Proteomic Identification of Interleukin-2 Therapy Response in Metastatic Renal Cell Cancer

Jones, Jon; Otu, Hasan H.; Grall, Franck; Spentzos, Dimitrios; Can, Handan; Aivado, Manuel; Belldegrun, Arie S.; Libermann, Towia A.

doi:10.1016/j.juro.2007.09.016

Cited by 12 publications

(7 citation statements)

References 20 publications

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“…Since then, other studies were performed with the same goal under different conditions or different proteomics approaches (3)(4)(5)(6)(7)(8). The method that was applied in this study is based on 2DE, the most traditional technology for separation of proteins.…”

Section: Discussionmentioning

confidence: 99%

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Differencial proteome of clear-cell renal cell carcinoma (ccRCC) tissues

et al. 2013

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Purpose: We attempted to detect, for the first time in a Brazilian cohort, differences in protein expression between clear-cell renal cell carcinoma (ccRCC) and their normal adjacent tissues, aiming to identify biomarkers and/or therapeutic target candidates for this disease. Material and Methods: Twenty-four ccRCC and adjacent normal tissues were collected after surgery and their protein extracts were quantified, pooled and separated by two--dimensional polyacrylamide gel electrophoresis (2DE), followed by statistical analysis of the stained gels. Spots of interest were excised from the gels, digested with trypsin and identified by MALDI-TOF-TOF mass spectrometry. Results: Twenty-six differential spots were detected between the two classes of tissues, among which twenty were identified by mass spectrometry and sixteen were found to be non-redundant. Eleven proteins were either underexpressed or undetected in the ccRCC extracts, such as prohibitin and peroxiredoxin-3, whereas five were found to be overexpressed or exclusively detected in the ccRCC extract, including αβ crystalin and heat shock protein 27. Conclusions: Several proteins were detected at differential levels when compared to normal adjacent tissues, and, moreover, many have been previously described by their relationship with RCC. Therefore, this work corroborates previous reports on the search for biomarkers for ccRCC, as well as it points out new candidates that may be validated in future studies.

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Section: Discussionmentioning

confidence: 99%

“…A constant effort has been made (3)(4)(5)(6)(7)(8) in the search for biomarker candidates for RCC. However, none of them achieved definitive diagnostic and prognostic value in clinical practice so far.…”

Section: Introductionmentioning

confidence: 99%

Differencial proteome of clear-cell renal cell carcinoma (ccRCC) tissues

et al. 2013

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“…A high-dose IL-2 trial is currently investigating its efficacy according to these predictive features to prospectively validate the selection criteria and to identify the patients likely to benefit the most from immunotherapy. A recent study based on a proteomic approach attempted to identify a new biomarker in the immunotherapy setting [56] .…”

Section: Immune Responsementioning

confidence: 99%

Kidney Cancer Pathology in the New Context of Targeted Therapy

2011

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The outcome in metastatic renal cancer remains poor with an overall survival at 5 years of less than 10%. However, molecular pathology in kidney cancer has developed extensively in the few last years, providing a basis for new systemic therapies including antiangiogenic drugs and mTOR inhibitors. Use of these targeted therapies in metastatic disease has improved the prognosis but still in a too-limited range, with a lack of consistent predictive biomarkers. The multiple entities of renal tumors add complexity to the research of biomarkers and the design of clinical trials. This review aims to focus on pathways in renal cancer (VHL/HIF, mTOR, c-MYC, c-MET, and immune response) in the respective tumor subtypes, accounting for the effects of targeted therapies and providing the framework to search for relevant predictive biomarkers and propose new trials. This overview underscores that the pathways are often intermingled and common (at least partially) to the different tumor subtypes.

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“…The authors identified protein differences between patients with good response to treatment and those who did not respond to treatment. The authors suggested that it is possible to avoid the undesirable side effects of treatment with IL-2 [28] .…”

Section: Rcc Versus Proteomicsmentioning

confidence: 99%

Renal Cell Carcinoma and Proteomics

Sandim¹,

Pereira²,

Ornellas³

et al. 2010

Urol Int

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Renal cell carcinoma (RCC) represents 3% of adult malignancies. About 30% of RCC patients develop metastatic disease. So far, drugs cannot significantly increase the survival of these patients. We present a recent review of proteomics and RCC. Proteomic technologies have been used in the research to discover new markers of RCC that might increase survival. Furthermore, newly discovered markers cannot increase patient survival, rather their prognostic value supporting therapeutic decisions or new agents targeted at these new markers. More research is required to develop proteomic technologies and biomarkers for identification and validation.

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Proteomic Identification of Interleukin-2 Therapy Response in Metastatic Renal Cell Cancer

Abstract: Introduction-To detect a predictive protein profile that distinguishes between IL-2 therapy responders and non-responders among metastatic RCC patients we used surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS).

Cited by 12 publications

References 20 publications

Differencial proteome of clear-cell renal cell carcinoma (ccRCC) tissues

Differencial proteome of clear-cell renal cell carcinoma (ccRCC) tissues

Kidney Cancer Pathology in the New Context of Targeted Therapy

Renal Cell Carcinoma and Proteomics

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