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> Disorders > Neoplastic Process > Kidney Neoplasm

Kidney Neoplasm

Kidney Neoplasms are a group of cancerous growths that originate in the kidney.
They can range from benign tumors to highly malignant carcinomas.
Accurate identification and classification of kidney neoplasms is crucial for effective treatment and management.
This MeSH term provides a comprehensive overview of the various types of kidney neoplasms, their characteristics, and the latest advancements in diagnostic and therapeutic approaches.
Resarchers can leverage this information to enhance their understading of kidney cancer and develop more effective solutions for patieents.

Most cited protocols related to «Kidney Neoplasm»

1
Kidney Tumor Transcriptome Profiling
Cited 22 times
Gene expression profiling in 66 samples (26 conventional RCCs, 17 papillary RCCs, four chromophobe RCCs, four ROs, two collecting duct carcinomas, one mucinous and spindle cell tumor, four Wilms' tumors, one clear cell sarcoma of the kidney, one rhabdoid tumor of the kidney as well as four adult and two fetal normal kidneys) was obtained using HG-U133 Plus2.0 GeneChip oligonucleotide microarray (Affymetrix Inc.; see manufacturer's manual for detailed protocol) containing 54,675 probe sets that correspond to 38,500 genes (and > 47,400 transcripts). Total RNA was purified with Qiagen RNeasy Mini Kit (Qiagen), and the cRNA synthesis and hybridization was performed by the Genomics Core Facility of EMBL (Heidelberg, Germany). The stained arrays were scanned, and perfect match and mismatch features on the scanned microarray images were quantified using default settings in Microarray Suite 5.0 software (MAS 5.0, Affymetrix Inc.) yielding signal intensity for each probe on the array. The hybridization (raw) data have been deposited in NCBI's Gene Expression Omnibus repository http://www.ncbi.nih.gov/geo/ and are available under the accession number "GSE11151".
The robust multi-array average algorithm of R and RMA implementation in Bioconductor package http://www.bioconductor.org was used to perform preprocessing of the .CEL files, including background adjustment, quartile normalization, and summarization. Expression measurements were transformed by computing the base-two logarithm before further analysis. Relative expression profiles were generated from the individual tumor expression profiles and the mean expression values of the four individual normal adult kidney expression profiles.
Yusenko M.V., Kuiper R.P., Boethe T., Ljungberg B., van Kessel A.G, & Kovacs G. (2009). High-resolution DNA copy number and gene expression analyses distinguish chromophobe renal cell carcinomas and renal oncocytomas. BMC Cancer, 9, 152.
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Publication 2009
Acid Hybridizations, Nucleic Adult Anabolism Cells Chromophobia Clear Cell Sarcoma of Soft Tissue Collecting Duct Carcinoma of the Kidney Complementary RNA Fetus Gene Chips Gene Expression Genes Hypernephroid Carcinomas Kidney Kidney Neoplasm Microarray Analysis Mucins Neoplasms Nephroblastoma Oligonucleotide Arrays
2
Pediatric Malignant Rhabdoid Tumor Genomics
Cited 20 times

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Publication 2016
BLOOD Cell Lines Child Cranium DNA Library Human Embryonic Stem Cells Kidney Kidney Neoplasm Liver Malignant Neoplasms Neoplasms Patients Therapeutics Tissues Wilms tumor and radial bilateral aplasia
3
Identifying Cirrhosis and Complications in Administrative Data
Cited 12 times
The primary outcomes of cirrhosis, decompensated cirrhosis and HCC were defined using relevant physician visit, emergency department visit, hospital diagnosis, procedure, death and pathology codes (Table 1). A secondary outcome of 2-year all-cause mortality following last clinic visit was reported as an overall measure of patient severity of illness.
We built a series of diagnostic algorithms for each outcome ranging from simple (e.g. a single physician visit code) to more complex. This was done to identify the most parsimonious algorithms that were also highly sensitive and/or specific. We aimed to utilize all available health administrative data, and include both hospital-based and outpatient physician visits in our algorithms. Data sources were searched for relevant codes ten years prior to two years following the date of last clinical assessment (up to March 31st, 2014 for TCLD and August 31st, 2013 for KHSC).
Cirrhosis algorithms ranged from cirrhosis codes only to combinations with codes for chronic liver disease or any complication (decompensation events, HCC or liver transplant). Algorithms were combined in such a way as to make them more sensitive (“or” combinations) or specific (“and” combinations). As physician visit codes were noted to be less specific, we aimed to increase specificity by combining two or more such codes with hospitalization codes.
Decompensation algorithms included hospital diagnostic and death codes for portal hypertension, hepatorenal syndrome, jaundice, hepatic coma, hepatic failure, bleeding esophageal varices, gastric varices (bleeding not specified), and ascites. There were no physician visit codes available for decompensation events. We included procedure codes for endoscopy or insertion of Sengstaken tube for upper gastrointestinal bleeding, transjugular intrahepatic portosystemic shunt, and paracentesis. Since several of these procedures could occur for reasons other than decompensated cirrhosis (such as bleeding from an ulcer, or ascites secondary to an extra-hepatic malignancy), we tested combinations of procedure codes with a cirrhosis code from a physician visit.
Hepatocellular carcinoma algorithms ranged from simple (a single physician visit code) to more complex. We tested several combinations in order to optimise both sensitivity and specificity. We combined physician visit codes, hospital diagnostic codes, and cause of death codes. Further, we included procedure codes for radiofrequency ablation. Since this procedure can also be used to ablate tumours outside the liver (e.g., renal tumours), we combined ablation codes with an outpatient code for cirrhosis. Finally, we tested our results with and without anatomical and pathology codes from the Ontario Cancer Registry.
Lapointe-Shaw L., Georgie F., Carlone D., Cerocchi O., Chung H., Dewit Y., Feld J.J., Holder L., Kwong J.C., Sander B, & Flemming J.A. (2018). Identifying cirrhosis, decompensated cirrhosis and hepatocellular carcinoma in health administrative data: A validation study. PLoS ONE, 13(8), e0201120.
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Publication 2018
Ascites Cancer of Liver Clinic Visits Diagnosis Disease, Chronic Endoscopy Esophageal Varices Gastric Varix Hepatic Coma Hepatic Insufficiency Hepatocellular Carcinomas Hepatorenal Syndrome Hospitalization Icterus Kidney Neoplasm Liver Liver Cirrhosis Liver Transplantations Malignant Neoplasms Neoplasms Outpatients Paracentesis Patients Physicians Portal Hypertension Radiofrequency Ablation Shunt, Transjugular Intrahepatic Portosystemic Ulcer Upper Gastrointestinal Tract
4
Korean Renal Cell Carcinoma Database
Cited 11 times
The new Web-based DB system was established to collect basic demographic and clinicopathological characteristics of a large cohort of patients with RCC in Korea. This project was approved by local ethics committee at Seoul National University Bundang Hospital (IRB number: B1202/145-102). The data included basic demographic (such as age, gender, height, and weight) and clinicopathological characteristics (such as clinical stage, perioperative parameters, pathological stage, Fuhrman nuclear grade and survival data) (Tables 1, 2, 3, 4, 5). AJCC cancer staging manual was used for TNM staging [15 ]. Private information (such as resident registration number and hospital ID number) was excluded to protect the patients' personal information.
Data from a total of 6,849 patients were collected from 8 tertiary care hospitals that agreed to participate in organizing KORCC study group as of 1 July 2015. These hospitals were Chonnam National University Hwasun Hospital (308 cases), Chungbuk National University Hospital (178 cases), Korea University Anam Hospital (105 cases), Kyungpook University Medical Center (890 cases), National Cancer Center (618 cases), Seoul St. Mary's Hospital (883 cases), Seoul National University Bundang Hospital (1,440 cases) and Seoul National University Hospital (2,427 cases). Data were collected for the management of renal masses of all tumor stages (pT1-4, N0-2, M0-1) at the Department of Urology at each hospital from 1990 to present (time frame varies among hospitals due to differences in their own DB collections). Hospitals have contributed to the database by adding all consecutive patients until now.
We analyzed the data of patients who underwent surgical treatments. They were compared with those of previous international studies to characterize Korean RCC. Some data were excluded from the analysis due to insufficient or missing variables.
Byun S.S., Hong S.K., Lee S., Kook H.R., Lee E., Kim H.H., Kwak C., Ku J.H., Jeong C.W., Lee J.Y., Hong S.H., Kim Y.J., Hwang E.C., Kwon T.G., Kim T.H., Kang S.H., Kim S.H, & Chung J. (2016). The establishment of KORCC (KOrean Renal Cell Carcinoma) database. Investigative and Clinical Urology, 57(1), 50-57.
Publication 2016
Gender Kidney Neoplasm Koreans Malignant Neoplasms Operative Surgical Procedures Patients Reading Frames Regional Ethics Committees
5
Generation of Comprehensive PDX Models
Cited 10 times
The process of generating PDX models in mice from fresh primary or metastatic human cancer is extensively described in the literature (10 , 13 (link)). While individual groups have developed specific methodological approaches, the fundamentals are common. Table 1 provides a summary of approaches used to generate the most comprehensive PDX collections currently available. Briefly, pieces of primary or metastatic solid tumors maintained as tissue structures are collected by surgery or biopsy procedures. Some studies have also used fluid drained from malignant ascites or pleural effusions. Tumors are implanted as pieces or single cell suspensions, either alone or in some studies coated with matrigel or mixed with human fibroblasts or mesenchymal stem cells. The most common site of implantation is on the dorsal region of mice (subcutaneous implantation), although implantation in the same organ as the original tumor may be an option (orthotopic implantation, i.e. pancreas, oral cavity, ovary, mammary fat pad, brain, etc.). In addition, independently of the tumor origin, several approaches have implanted primary tumors in the renal capsule in an effort to increase engraftment success rates. A variety of mouse strains having different degrees of immunosuppression have been used in these studies. Supplementary Table 1 lists the principal characteristics of the most commonly used mouse strains including their level of immune suppression as well as advantages or disadvantages. For hormone sensitive tumors, some studies have used hormone supplementation with the intent of increasing engraftment rates.
Some approaches may have theoretical advantages with regard to higher and faster engraftment rates and generation of models that better recapitulate human tumors and are, therefore, more predictive. However, it is important to mention that very few studies have properly addressed comparative implantation methods for these endpoints. Studies in which PDX models have been generated simultaneously from primary tumors and metastatic lesions suggest that metastases have a higher engraftment rate (14 (link), 15 ). Defining the most appropriate host mouse strains to generate PDX models is an important consideration. It is assumed that more severely immunosuppressed models such as non-obese diabetic/severe combined immunodeficiency disorder (NOD/SCID) or NOD/SCID/IL2λ-receptor null (NSG) models are better suited for PDX generation due to higher engraftment rates. Indeed, these are the preferred rodent strains for many groups. However, in human breast cancer (HBC) where this question has been robustly interrogated, implantation in NOD/SCID versus NSG mice yielded similar take rates (16 (link)). In addition, host supplementation with estradiol pellets increased engraftment rates from 2.6 to 21.4 % while, for reasons that are unclear, co-implantation with immortalized human fibroblasts decreased engraftment rate (16 (link)). In contrast, in another study, a mixture of irradiated and non-irradiated human fibroblasts provided improved results (17 (link)). Likewise orthotopic tumor implantation (“orthoxenografts”, (18 (link))) may also confer a translational advantage, as the tumor develops in the same anatomical microenvironment. Generation of orthoxenografts is more labor-intensive, requires complex surgery, is more expensive and often requires imaging methods to monitor tumor growth. However, for several tumor types (e.g. ovarian cancer or lung cancer), this approach substantially increases tumor take rates (19 (link)). In this vein, orthotopic implantation in the testis is essential for the growth of testicular germ cell tumors. As for tumor implantation in the renal capsule, it yielded an impressive 90 % engraftment rate in non-small cell lung cancer (NSCLC) as compared to 25% following subcutaneous implantation, although these results were not obtained from a single comparative study (20 (link), 21 (link)). Furthermore, renal cell capsule implantation shortens time to engraftment, which is one of the most important variables for studies seeking to implement real time PDX data for personalized cancer treatment (20 (link)).
Hidalgo M., Amant F., Biankin A.V., Budinská E., Byrne A.T., Caldas C., Clarke R.B., de Jong S., Jonkers J., Mælandsmo G.M., Roman-Roman S., Seoane J., Trusolino L, & Villanueva A. (2014). Patient Derived Xenograft Models: An Emerging Platform for Translational Cancer Research. Cancer discovery, 4(9), 998-1013.
Publication 2014
Ascites Biopsy Brain Breast Capsule Cells Estradiol Fibroblasts Genes, Neoplasm Glycocalyx Homo sapiens Hormones Immunosuppression Kidney Kidney Neoplasm Lung Cancer Malignant Neoplasms Mammary Carcinoma, Human matrigel Mesenchymal Stem Cells Mus Neoplasm Metastasis Neoplasms Non-Small Cell Lung Carcinoma Obesity Obstetric Labor Operative Surgical Procedures Oral Cavity Ovarian Cancer Ovary Ovum Implantation Pad, Fat Pancreas Pellets, Drug Pleural Effusion Protein Biosynthesis Rodent SCID Mice Strains Testicular Germ Cell Tumor Testis Tissues Veins

Most recents protocols related to «Kidney Neoplasm»

1
Canine Bladder Tumor Grading Protocol
We selected formalin-fixed, paraffin-embedded samples of UC, cystitis, and normal canine bladders from the archive at the Veterinary Pathology Diagnostic Services at the University of Sydney (New South Wales, Australia). An anatomic pathologist confirmed the diagnoses of UC, cystitis, and normal before immunohistochemical analysis was performed. Carcinoma cases had also been confirmed by histopathology for tumor origin in the kidney, bladder, or urethra. Samples without propria-submucosa were excluded. Information collected from the medical records included age, sex, breed, date of treatment initiation, treatment protocol, outcome, and, when available, cause of death. Cause of death was classified as: related to primary UC (such as acute renal failure, urinary obstruction, uremia), related to metastatic UC, or associated with other diseases unrelated to UC. All cases were assessed histologically and graded according to the World Health Organization (WHO) tumor classification system 201610 (link)
; tumors are differentiated into 3 grades: G1, G2, and G3. The lowest grade (G1) displays slim papilla with no atypia; the highest grade (G3) displays major atypia with marked loss of normal architecture. A classification of G2 covers the wide spectrum of lesions seen between G1 and G3 and includes increasing layers within the papilla and rare atypia.
Setyo L.C., Donahoe S.L., Shearer P.L., Wang P, & Krockenberger M.B. (2023). Immunohistochemical analysis of expression of VEGFR2, KIT, PDGFR-β, and CDK4 in canine urothelial carcinoma. Journal of Veterinary Diagnostic Investigation : Official Publication of the American Association of Veterinary Laboratory Diagnosticians, Inc, 35(2), 109-115.
Publication 2023
Canis familiaris Carcinoma Cystitis Diagnosis Formalin Kidney Failure, Acute Kidney Neoplasm Neoplasms Nipples Paraffin Embedding Pathologists Treatment Protocols Uremia Urethra Urinary Bladder Urine Vision
2
Automated Kidney Tumor Classification
The study was reviewed and approved by Ethics Committee of the Affiliated Hospital of Southwest Medical University (18 January 2017, KY2021023). CT data were retrieved from the 2019 Kidney and Kidney Tumor Segmentation Challenge (KiTS19) (https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=61081171) of The Cancer Imaging Archive (TCIA) open access database. Arterial phase-enhanced images of 210 patients from the database were used to establish an automatic classification model. The kidneys and tumors were already manually segmented. These CT images were randomly divided into a training set (168 cases) and test set (42 cases).
Li Y., Gao X., Tang X., Lin S, & Pang H. (2023). Research on automatic classification technology of kidney tumor and normal kidney tissue based on computed tomography radiomics. Frontiers in Oncology, 13, 1013085.
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Publication 2023
Arteries Ethics Committees, Clinical Kidney Kidney Neoplasm Malignant Neoplasms Neoplasms Patients
3
Histopathological Diagnosis of Renal Tumors
The histopathological diagnosis was considered the gold standard. Histopathology diagnosis was available for all tumors after percutaneous biopsy samples were obtained using an 18-gauge semiautomatic side-cutting needle (SemiCut, MDL, Delebio, Italy). At least two samples of each tumor were obtained and analyzed according to the World Health Organization guidelines by a pathologist with more than 4 years of specialized experience in diagnosing renal tumors.
Pietersen P.I., Lynggård Bo Madsen J., Asmussen J., Lund L., Nielsen T.K., Pedersen M., Engvad B, & Graumann O. (2023). Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al.. Journal of Clinical Imaging Science, 13, 7.
Publication 2023
Biopsy Gold Kidney Neoplasm Needles Neoplasms Pathologists
4
Multiparametric MRI for Renal Tumor Diagnosis
All MRI examinations were performed using a clinical 3.0 T system (Ingenia, Phillips Healthcare, Best, Netherlands) with a 32-channel large anterior surface body coil combined with a posterior moveable coil. The respiration triggering device was placed under the anterior coil at the diaphragm level. All patients underwent a survey in two plans with the respiration trigger and two plans with breath-hold, respiration triggered T2-weighted (T2w) turbo spin-echo sequence in transversal and coronal plan, a fat-suppressed diffusion-weighted imaging (DWI) sequence in the transverse plane, and T1-weighted (T1w) DIXON sequence performed both before and 25 s after administration of a gadolinium-containing agent for corticomedullary phase as well as at 120 s after administration for the nephrographic phase. The MRI protocol is presented in [Table 1]. The contrast agent was injected rapidly through an antecubital vein and immediately followed by a flush of 30 mL saline solution (0.9% NaCl). Gadovist (Bayer, Leverkusen, Germany) was used as a contrast agent and administered at 0.1 mL/kg, and a maximum of 7.5 mL was injected. For all MRI sequences, sensitivity encoding was used. [Figure 2] presents the sequences used in the assessments according to Cornelis’ proposed algorithm.
Before receiving histopathology results and diagnosis, two radiologists (OG and JTA), with 9 and 14 years MRI experience in the interpretation of renal tumors, assessed and described in consensus the images in the prescribed order. For each tumor, the radiologists evaluated tumor appearance, one sequence at a time, according to Cornelis et al.’s algorithm [Table 2].[18 (link)] If an MRI diagnosis was established after 1–4 sequences, all remaining sequences were still evaluated. For example, high signal intensity in the first sequence (T2w) suggests cc-RCC or OC, [Table 2]. If the tumor shows a signal drop on the out-phase on the second sequence (dual chemical shift MRI), cc-RCC or AML is suggested. The combination of the first two sequences excludes all remaining tumor types, and cc-RCC is proposed as the diagnosis. In another scenario, a tumor might present intermediate/middle intensity during the first sequence, suggesting Ch-RCC. In these instances, images from all remaining sequences were still evaluated.
Tumor size was measured in two dimensions on the transverse T2w image: medial-lateral and anterior-posterior, where the largest diameter was noted.
Pietersen P.I., Lynggård Bo Madsen J., Asmussen J., Lund L., Nielsen T.K., Pedersen M., Engvad B, & Graumann O. (2023). Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al.. Journal of Clinical Imaging Science, 13, 7.
Publication 2023
Aftercare Cell Respiration Contrast Media Diagnosis Diffusion ECHO protocol Flushing Gadolinium Gadovist Human Body Hypersensitivity Kidney Neoplasm Medical Devices Neoplasms Normal Saline Patients Physical Examination Radiologist Respiratory Diaphragm Saline Solution Signal Peptides Veins
5
Fast-track Renal Tumor Diagnosis
Consecutive patients in a fast-track program for the investigation of renal tumors were prospectively recruited from the hospital’s urology outpatient clinic. Patients were eligible if all of the following criteria were met:

- Presentation of suspected renal tumor either found by computed CT or ultrasound, and

- Age ≥18 years, and

- Normal kidney function defined as estimated glomerulus filtration ratio ≥60 mL/min/1,73 m2, and

- Informed consent understood and provided.

Exclusion criteria were: Pregnancy, graft kidney, contrast allergy, patients with non-MRI-compatible components, or the inability to meet a patient’s fast-track guarantee for diagnosing renal tumors within a stated time frame.
Included patients were offered an additional MRI examination with the experimental sequences on the same day of the biopsy but before the invasive procedure. [Figure 1] presents the flowchart of patients included in the study. Histopathological diagnosis, obtained either from a subsequent percutaneous biopsy or surgical radical or partial nephrectomy, served as the gold standard.
Pietersen P.I., Lynggård Bo Madsen J., Asmussen J., Lund L., Nielsen T.K., Pedersen M., Engvad B, & Graumann O. (2023). Multiparametric magnetic resonance imaging for characterizing renal tumors: A validation study of the algorithm presented by Cornelis et al.. Journal of Clinical Imaging Science, 13, 7.
Publication 2023
Biopsy Diagnosis Filtration Gold Grafts Hypersensitivity Kidney Kidney Glomerulus Kidney Neoplasm Nephrectomy Operative Surgical Procedures Patients Pregnancy Reading Frames Ultrasonography

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The CB17SC scid−/− female mice are a well-established immunodeficient mouse model. The scid mutation causes a severe combined immunodeficiency (SCID) phenotype, leading to the absence of functional T and B cells. This model is commonly used in research applications that require the engraftment of human cells or tissues.
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More about "Kidney Neoplasm"

Renal Neoplasms, Kidney Tumors, Renal Carcinoma, Renal Cell Carcinoma (RCC), Wilms' Tumor, Oncocytoma, Angiomyolipoma.
Kidney neoplasms are a diverse group of cancerous growths that originate in the renal tissue.
These malignancies can range from benign tumors to highly aggressive carcinomas, making accurate identification and classification crucial for effective treatment and management.
Researchers studying kidney neoplasms may utilize various techniques and tools, such as CB17SC scid−/− female mice for animal models, PeqGOLD Total RNA Kit and TRIzol reagent for RNA extraction, Penicillin/streptomycin for cell culture, Stata 15 for statistical analysis, DNeasy Tissue Kit and DNase I for DNA extraction and purification, and HumanHT-12 V4.0 expression beadchip or Human Genome U133 Plus 2.0 Array for gene expression profiling.
Understanding the complex nature of kidney neoplasms, their subtypes, and the latest advancements in diagnostic and therapeutic approaches is essential for researchers and clinicians to develop more effective solutions for patients.
By leveraging the insights provided by this comprehensive overview, researchers can enhance their understanding of kidney cancer and drive innovation in the field.