Journal articles: '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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Pastore, A. L., G. Palleschi, L. Silvestri, D. Moschese, S. Ricci, V. Petrozza, A. Carbone, and A. Di Carlo. "Serum and Urine Biomarkers for Human Renal Cell Carcinoma." Disease Markers 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/251403.

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Renal cell carcinoma (RCC) diagnosis is mostly achieved incidentally by imaging provided for unrelated clinical reasons. The surgical management of localized tumors has reported excellent results. The therapy of advanced RCC has evolved considerably over recent years with the widespread use of the so-called “targeted therapies.” The identification of molecular markers in body fluids (e.g., sera and urine), which can be used for screening, diagnosis, follow-up, and monitoring of drug-based therapy in RCC patients, is one of the most ambitious challenges in oncologic research. Although there are some promising reports about potential biomarkers in sera, there is limited available data regarding urine markers for RCC. The following review reports some of the most promising biomarkers identified in the biological fluids of RCC patients.

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Czyzyk-Krzeska, Maria F., Julio A. Landero Figueroa, Shuchi Gulati, John T. Cunningham, Jarek Meller, Behrouz ShamsaeI, Bhargav Vemuri, and David R. Plas. "Molecular and Metabolic Subtypes in Sporadic and Inherited Clear Cell Renal Cell Carcinoma." Genes 12, no. 3 (March 9, 2021): 388. http://dx.doi.org/10.3390/genes12030388.

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The promise of personalized medicine is a therapeutic advance where tumor signatures obtained from different omics platforms, such as genomics, transcriptomics, proteomics, and metabolomics, in addition to environmental factors including metals and metalloids, are used to guide the treatments. Clear cell renal carcinoma (ccRCC), the most common type of kidney cancer, can be sporadic (frequently) or genetic (rare), both characterized by loss of the von Hippel-Lindau (VHL) gene that controls hypoxia inducible factors. Recently, several genomic subtypes were identified with different prognoses. Transcriptomics, proteomics, metabolomics and metallomic data converge on altered metabolism as the principal feature of the disease. However, in view of multiple biochemical alterations and high level of tumor heterogeneity, identification of clearly defined subtypes is necessary for further improvement of treatments. In the future, single-cell combined multi-omics approaches will be the next generation of analyses gaining deeper insights into ccRCC progression and allowing for design of specific signatures, with better prognostic/predictive clinical applications.

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Frantsiyants, E. M., N. D. Ushakova, D. A. Rozenko, N. N. Popova, A. D. Rozenko, and A. V. Shulga. "Markers of structural and cellular renal damage in localized renal cell carcinoma before treatment." South Russian Journal of Cancer 3, no. 1 (February 21, 2022): 31–39. http://dx.doi.org/10.37748/2686-9039-2022-3-1-4.

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Purpose of the study. The purpose of the study was to analyze parameters of molecular markers of structural and cellular renal damage in localized renal cell carcinoma (RCC) with determining the nature of the initial abnormalities in the kidney functional state before the treatment.Patients and methods. The study included 46 patients receiving elective surgical treatment for localized renal cancer in the Department of Oncourology, National Medical Research Centre for Oncology. The comparison group included the clinical and laboratory data of 13 healthy people comparable with the RCC patients in terms of age and gender. Cystatin C, IL‑18, KIM‑1, L-FABP, NGAL were determined in blood and urine in all patients.Results. Evaluation of the kidney functional state of RCC patients showed that the initial values of serum creatinine and the glomerular filtration rate were similar to the reference levels in healthy people, but statistically significant differences were found in the ratios of cystatin C concentrations in the blood and urine in all patients, compared with normal values. Determination of L-FABP indices in RCC patients showed that their levels were 2.5 times higher than normal values, and the urine concentration of IL‑18 was 1.7 times higher than normal values (p < 0.05). Blood and urine levels of NGAL and KIM‑1 did not differ significantly from the comparison group.Conclusions. The development of localized RCC is accompanied by the formation of tubulointerstitial dysfunction with impaired renal filtration capacity. All RCC patients showed elevated endogenous markers of structural and cellular renal damage – cystatin C, L-FABP, and IL‑18.

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Nuzzo, Pier Vitale, Jacob E. Berchuck, Sandor Spisak, Keegan Korthauer, Amin Nassar, Sarah Abou Alaiwi, Ankur Chakravarthy, et al. "Sensitive detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes." Journal of Clinical Oncology 38, no. 6_suppl (February 20, 2020): 728. http://dx.doi.org/10.1200/jco.2020.38.6_suppl.728.

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728 Background: Improving early cancer detection has the potential to significantly reduce cancer-related mortality. Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMedDIP-seq) is a highly sensitive, low-input, cost-efficient and bisulfite-free assay capable of detecting and classifying various tumor types. We tested the feasibility of cfMeDIP-seq to detect RCC in plasma samples and, for the first time, in urine cell-free DNA (cfDNA), with an emphasis on early-stage disease. Methods: We performed cfMeDIP-seq on 117 samples (72 plasma and 45 urine samples): 68 stage I-IV RCC cases pre-nephrectomy, 21 stage IV urothelial bladder cancer (UBC) plasma samples from 15 patients, and 28 healthy cancer-free controls. 60.5% of plasma samples and 66.7% of urine samples came from patients with TNM Stage I/II disease. cfDNA was immunoprecipitated and enriched using an antibody targeting 5-methylcytosine and amplified to create a sequence-ready library. The top differentially methylated regions (DMRs) which partitioned RCC and control samples or UBC were used to train a regularized binomial generalized linear model using 80% of the samples as a training set. The 20% of withheld test samples were then assigned a probability of being RCC or control. This process was repeated 100 times. This was performed using both plasma and urine cfDNA samples. Results: We identified 89,799 DMRs in plasma samples and 38,462 DMRs in urine samples. Iterative training and classification of held out samples, using the 300 DMRs which partitioned RCC and control samples, resulted in a mean AUROC of 0.990 (95% CI 0.984-0.997) in plasma samples and 0.791 (95% CI 0.759-0.823) in urine samples. Classification performance between tumor types was evaluated comparing plasma cfDNA from patients with RCC and UBC, resulting in a mean AUROC of 0.954 (95% CI 0.940-0.969). Conclusions: cfMeDIP-seq is a powerful tool for genome-wide discovery of non-invasive DNA methylation biomarkers. This is the first independent validation of plasma cfMeDIP-seq, demonstrating near-perfect classification of RCC in a cohort enriched for patients with early-stage disease and the potential of urine cfDNA methylome-based biomarkers for cancer detection.

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Bosso, Niccolò, Clizia Chinello, Stefano Carlo Maria Picozzi, Erica Gianazza, Veronica Mainini, Carmen Galbusera, Francesca Raimondo, et al. "Human urine biomarkers of renal cell carcinoma evaluated by ClinProt." PROTEOMICS - CLINICAL APPLICATIONS 2, no. 7-8 (July 2008): 1036–46. http://dx.doi.org/10.1002/prca.200780139.

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Seliger, B., R. Lichtenfels, C. Recktenwald, S. Dressler, D. Atkins, and S. Stevanovic. "Candidate biomarkers in renal cell carcinoma." Journal of Clinical Oncology 29, no. 7_suppl (March 1, 2011): 405. http://dx.doi.org/10.1200/jco.2011.29.7_suppl.405.

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405 Background: Renal cell carcinoma (RCC) represents a heterogeneous disease with widely varying prognosis. Therefore, the screening for biomarkers, which allow the diagnosis as well as the assessment of the individual risk of disease progression and mortality are a prerequisite for the selection of patients for different modes of therapies and the implementation of individually tailored surveillance protocols. Methods: Various proteome-based technologies such as 2DE-based proteomics, PROTEOMEX or ligandomics in combination with mass spectrometry have been applied. Bioinformatic data mining led to the categorization and priorization of the respective target lists. Selected candidate targets were further independently verified by qRT-PCR, Western blot and/or immunohistochemistry. Results: A large series of differentially expressed/immunoreactive proteins have been identified in clear cell RCC when compared to normal kidney epithelium. With the different approaches distinct sets of potential candidate targets were defined and categorized into different protein families and functions and according to their cellular localization. Moreover, the limited sharing rates between the respective target lists demonstrate their complementarity. Some selected markers were further validated by qRT-PCR, Western blot analysis and/or immunohistochemical stainings of tissue micro arrays comprised of RCC lesions of different TNM classification and histology revealing distinct expression pattern in regard to the RCC subtype, tumor grading,staging or additional molecular features. Using the ligandomics approach proteins have been identified, which were able to mount an immune response in vitro. Conclusions: Some candidate markers might have the potential to be used as diagnostic and prognostic factors if not as novel targets for therapy and thus could be employed for the expression profiling of a larger series of RCC patients. No significant financial relationships to disclose.

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Lalhruaizela, Samuel, Zothansanga Zadeng, and Lal Hruaitluanga. "Transitional cell carcinoma of the renal pelvis masquerading as renal tuberculosis." International Surgery Journal 7, no. 4 (March 26, 2020): 1313. http://dx.doi.org/10.18203/2349-2902.isj20201015.

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We report a case of transitional cell carcinoma of the right renal pelvis mimicking the signs, symptoms and radiological findings of renal tuberculosis (TB). She had been diagnosed initially for urinary tract infection and radiological diagnosis initially was more towards renal TB and urine cytology and cultures were normal. Specific investigations for tuberculosis all showed negative results. But as neoplasia could not be ruled out by ureterorenoscopy due to presence of multiple ureteric strictures, decision was taken for an exploratory surgery. During surgery it was found that there was a tumour in the upper pole of kidney involving the renal pelvis and was found to be papillary transitional cell carcinoma on histopathological examination.

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Gómez Del Cañizo, C., Nicolás V. Díez, I. Ruppén-Cañas, V. Gómez Dos Santos, P. Ximénez-Embún, Rodríguez S. Álvarez, Palacios V. Hevia, et al. "298 Utility of quantitative proteomics techniques to identify renal cell carcinoma biomarkers." European Urology Supplements 13, no. 1 (April 2014): e298-e298a. http://dx.doi.org/10.1016/s1569-9056(14)60293-1.

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Jones, Jon, and Allan J. Pantuck. "Genomics and proteomics in renal cell carcinoma: Diagnosis, prognosis, and treatment selection." Current Urology Reports 9, no. 1 (January 2008): 9–14. http://dx.doi.org/10.1007/s11934-008-0004-5.

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Dudek, Alexandra, Lauren Appleyard, Tim S. O'Brien, Simon Chowdhury, Penny Champion, Ben Challacombe, Gordon Kooiman, and Guy Carpenter. "Salivary markers in renal cell carcinoma." Journal of Clinical Oncology 32, no. 4_suppl (February 1, 2014): 489. http://dx.doi.org/10.1200/jco.2014.32.4_suppl.489.

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489 Background: Kidney cancer ranks number 8 among cancer diagnoses in the UK with around 9,600 new diagnoses made each year (Cancer Research UK. Risks and causes of kidney cancer. http://www.cancerresearchuk.org/cancer-help/type/kidney-cancer/about/risks-and-causes-of-kidney-cancer). This study aimed to identify overexpressed proteins in human saliva that could serve as markers for renal cell carcinoma. Methods: Saliva was collected from 144 participants (95 male and 28 female).; 123 RCC patients (85%) and 21 healthy controls (15%), Total salivary protein levels were determined by BCA protein assay. Then 10ug of total saliva protein were evaluated via Western blotting on 4-12% Bis-Tris SDS-PAGE gels. Blots were probed for albumin as well as for three proteins associated with RCC; profilin1, 14-3-3 zeta, and endogenous avidin binding protein (EABP). Additionally, 6 saliva samples were evaluated via quantitative proteomics in a Tandem mass tag (TMT) labelling experiment comparing 4 RCC patients vs. 2 renal cyst patients. Results: Profilin1 levels were determined visually on a scale of 0 to 3 depending on band intensities on Western blots. Cancer patients had a higher percentage of levels 2 and 3 with 62 patients (50.4%). The control group only had 2 patients at level 2 (9.5%) and none at level 3. No difference in profilin1 levels was seen between metastatic vs. non-metastatic disease. Differences were seen in gender and histology, with female and non-CC patients having higher profilin levels. There is a potential link between profilin1 levels and surgical or drug treatment. 14-3-3 zeta could not be detected in saliva with these analyses. Albumin was present across all samples. EABP was found in 40.6% of cancer patients vs. 0% of controls; however no clear trend was seen with respect to disease burden, histology, or gender. Proteomic analysis gave a total of 33 hits showing raised protein levels of up to 20x higher in cancer patients vs. controls. Profilin1 was 2x and 14-3-3 zeta 5x more prevalent. Conclusions: This study has successfully identified profilin1 as a detectable salivary marker for renal cell carcinoma. [Table: see text]

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Zengin, Zeynep Busra, Nazli Dizman, Nicholas Salgia, Jeremy Jones, Jingbo Zhang, Yunchao Liu, Bing Xu, et al. "Circulating tumor DNA sequencing analysis of patients with metastatic renal cell carcinoma (mRCC)." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): e17100-e17100. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e17100.

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e17100 Background: Despite extensive work to characterize genomic alterations (GAs) in metastatic renal cell carcinoma (mRCC), GAs are not currently used for treatment sequencing or selection. Circulating tumor DNA (ctDNA) in both blood and urine may elucidate potential mRCC biomarkers through a minimally invasive approach. We aimed to validate previous blood-based ctDNA studies (Pal et al Eur Urol 2017) and compare detection rates of clinically relevant GAs in plasma and urine. Methods: From a single institution, patients (pts) with mRCC were recruited to provide a plasma and urine specimen. ctDNA next-generation sequencing was performed using an investigational 120-gene panel, and we limited our assessment to 7 GAs with biological relevance in RCC ( VHL, MTOR, PIK3CA, TSC2, MET, AKT1, TSC1). Further, only pathogenic alterations previously recognized in RCC and cited in the Catalogue of Somatic Mutations in Cancer (COSMIC) database were considered. Clinicopathologic variables, treatment type and response to therapy were collected from an institutional mRCC patient database. Concordance analysis was performed at the gene level between blood and urine using previously published approaches (Chae et al Oncotarget 2016). Results: 50 pts (40M:10F) were enrolled with a median age of 65. 40 pts (80%) had clear cell histology, while the remainder were papillary (12%), chromophobe (4%) or other (4%). Pts received a median of 1 line of therapy (range, 0-7). GAs were identified in 45 pts (90%) in blood and in 45 pts (90%) in urine . Applying the above criteria, the most frequently observed GAs in blood specimens were TSC2 (9%), MTOR (4%), and VHL (2%). The most frequently observed GAs in urine were VHL (4%) and MTOR (2%). The rate of concordance between blood- and urine-detected GAs was 93%. Of pts bearing mTOR pathway alterations in blood or urine, 3 received everolimus-based therapy. All 3 pts remain on therapy at 10.4, 13.8 and 14.0 months, respectively. Conclusions: Biologically relevant GAs can be detected in pts with mRCC using blood and urine. Our methodology showed high concordance between both platforms. Consistent with prior reports, ctDNA assessment of pts with pretreated mRCC shows a higher frequency of TOR pathway alterations and a lower frequency of VHL mutation.

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Nuzzo, Pier Vitale, Jacob E. Berchuck, Keegan Korthauer, Sandor Spisak, Amin H. Nassar, Sarah Abou Alaiwi, Ankur Chakravarthy, et al. "Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes." Nature Medicine 26, no. 7 (June 22, 2020): 1041–43. http://dx.doi.org/10.1038/s41591-020-0933-1.

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Raimondo, Francesca, Samuele Corbetta, Andrea Savoia, Clizia Chinello, Marta Cazzaniga, Francesco Rocco, Silvano Bosari, et al. "Comparative membrane proteomics: a technical advancement in the search of renal cell carcinoma biomarkers." Molecular BioSystems 11, no. 6 (2015): 1708–16. http://dx.doi.org/10.1039/c5mb00020c.

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Koch, Even, Kenneth Finne, Øystein Eikrem, Lea Landolt, Christian Beisland, Sabine Leh, Nicolas Delaleu, et al. "Transcriptome-proteome integration of archival human renal cell carcinoma biopsies enables identification of molecular mechanisms." American Journal of Physiology-Renal Physiology 316, no. 5 (May 1, 2019): F1053—F1067. http://dx.doi.org/10.1152/ajprenal.00424.2018.

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Renal cell cancer is among the most common forms of cancer in humans, with around 35,000 deaths attributed to kidney carcinoma in the European Union in 2012 alone. Clear cell renal cell carcinoma (ccRCC) represents the most common form of kidney cancer and the most lethal of all genitourinary cancers. Here, we apply omics technologies to archival core biopsies to investigate the biology underlying ccRCC. Knowledge of these underlying processes should be useful for the discovery and/or confirmation of novel therapeutic approaches and ccRCC biomarker development. From partial or full nephrectomies of 11 patients, paired core biopsies of ccRCC-affected tissue and adjacent (“peritumorous”) nontumor tissue were both sampled and subjected to proteomics analyses. We combined proteomics results with our published mRNA sequencing data from the same patients and with published miRNA sequencing data from an overlapping patient cohort from our institution. Statistical analysis and pathway analysis were performed with JMP Genomics and Ingenuity Pathway Analysis (IPA), respectively. Proteomics analysis confirmed the involvement of metabolism and oxidative stress-related pathways in ccRCC, whereas the most affected pathways in the mRNA sequencing data were related to the immune system. Unlike proteomics or mRNA sequencing alone, a combinatorial cross-omics pathway analysis approach captured a broad spectrum of biological processes underlying ccRCC, such as mitochondrial damage, repression of apoptosis, and immune system pathways. Sirtuins, immunoproteasome genes, and CD74 are proposed as potential targets for the treatment of ccRCC.

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Mahadita, Gede Wira, and Yenny Kandarini. "Wunderlich syndrome pada penderita clear cell renal cell carcinoma." Jurnal Penyakit Dalam Udayana 4, no. 2 (December 30, 2020): 24–30. http://dx.doi.org/10.36216/jpd.v4i2.139.

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Wunderlich's syndromes is a collection of symptoms consisting of pain, palpable mass in the flank region, hematuria associated with spontaneous renal bleeding. Renal cell carcinoma (RCC) is defined as a group of malignancies originating from the epithelium of the renal tubules. Reportedly a man, aged 47 years, with complaints of pain in the waist and upper left abdomen, accompanied by reddish urine since 3 days before being admitted to the hospital, but also experienced one month ago. On physical examination, there was a solid mass in the abdomen accompanied by tenderness. Ultrasound examination of the upper-lower abdomen showed a solid lobulated mass of impression originating from the left kidney. MSCT examination found a mass of the left kidney measuring about 11.2 cm x 16.7 cm x 20.2 cm which caused enhancement of the left renal artery. The patient then underwent a radical nephrectomy, found a left kidney tumor measuring 20 cm which was attached to the diaphragm. The result of the PA histo examination, obtained tumor cells with an increased N / C ratio, polygonal to round oval shape, moderate pleimorphic core, hyperchromatic, prominent core children, wide clear vacuole cytoplasm and partly eosinophilic with the impression of Clear Cell Renal Cell Carcinoma Grade. III. Patient diagnosed as CCRCC with wunderlich syndrome manifestation. .Further management was planned for systemic chemotherapy or radiation treatment, but the patient refused. The patient was discharged on the 20th day of treatment in good condition.

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Hakimi, A. Ari, Chung-Han Lee, Justin R. Cross, Zhen Li, Yang Chen, Bruce Neri, Victor E. Reuter, Robert John Motzer, Paul Russo, and James Hsieh. "Global metabolic profiling of clear cell renal cell carcinoma." Journal of Clinical Oncology 31, no. 6_suppl (February 20, 2013): 379. http://dx.doi.org/10.1200/jco.2013.31.6_suppl.379.

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379 Background: Recent data has suggested that metabolomic profiling in various cancer states may lead to novel biomarkers and innovative therapeutic strategies. We profiled the metabolome of 140 clear cell renal cell carcinomas (ccRCC) and matched normal tissue of various clinical stages. Methods: In collaboration with Metabolon, Inc., 140 clinically annotated tumors were subject to three global metabolic profiling mass spectroscopy platforms. Demographic, clinical, and pathologic data were recorded and patients were grouped into local, locally advanced and metastatic categories using clinical and pathologic criteria. Welch’s paired two sample t tests were used to identify biochemicals that differed significantly between the tumor and normal tissue groups (p value ≤0.001). Supervised clustering using random forest analysis was performed to identify metabolites that differentiated tumors and normals, as well as those associated with tumor progression. Results: A total of 877 biochemicals (including 300 unnamed metabolites) were identified. Several known cancer metabolic pathways were found to be altered consistent with the Warburg effect including accelerated glycolysis and pentose phosphate pathway (PPP), increased lipogenesis, elevated polyamine production, altered nitrogen handling, cell membrane metabolism, inflammation, and oxidative stress. Interestingly, several novel unexpected pathways were found to be altered and associated with disease progression including alterations in the 2-hydroxyglutarate pathway (2HG). 2HG levels were increased over 6 fold in tumors compared to normal and increased further with respect to disease progression (p = 0.019, q = 0.055). Several promising biomarker candidates were identified as well. Conclusions: We provide the first report of large scale metabolomic analysis of ccRCC, revealing several known and novel alterations to cancer-specific metabolic pathways. Investigation of novel pathway biology and biomarker validation in blood and urine samples is currently underway.

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Oto, Julia, Álvaro Fernández-Pardo, Marta Roca, Emma Plana, Mª José Solmoirago, José V. Sánchez-González, César D. Vera-Donoso, et al. "Urine metabolomic analysis in clear cell and papillary renal cell carcinoma: A pilot study." Journal of Proteomics 218 (April 2020): 103723. http://dx.doi.org/10.1016/j.jprot.2020.103723.

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Cimadamore, Alessia, Silvia Gasparrini, Francesco Massari, Matteo Santoni, Liang Cheng, Antonio Lopez-Beltran, Marina Scarpelli, and Rodolfo Montironi. "Emerging Molecular Technologies in Renal Cell Carcinoma: Liquid Biopsy." Cancers 11, no. 2 (February 7, 2019): 196. http://dx.doi.org/10.3390/cancers11020196.

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: Liquid biopsy, based on the circulating tumor cells (CTCs) and cell-free nucleic acids has potential applications at multiple points throughout the natural course of cancer, from diagnosis to follow-up. The advantages of doing ctDNA assessment vs. tissue-based genomic profile are the minimal procedural risk, the possibility to serial testing in order to monitor disease-relapse and response to therapy over time and to reduce hospitalization costs during the entire process. However, some critical issues related to ctDNA assays should be taken into consideration. The sensitivity of ctDNA assays depends on the assessment technique and genetic platforms used, on tumor-organ, stage, tumor heterogeneity, tumor clonality. The specificity is usually very high, whereas the concordance with tumor-based biopsy is generally low. In patients with renal cell carcinoma (RCC), qualitative analyses of ctDNA have been performed with interesting results regarding selective pressure from therapy, therapeutic resistance, exceptional treatment response to everolimus and mutations associated with aggressive behavior. Quantitative analyses showed variations of ccfDNA levels at different tumor stage. Compared to CTC assay, ctDNA is more stable than cells and easier to isolate. Splice variants, information at single-cell level and functional assays along with proteomics, transcriptomics and metabolomics studies can be performed only in CTCs.

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Guedes De Pinho, P., M. Monteiro, N. Moreira, C. Jerónimo, R. Henrique, M. Bastos, A. Gil, and M. Carvalho. "Renal cell carcinoma detection by analysis of Volatile Organic Compounds in urine." Toxicology Letters 258 (September 2016): S282. http://dx.doi.org/10.1016/j.toxlet.2016.06.1984.

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Guliev, B. G. "Urinary fistulas after partial nephrectomy in renal cell carcinoma." Vestnik Urologii 9, no. 2 (July 10, 2021): 111–24. http://dx.doi.org/10.21886/2308-6424-2021-9-2-111-124.

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Urinary fistulas after partial nephrectomy are rare complications of this operation. There are various reasons for their development, prevention and treatment. This review analyzes the results of the cases' prevalence of urine leakage after partial nephrectomy with various approaches, occurrence's predictors of urinary fistulas, possible ways of their intraoperative prevention and treatment methods. The obtained data show that the size of tumors, their endophytic nature and proximity to the kidney pelvicalyceal system, as well as suturing of its defect, can be predictors of the development of urinary fistulas (UFs). Some authors point to the influence of long ischemia time and high blood loss on the occurrence of UFs. The main method of treating UFs is ureteral stenting or percutaneous drainage of the kidney pelvicalyceal system. For long-term persistent UFs, the method of choice can be simultaneous introduction of 2 stents, retrograde or percutaneous injection of fibrin glue, percutaneous cryoablation of the UFs.

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Kazmierczak, S. C., F. Van Lente, A. M. McHugh, and W. E. Katzin. "Macroamylasemia with a markedly increased amylase clearance ratio in a patient with renal cell carcinoma." Clinical Chemistry 34, no. 2 (February 1, 1988): 435–38. http://dx.doi.org/10.1093/clinchem/34.2.435.

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Abstract We report hyperamylasemia, macroamylasemia, and a markedly increased amylase clearance/creatinine clearance ratio in a patient with renal cell carcinoma. Serum amylase activity was characterized as macroamylase by gel exclusion chromatography. Electrophoretic separation revealed an atypical band of amylase, migrating anodal to the S2 control fraction. Electrophoresis of urine revealed the presence of both S1 and S2 fractions, but not the atypical band found in serum. Quantification of the salivary- and pancreatic-type amylase fractions showed amylase in urine to be 100% salivary. Immunofixation disclosed the macroamylase to consist of an immune complex between amylase and IgA-lambda antibody. Binding-capacity studies showed that the serum immunoglobulin was present in excess and could bind 46% and 49% additional S-type amylase activity derived from saliva and the patient's urine, respectively. The amylase clearance/creatinine clearance ratio was markedly supranormal (0.134), unexpected in a patient with macroamylasemia. A biopsy specimen of the renal cell tumor was found to contain significant salivary-type amylase activity. These results suggest production of amylase by tumor tissue in the renal carcinoma and secretion of S-type amylase into the patient's urine. Evidently, macroamylase should be confirmed by gel exclusion chromatography.

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Bifarin, Olatomiwa O., David A. Gaul, Samyukta Sah, Rebecca S. Arnold, Kenneth Ogan, Viraj A. Master, David L. Roberts, et al. "Urine-Based Metabolomics and Machine Learning Reveals Metabolites Associated with Renal Cell Carcinoma Stage." Cancers 13, no. 24 (December 13, 2021): 6253. http://dx.doi.org/10.3390/cancers13246253.

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Urine metabolomics profiling has potential for non-invasive RCC staging, in addition to providing metabolic insights into disease progression. In this study, we utilized liquid chromatography-mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and machine learning (ML) for the discovery of urine metabolites associated with RCC progression. Two machine learning questions were posed in the study: Binary classification into early RCC (stage I and II) and advanced RCC stages (stage III and IV), and RCC tumor size estimation through regression analysis. A total of 82 RCC patients with known tumor size and metabolomic measurements were used for the regression task, and 70 RCC patients with complete tumor-nodes-metastasis (TNM) staging information were used for the classification tasks under ten-fold cross-validation conditions. A voting ensemble regression model consisting of elastic net, ridge, and support vector regressor predicted RCC tumor size with a R2 value of 0.58. A voting classifier model consisting of random forest, support vector machines, logistic regression, and adaptive boosting yielded an AUC of 0.96 and an accuracy of 87%. Some identified metabolites associated with renal cell carcinoma progression included 4-guanidinobutanoic acid, 7-aminomethyl-7-carbaguanine, 3-hydroxyanthranilic acid, lysyl-glycine, glycine, citrate, and pyruvate. Overall, we identified a urine metabolic phenotype associated with renal cell carcinoma stage, exploring the promise of a urine-based metabolomic assay for staging this disease.

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Sreedharan, Shilpa, John A. Petros, Viraj A. Master, Kenneth Ogan, John G. Pattaras, David L. Roberts, Fei Lian, and Rebecca S. Arnold. "Aquaporin-1 Protein Levels Elevated in Fresh Urine of Renal Cell Carcinoma Patients: Potential Use for Screening and Classification of Incidental Renal Lesions." Disease Markers 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/135649.

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Introduction and Objectives. There are over 65,000 new cases of renal cell carcinoma (RCC) each year, yet there is no effective clinical screening test for RCC. A single report claimed no overlap between urine levels of aquaporin-1 (AQP1) in patients with and without RCC (Mayo Clin Proc. 85:413, 2010). Here, we used archived and fresh RCC patient urine to validate this report.Methods. Archived RCC, fresh prenephrectomy RCC, and non-RCC negative control urines were processed for Western blot analysis. Urinary creatinine concentrations were quantified by the Jaffe reaction (Nephron 16:31, 1976). Precipitated protein was dissolved in 1x SDS for a final concentration of 2 μg/µL creatinine.Results. Negative control and archived RCC patient urine failed to show any AQP1 protein by Western blot analysis. Fresh RCC patient urine is robustly positive for AQP1. There was no signal overlap between fresh RCC and negative control, making differentiation straightforward.Conclusions. Our data confirms that fresh urine of patients with RCC contains easily detectable AQP1 protein. However, archival specimens showed an absence of detectable AQP1 indistinguishable from negative control. These findings suggest that a clinically applicable diagnostic test for AQP1 in fresh urine may be useful for detecting RCC.

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Bouchalova, Pavla, Jindrich Beranek, Petr Lapcik, David Potesil, Jan Podhorec, Alexandr Poprach, and Pavel Bouchal. "Transgelin Contributes to a Poor Response of Metastatic Renal Cell Carcinoma to Sunitinib Treatment." Biomedicines 9, no. 9 (September 3, 2021): 1145. http://dx.doi.org/10.3390/biomedicines9091145.

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Renal cell carcinoma (RCC) represents about 2–3% of all cancers with over 400,000 new cases per year. Sunitinib, a vascular endothelial growth factor tyrosine kinase receptor inhibitor, has been used mainly for first-line treatment of metastatic clear-cell RCC with good or intermediate prognosis. However, about one-third of metastatic RCC patients do not respond to sunitinib, leading to disease progression. Here, we aim to find and characterize proteins associated with poor sunitinib response in a pilot proteomics study. Sixteen RCC tumors from patients responding (8) vs. non-responding (8) to sunitinib 3 months after treatment initiation were analyzed using data-independent acquisition mass spectrometry, together with their adjacent non-cancerous tissues. Proteomics analysis quantified 1996 protein groups (FDR = 0.01) and revealed 27 proteins deregulated between tumors non-responding vs. responding to sunitinib, representing a pattern of deregulated proteins potentially contributing to sunitinib resistance. Gene set enrichment analysis showed an up-regulation of epithelial-to-mesenchymal transition with transgelin as one of the most significantly abundant proteins. Transgelin expression was silenced by CRISPR/Cas9 and RNA interference, and the cells with reduced transgelin level exhibited significantly slower proliferation. Our data indicate that transgelin is an essential protein supporting RCC cell proliferation, which could contribute to intrinsic sunitinib resistance.

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Nuzzo, Pier Vitale, Jacob E. Berchuck, Keegan Korthauer, Sandor Spisak, Amin H. Nassar, Sarah Abou Alaiwi, Ankur Chakravarthy, et al. "Author Correction: Detection of renal cell carcinoma using plasma and urine cell-free DNA methylomes." Nature Medicine 26, no. 10 (September 7, 2020): 1663. http://dx.doi.org/10.1038/s41591-020-1078-y.

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Koide, Takuya. "THE CLINICAL SIGNIFICANCE OF TISSUE, BLOOD AND URINE POLYAMINE IN RENAL CELL CARCINOMA." Japanese Journal of Urology 83, no. 8 (1992): 1228–37. http://dx.doi.org/10.5980/jpnjurol1989.83.1228.

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Bifarin, Olatomiwa O., David A. Gaul, Samyukta Sah, Rebecca S. Arnold, Kenneth Ogan, Viraj A. Master, David L. Roberts, et al. "Machine Learning-Enabled Renal Cell Carcinoma Status Prediction Using Multiplatform Urine-Based Metabolomics." Journal of Proteome Research 20, no. 7 (June 23, 2021): 3629–41. http://dx.doi.org/10.1021/acs.jproteome.1c00213.

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Falegan, Oluyemi, Mark Ball, Rustem Shaykhutdinov, Phillip Pieroraio, Farshad Farshidfar, Hans Vogel, Mohamad Allaf, and Matthew Hyndman. "Urine and Serum Metabolomics Analyses May Distinguish between Stages of Renal Cell Carcinoma." Metabolites 7, no. 1 (February 3, 2017): 6. http://dx.doi.org/10.3390/metabo7010006.

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Inouye, Brian M., George Chiang, Robert O. Newbury, and Nicholas Holmes. "Adolescent Xanthogranulomatous Pyelonephritis Mimicking Renal Cell Carcinoma on Urine Cytology: An Atypical Presentation." Urology 81, no. 4 (April 2013): 885–87. http://dx.doi.org/10.1016/j.urology.2012.12.019.

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Basu, Arnab, Kanthi Athreya Kollengode, Genevieve Danenberg, Hugh Manoli, Ali Rafatnia, Eesha Chakravartty, Alan L. Epstein, and Jacek K. Pinski. "MDSC clinical assay for cancer detection and monitoring in renal cell carcinoma." Journal of Clinical Oncology 36, no. 6_suppl (February 20, 2018): TPS713. http://dx.doi.org/10.1200/jco.2018.36.6_suppl.tps713.

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TPS713 Background: Human Myeloid Derived Suppressor Cells (MDSCs) have gained recognition as a significant population of cells that arise in cancer patients to mediate immune tolerance. Some studies have shown MDSC concentrations to be associated with overall survival and response to therapy in renal cell carcinoma. MDSCs comprise a heterogenous population that are yet to be fully characterized. We have identified a set of biomarkers uniquely expressed by the suppressive human MDSC phenotype and have developed an assay targeted to these markers. MDSCs are potentially a relatively cheap and easily performed screening and monitoring tool in cancers. This study will examine how a proprietary clinical assay works in detecting and monitoring MDSCs in blood and urine samples from patients with localized or metastatic renal cell cancer. Methods: The pilot research trial will enroll 63 subjects in a 1:1:1 ratio in three groups, normal controls over age 40 without evidence of any malignancy, patients with metastatic disease and localized renal cell carcinoma prior to nephrectomy. This sample size provides 80% power to detect a 1SD difference in MDSC concentrations in these groups on an F test. Blood and urine samples will be drawn at baseline and at 4 months for comparison. The percent CD33+ HLA-DRlow HIF1a+, CD33+ HLADRlow C/EBPb+, CD11b+ HLA-DRlow HIF1a+, and CD11b+ HLA-DRlow C/EBPb+cells as a fraction of PBMC will be determined. Primary Outcome Measures will be 1. Change in MDSC levels in patients with known localized renal cell carcinoma who undergo surgical treatment. 2. Change in MDSC level in patients with known metastatic renal cell carcinoma who initiate systemic treatment and 3. The direction and magnitude of the changes compared with radiographically assessed tumor burden. Secondary outcome measures are to assess MDSC level measurements in urine cytology analysis at baseline and after treatment to determine whether the two tests correlate in any of the 3 groups of patients defined in this study. Conclusion: This pilot study will examine if a MDSC clinical assay works in detecting and monitoring MDSCs. Recruitment is open to patients at the USC Cancer center and LAC+USC medical center. Clinical trial information: NCT02664883.

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Zhang, Xiao Li, Zheng Zhi Wu, Yun Xu, Ji Guo Wang, Yong Qiang Wang, Mei Qun Cao, and Chang Hao Wang. "Saliva proteomic analysis reveals possible biomarkers of renal cell carcinoma." Open Chemistry 18, no. 1 (August 3, 2020): 918–26. http://dx.doi.org/10.1515/chem-2020-0048.

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AbstractEarly diagnosis is a key to improve the prognosis of renal cell carcinoma (RCC); however, reliable RCC biomarkers are lacking in clinical practice. In this study, we used isobaric tags for relative and absolute quantification-based mass spectrometry to identify salivary proteins as biomarkers for the diagnosis of RCC. The objective of this study is to discover biomarkers from saliva by utilizing high-throughput quantitative proteomics approaches. Saliva proteins from 124 RCC patients and healthy individuals were identified and quantified. RCC putative biomarkers were verified by real-time polymerase chain reaction or enzyme-linked immunosorbent assay in a prevalidation sample set. Seventy-one differentially expressed salivary proteins were identified. Serotransferrin, haptoglobin, KRT9, and S100A9, which in previous studies were found to be most closely related to cancers, were selected as putative RCC biomarkers. Haptoglobin and S100A9 were significantly elevated in RCC compared with healthy control samples, although the expression of serotransferrin and KRT9 did not differ between the groups. Furthermore, receiver operating characteristic curves with a cut-off value of 75.49 ng/mL for S100A9 revealed a sensitivity of 87.10% and a specificity of 91.94% for discriminating RCC patients from healthy individuals. Salivary haptoglobin differentiated RCC patients from healthy controls with a sensitivity of 85.48% and specificity of 80.65% (cut-off value 43.02 µg/mL). These results provide experimental evidence to support S100A9 and haptoglobin as potential novel, noninvasive biomarkers for the diagnosis of RCC.

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He, Jinzhao, and Baoxue Yang. "Aquaporins in Renal Diseases." International Journal of Molecular Sciences 20, no. 2 (January 16, 2019): 366. http://dx.doi.org/10.3390/ijms20020366.

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Aquaporins (AQPs) are a family of highly selective transmembrane channels that mainly transport water across the cell and some facilitate low-molecular-weight solutes. Eight AQPs, including AQP1, AQP2, AQP3, AQP4, AQP5, AQP6, AQP7, and AQP11, are expressed in different segments and various cells in the kidney to maintain normal urine concentration function. AQP2 is critical in regulating urine concentrating ability. The expression and function of AQP2 are regulated by a series of transcriptional factors and post-transcriptional phosphorylation, ubiquitination, and glycosylation. Mutation or functional deficiency of AQP2 leads to severe nephrogenic diabetes insipidus. Studies with animal models show AQPs are related to acute kidney injury and various chronic kidney diseases, such as diabetic nephropathy, polycystic kidney disease, and renal cell carcinoma. Experimental data suggest ideal prospects for AQPs as biomarkers and therapeutic targets in clinic. This review article mainly focuses on recent advances in studying AQPs in renal diseases.

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Chu, Myeong Su. "Hemangioma in Renal Pelvis." Kosin Medical Journal 36, no. 2 (December 31, 2021): 175–79. http://dx.doi.org/10.7180/kmj.2021.36.2.175.

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<p>Hemangioma in the renal pelvis is a very rare benign tumor that may be mistaken for renal cell carcinoma. We present, herein, a case of a 59-year-old woman with a renal mass that was diagnosed as a cavernous hemangioma in the renal pelvis. The patient underwent intravenous pyelography, urine cytology, retrograde pyelography, kidney dynamic computed tomography (CT), and surgical excision.</p>

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Ribeiro, A., V. Sandim, D. Pereira, A. Ornellas, G. Domont, and G. Alves. "MP-14.10: Differential Proteomics of Renal Cell Carcinoma Tissues Aiming the Investigation of New Biomarkers." Urology 74, no. 4 (October 2009): S111. http://dx.doi.org/10.1016/j.urology.2009.07.861.

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Kaffenberger, Samuel D., Giovanni Ciriello, Andrew G. Winer, Martin Henner Voss, Jodi Kathleen Maranchie, Pheroze Tamboli, Kimryn Rathmell, et al. "Proteomic stratification of clear cell renal cell carcinoma utilizing The Cancer Genome Atlas (TCGA) with external validation." Journal of Clinical Oncology 33, no. 7_suppl (March 1, 2015): 406. http://dx.doi.org/10.1200/jco.2015.33.7_suppl.406.

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406 Background: Proteomics represents the ultimate convergence of DNA and expression alterations. We therefore sought to leverage TCGA reverse phase protein array (RPPA) data with an independent proteomic platform to identify druggable targets and pathways associated with prognosis in clear cell renal cell carcinoma (ccRCC). Methods: Unsupervised hierarchical consensus clustering was performed and differentially expressed proteins were identified for pathway analysis. Associations with clinicogenomic factors were assessed and Cox proportional hazards models were performed for disease-specific survival (DSS). Results: RPPA clustering of 324 patients from the ccRCC TCGA revealed 5 robust clusters characterized by alterations in specific pathways and divergent prognoses. Cluster 1 was characterized by poor DSS, decreased expression of receptor tyrosine kinases (RTK) and upregulation of the mTOR pathway. It was also associated with mTOR pathway genomic alterations, sarcomatoid histology and the ccb prognostic mRNA signature (all p<0.001). Cluster 2 was characterized by increased expression of RTKs and interestingly, had upregulation of the mTOR pathway with excellent DSS. After accounting for stage and grade, cluster designation remained independently associated with DSS (HR 0.23 for cluster 2, 95% CI 0.08-0.68; p=0.008). External validation was performed on a separate cohort of 189 patients with a different quantitative proteomics platform. A panel of phosphoproteins (pHER1, pHER2, pHER3, pSHC, pMEK, pAKT), highly discriminant between the most divergent RPPA clusters (1 and 2) was evaluated. Those at the highest quartile of activation in > 3 proteins were associated with improved DSS (HR 0.19, 95% CI 0.05-0.082; p=0.03). Patients with mTOR pathway activation segregated to those with coincident RTK activation (n=83) and those without (n=13). Conclusions: We have identified and validated proteomic signatures which cluster ccRCC patients into 5 prognostic groups. Furthermore, two distinct mTOR-activated clusters—one with high RTK activity and one with increased mTOR pathway genomic alterations were revealed, which may have prognostic and therapeutic implications.

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Ammon, A., M. H. Weber, I. Wallner, N. Marschner, M. Droese, H. J. Gröne, and W. Hiddemann. "Immunocytochemical determination of the tumor-associated glycoproteins MCA, CA 125 and BW 495/36-P in urine of patients with epithelial tumors of the kidney and urinary bladder." International Journal of Biological Markers 10, no. 1 (January 1995): 17–23. http://dx.doi.org/10.1177/172460089501000104.

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Pre-operative and, in some cases, post-operative urine samples from 29 patients with renal cell or urinary bladder carcinoma were compared to samples from 24 healthy persons and 10 patients with nephrolithiasis and 9 patients with other benign disorders of the efferent urinary tract. The specimens were examined for the presence of MCA, CA 125 and BW 495/36-P expressing epithelial cells. The urine concentrations of the soluble antigens MCA and CA 125 were determined simultaneously in urine samples from 35 patients with renal cell or urinary bladder carcinoma, 10 patients with cystitis and 30 healthy individuals. MCA and BW 495/36-P expressing epithelial cells were significantly increased in all pre-operative urine samples of the tumor patients compared to the group of healthy persons. This increase was also seen with CA 125-positive cells in patients with bladder carcinoma, not however in patients with renal cell carcinoma. BW 495/36-P positive cells were also found in both groups of tumor patients in greater numbers than in the patients with nephrolithiasis or other benign urinary tract disorders. Based on a specificity of 97% when compared to the control urine samples, the cytological determination of the antigens MCA, CA 125 and BW 495/36-P in urinary tract cells of all tumor patients revealed a sensitivity of 48%, 33% and 79% as well as a positive predictive value of 92%, 89% and 95%, respectively. The sensitivity of CA 125 increased to 67% upon isolated analysis of patients with bladder carcinoma. The majority of labelled cells were not identifiable as tumor cells morphologically and appeared as normal transitional epithelial cells. The urinary concentration of soluble MCA was greatest in healthy patients whereas the concentration of CA 125 was increased in patients with bladder carcinoma. Our results indicate that especially the determination of BW 495/36-P expressing epithelial cells could be a helpful supplement to the cytological examination of urinary epithelium with regard to renal cell and bladder carcinoma. Determination of CA 125-positive cells appears to be of diagnostic relevance only in cases of suspected bladder carcinoma.

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Zhao, An, Michel Péoc'h, Michèle Cottier, Christian Genin, Nicolas Mottet, and Guorong Li. "Cell-free RNA content in urine as a possible molecular diagnostic tool for clear cell renal cell carcinoma." International Journal of Cancer 136, no. 11 (November 28, 2014): 2610–15. http://dx.doi.org/10.1002/ijc.29313.

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Kanukoev, K. Yu, N. S. Sergeeva, T. A. Karmakova, N. V. Marshutina, M. P. Solokhina, K. M. Nyushko, B. Ya Alekseev, and A. D. Kaprin. "KIM-1 (kidney injury molecule 1) in the urine of renal cell carcinoma patients." Cancer Urology 16, no. 3 (November 19, 2020): 21–28. http://dx.doi.org/10.17650/1726-9776-2020-16-3-21-28.

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Objective: to assess the potential clinical significance of KIM-1 (kidney injury molecule 1) as a urinological marker for kidney cancer.Materials and methods. An enzyme-linked immunosorbent assay was used to assess urinary KIM-1 (uKIM-1 — kidney injury molecule 1) levels in 67 patients with renal cell carcinoma (RCC) and 36 healthy volunteers (a control group).Results. Both in patients and in healthy individuals, uKIM-1 levels were age independent. A difference between mean uKIM-1 values in RCC patients (2.4 ± 0.2 ng/ml) and the control group (0.7 ± 0.1 ng/ml) was statistically significant (p <0.0001). In RCC patients the higher uKIM-1 level was observed at more advanced clinical disease stages: the values increasedfrom 2.0 ± 0.2 ng/ml at the stage I and 3.0 ± 0.5 ng/ml at the stage II—III to 4.4 ± 1.2 ng/ml at the stage IV. In the group of patients with stage IRCC, most representative by the number of cases (n = 44) the uKIM-1 levels correlated with the tumor size and were increased in patients with different histological subtypes of the tumor, including clear cell, papillary and chromophobe RCC. After nephrectomy, a monotonous decrease in uKIM-1 level was observed, and after 6 days its values approached the mean value in the control group. Two days after kidney resection, uKIM-1 increased and then decreased, remaining elevated after 6 days.Conclusion. This study demonstrates that uKIM-1 can be attributed to potentially significant urine tumor-associated markers of RCC.

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Dubal, Sanjivani B., Saleem Pathuthara, Dulhan Ajit, Santosh Menon, and Shubhada V. Kane. "Case Report of Renal Cell Carcinoma Diagnosed in Voided Urine Confirmed by CD10 Immunocytochemistry." Acta Cytologica 55, no. 4 (2011): 372–76. http://dx.doi.org/10.1159/000326940.

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Haake, Scott M., Jiannong Li, Yun Bai, Fumi Kinose, Bin Fang, Eric A. Welsh, Roy Zent, et al. "Tyrosine Kinase Signaling in Clear Cell and Papillary Renal Cell Carcinoma Revealed by Mass Spectrometry–Based Phosphotyrosine Proteomics." Clinical Cancer Research 22, no. 22 (May 24, 2016): 5605–16. http://dx.doi.org/10.1158/1078-0432.ccr-15-1673.

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

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