Literature DB >> 33803184

Molecular and Metabolic Subtypes in Sporadic and Inherited Clear Cell Renal Cell Carcinoma.

Maria F Czyzyk-Krzeska1,2,3, Julio A Landero Figueroa3,4, Shuchi Gulati5, John T Cunningham1, Jarek Meller3,6,7,8,9, Behrouz ShamsaeI8, Bhargav Vemuri1, David R Plas1.   

Abstract

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.

Entities:  

Keywords:  VHL; clear cell renal cell carcinoma; metabolomics; metallomics; precision medicine; proteomics; transcriptomics

Mesh:

Year:  2021        PMID: 33803184      PMCID: PMC7999481          DOI: 10.3390/genes12030388

Source DB:  PubMed          Journal:  Genes (Basel)        ISSN: 2073-4425            Impact factor:   4.096


  109 in total

1.  Cisplatin resistance in cell models: evaluation of metallomic and biological predictive biomarkers to address early therapy failure.

Authors:  Marta Espina; Mario Corte-Rodríguez; Leticia Aguado; María Montes-Bayón; Marta I Sierra; Pablo Martínez-Camblor; Elisa Blanco-González; L María Sierra
Journal:  Metallomics       Date:  2017-05-24       Impact factor: 4.526

2.  Lenvatinib, everolimus, and the combination in patients with metastatic renal cell carcinoma: a randomised, phase 2, open-label, multicentre trial.

Authors:  Robert J Motzer; Thomas E Hutson; Hilary Glen; M Dror Michaelson; Ana Molina; Timothy Eisen; Jacek Jassem; Jakub Zolnierek; Jose Pablo Maroto; Begoña Mellado; Bohuslav Melichar; Jiri Tomasek; Alton Kremer; Han-Joo Kim; Karen Wood; Corina Dutcus; James Larkin
Journal:  Lancet Oncol       Date:  2015-10-22       Impact factor: 41.316

3.  Urine metabolomic analysis identifies potential biomarkers and pathogenic pathways in kidney cancer.

Authors:  Kyoungmi Kim; Sandra L Taylor; Sheila Ganti; Lining Guo; Michael V Osier; Robert H Weiss
Journal:  OMICS       Date:  2011-02-24

Review 4.  Current Status and Future Directions of Immunotherapy in Renal Cell Carcinoma.

Authors:  Bryden Considine; Michael E Hurwitz
Journal:  Curr Oncol Rep       Date:  2019-03-08       Impact factor: 5.075

Review 5.  The AlkB Family of Fe(II)/α-Ketoglutarate-dependent Dioxygenases: Repairing Nucleic Acid Alkylation Damage and Beyond.

Authors:  Bogdan I Fedeles; Vipender Singh; James C Delaney; Deyu Li; John M Essigmann
Journal:  J Biol Chem       Date:  2015-07-07       Impact factor: 5.157

6.  Metabolomic profile of glycolysis and the pentose phosphate pathway identifies the central role of glucose-6-phosphate dehydrogenase in clear cell-renal cell carcinoma.

Authors:  Giuseppe Lucarelli; Vanessa Galleggiante; Monica Rutigliano; Francesca Sanguedolce; Simona Cagiano; Pantaleo Bufo; Gaetano Lastilla; Eugenio Maiorano; Domenico Ribatti; Andrea Giglio; Grazia Serino; Antonio Vavallo; Carlo Bettocchi; Francesco Paolo Selvaggi; Michele Battaglia; Pasquale Ditonno
Journal:  Oncotarget       Date:  2015-05-30

Review 7.  From correlation to causation: analysis of metabolomics data using systems biology approaches.

Authors:  Antonio Rosato; Leonardo Tenori; Marta Cascante; Pedro Ramon De Atauri Carulla; Vitor A P Martins Dos Santos; Edoardo Saccenti
Journal:  Metabolomics       Date:  2018-02-27       Impact factor: 4.290

8.  The Landscape of Iron Metabolism-Related and Methylated Genes in the Prognosis Prediction of Clear Cell Renal Cell Carcinoma.

Authors:  Yanhua Mou; Yao Zhang; Jinchun Wu; Busheng Hu; Chunfang Zhang; Chaojun Duan; Bin Li
Journal:  Front Oncol       Date:  2020-05-22       Impact factor: 6.244

9.  The iron load of lipocalin-2 (LCN-2) defines its pro-tumour function in clear-cell renal cell carcinoma.

Authors:  Claudia Rehwald; Matthias Schnetz; Anja Urbschat; Christina Mertens; Julia K Meier; Rebekka Bauer; Patrick Baer; Sofia Winslow; Frederik C Roos; Klaus Zwicker; Arnaud Huard; Andreas Weigert; Bernhard Brüne; Michaela Jung
Journal:  Br J Cancer       Date:  2019-11-27       Impact factor: 7.640

Review 10.  The Multiple Potential Biomarkers for Predicting Immunotherapy Response-Finding the Needle in the Haystack.

Authors:  Tamiem Adam; Therese M Becker; Wei Chua; Victoria Bray; Tara L Roberts
Journal:  Cancers (Basel)       Date:  2021-01-13       Impact factor: 6.639

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  2 in total

1.  Identification of a Necroptosis-Related Prognostic Index and Associated Regulatory Axis in Kidney Renal Clear Cell Carcinoma.

Authors:  Yong Luo; Guian Zhang
Journal:  Int J Gen Med       Date:  2022-06-03

Review 2.  First-Line Treatments for Metastatic Clear Cell Renal Cell Carcinoma: An Ever-Enlarging Landscape.

Authors:  Shuchi Gulati; Chris Labaki; Georgia Sofia Karachaliou; Toni K Choueiri; Tian Zhang
Journal:  Oncologist       Date:  2022-03-04       Impact factor: 5.837

  2 in total

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