Oncogenic Kras maintains pancreatic tumors through regulation of anabolic glucose metabolism
Haoqiang Ying,Alec C. Kimmelman,Costas A. Lyssiotis,Sujun Hua,Gerald C. Chu,Eliot Fletcher-Sananikone,Jason W. Locasale,Jaekyoung Son,Hailei Zhang,Jonathan L. Coloff,Haiyan Yan,Wei Wang,Shujuan Chen,Andrea Viale,Hongwu Zheng,Jihye Paik,Carol Lim,Alexander R. Guimaraes,Eric S. Martin,Jeffery Chang,Aram F. Hezel,Samuel R. Perry,Jian Hu,Boyi Gan,Yonghong Xiao,John M. Asara,Ralph Weissleder,Y. Alan Wang,Lynda Chin,Lewis C. Cantley,Ronald A. DePinho +30 more
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TLDR
In vivo mechanistic insights are provided into how oncogenic Kras promotes metabolic reprogramming in native tumors and illuminates potential metabolic targets that can be exploited for therapeutic benefit in PDAC.About:
This article is published in Cell.The article was published on 2012-04-27 and is currently open access. It has received 1559 citations till now. The article focuses on the topics: KRAS.read more
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Cancer Genome Landscapes
Bert Vogelstein,Nickolas Papadopoulos,Victor E. Velculescu,Shibin Zhou,Luis A. Diaz,Kenneth W. Kinzler +5 more
TL;DR: This work has revealed the genomic landscapes of common forms of human cancer, which consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of "hills" (Genes altered infrequently).
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The Emerging Hallmarks of Cancer Metabolism
TL;DR: This Perspective has organized known cancer-associated metabolic changes into six hallmarks: deregulated uptake of glucose and amino acids, use of opportunistic modes of nutrient acquisition, useof glycolysis/TCA cycle intermediates for biosynthesis and NADPH production, increased demand for nitrogen, alterations in metabolite-driven gene regulation, and metabolic interactions with the microenvironment.
Journal ArticleDOI
The consensus molecular subtypes of colorectal cancer
Justin Guinney,Rodrigo Dienstmann,Rodrigo Dienstmann,Xingwu Wang,Xingwu Wang,Aurélien de Reyniès,Andreas Schlicker,Charlotte Soneson,Laetitia Marisa,Paul Roepman,Gift Nyamundanda,Paolo Angelino,Brian M. Bot,Jeffrey S. Morris,Iris Simon,Sarah Gerster,Evelyn Fessler,Felipe De Sousa E Melo,Edoardo Missiaglia,Hena R. Ramay,David Barras,Krisztian Homicsko,Dipen M. Maru,Ganiraju C. Manyam,Bradley M. Broom,Valérie Boige,Beatriz Perez-Villamil,Ted Laderas,Ramon Salazar,Joe W. Gray,Douglas Hanahan,Josep Tabernero,René Bernards,Stephen H. Friend,Pierre Laurent-Puig,Jan Paul Medema,Anguraj Sadanandam,Lodewyk F. A. Wessels,Mauro Delorenzi,Mauro Delorenzi,Scott Kopetz,Louis Vermeulen,Sabine Tejpar +42 more
TL;DR: An international consortium dedicated to large-scale data sharing and analytics across expert groups is formed, showing marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMSs) with distinguishing features.
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The Warburg Effect: How Does it Benefit Cancer Cells?
TL;DR: Several proposed explanations for the function of Warburg Effect are analyzed, emphasize their rationale, and discuss their controversies.
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The biology and function of fibroblasts in cancer
TL;DR: Cancer-associated fibroblasts (CAFs) become synthetic machines that produce many different tumour components and have a role in creating extracellular matrix structure and metabolic and immune reprogramming of the tumour microenvironment with an impact on adaptive resistance to chemotherapy.
References
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Hallmarks of cancer: the next generation.
TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.
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Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
Aravind Subramanian,Pablo Tamayo,Vamsi K. Mootha,Sayan Mukherjee,Benjamin L. Ebert,Michael A. Gillette,Amanda G. Paulovich,Scott L. Pomeroy,Todd R. Golub,Eric S. Lander,Jill P. Mesirov +10 more
TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
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Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
TL;DR: It is proposed that the metabolism of cancer cells, and indeed all proliferating cells, is adapted to facilitate the uptake and incorporation of nutrients into the biomass needed to produce a new cell.
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Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
TL;DR: The hierarchical model of Lonnstedt and Speed (2002) is developed into a practical approach for general microarray experiments with arbitrary numbers of treatments and RNA samples and the moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom.
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