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.

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

Prognostic and Predictive Factors for 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.

/pdf/hif-pathway-and-c-myc-as-biomarkers-for-response-to-30ibhh9qgk.pdf

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

In recent years, there has been a remarkable increase in interest in biomarkers, especially as a tool with tremendous utility in cancer. Biomarkers provide opportunities for early detection, accurate diagnosis, and predicting clinical outcome with regard to response to therapy, potential tumor recurrence, and survival, and they provide additional insights into the pathogenesis of disease. Biomarkers also provide both a strategy for clustering “like” subsets of tumors on a population level, and also allow individualized tumor information for case-by-case decision-making. Biomarkers are especially attractive because they are quantitative, objective, and readily adaptable for clinical implementation. Traditional clinical practice relies heavily on signs and symptoms as well as radiographic imagery, which can be highly subjective as well as influenced by a variety of sources independent of the cancer. In contrast, biomarkers are helpful as more objective and reliable factors, which can either supplement or replace these largely subjective measures. Moreover, biomarkers can potentially play important roles in clinical research by clarifying measurable endpoints, which may lead to significant decrease of cost and duration of clinical trials. Currently, research institutes, pharmaceutical companies, and the United States Food and Drug Administration (FDA) are putting vigorous effort toward integrating biomarkers more extensively into clinical trials.

Biomarkers for Renal Cell Carcinoma

Biallelic inactivation of the von Hippel-Lindau (VHL) gene occurs in the majority of sporadic clear cell renal cell carcinomas (ccRCCs) due to a combination of somatic mutations, VHL promoter methylation and loss of heterozygosity by allele deletion. The most well-documented function of pVHL relates to its role as the substrate-recognition component of the VHL-elongin C-elongin B-cullin 2-Rbx1 E3 ubiquitin ligase complex. This complex is best known for its ability to target hypoxia-inducible factors (HIFs) for polyubiquitination and proteasomal degradation. HIFs play a critical role in cellular adaptation to reduced oxygen tension. Three HIFα family members (HIF1α, HIF2α and HIF3α) and two HIFβ (HIF1β and HIF2β) have been described. The balance of evidence suggests that in ccRCC, HIF1α acts as a tumour suppressor, while HIF2α acts as a renal oncoprotein. pVHL also has HIF-independent functions though these are less well characterised. In this chapter, we examine in detail the role of the VHL gene and protein in ccRCC, alongside that of its main downstream target, hypoxia-inducible factor (HIF). The results from several studies which have investigated whether VHL mutational status or HIFα expression is a useful biomarker in ccRCC are reviewed.

VHL and HIF in Clear Cell Renal Cell Carcinoma: Molecular Abnormalities and Potential Clinical Applications

4630 Background: Relevant biomarkers in RCC are needed to identify appropriate candidates for selected targeted therapies. Mutations in the von Hippel-Lindau (VHL) gene result in the accumulation o...

Hypoxia-inducible factor (HIF) 1α and 2α as predictive markers of outcome to VEGFR tyrosine kinase inhibitors (TKI) in renal cell carcinoma (RCC).

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

M. Leon

Author Tools

Chat about Author

Papers

Hypoxia-inducible factor (HIF) 1α and 2α as predictive markers of outcome to VEGFR tyrosine kinase inhibitors (TKI) in renal cell carcinoma (RCC).