The DOI matches its Crossref record; 36 of the 37 references it cites were found in a registry or an index.
Acid-Mediated Tumor Invasion: a Multidisciplinary Study
Abstract
The acid-mediated tumor invasion hypothesis proposes altered glucose metabolism and increased glucose uptake, observed in the vast majority of clinical cancers by fluorodeoxyglucose-positron emission tomography, are critical for development of the invasive phenotype. In this model, increased acid production due to altered glucose metabolism serves as a key intermediate by producing H+ flow along concentration gradients into adjacent normal tissue. This chronic exposure of peritumoral normal tissue to an acidic microenvironment produces toxicity by: (a) normal cell death caused by the collapse of the transmembrane H+ gradient inducing necrosis or apoptosis and (b) extracellular matrix degradation through the release of cathepsin B and other proteolytic enzymes. Tumor cells evolve resistance to acid-induced toxicity during carcinogenesis, allowing them to survive and proliferate in low pH microenvironments. This permits them to invade the damaged adjacent normal tissue despite the acid gradients. Here, we describe theoretical and empirical evidence for acid-mediated invasion. In silico simulations using mathematical models provide testable predictions concerning the morphology and cellular and extracellular dynamics at the tumor-host interface. In vivo experiments confirm the presence of peritumoral acid gradients as well as cellular toxicity and extracellular matrix degradation in the normal tissue exposed to the acidic microenvironment. The acid-mediated tumor invasion model provides a simple mechanism linking altered glucose metabolism with the ability of tumor cells to form invasive cancers. (Cancer Res 2006; 66(10): 5216-23)
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“This leads to diversion of glucose to lactate thereby creating low pH conditions which modulates TME (Warburg et al., 1927; Gatenby et al., 2006; Salimian Rizi et al., 2015).”
From Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism (2016) · cites this paper as Gatenby et al., 2006
In the citing paper
“The Warburg effect, commonly observed characteristic of many cancer types, is identified as the reliance of cancer cells on aerobic glycolysis even under normoxia.”
From Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism (2016) · cites this paper as Gatenby et al., 2006
Citations
Cites
Why Do Cancers Have High Aerobic Glycolysis?
Gatenby, R. A., & Gillies, R. J. (2004) · Nature reviews. Cancer · doi:10.1038/nrc1478 · Cited by 4,784
Self-citation(1989) · PubMed · Cited by 3,343
Hypoxia-mediated selection of cells with diminished apoptotic potential in solid tumours
Graeber, T. G., Osmanian, C., Jacks, T., Housman, D. E., Koch, C. J., Lowe, S. W., & Giaccia, A. J. (1996) · Nature · doi:10.1038/379088a0 · Cited by 2,300
Molecular imaging of cancer with positron emission tomography
Gambhir, S. S. (2002) · Nature reviews. Cancer · doi:10.1038/nrc882 · Cited by 1,658
Helmlinger, G., Yuan, F., Dellian, M., & Jain, R. K. (1997) · Nature Medicine · doi:10.1038/nm0297-177 · Cited by 1,651
The effects of extracellular pH on immune function
Lardner, A. (2001) · Journal of Leukocyte Biology · doi:10.1189/jlb.69.4.522 · Cited by 864
Clinical Applications of PET in Oncology
ROHREN, E. M., Turkington, T. G., & Coleman, R. E. (2004) · Radiology · doi:10.1148/radiol.2312021185 · Cited by 862
Lu, H., Forbes, R. A., & Verma, A. M. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m202487200 · Cited by 832
WARBURN, O., & Dickens, F. (1931) · The American Journal of the Medical Sciences · doi:10.1097/00000441-193107000-00022 · Cited by 815
A reaction-diffusion model of cancer invasion.
Gatenby, R. A., & Gawlinski, E. T. (1996) · PubMed · Cited by 580
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Zhang, C.-A. (2011) · Journal of Chinese Integrative Medicine · doi:10.3736/jcim20110812 · Cited by 3
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Cárdenas, O. S., García-Garza, R., Ramírez-Durón, R., Muñoz-Maldonado, G. E., Villanueva-Olivo, A., Montes‐de‐Oca‐Luna, R., & Soto‐Domínguez, A. (2017) · PubMed Central · Cited by 3
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Chan, L., Chan, P. S.-T., Zheng, Y., Wong, A., Liu, Y., & Benzie, I. F. F. (2008) · Studies in computational intelligence · doi:10.1007/978-3-540-78297-1_9 · Cited by 3
Stevens, R. P., Holston, J. L., Maatouk, K., Zhou, C., Stone, M. J., Pastukh, V. V., Francis, C. M., Kumar, S., Gwin, M. S., Sayner, S., et al. (2025) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00331.2024 · Cited by 2
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Castellone, R. D. (2011) · ProQuest Demo Repository
Bernardo, M. D., de Castro, A. C. R., Morales, Y., Boueiri, S., Brito, S., Rondón, C., Ortiz, R., & Hernández, N. (2014) · Universidad Industrial de Santander
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Zhou, Y. J. (2014) · D-Scholarship@Pitt (University of Pittsburgh)
Zhang, X. (2010) · UA Campus Repository (The University of Arizona)
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B, K. S. A., Maini, P. K., & Gatenby, R. A. (2010)
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Wanki, G. A. (2015) · ThinkTech (Texas Tech University)
Daneshian, L. (2015) · Scholar Commons (University of South Carolina)
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Pellegrini, P. (2016) · Figshare
Neurochirurgie, L. F., & Medizin, F. (2014)
Ungard, R. G., Buckley, N., & Singh, G. (2016) · Springer eBooks · doi:10.1007/978-3-319-28558-0_7
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Metadata
- Authors
- Gatenby, R. A., Gawlinski, E. T., Gmitro, A. F., Kaylor, B., & Gillies, R. J.
- Affiliations
- University of Arizona (US)
- Temple University (US)
- Venue
- Cancer Research
- Published
- 2006-05-15
- Volume
- 66
- Issue
- 10
- Pages
- 5216-5223
- ISSN
- 0008-5472 (ISSN-L)
- 1538-7445
- OpenAlex
- W2118604693
- Cited by
- 771
- References
- 37
- Citations by year
- 2026: 19 · 2025: 18 · 2024: 25 · 2023: 31 · 2022: 42 · 2021: 47 · 2020: 54 · 2019: 46 · 2018: 36 · 2017: 48 · 2016: 48 · 2015: 48 · 2014: 41 · 2013: 44 · 2012: 36
- FWCI
- 12.90
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (U56CA113004, R01CA093650)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Keywords
- tumor acidosis, extracellular matrix degradation, cathepsin B, normal tissue toxicity, tumor-host interface, carcinogenesis, acid resistance
- MeSH terms
- Acidosis, Animals, Breast Neoplasms, Cell Movement, Glucose, Glycolysis, Humans, Hydrogen-Ion Concentration, Male, Models, Biological, Neoplasm Invasiveness, Neoplasm Metastasis, Prostatic Neoplasms, Mice, SCID, Cell Line, Tumor, Cell Growth Processes, Mice
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