formation and retention, nitric oxide synthesis, cell apoptosis and promotes cell regeneration. Thus, further studies are required to fully understand the role of OPN in kidney physiology and pathology. Eventually, these studies may result in the identification of OPN as a valuable marker for renal dysfunction prognosis and treatment.

Patient derived renal cell carcinoma xenografts exhibit distinct sensitivity patterns in response to antiangiogenic therapy and constitute a suitable tool for biomarker development

Systemic treatment is necessary for one third of patients with renal cell carcinoma. No valid biomarker is currently available to tailor personalized therapy. In this study we established a representative panel of patient derived xenograft (PDX) mouse models from patients with renal cell carcinomas and determined serum levels of high mobility group B1 (HMGB1) protein under treatment with sunitinib, pazopanib, sorafenib, axitinib, temsirolimus and bevacizumab. Serum HMGB1 levels were significantly higher in a subset of the PDX collection, which exhibited slower tumor growth during subsequent passages than tumors with low HMGB1 serum levels. Pre-treatment PDX serum HMGB1 levels also correlated with response to systemic treatment: PDX models with high HMGB1 levels predicted response to bevacizumab. Taken together, we provide for the first time evidence that the damage associated molecular pattern biomarker HMGB1 can predict response to systemic treatment with bevacizumab. Our data support the future evaluation of HMGB1 as a predictive biomarker for bevacizumab sensitivity in patients with renal cell carcinoma.

Pretreatment neutrophil-to-lymphocyte ratio is associated with outcome of advanced-stage cancer patients treated with immunotherapy: a meta-analysis

BACKGROUND

To investigate the association between pretreatment blood neutrophil-to-lymphocyte ratio (NLR) and clinical outcomes for advanced-stage cancer patients treated with immunotherapy.

METHODS

We conducted a comprehensive literature search to assess the relationship between pretreatment blood NLR and overall survival (OS) or progression-free survival (PFS) in advanced-stage cancer patients treated with immunotherapy. Published data including hazard ratios (HRs) and related 95% confidence interval (CI) were extracted. Pooled estimates of treatment outcomes were calculated using RevMan 5.3.5.

RESULTS

Twenty-seven studies with 4647 patients were included in the current study. The pooled results suggested that high pretreatment blood NLR was correlated with significant shorter OS (HR = 1.98, 95% CI 1.66-2.36, P < 0.001) and PFS (HR = 1.78, 95% CI 1.48-2.15, P < 0.001). Subgroup analysis stratified by study targets revealed that anti-VEGF/VEGFR therapy (HR = 2.04, 95% CI 1.61-2.60, P < 0.001) and immune checkpoints blockade (HR = 2.16, 95% CI 1.86-2.51, P < 0.001) were significantly associated with inferior OS while other targets (HR = 1.63, 95% CI 0.89-2.99, P = 0.120) were not associated with OS. There was no correlation between distinct NLR cutoff values and OS ([Formula: see text] = 0.218, P = 0.329) or PFS benefit ([Formula: see text] = - 0.386, P = 0.140). Of note, HRs of PFS showed significant correlation with HRs of OS ([Formula: see text] = 0.656, P = 0.015).

CONCLUSION

Elevated pretreatment blood NLR was a promising prognostic and predictive biomarker for advanced-stage cancer patients treated with immunotherapy.

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.

Crosstalk between VEGFR and other receptor tyrosine kinases for TKI therapy of metastatic renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC), and is frequently accompanied by the genetic features of von Hippel–Lindau (VHL) loss. VHL loss increases the expression of hypoxia-inducible factors (HIFs) and their targets, including epidermal growth factor (EGF), vascular endothelial growth factor (VEGF), and platelet-derived growth factor (PDGF). The primary treatment for metastatic RCC (mRCC) is molecular-targeted therapy, especially anti-angiogenic therapy. VEGF monoclonal antibodies and VEGF receptor (VEGFR) tyrosine kinase inhibitors (TKIs) are the main drugs used in anti-angiogenic therapy. However, crosstalk between VEGFR and other tyrosine kinase or downstream pathways produce resistance to TKI treatment, and the multi-target inhibitors, HIF inhibitors or combination strategies are promising strategies for mRCC. HIFs are upstream of the crosstalk between the growth factors, and these factors may regulate the expression of VEGR, EGF, PDGF and other growth factors. The frequent VHL loss in ccRCC increases HIF expression, and HIFs may be an ideal candidate to overcome the TKI resistance. The combination of HIF inhibitors and immune checkpoint inhibitors is also anticipated. Various clinical trials of programmed cell death protein 1 inhibitors are planned. The present study reviews the effects of current and potential TKIs on mRCC, with a focus on VEGF/VEGFR and other targets for mRCC therapy.

The role of osteopontin in the progression of solid organ tumour

Osteopontin (OPN) is a bone sialoprotein involved in osteoclast attachment to mineralised bone matrix, as well as being a bone matrix protein, OPN is also a versatile protein that acts on various receptors which are associated with different signalling pathways implicated in cancer. OPN mediates various biological events involving the immune system and the vascular system; the protein plays a role in processes such as immune response, cell adhesion and migration, and tumorigenesis. This review discusses the potential role of OPN in tumour cell proliferation, angiogenesis and metastasis, as well as the molecular mechanisms involved in these processes in different cancers, including brain, lung, kidney, liver, bladder, breast, oesophageal, gastric, colon, pancreatic, prostate and ovarian cancers. The understanding of OPN’s role in tumour development and progression could potentially influence cancer therapy and contribute to the development of novel anti-tumour treatments.

Differentiation of renal cell carcinoma subtypes with different iodine quantification methods using single-phase contrast-enhanced dual-energy CT: areal vs. volumetric analyses

PURPOSE

To investigate the possibility of iodine quantification during a single nephrographic phase in characterizing renal cell carcinoma (RCC) subtypes and if there is a difference between areal and volumetric iodine quantification methods.

MATERIALS AND METHODS

This retrospective study included 110 patients with 113 histopathologically confirmed RCCs scanned by dual-energy CT at the nephrographic phase before surgeries. For each lesion, an areal measurement of the iodine concentration with maximum enhancement (I _{max enhan}) and the iodine concentration with maximum area among slices (I _{max area}), as well as a volumetric iodine concentration of the whole-tumor (I _volume), were evaluated by two independent radiologists. The diagnostic performances in a single nephrographic phase for characterizing RCC subtypes were evaluated, and three iodine quantification methods were compared with each other.

RESULTS

There were significant differences (clear cell vs. papillary and clear cell vs. chromophobe RCC) and no significant differences (papillary vs. chromophobe RCC) at the nephrographic phase in all three methods. The area under the receiver operating characteristic (ROC) curve (AUC) derived from the I _{max enhan} for discriminating clear cell from papillary RCC was significantly higher than that derived from the I _{max area} (P = 0.0357) and the I _volume (P = 0.0206), and no significant differences existed among the three methods in distinguishing clear cell RCC from chromophobe RCC. The reliability of all three parameters was very high with an interclass correlation coefficient (ICC) exceeding 0.8.

CONCLUSIONS

Iodine quantification in a single nephrographic phase can be used to differentiate RCC subtypes preoperatively, and the areal maximum enhancement iodine quantification would probably be the most appropriate approach.

Tumour vasculature immaturity, oxidative damage and systemic inflammation stratify survival of colorectal cancer patients on bevacizumab treatment

Despite treatment of patients with metastatic colorectal cancer (mCRC) with bevacizumab plus chemotherapy, response rates are modest and there are no biomarkers available that will predict response. The aim of this study was to assess if markers associated with three interconnected cancer-associated biological processes, specifically angiogenesis, inflammation and oxidative damage, could stratify the survival outcome of this cohort. Levels of angiogenesis, inflammation and oxidative damage markers were assessed in pre-bevacizumab resected tumour and serum samples of mCRC patients by dual immunofluorescence, immunohistochemistry and ELISA. This study identified that specific markers of angiogenesis, inflammation and oxidative damage stratify survival of patients on this anti-angiogenic treatment. Biomarkers of immature tumour vasculature (% IMM, p=0.026, n=80), high levels of oxidative damage in the tumour epithelium (intensity of 8-oxo-dG in nuclear and cytoplasmic compartments, p=0.042 and 0.038 respectively, n=75) and lower systemic pro-inflammatory cytokines (IL6 and IL8, p=0.053 and 0.049 respectively, n=61) significantly stratify with median overall survival (OS). In summary, screening for a panel of biomarkers for high levels of immature tumour vasculature, high levels of oxidative DNA damage and low levels of systemic pro-inflammatory cytokines may be beneficial in predicting enhanced survival outcome following bevacizumab treatment for mCRC.

The kidney cancer research priority-setting partnership: Identifying the top 10 research priorities as defined by patients, caregivers, and expert clinicians

It is critically important to define disease-specific research priorities to better allocate limited resources. There is growing recognition of the value of involving patients and caregivers, as well as expert clinicians in this process. To our knowledge, this has not been done this way for kidney cancer. Using the transparent and inclusive process established by the James Lind Alliance, the Kidney Cancer Research Network of Canada (KCRNC) sponsored a collaborative consensus-based priority-setting partnership (PSP) to identify research priorities in the management of kidney cancer. The final result was identification of 10 research priorities for kidney cancer, which are discussed in the context of current initiatives and gaps in knowledge. This process provided a systematic and effective way to collaboratively establish research priorities with patients, caregivers, and clinicians, and provides a valuable resource for researchers and funding agencies.

Development of Response Classifier for Vascular Endothelial Growth Factor Receptor (VEGFR)-Tyrosine Kinase Inhibitor (TKI) in Metastatic Renal Cell Carcinoma

Vascular endothelial growth factor receptor (VEGFR)-targeted therapy improved the outcome of metastatic renal cell carcinoma (mRCC) patients. However, a prediction of the response to VEGFR-tyrosine kinase inhibitor (TKI) remains to be elucidated. We aimed to develop a classifier for VEGFR-TKI responsiveness in mRCC patients. Among 101 mRCC patients, ones with complete response, partial response, or ≥24 weeks stable disease in response to VEGFR-TKI treatment were defined as clinical benefit group, whereas patients with <24 weeks stable disease or progressive disease were classified as clinical non-benefit group. Clinicolaboratory-histopathological data, 41 gene mutations, 20 protein expression levels and 1733 miRNA expression levels were compared between clinical benefit and non-benefit groups. The classifier was built using support vector machine (SVM). Seventy-three patients were clinical benefit group, and 28 patients were clinical non-benefit group. Significantly different features between the groups were as follows: age, time from diagnosis to TKI initiation, thrombocytosis, tumor size, pT stage, ISUP grade, sarcomatoid change, necrosis, lymph node metastasis and expression of pAKT, PD-L1, PD-L2, FGFR2, pS6, PDGFRβ, HIF-1α, IL-8, CA9 and miR-421 (all, P < 0.05). A classifier including necrosis, sarcomatoid component and HIF-1α was built with 0.87 accuracy using SVM. When the classifier was checked against all patients, the apparent accuracy was 0.875 (95% CI, 0.782-0.938). The classifier can be presented as a simple decision tree for clinical use. We developed a VEGFR-TKI response classifier based on comprehensive inclusion of clinicolaboratory-histopathological, immunohistochemical, mutation and miRNA features that may help to guide appropriate treatment in mRCC patients.

HIF pathway and c-Myc as biomarkers for response to sunitinib in metastatic clear-cell renal cell carcinoma

BACKGROUND

Clear-cell renal cell carcinoma (ccRCC) is a heterogeneous disease with a different clinical behavior and response to targeted therapies. Differences in hypoxia-inducible factor (HIF) expression have been used to classify von Hippel-Lindau gene (VHL)-deficient ccRCC tumors. c-Myc may be driving proliferation in HIF-2α-expressing tumors in a growth factor-independent manner.

OBJECTIVE

To explore the HIF-1α, HIF-2α and c-Myc baseline expression as potential predictors of sunitinib outcome as well as the effectiveness and safety with sunitinib in patients with metastatic ccRCC in routine clinical practice.

METHODS

This was an observational and prospective study involving 10 Spanish hospitals. Formalin-fixed, paraffin-embedded primary tumor samples from metastatic ccRCC patients who received sunitinib as first-line treatment were analyzed. Association between biomarker expression and sunitinib treatment outcomes was evaluated. Kaplan-Meier method was applied to measure progression-free survival (PFS) and overall survival.

RESULTS

Eighty-one patients were included: median PFS was 10.8 months (95% CI: 7.4-13.5 months), median overall survival was 21.8 months (95% CI: 14.7-29.8 months) and objective response rate was 40.7%, with 7.4% of patients achieving a complete response. Molecular marker staining was performed in the 69 available tumor samples. Significant association with lower PFS was identified for double c-Myc/HIF-2α-positive staining tumors (median 4.3 vs 11.5 months, hazard ratio =2.64, 95% CI: 1.03-6.80, P=0.036). A trend toward a lower PFS was found in positive c-Myc tumors (median 5.9 vs 10.9 months, P=0.263). HIF-1α and HIF-2α expression levels were not associated with clinical outcome.

CONCLUSION

These preliminary results suggest that predictive subgroups might be defined based on biomarkers such as c-Myc/HIF-2α. Further validation with more patients will be needed in order to confirm it. Outcomes with sunitinib in metastatic ccRCC in daily clinical practice resemble those obtained in clinical trials.

Molecular Classification of Renal Cell Carcinoma and Its Implication in Future Clinical Practice

Renal cell carcinoma (RCC) encompasses a wide spectrum of morphologically and molecularly distinct (>10) cancer subtypes originated from the kidney epithelium. Metastatic RCC (mRCC) is lethal and refractory to conventional chemotherapeutic agents. The incorporation of targeted therapies and immune checkpoint inhibitors into the current practice of mRCC has markedly improved the median overall survival of clear cell RCC (ccRCC) patients, the most common subtype, but not rare kidney cancer (RKC or non-ccRCC, nccRCC). Varied treatment response in mRCC patients is observed, which presents clinical challenges/opportunities at the modern mRCC therapeutic landscape consisting of 12 approved drugs representing 6 different effective mechanisms. Key contributing factors include inter- and intra-RCC heterogeneity. With the advances in pan-omics technologies, we now have a better understanding of the molecular pathobiology of individual RCC subtype. Here, we attempt to classify ccRCC based on contemporary molecular features with emphasis on their respective potential significance in clinical practice.

Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib-Treated Cancer

The tyrosine kinase inhibitor sunitinib is used as first‐line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed‐dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD‐guided strategies for the individualization of anti‐angiogenic therapies.

Renal cell carcinoma: the search for a reliable biomarker

One particular challenge in the treatment of kidney tumors is the range of histologies and tumor phenotypes a renal mass can represent. A kidney tumor can range from benign (e.g., oncocytoma) to a clinically indolent malignancy (e.g., papillary type I, chromophobe) to aggressive disease [e.g., papillary type II or high-grade clear cell renal cell carcinoma (ccRCC)]. Even among various subtypes, kidney cancers are genetically diverse with variable prognoses and treatment response rates. Therefore, the key to proper treatment is the differentiation of these subtypes. Currently, a wide array of diagnostic, prognostic, and predictive biomarkers exist that may help guide the individualized care of kidney cancer patients. This review will discuss the various serum, urine, imaging, and immunohistological biomarkers available in practice.

Overcome tumor heterogeneity-imposed therapeutic barriers through convergent genomic biomarker discovery: A braided cancer river model of kidney cancer

Tumor heterogeneity, encompassing genetic, epigenetic, and microenvironmental variables, is extremely complex and presents challenges to cancer diagnosis and therapy. Genomic efforts on genetic intratumor heterogeneity (G-ITH) confirm branched evolution, support the trunk-branch cancer model, and present a seemingly insurmountable obstacle to conquering cancers. G-ITH is conspicuous in clear cell renal cell carcinoma (ccRCC), where its presence complicates identification and validation of biomarkers and thwarts efforts in advancing precision cancer therapeutics. However, long-term clinical benefits on targeted therapy are not uncommon in metastatic ccRCC patients, implicating that there are underlying constraints during ccRCC evolution, which in turn force a nonrandom sequence of parallel gene/pathway/function/phenotype convergence within individual tumors. Accordingly, we proposed a "braided cancer river model" depicting ccRCC evolution, which deduces cancer development based on multiregion tumor genomics of exceptional mTOR inhibitor (mTORi) responders. Furthermore, we employ an outlier case to explore the river model and highlight the importance of "Five NGS Matters: Number, Frequency, Position, Site and Time" in assessing cancer genomics for precision medicine. This mutable cancer river model may capture clinically significant phenotype-convergent events, predict vulnerability/resistance mechanisms, and guide effective therapeutic strategies. Our model originates from studying exceptional responders in ccRCC, which warrants further refinement and future validation concerning its applicability to other cancer types. The goal of this review is employing kidney cancer as an example to illustrate critical issues concerning tumor heterogeneity.

Renal cell carcinoma

Renal cell carcinoma (RCC) denotes cancer originated from the renal epithelium and accounts for >90% of cancers in the kidney. The disease encompasses >10 histological and molecular subtypes, of which clear cell RCC (ccRCC) is most common and accounts for most cancer-related deaths. Although somatic VHL mutations have been described for some time, more-recent cancer genomic studies have identified mutations in epigenetic regulatory genes and demonstrated marked intra-tumour heterogeneity, which could have prognostic, predictive and therapeutic relevance. Localized RCC can be successfully managed with surgery, whereas metastatic RCC is refractory to conventional chemotherapy. However, over the past decade, marked advances in the treatment of metastatic RCC have been made, with targeted agents including sorafenib, sunitinib, bevacizumab, pazopanib and axitinib, which inhibit vascular endothelial growth factor (VEGF) and its receptor (VEGFR), and everolimus and temsirolimus, which inhibit mechanistic target of rapamycin complex 1 (mTORC1), being approved. Since 2015, agents with additional targets aside from VEGFR have been approved, such as cabozantinib and lenvatinib; immunotherapies, such as nivolumab, have also been added to the armamentarium for metastatic RCC. Here, we provide an overview of the biology of RCC, with a focus on ccRCC, as well as updates to complement the current clinical guidelines and an outline of potential future directions for RCC research and therapy.

Molecular Markers and Targeted Therapeutics in Metastatic Tumors of the Spine: Changing the Treatment Paradigms

STUDY TYPE

A review of the literature.

OBJECTIVE

The aim of this study was to discuss the evolution of molecular signatures and the history and development of targeted therapeutics in metastatic tumor types affecting the spinal column.

SUMMARY OF BACKGROUND DATA

Molecular characterization of metastatic spine tumors is expected to usher in a revolution in diagnostic and treatment paradigms. Molecular characterization will provide critical information that can be used for initial diagnosis, prognosticating the ideal treatment strategy, assessment of treatment efficacy, surveillance and monitoring recurrence, and predicting complications, clinical outcome, and overall survival in patients diagnosed with metastatic cancers to the spinal column.

METHODS

A review of the literature was performed focusing on illustrative examples of the role that molecular-based therapeutics have played in clinical outcomes for patients diagnosed with metastatic tumor types affecting the spinal column.

RESULTS

The impact of molecular therapeutics including receptor tyrosine kinases and immune checkpoint inhibitors and the ability of molecular signatures to provide prognostic information are discussed in metastatic breast cancer, lung cancer, prostate cancer, melanoma, and renal cell cancer affecting the spinal column.

CONCLUSION

For the providers who will ultimately counsel patients diagnosed with metastases to the spinal column, molecular advancements will radically alter the management/surgical paradigms utilized. Ultimately, the translation of these molecular advancements into routine clinical care will greatly improve the quality and quantity of life for patients diagnosed with spinal malignancies and provide better overall outcomes and counseling for treating physicians.

LEVEL OF EVIDENCE

N/A.

Predictive Immunohistochemical Markers Related to Drug Selection for Patients Treated with Sunitinib or Sorafenib for Metastatic Renal Cell Cancer

Targeted drug decisions in metastatic renal cell carcinoma are exclusively made on the basis of clinical criteria. We investigated whether these biomarkers (HIF-1α, HIF-2α, CAIX, VEGF, VEGFR1, VEGFR2, VEGFR3, PDGFB, PDGFRA, PDGFRB, CD31, CD44, bcl-xL, KIT, p21, CXCR4, PTEN, (CSF)-1R, RET, and FLT-3) can predictive the different effects between sunitinib and sorafenib treatments and are available to guide targeted drug selection. We enrolled all patients who underwent nephrectomy with postoperative sunitinib- or sorafenib-treatment at our institution from 2007 to 2012. Immunohistochemical approach was applied to assess the potential differential effects of immunostainings between sunitinib- and sorafenib-treated groups. We found that patients with high HIF-2α, CD31 expression showed greater relative PFS and OS benefit and patients with high CAIX expression presented greater relative OS benefit from sunitinib than from sorafenib, patients with high VEGFR1 or PDGFRB expression levels exhibited worse relative PFS benefit from sunitinib than from sorafenib. Namely high HIF-2α, CD31, and CAIX expression levels along with low VEGFR1 and PDGFRB expression levels improved the benefit of sunitinib treatment compared with sorafenib treatment. These results can identify whether patients can benefit more from sunitinib or sorafenib for drug selection guidance, eventually with precision medicine.

Mechanistically distinct cancer-associated mTOR activation clusters predict sensitivity to rapamycin

Genomic studies have linked mTORC1 pathway-activating mutations with exceptional response to treatment with allosteric inhibitors of mTORC1 called rapalogs. Rapalogs are approved for selected cancer types, including kidney and breast cancers. Here, we used sequencing data from 22 human kidney cancer cases to identify the activating mechanisms conferred by mTOR mutations observed in human cancers and advance precision therapeutics. mTOR mutations that clustered in focal adhesion kinase targeting domain (FAT) and kinase domains enhanced mTORC1 kinase activity, decreased nutrient reliance, and increased cell size. We identified 3 distinct mechanisms of hyperactivation, including reduced binding to DEP domain-containing MTOR-interacting protein (DEPTOR), resistance to regulatory associated protein of mTOR-mediated (RAPTOR-mediated) suppression, and altered kinase kinetics. Of the 28 mTOR double mutants, activating mutations could be divided into 6 complementation groups, resulting in synergistic Rag- and Ras homolog enriched in brain-independent (RHEB-independent) mTORC1 activation. mTOR mutants were resistant to DNA damage-inducible transcript 1-mediated (REDD1-mediated) inhibition, confirming that activating mutations can bypass the negative feedback pathway formed between HIF1 and mTORC1 in the absence of von Hippel-Lindau (VHL) tumor suppressor expression. Moreover, VHL-deficient cells that expressed activating mTOR mutants grew tumors that were sensitive to rapamycin treatment. These data may explain the high incidence of mTOR mutations observed in clear cell kidney cancer, where VHL loss and HIF activation is pathognomonic. Our study provides mechanistic and therapeutic insights concerning mTOR mutations in human diseases.

Transcriptome Sequencing (RNAseq) Enables Utilization of Formalin-Fixed, Paraffin-Embedded Biopsies with Clear Cell Renal Cell Carcinoma for Exploration of Disease Biology and Biomarker Development

Formalin-fixed, paraffin-embedded (FFPE) tissues are an underused resource for molecular analyses. This proof of concept study aimed to compare RNAseq results from FFPE biopsies with the corresponding RNAlater^® (Qiagen, Germany) stored samples from clear cell renal cell carcinoma (ccRCC) patients to investigate feasibility of RNAseq in archival tissue. From each of 16 patients undergoing partial or full nephrectomy, four core biopsies, such as two specimens with ccRCC and two specimens of adjacent normal tissue, were obtained with a 16g needle. One normal and one ccRCC tissue specimen per patient was stored either in FFPE or RNAlater^®. RNA sequencing libraries were generated applying the new Illumina TruSeq^® Access library preparation protocol. Comparative analysis was done using voom/Limma R-package. The analysis of the FFPE and RNAlater^® datasets yielded similar numbers of detected genes, differentially expressed transcripts and affected pathways. The FFPE and RNAlater datasets shared 80% (n = 1106) differentially expressed genes. The average expression and the log2 fold changes of these transcripts correlated with R² = 0.97, and R² = 0.96, respectively. Among transcripts with the highest fold changes in both datasets were carbonic anhydrase 9 (CA9), neuronal pentraxin-2 (NPTX2) and uromodulin (UMOD) that were confirmed by immunohistochemistry. IPA revealed the presence of gene signatures of cancer and nephrotoxicity, renal damage and immune response. To simulate the feasibility of clinical biomarker studies with FFPE samples, a classifier model was developed for the FFPE dataset: expression data for CA9 alone had an accuracy, specificity and sensitivity of 94%, respectively, and achieved similar performance in the RNAlater dataset. Transforming growth factor-ß1 (TGFB1)-regulated genes, epithelial to mesenchymal transition (EMT) and NOTCH signaling cascade may support novel therapeutic strategies. In conclusion, in this proof of concept study, RNAseq data obtained from FFPE kidney biopsies are comparable to data obtained from fresh stored material, thereby expanding the utility of archival tissue specimens.

A decade of pharmacogenomics research on tyrosine kinase inhibitors in metastatic renal cell cancer: a systematic review

OBJECTIVE

The individual response to targeted tyrosine kinase inhibitors (TKIs) in the treatment of metastatic renal cell cancer (mRCC) is highly variable. Outlined in this article are findings on potential biomarkers for TKI treatment outcome in mRCC and an evaluation of the status of clinical implementation.

METHODS

Articles were selected by two independent reviewers using a systematic search in five medical databases on renal cell carcinoma, TKIs, and pharmacogenetics.

RESULTS

Many researchers have focused on predictive biomarkers for treatment outcome of targeted therapies in mRCC patients. Attempts to explain differences in efficacy and toxicity of TKIs by use of genetic variants in genes related to the pharmacokinetics and pharmacodynamics of the drug have been successful.

CONCLUSION

Most findings on potential biomarkers have not been validated and therefore biomarker testing to guide choice of therapy and dose in mRCC is not yet feasible.

Favorable prognostic influence of T-box transcription factor Eomesodermin in metastatic renal cell cancer patients

T-box transcription factors, T-box expressed in T cells (T-bet) encoded by Tbx21 and Eomesodermin (Eomes), drive the differentiation of effector/memory T cell lineages and NK cells. The aim of the study was to determine the prognostic influence of the expression of these transcription factors in peripheral blood (pB) in a cohort of 41 metastatic (m) RCC patients before receiving sorafenib treatment and to analyze their association with the immunophenotype in pB. In contrast to Tbx21, in the multivariate analysis including clinical features, Eomes mRNA expression was identified as an independent good prognostic factor for progression-free survival (PFS, p = 0.042) and overall survival (OS, p = 0.001) in addition to a favorable ECOG performance status (p = 0.01 and p = 0.008, respectively). Eomes expression correlated positively not only with expression of Tbx21 and TGFβ1 mRNA, but also with mRNA expression of the activation marker ICOS, and with in vivo activated HLA-DR(+) T cells. Eomes expression was negatively associated with TNFα-producing T cells. On protein level, Eomes was mainly expressed by CD56(+)CD3(-) NK cells in pB. In conclusion, we identified a higher Eomes mRNA expression as an independent good prognostic factor for OS and PFS in mRCC patients treated with sorafenib.

An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort.

Lentivirus-Mediated RNAi Silencing of VEGF Inhibits Angiogenesis and Growth of Renal Cell Carcinoma in a Nude Mouse Xenograft Model

To construct and screen short hairpin RNA (shRNA) targeting vascular endothelial growth factor (VEGF), and investigate potential values of VEGF-shRNA on angiogenesis and growth in renal cell carcinoma (RCC) in a xenograft tumor model. VEGF-shRNA fragment was designed to connect plasmid vector, and RCC cells were transfected with shRNA. Real-time fluorescent quantitative polymerase chain reaction (RTFQ-PCR) was used to detect interference efficiency of VEGF gene. The xenograft tumor model was established in nude mice, and mice were randomly divided into blank control (BC) group, negative control (NC) group, and experimental group. RNA interference (RNAi) effect was detected by immunohistochemistry, and tumor volume changes were observed. Tumor-bearing nude mice model was established and mice were randomly divided into BC group, NC group, and treatment group. The tumor volume changes and tumor inhibition rate were recorded, and angiogenesis status was observed. The apoptosis of tumor cells and genetic toxicity of VEGF-shRNA were detected. VEGF-shRNA can inhibit VEGF mRNA expression with an inhibition ratio of 72.3%. Compared with NC group and BC group, experimental group presents smaller tumor volume, weight, and poor growth (all p < 0.05). Positive VEGF rate in experimental group is significantly lower than that in NC group and BC group (all p < 0.05). Significantly lower tumor volume, less microvessel density (MVD) value, and higher apoptotic index (AI) are found in treatment group compared with BC group and NC group (all p < 0.05). There was no significant difference in AI between treatment group and BC group regarding adjacent normal tissues (p > 0.05). VEGF plays an important role in the occurrence and development of RCC, chemical synthesis of VEGF small interfering RNA (siRNA) can specifically inhibit VEGF expression, angiogenesis and growth in RCC, and can promote cell apoptosis without genetic toxicity to normal tissues.

Kidney cancer and 2014: is innovation really over?

ABSTRACT 

2014 has been a year of significant innovations on kidney cancer treatments, the most relevant of which will be shown below. In particular, we analyzed the consolidated knowledge regarding the role of surgery in localized and advanced renal cell carcinoma and the targeted therapies already approved for metastatic renal cell carcinoma. Furthermore, we examined the outstanding issues, with particular reference to the choice of the second-line and the role of adjuvant and neoadjuvant treatments. Finally, we outlined the future therapeutic perspectives and those definitely abandoned.

Predictive molecular biomarkers to guide clinical decision making in kidney cancer: current progress and future challenges

Although the past decade has seen a surfeit of new targeted therapies for renal cell carcinoma (RCC), no predictive molecular biomarker is currently used in routine clinical practice to guide personalized therapy as a companion diagnostic. Many putative biomarkers have been suggested, but none have undergone rigorous validation. There have been considerable advances in the biological understanding of RCC in recent years, with the development of accompanying molecular diagnostics that with additional validation, may be helpful for routine clinical decision making. In this review, we summarize the current understanding of predictive biomarkers in RCC management and also highlight upcoming developments of interest in biomarker research for personalizing RCC diagnostics and therapeutics.

IL8 polymorphisms and overall survival in pazopanib- or sunitinib-treated patients with renal cell carcinoma

BACKGROUND

We evaluated germline single nucleotide polymorphisms (SNPs) for association with overall survival (OS) in pazopanib- or sunitinib-treated patients with advanced renal cell carcinoma (aRCC).

METHODS

The discovery analysis tested 27 SNPs within 13 genes from a phase III pazopanib trial (N=241, study 1). Suggestive associations were then pursued in two independent datasets: a phase III trial (COMPARZ) comparing pazopanib vs sunitinib (N=729, study 2) and an observational study of sunitinib-treated patients (N=89, study 3).

RESULTS

In study 1, four SNPs showed nominally significant association (P≤0.05) with OS; two of these SNPs (rs1126647, rs4073) in IL8 were associated (P≤0.05) with OS in study 2. Because rs1126647 and rs4073 were highly correlated, only rs1126647 was evaluated in study 3, which also showed association (P≤0.05). In the combined data, rs1126647 was associated with OS after conservative multiple-test adjustment (P=8.8 × 10(-5); variant vs reference allele hazard ratio 1.32, 95% confidence interval: 1.15-1.52), without evidence for heterogeneity of effects between studies or between pazopanib- and sunitinib-treated patients.

CONCLUSIONS

Variant alleles of IL8 polymorphisms are associated with poorer survival outcomes in pazopanib- or sunitinib-treated patients with aRCC. These findings provide insight in aRCC prognosis and may advance our thinking in development of new therapies.