Dataset Information

Advances in Renal Cell Imaging.

ABSTRACT: A great variety of cell imaging technologies are used routinely every day for the investigation of kidney cell types in applications ranging from basic science research to drug development and pharmacology, clinical nephrology, and pathology. Quantitative visualization of the identity, density, and fate of both resident and nonresident cells in the kidney, and imaging-based analysis of their altered function, (patho)biology, metabolism, and signaling in disease conditions, can help to better define pathomechanism-based disease subgroups, identify critical cells and structures that play a role in the pathogenesis, critically needed biomarkers of disease progression, and cell and molecular pathways as targets for novel therapies. Overall, renal cell imaging has great potential for improving the precision of diagnostic and treatment paradigms for individual acute kidney injury or chronic kidney disease patients or patient populations. This review highlights and provides examples for some of the recently developed renal cell optical imaging approaches, mainly intravital multiphoton fluorescence microscopy, and the new knowledge they provide for our better understanding of renal pathologies.

SUBMITTER: Gyarmati G

PROVIDER: S-EPMC5773263 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Publications

Advances in Renal Cell Imaging.

Gyarmati Georgina G Kadoya Hiroyuki H Moon Ju-Young JY Burford James L JL Ahmadi Nariman N Gill Inderbir S IS Hong Young-Kwon YK Dér Bálint B Peti-Peterdi János J

Seminars in nephrology 20180101 1

A great variety of cell imaging technologies are used routinely every day for the investigation of kidney cell types in applications ranging from basic science research to drug development and pharmacology, clinical nephrology, and pathology. Quantitative visualization of the identity, density, and fate of both resident and nonresident cells in the kidney, and imaging-based analysis of their altered function, (patho)biology, metabolism, and signaling in disease conditions, can help to better def ...[more]

PMID: 29291762

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Project description:Genitourinary (GU) cancers are a group of epithelial malignancies associated with the organs involved in the excretion of urine. Renal cell, urothelial, and prostatic carcinoma are the overwhelming subtypes diagnosed by oncologists. Each of these was traditionally treated surgically when local and non-invasive. When these carcinomas spread, invade, or metastasize, surgical control lacks in efficacy. Chemotherapeutic regimens have been implemented for decades and have increased overall survival but many patients progress. Molecular targeting through tyrosine kinase inhibition of the vascular endothelial growth factor (VEGF) has emerged as a frontline therapy in kidney cancer with more durable responses. More recently, immunotherapy has begun to find efficacy in many other solid tumors including melanoma and non-small cell lung cancer. The inherent genetic instability of this group of cancers makes them ideal solid tumors for immune modulation. Vaccines manufactured to initiate T-Cell regulation through neoplastic-antigen presentation are available for prostate cancer and are currently on trial in renal cell carcinoma (RCC). Programmed death-1 (PD-1) and its ligand (PD-L1) are intricate members of cellular immunity against neoplastic cells. In an activated, unbound state, these molecules permit T-cell activation and cytotoxic killing of cancer cells. However, when they are linked, cellular immunity is attenuated and local cancer cells are permitted the opportunity to proliferate and invade. A novel class of monoclonal antibodies have been developed which stop PD-1 linkage and thus uncouple the 'stop' signal of these neoplastic regulatory cells. The increased overall and progression free survival have made them attractive options alone as well as in combination with anti-VEGF inhibitors for patients. Although more tolerable than chemotherapy, immunotherapeutics have adverse potential toxicities. Overall, the use of immunomodulatory medications have opened a new paradigm in the anti-neoplastic regimen of GU cancers and further developments will determine the appropriate patient to treat for optimum tumor burden eradication.

Project description:Background: While subtyping of the majority of malignant chromophobe renal cell carcinoma (cRCC) and benign renal oncocytoma (rO) is possible on morphology alone, additional histochemical, immunohistochemical or molecular investigations are required in a subset of cases. As currently used histochemical and immunohistological stains as well as genetic aberrations show considerable overlap in both tumors, additional techniques are required for differential diagnostics. Mass spectrometry imaging (MSI) combining the detection of multiple peptides with information about their localization in tissue may be a suitable technology to overcome this diagnostic challenge. Patients and Methods: Formalin-fixed paraffin embedded (FFPE) tissue specimens from cRCC (n=71) and rO (n=64) were analyzed by MSI. Data were classified by linear discriminant analysis (LDA), classification and regression trees (CART), k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF) algorithm with internal cross validation and visualized by t-distributed stochastic neighbor embedding (t-SNE). Most important variables for classification were identified and the classification algorithm was optimized. Results: Applying different machine learning algorithms on all m/z peaks, classification accuracy between cRCC and rO was 85%, 82%, 84%, 77% and 64% for RF, SVM, KNN, CART and LDA. Under the assumption that a reduction of m/z peaks would lead to improved classification accuracy, m/z peaks were ranked based on their variable importance. Reduction to six most important m/z peaks resulted in improved accuracy of 89%, 85%, 85% and 85% for RF, SVM, KNN, and LDA and remained at the level of 77% for CART. t-SNE showed clear separation of cRCC and rO after algorithm improvement. Conclusion: In summary, we acquired MSI data on FFPE tissue specimens of cRCC and rO, performed classification and detected most relevant biomarkers for the differential diagnosis of both diseases. MSI data might be a useful adjunct method in the differential diagnosis of cRCC and rO.

Dataset Information

Advances in Renal Cell Imaging.

Publications

Advances in Renal Cell Imaging.

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