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DOI . ORG {}

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  3. CMS
  4. Monthly Traffic Estimate
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  6. Keywords
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We began analyzing https://www.tandfonline.com/doi/full/10.4161/cc.11.6.19530, but it redirected us to https://www.tandfonline.com/doi/full/10.4161/cc.11.6.19530. The analysis below is for the second page.

Title[redir]:
Full article: Using the “reverse Warburg effect” to identify high-risk breast cancer patients
Description:
Previously, we identified a loss of stromal Cav-1 as a predictive biomarker of early tumor recurrence, metastasis, tamoxifen-resistance and decreased survival in human breast cancer patients.1,2 Th...

Matching Content Categories {📚}

  • Science
  • Education
  • Health & Fitness

Content Management System {📝}

What CMS is doi.org built with?

Custom-built

No common CMS systems were detected on Doi.org, and no known web development framework was identified.

Traffic Estimate {📈}

What is the average monthly size of doi.org audience?

🏙️ Massive Traffic: 50M - 100M visitors per month


Based on our best estimate, this website will receive around 80,479,999 visitors per month in the current month.

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How Does Doi.org Make Money? {💸}

We find it hard to spot revenue streams.

Not all websites focus on profit; some are designed to educate, connect people, or share useful tools. People create websites for numerous reasons. And this could be one such example. Doi.org could be secretly minting cash, but we can't detect the process.

Keywords {🔍}

open, cancer, stromal, mct, tumor, breast, science, cell, source, windowgoogle, scholar, cav, pmid, cells, windowpubmed, windowweb, cycle, patients, expression, survival, warburg, metabolism, epithelial, caveolin, effect, oxidative, fibroblasts, biology, lactate, microenvironment, prognostic, jefferson, high, research, martinezoutschoorn, stroma, levels, journal, center, university, stress, mitochondrial, httpdxdoiorgcc, glycolysis, staining, medicine, clinical, metabolic, table, reverse,

Topics {✒️}

google scholar r-development-core-team uk/ncriconference/2011abstracts/abstracts/a222 'physical sciences lens' hif-1α-dependent mechanism source neuron-glia metabolic coupling social care medicine fda-approved drugs inhibit l-lactate/ketone efflux hif-1alpha-dependent mechanism citation30 isoform-specific antibodies stromal-epithelial “lactate shuttle” references witkiewicz ak �battery-operated tumor growth” google scholar pértega-gomes stromal-epithelial metabolic coupling mutually exclusive events hif1-α target gene induces donor-specific suppression hif1-α transcription factors breakthrough breast cancer triple-negative breast carcinoma laser-captured tumor stroma drives l-lactate secretion fda-approved therapeutics l-lactate uptake/import twitter page taylor site-specific metastasis source caveolin-1 predicts outcome c-terminal amino acids tumor/stromal caveolin‐1 expression tumor/stromal caveolin-1 expression high-risk patient population stromal high-risk groups studied cav-1-deficient-mice pet activation studies descriptive statistics l-lactate/ketone uptake predict clinical outcome fibroblasts drives tumor-stroma joint frequency distribution l-lactate efflux/export independently predicts poor antioxidants [n-acetyl-cysteine google scholar whitaker-menezes kaplan-meier method kaplan-meier curves methods materials breast cancer progression breast cancer research specific monocarboxylate transporter-1

Questions {❓}

  • Is cancer a metabolic rebellion against host aging?
  • Is cancer a metabolic rebellion against host aging?
  • Is lactate food for neurons?
  • Is lactate food for neurons?
  • Why publish with us?

Schema {🗺️}

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            name:Using the “reverse Warburg effect” to id ....
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      name:Using the “reverse Warburg effect” to identify high-risk breast cancer patients
      headline:Using the “reverse Warburg effect” to identify high-risk breast cancer patients
      abstract:We have recently proposed a new model of cancer metabolism to explain the role of aerobic glycolysis and L-lactate production in fueling tumor growth and metastasis. In this model, cancer cells secrete hydrogen peroxide (H2O2), initiating oxidative stress and aerobic glycolysis in the tumor stroma. This, in turn, drives L-lactate secretion from cancer-associated fibroblasts. Secreted L-lactate then fuels oxidative mitochondrial metabolism (OXPHOS) in epithelial cancer cells, by acting as a paracrine onco-metabolite. We have previously termed this type of two-compartment tumor metabolism the “Reverse Warburg Effect,” as aerobic glycolysis takes place in stromal fibroblasts, rather than epithelial cancer cells. Here, we used MCT4 immuno-staining of human breast cancer tissue microarrays (TMAs; > 180 triple-negative patients) to directly assess the prognostic value of the “Reverse Warburg Effect.” MCT4 expression is a functional marker of hypoxia, oxidative stress, aerobic glycolysis, and L-lactate efflux. Remarkably, high stromal MCT4 levels (score = 2) were specifically associated with decreased overall survival (< 18% survival at 10 y post-diagnosis). In contrast, patients with absent stromal MCT4 expression (score = 0), had 10-y survival rates of ~97% (p-value < 10−32). High stromal levels of MCT4 were strictly correlated with a loss of stromal Cav-1 (p-value < 10−14), a known marker of early tumor recurrence and metastasis. In fact, the combined use of stromal Cav-1 and stromal MCT4 allowed us to more precisely identify high-risk triple-negative breast cancer patients, consistent with the goal of individualized risk-assessment and personalized cancer treatment. However, epithelial MCT4 staining had no prognostic value, indicating that the “conventional” Warburg effect does not predict clinical outcome. Thus, the “Reverse Warburg Effect” or “parasitic” energy-transfer is a key determinant of poor overall patient survival. As MCT4 is a druggable-target, MCT4 inhibitors should be developed for the treatment of aggressive breast cancers, and possibly other types of human cancers. Similarly, we discuss how stromal MCT4 could be used as a biomarker for identifying high-risk cancer patients that could likely benefit from treatment with FDA-approved drugs or existing MCT-inhibitors (such as, AR-C155858, AR-C117977, and AZD-3965).
      description:We have recently proposed a new model of cancer metabolism to explain the role of aerobic glycolysis and L-lactate production in fueling tumor growth and metastasis. In this model, cancer cells secrete hydrogen peroxide (H2O2), initiating oxidative stress and aerobic glycolysis in the tumor stroma. This, in turn, drives L-lactate secretion from cancer-associated fibroblasts. Secreted L-lactate then fuels oxidative mitochondrial metabolism (OXPHOS) in epithelial cancer cells, by acting as a paracrine onco-metabolite. We have previously termed this type of two-compartment tumor metabolism the “Reverse Warburg Effect,” as aerobic glycolysis takes place in stromal fibroblasts, rather than epithelial cancer cells. Here, we used MCT4 immuno-staining of human breast cancer tissue microarrays (TMAs; > 180 triple-negative patients) to directly assess the prognostic value of the “Reverse Warburg Effect.” MCT4 expression is a functional marker of hypoxia, oxidative stress, aerobic glycolysis, and L-lactate efflux. Remarkably, high stromal MCT4 levels (score = 2) were specifically associated with decreased overall survival (< 18% survival at 10 y post-diagnosis). In contrast, patients with absent stromal MCT4 expression (score = 0), had 10-y survival rates of ~97% (p-value < 10−32). High stromal levels of MCT4 were strictly correlated with a loss of stromal Cav-1 (p-value < 10−14), a known marker of early tumor recurrence and metastasis. In fact, the combined use of stromal Cav-1 and stromal MCT4 allowed us to more precisely identify high-risk triple-negative breast cancer patients, consistent with the goal of individualized risk-assessment and personalized cancer treatment. However, epithelial MCT4 staining had no prognostic value, indicating that the “conventional” Warburg effect does not predict clinical outcome. Thus, the “Reverse Warburg Effect” or “parasitic” energy-transfer is a key determinant of poor overall patient survival. As MCT4 is a druggable-target, MCT4 inhibitors should be developed for the treatment of aggressive breast cancers, and possibly other types of human cancers. Similarly, we discuss how stromal MCT4 could be used as a biomarker for identifying high-risk cancer patients that could likely benefit from treatment with FDA-approved drugs or existing MCT-inhibitors (such as, AR-C155858, AR-C117977, and AZD-3965).
      author:
            type:Person
            name:Sharon Sneddon
            type:Person
            name:Ricardo Gandara
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Zhao Lin
            type:Person
            name:Ubaldo E. Martinez-Outschoorn
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Nancy J. Philp
            type:Person
            name:Abhijit Dasgupta
            type:Person
            name:Federica Sotgia
            type:Person
            name:Diana Whitaker-Menezes
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Agnieszka K. Witkiewicz
            type:Person
            name:Michael P. Lisanti
      keywords:two compartment tumor metabolism, tumor stroma, pseudohypoxia, predictive biomarker, oxidative stress, monocarboxylic acid transporter, metabolic coupling, lactate shuttle, caveolin-1, SLC16A3, MCT4
      pageStart:1108
      pageEnd:1117
      datePublished:2012-03-15
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      name:Ricardo Gandara
      name:Agnieszka K. Witkiewicz
      name:Zhao Lin
      name:Ubaldo E. Martinez-Outschoorn
      name:Agnieszka K. Witkiewicz
      name:Nancy J. Philp
      name:Abhijit Dasgupta
      name:Federica Sotgia
      name:Diana Whitaker-Menezes
      name:Agnieszka K. Witkiewicz
      name:Agnieszka K. Witkiewicz
      name:Agnieszka K. Witkiewicz
      name:Agnieszka K. Witkiewicz
      name:Agnieszka K. Witkiewicz
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Social Networks {👍}(4)

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