Stratification of clear cell renal cell carcinoma by signaling pathway analysis

Cremona, Mattia; Espina, Virginia; Caccia, Dario; Veneroni, Silvia; Colecchia, Maurizio; Pierobon, Mariaelena; Deng, Jianghong; Mueller, Claudius; Procopio, Giuseppe; Lanzi, Cinzia; Daidone, Maria Grazia; Cho, William C.; Petricoin, Emanuel F.; Liotta, Lance A.; Bongarzone, Italia

doi:10.1586/14789450.2014.893193

Cited by 9 publications

(7 citation statements)

References 51 publications

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“…Although significant advances have been made in the treatment of RCC, few biomarkers for detection of this disease have been identified. Most current biomarker studies have relied on DNA markers [15]–[17], gene expression [18], [19] and microRNAs [20]. Nevertheless, there are no biomarkers for routine clinical use in ccRCC.…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

Yang

Zhao

et al. 2014

PLoS ONE

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ObjectiveTo investigate discriminating protein patterns and serum biomarkers between clear cell renal cell carcinoma (ccRCC) patients and healthy controls, as well as between paired pre- and post-operative ccRCC patients.MethodsWe used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with ccRCC. A total of 162 serum samples were analyzed in this study, among which there were 58 serum samples from ccRCC patients, 40 from additional paired pre- and post-operative ccRCC patients (n = 20), and 64 from healthy volunteers as healthy controls. ClinProTools software identified several distinct markers between ccRCC patients and healthy controls, as well as between pre- and post-operative patients.ResultsPatients with ccRCC could be identified with a mean sensitivity of 88.38% and a mean specificity of 91.67%. Of 67 m/z peaks that differed among the ccRCC, healthy controls, pre- and post-operative ccRCC patients, 24 were significantly different (P<0.05). Three candidate peaks, which were upregulated in ccRCC group and showed a tendency to return to healthy control values after surgery, were identified as peptide regions of RNA-binding protein 6 (RBP6), tubulin beta chain (TUBB), and zinc finger protein 3 (ZFP3) with the m/z values of 1466.98, 1618.22, and 5905.23, respectively.ConclusionMB-MALDI-TOF-MS method could generate serum peptidome profiles of ccRCC, and provide a new approach to identify potential biomarkers for diagnosis as well as prognosis of this malignancy.

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Section: Discussionmentioning

confidence: 99%

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

Yang

Zhao

et al. 2014

PLoS ONE

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“…[ 107 ] Due to the encouraging data, RPPA has been applied to several clinical trials for the evaluation of single and combinatorial drug efficacy in patients with metastatic and locally advanced cancers. [ 108 – 113 ]…”

Section: Potentials and Challenges Of Affinity-based Proteomicsmentioning

confidence: 99%

Immunocapture strategies in translational proteomics

Fredolini

Byström

et al. 2015

Expert Review of Proteomics

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Aiming at clinical studies of human diseases, antibody-assisted assays have been applied to biomarker discovery and toward a streamlined translation from patient profiling to assays supporting personalized treatments. In recent years, integrated strategies to couple and combine antibodies with mass spectrometry-based proteomic efforts have emerged, allowing for novel possibilities in basic and clinical research. Described in this review are some of the field’s current and emerging immunocapture approaches from an affinity proteomics perspective. Discussed are some of their advantages, pitfalls and opportunities for the next phase in clinical and translational proteomics.

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“…We analysed the expression of this panel of proteins using ELISA or a miniaturized multiple protein analysis platforms such as RPPA to parallel profiling of multiple protein markers [15,24]. …”

Section: Discussionmentioning

confidence: 99%

Expression of Iron-Related Proteins Differentiate Non-Cancerous and Cancerous Breast Tumors

Pizzamiglio

Bortoli

Taverna

et al. 2017

IJMS

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We have previously reported hepcidin and ferritin increases in the plasma of breast cancer patients, but not in patients with benign breast disease. We hypothesized that these differences in systemic iron homeostasis may reflect alterations in different iron-related proteins also play a key biochemical and regulatory role in breast cancer. Thus, here we explored the expression of a bundle of molecules involved in both iron homeostasis and tumorigenesis in tissue samples. Enzyme-linked immunosorbent assay (ELISA) or reverse-phase protein array (RPPA), were used to measure the expression of 20 proteins linked to iron processes in 24 non-cancerous, and 56 cancerous, breast tumors. We found that cancerous tissues had higher level of hepcidin than benign lesions (p = 0.012). The univariate analysis of RPPA data highlighted the following seven proteins differentially expressed between non-cancerous and cancerous breast tissue: signal transducer and transcriptional activator 5 (STAT5), signal transducer and activator of transcription 3 (STAT3), bone morphogenetic protein 6 (BMP6), cluster of differentiation 74 (CD74), transferrin receptor (TFRC), inhibin alpha (INHA), and STAT5_pY694. These findings were confirmed for STAT5, STAT3, BMP6, CD74 and INHA when adjusting for age. The multivariate statistical analysis indicated an iron-related 10-protein panel effective in separating non-cancerous from cancerous lesions including STAT5, STAT5_pY694, myeloid differentiation factor 88 (MYD88), CD74, iron exporter ferroportin (FPN), high mobility group box 1 (HMGB1), STAT3_pS727, TFRC, ferritin heavy chain (FTH), and ferritin light chain (FTL). Our results showed an association between some iron-related proteins and the type of tumor tissue, which may provide insight in strategies for using iron chelators to treat breast cancer.

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Stratification of clear cell renal cell carcinoma by signaling pathway analysis

Cited by 9 publications

References 51 publications

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

Identification of Potential Serum Proteomic Biomarkers for Clear Cell Renal Cell Carcinoma

Immunocapture strategies in translational proteomics

Expression of Iron-Related Proteins Differentiate Non-Cancerous and Cancerous Breast Tumors

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