Relevant bibliographies by topics / Proteomics, Urine, Renal Cell Carcinoma

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Proteomics, Urine, Renal Cell Carcinoma'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Proteomics, Urine, Renal Cell Carcinoma"

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Santorelli, Lucia, Martina Stella, Clizia Chinello, Giulia Capitoli, Isabella Piga, Andrew Smith, Angelica Grasso, Marco Grasso, Giorgio Bovo, and Fulvio Magni. "Does the Urinary Proteome Reflect ccRCC Stage and Grade Progression?" Diagnostics 11, no. 12 (December 16, 2021): 2369. http://dx.doi.org/10.3390/diagnostics11122369.

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Due its ability to provide a global snapshot of kidney physiology, urine has emerged as a highly promising, non-invasive source in the search for new molecular indicators of disease diagnosis, prognosis, and surveillance. In particular, proteomics represents an ideal strategy for the identification of urinary protein markers; thus, a urinomic approach could also represent a powerful tool in the investigation of the most common kidney cancer, which is clear cell Renal Cell Carcinoma (ccRCC). Currently, these tumors are classified after surgical removal using the TNM and nuclear grading systems and prognosis is usually predicted based upon staging. However, the aggressiveness and clinical outcomes of ccRCC remain heterogeneous within each stratified group, highlighting the need for novel molecular indicators that can predict the progression of these tumors. In our study, we explored the association between the urinary proteome and the ccRCC staging and grading classification. The urine proteome of 44 ccRCC patients with lesions of varying severity was analyzed via label-free proteomics. MS data revealed several proteins with altered abundance according to clinicopathological stratification. Specifically, we determined a panel of dysregulated proteins strictly related to stage and grade, suggesting the potential utility of MS-based urinomics as a complementary tool in the staging process of ccRCC.
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Sandim, Vanessa, Denise de Abreu Pereira, Dário Eluan Kalume, Ana Lucia Oliveira-Carvalho, Antonio Augusto Ornellas, Marcia Regina Soares, Gilda Alves, and Russolina Benedeta Zingali. "Proteomic analysis reveals differentially secreted proteins in the urine from patients with clear cell renal cell carcinoma." Urologic Oncology: Seminars and Original Investigations 34, no. 1 (January 2016): 5.e11–5.e25. http://dx.doi.org/10.1016/j.urolonc.2015.07.016.

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Wu, Deng-Long, Wen-Hong Zhang, Wen-Jing Wang, San-Bao Jing, and Yue-Ming Xu. "Proteomic Evaluation of Urine from Renal Cell Carcinoma Using SELDI-TOF-MS and Tree Analysis Pattern." Technology in Cancer Research & Treatment 7, no. 3 (June 2008): 155–60. http://dx.doi.org/10.1177/153303460800700301.

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Sandim, Vanessa, Denise A. Pereira, Antonio A. Ornellas, and Gilda Alves. "Renal Cell Carcinoma and Proteomics." Urologia Internationalis 84, no. 4 (2010): 373–77. http://dx.doi.org/10.1159/000296283.

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Miranda-Poma, Jesús, Lucía Trilla-Fuertes, Rocío López-Vacas, Elena López-Camacho, Eugenia García-Fernández, Ana Pertejo, María I. Lumbreras-Herrera, et al. "Proteomics Characterization of Clear Cell Renal Cell Carcinoma." Journal of Clinical Medicine 12, no. 1 (January 3, 2023): 384. http://dx.doi.org/10.3390/jcm12010384.

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Purpose: To explore the tumor proteome of patients diagnosed with localized clear cell renal cancer (ccRCC) and treated with surgery. Material and methods: A total of 165 FFPE tumor samples from patients diagnosed with ccRCC were analyzed using DIA-proteomics. Proteomics ccRCC subtypes were defined using a consensus cluster algorithm (CCA) and characterized by a functional approach using probabilistic graphical models and survival analyses. Results: We identified and quantified 3091 proteins, including 2026 high-confidence proteins. Two proteomics subtypes of ccRCC (CC1 and CC2) were identified by CC using the high-confidence proteins only. Characterization of molecular differences between CC1 and CC2 was performed in two steps. First, we defined 514 proteins showing differential expression between the two subtypes using a significance analysis of microarrays analysis. Proteins overexpressed in CC1 were mainly related to translation and ribosome, while proteins overexpressed in CC2 were mainly related to focal adhesion and membrane. Second, a functional analysis using probabilistic graphical models was performed. CC1 subtype is characterized by an increased expression of proteins related to glycolysis, mitochondria, translation, adhesion proteins related to cytoskeleton and actin, nucleosome, and spliceosome, while CC2 subtype showed higher expression of proteins involved in focal adhesion, extracellular matrix, and collagen organization. Conclusions: ccRCC tumors can be classified in two different proteomics subtypes. CC1 and CC2 present specific proteomics profiles, reflecting alterations of different molecular pathways in each subtype. The knowledge generated in this type of studies could help in the development of new drugs targeting subtype-specific deregulated pathways.
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Bonn, Dorothy. "Urine test for renal-cell carcinoma." Lancet Oncology 5, no. 2 (February 2004): 72. http://dx.doi.org/10.1016/s1470-2045(04)01368-3.

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Claps, Francesco, and M. Carmen Mir. "Novel Expanding Renal Cell Carcinoma Biomarkers." Société Internationale d’Urologie Journal 2, no. 1 (January 18, 2021): 32–42. http://dx.doi.org/10.48083/xlqz8269.

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Identification of reliable molecular biomarkers that can complement clinical practice represents a fascinating challenge in any cancer field. Renal tumors are usually asymptomatic and incidentally identified during imaging studies undertaken for unrelated causes. However, in 25% to 30% of patients the first diagnosis is accompanied by symptoms and associated with distant metastasis. Thus, early diagnosis may reduce the risk of disease progression also avoiding side effects of inadequate treatments. Moreover, the ability to categorize patients' risk of recurrence after radical treatment, or even predict benefit from a target therapy, represents a compelling challenge. Here we review the current state-of-the-art on RCC biomarkers, particularly focusing on the new approaches of genomics, liquid biopsy, proteomics, and metabolomics.
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Kawakami, Hitoshi, Yoshihiko Hoshida, Jun Hanai, Nobuhiko Uchino, Shinya Sasaki, Akemi Mori, Kouich Ikegami, Tomomi Kishimoto, and Katsuyuki Aozasa. "Voided Urine Cytology of Papillary Renal Cell Carcinoma and Renal Calculus." Acta Cytologica 45, no. 5 (2001): 771–74. http://dx.doi.org/10.1159/000328303.

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Dihazi, Hassan. "Prognosis markers for metastatic renal cell carcinoma: quantitative proteomics approach." Expert Review of Proteomics 10, no. 1 (February 2013): 21–24. http://dx.doi.org/10.1586/epr.12.71.

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Freund, S., T. Johl, K. Haberecht, J. Wissing, F. Klawonn, P. Hammerer, and L. Jänsch. "276 KINOME PROFILING IN RENAL CELL CARCINOMA BY QUANTITATIVE PROTEOMICS." European Urology Supplements 10, no. 2 (March 2011): 107. http://dx.doi.org/10.1016/s1569-9056(11)60274-1.

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Dissertations / Theses on the topic "Proteomics, Urine, Renal Cell Carcinoma"

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CAZZANIGA, MARTA. "Ricerca di una firma molecolare tipizzante tumori renali mediante approccio proteomico di profiling in spettrometria di massa." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2016. http://hdl.handle.net/10281/104019.

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Renal cell carcinoma accounts for about 85% of primary kidney tumors and its incidence worldwide is increasing rapidly. Although the diagnosis of RCC is routinely performed by means of multiple imaging techniques, benign solid renal masses sometimes cannot be confidently differentiated from malignant ones. Moreover, the TNM (Tumor-Node-Metastasis) classification system, the Fuhrman grading system and serum markers are still the main factors used to predict the outcome of patients. For these reasons, RCC still remains a significant clinical challenge not only in terms of early diagnosis but also clinical management. Moreover, since the main alterations in regulation processes caused by tumorigesis not only involve genes but also proteins, MS-based protein profiling is considered an effective approach both for the discovery of multiple biomarkers and for the detection of disease specific modifications. Therefore, this PhD project has been focused on the study and characterisation of the urinary peptidome and proteome of RCC patients, patients affected by other kidney neoplasms and control subjects in order to evaluate potential molecular signatures capable of characterising renal cancers. For this purpose, sistematic analysis at the peptidome level employing a protein profiling approach based on MALDI-TOF mass spectrometry analysis combined with pre-purification step of urine samples using functionalized magnetic beads, has been performed. This technique has allowed, on one hand, to build models of potential biomarkers able to discriminate not only ccRCC patients from controls, but also to significantly distinguish malignant renal masses from benign forms and, on the other hand, to highlight alterations of endogenous peptides according to clinical data (stage, grade, dimension). The identification of discriminant and/or tumor progression related signals has been obtained through a nLC-ESI MS/MS approach on urine pools of 80 healthy volunteers and 80 RCC patients. For the proteomic analysis, a tryptic digestion of urine samples using the FASP (Filter Aided Sample Preparation) protocol followed by shotgun analysis by nanoUHPLC-ESI MS/MS has been performed. The relative label-free quantification has facilitated the investigation of protein alterations in ccRCC subjects. The subsequent functional analysis has highlighted the bological processes and the molecular functions in which the varied proteins are involved. Moreover, in the study of a complex system such as the kidney, a systematic comparison between different –omic sciences (peptidomics/proteomics) could highlight functions, biological processes and molecular targets that are implicated in the deregulation caused by the presence of the tumor and for this reason an integration of the collected data has been performed in order to identify potential targets and biological effectors that could improve the understanding of the intricate and multifactorial mechanisms underlying kidney malignancies.
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Vasudev, Naveen Srinath. "The Application of Proteomics to Biological Fluids for Biomarker Discovery in Renal Cell Carcinoma." Thesis, University of Leeds, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.521538.

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MOROSI, LAVINIA. "Studi di proteomica subcellulare nelle patologie renali: carcinoma renale e nefropatia diabetica." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2012. http://hdl.handle.net/10281/28933.

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ABSTRACT Renal cell carcinoma (RCC) is among the 10 leading causes of cancer-related deaths worldwide and its incidence is increasing steadily. At the time of diagnosis, 30% of patients have metastases and another third will develop metastatic disease within 10 years. Moreover metastatic RCC is radio- and chemotherapy resistant. Diabetic nephropathy (DN) is a common diabetic complication that causes a renal massive functional deficit making dialysis or transplantation essential for the survival of patients and it is associated with alterations in the expression of several renal proteins. Therefore, it is important to identify differentially expressed proteins to be used as potential diagnostic and/or prognostic markers in RCC and DN. A promising strategy is comparative subcellular proteomics of urinary exosomes, membranous vesicles released from cells and membrane microdomains, lipid arfts and caveolae. About 30 ml of urines were collected from 29 clear cell RCC patients and 28 healthy matched controls and stored at -80°C, after antiproteases addition. Diabetes was induced in 10 Sprague Dawley rats by streptozotocin injection. Control rats (n=4) underwent only buffer injection. Out of 10 diabetic rats, 4 were chronically treated with insulin. After 3 months, 24 hours urines were collected. In both cases (RCC patients and diabetic rats with their healthy controls respectively) exosomes were then isolated from total urines by ultracentrifugation after cells and debris clearing. As regards RCC esults show that the protein profile of urinary exosomes is peculiar: the most abundant urinary proteins of plasmatic origin (i.e. albumin) are markedly reduced, while the Tamm Horsfall protein (THP) is highly enriched and affected by a significant biological variability. Moreover, protein profiles of exosomal fractions isolated from urine of ccRCC and matched controls show some difference. Mass spectrometry analysis of two pools of exosomes isolated from CTRL and RCC patients urines permits the identification of 261 proteins in CTRL and 187 proteins in RCC. Some of these protein Aquaporin-1, Matrix Metallo-protease 9 and Carbonic Anhydrase 9, display differential amount in ccRCC patient urine exosomes by EF/WB. Moreover subcellular fractions were prepared by differential centrifugation from surgical samples of RCC and adjacent normal kidney (ANK). MD were isolated from plasma-membrane-enriched fractions after treatment with Triton X-100 and sucrose density gradient ultracentrifugation. MD derived from RCC and ANK tissues of 7 patients were pooled, and proteins separated by 4-12% and 12% gel electrophoresis. After Coomassie Blue staining, bands were excised and analyzed by LC-MS/MS after trypsin digestion. We identified 83 proteins from microdomains isolated from RCC tissue, and 95 proteins from ANK. About 60% of the identified proteins are membrane-associated and about half of these resulted microdomain-associated. GRAVY scores assignment shows that most identified proteins (about 70%) are in the hydrophobic range. From a functional point of view, we found proteins involved in signal transduction (Ras related proteins), channels (Aquaporin-1), carriers (P-glycoprotein) and cytoskeleton structural constituents (Spectrin). We chose some promising proteins such as Renal dipeptidase (identified only in ANK MD) or Emmprin (overexpressed in RCC tissue) and investigated their differential expression of by WB About DN study, protein profiles of exosomes obtained from the three groups of rat (healthy controls CTRL, diabetic D and diabetic treated with insulin DI) show differences, mainly at low molecular weights. Some differential bands were excised and analyzed by LC-MS/MS after digestion by tripsin. In particular we identified the Major Urinary Proteins, known as MUPs from CTRL and DI gels, while these proteins are not present in the same bands excised from D gels. MUPs regulate glucose and lipid metabolism suggesting an involvement in hyperglycemia, insulin resistance and/or glucose intolerance in diabetes.
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Tsai, Yi Huai, and 蔡逸懷. "Comparative Urine Metabolomics of Renal Cell Carcinoma by 12C/13C-Isotope Dansylation Labeling and Liquid Chromatography/ Mass Spectrometry." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107CGU05114025%22.&searchmode=basic.

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Gong, Ching-Chun, and 龔靜君. "Investigation on the Association of Renal and Urothelial Cell Carcinoma with Metal Levels in Urine and Tissues of Renal Cortex, Pelvis,and Ureter." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/30574454009799885322.

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碩士
國立臺灣大學
職業醫學與工業衛生研究所
99
Several epidemiological studies reported the association between trace metals exposure and cancers. In Taiwan, a significant dose-response relationship between arsenic exposure and urothelial cell carcinoma was also demonstrated. Besides, animal studies showd tumor growth in animals exposed to arsenic, cadmium, lead and nickel. However, the roles of trace metals in the development of kidney cancer are unclear. The purpose of this study was to characterize the distribution of trace metals in urine and in renal cortex, pelvis, and ureter of the study subjects to further explore the relationship between trace metals and kidney cancer. In this study, 41 urothelial cell carcinoma (UCC) cases, 11 renal cell carcinoma (RCC) cases, and 8 controls were obtained from the Urological Department of the National Taiwan University Hospital. All UCC and RCC subjects were histologically diagnosed and classified according to the TNM classification system. Questionnaire was admintered to collect individual’s information, such as age, body height, weight, smoking history, occupation, alcohol drinking, dietary habit, herbal medicine uses, and familial disease history. Normal and tumor tissue samples of renal cortex, renal pelvis, and ureter were decomposed by using a microwave-assisted method in closed vessels. The inductively coupled plasma mass spectrometry was used to determine the contents of trace metals in normal and tumor renal tissue. Urine sample was first filtered through a 0.45-μm membrane prior to being analysed by ICP-MS. In this study no significant difference was found in urinary metal levels of kidney cancer cases among different stages. With respect to trace metals in renal tissues, the concentrations of cadmium in normal tissues were significantly higher than in tumor tissues of both renal cortex and pelvis, respectively, whereas the concentrations of arsenic and strontium in normal tissues were significantly higher than in tumor tissue only in renal cortex. For ureter, the concentrations of arsenic and cadmium in tumor tissue were significantly higher than in normal tissue, while those of manganese and copper in tumor tissue were also higher, though not statisticaly significantly, than in normal tissue. In summary, the concentrations of various trace metals in tumor and normal tissues differed in cortex, pelvis, or ureter, which might be caused by the fast proliferation of tumor cell or the over-expression of metallothionein in tumor cell. However, the real mechanism is still warrants further studies.
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Chiang, Jung-Chun, and 江榮春. "Proteomics analysis reveals urine biomarkers for children glomerular nephritis and possible mechanism of human renal proximal tubular epithelial cell injury induced by aristolochic acid." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/45804993601823751974.

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碩士
國立宜蘭大學
生物技術研究所碩士班
97
Glomerulonephritis (GN) is the major cause of end-stage renal diseases worldwide. They are considered to be consequences of injury primarily to the glomerulus. Because of noninvasiveness and simplicity of specimen collection, human urine is one of the most useful biofluids for proteomics study. Identification of urinary biomarkers may lead to the development of a simple diagnostic test for earlier disease detection, or improvement in prognosis. In the current study, we seek to discover urine biomarkers for glomerular nephritis, including poststreptococcal glomerulonephritis (PSGN), Henoch-Schoenlein purpura nephritis (HSPN) and immunoglobulin A nephropathy (IgAN) using gel-based (2-DE) and gel-free proteomics approaches. Four significantly altered proteins were identified by LC-ESI-Q-TOF-MS/MS as Tamm-Horsfall protein, precursor of Alpha1-acid glycoprotein 1 also called orosomucoid-1, thioredoxin peroxidase B, and chain B of haemoglobin. Western blot and 2-D western analyses were performed to evaluate the sensitivity and specificity of these proteins. Among the four proteins, Alpha1-acid glycoprotein 1 and thioredoxin peroxidase B were considered potential biomarkers for glomerulonephritis. Furthermore, in order to evaluate the possible mechanism of renal tubular cell injury caused by Chinese herb nephropathy (CHN), aristolochic acid (AA) was applied to treat human renal proximal tubular epithelial cell line, HK-2. AA is a natural nephrotoxant from Aristolochiaceae plants which is widely used in traditional Chinese medicine (TCM). Previous studies have shown that AA is responsible for CHN (also called aristolochic acid nephropathy, AAN), a rapidly progressive interstitial nephropathy. In Asian countries, where TCMs are very popular, the complexity of the pharmacopoeia represents a high risk for AAN because of the frequent substitution of the botanical products by AA-containing herbs. In the present study, we applied gel-based proteomics (2-DE) to reveal the mechanism of AA-induced cytotoxicity for HK-2 cell line. Seven significantly altered proteins were identified by LC-ESI-Q-TOF-MS/MS as myosin, chaperonin, heat shock 70 kDa protein 8, tropomyosin 3, vimentin, beta actin, and calreticulin precursor. These protein are involved in cytoskeleton structure and transdifferentiation, indicating that AA may trigger cytoskeleton reorganization and cell transdifferentiation of HK-2 cell.
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Penedo, Susana Patrícia Guerreiro Jorge. "Deciphering the interplay of molecular alterations underpinning renal cell carcinoma by label-free mass spectrometry and clinical proteomics: A systems medicine approach for precision diagnosis." Doctoral thesis, 2020. http://hdl.handle.net/10362/115264.

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Renal neoplasia is the 14th most common tumor type diagnosed worldwide. With a vast heterogeneity, renal neoplasia encompasses different subtypes. 90% of the neoplasms arise from the epithelial layer of the nephron and vary from benign renal masses (renal oncocytoma, RO) to more indolent or aggressive cancers (renal cell carcinomas, RCC). As RCC subtypes, clear cell (ccRCC) subtype is the most predominant subtype, followed by papillary (pRCC) and chromophobe (chRCC). Despite the different outcomes, some overlapped histological and morphological features difficult their differentiation and diagnosis. Therefore, new approaches for a clear and accurate diagnosis are still needed. To achieve this goal, renal tissue biopsies diagnosed with ccRCC (n = 7), pRCC (n = 5), chRCC (n = 5), RO (n = 5) and normal adjacent tissue (NAT, n= 5) were enrolled in this study. As a very resourceful tool for proteome analysis and biomarker discovery, mass spectrometry (MS)-based methods were used to interrogate the proteome of each tumor in order to undisclosed differences trough which to develop faster and accurate diagnostics. The results achieved with this doctoral thesis include i) the accomplishment of an effective ultrasonic workflow to recover the proteome of optimal cutting temperature (OCT)-embedded tissues, ii) a novel analytical approach based on MALDI-MS profiling to distinguish chRCC from RO, iii) a 109-protein panel to discriminate between chRCC and RO and NAT, iv) a top 24-protein panel to diagnose ccRCC, pRCC, chRCC and RO based on absolute concentration values, v) the translation and validation of three promising biomarkers by immunohistochemical analysis, and vi) an approach for phosphopeptide enrichment. This work brings new insights into the different mechanisms underlying formation of these tumors as well as it provides valuable information to improve clinical diagnosis by opening new avenues for immunohistochemistry and mass spectrometry-based approaches.
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Book chapters on the topic "Proteomics, Urine, Renal Cell Carcinoma"

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Craven, Rachel A., and Rosamonde E. Banks. "Understanding and Managing Renal Cell Carcinoma: Can Proteomic Studies Contribute to Clinical Practice?" In Proteomics in Nephrology - Towards Clinical Applications, 88–106. Basel: KARGER, 2008. http://dx.doi.org/10.1159/000125936.

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"Renal Cell Carcinoma (RCC)." In Encyclopedia of Genetics, Genomics, Proteomics and Informatics, 1669. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6754-9_14372.

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"RCC (renal cell carcinoma, human chromosome 3p14.2)." In Encyclopedia of Genetics, Genomics, Proteomics and Informatics, 1637. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6754-9_14153.

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Conference papers on the topic "Proteomics, Urine, Renal Cell Carcinoma"

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Lin, Selena, Jennifer A. Linehan, Ruby Kuang, Selvi Guharaj, Timothy G. Wilson, and Dave SB Hoon. "Abstract 1595: Detection of tumor-derived DNA in urine cell-free DNA of pre-operative renal cell carcinoma patients." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-1595.

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Meng, Wei, Hansjuerg Alder, Kirsteen Maclean, Simon Kirste, Petra Stegmaier, Anca Grosu, Arnab Chakravarti, and Tim Lautenschlaeger. "Abstract 889: MicroRNA-21-5p upregulation in urine samples serves as novel biomarkers for early stage renal cell carcinoma patients diagnosis." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-889.

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