Cargando…
Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells
Tumor cell metabolic heterogeneity is thought to contribute to tumor recurrence, distant metastasis and chemo-resistance in cancer patients, driving poor clinical outcome. To better understand tumor metabolic heterogeneity, here we used the MCF7 breast cancer line as a model system to metabolically...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673134/ https://www.ncbi.nlm.nih.gov/pubmed/26323205 |
_version_ | 1782404674082570240 |
---|---|
author | Lamb, Rebecca Ozsvari, Bela Bonuccelli, Gloria Smith, Duncan L. Pestell, Richard G. Martinez-Outschoorn, Ubaldo E. Clarke, Robert B. Sotgia, Federica Lisanti, Michael P. |
author_facet | Lamb, Rebecca Ozsvari, Bela Bonuccelli, Gloria Smith, Duncan L. Pestell, Richard G. Martinez-Outschoorn, Ubaldo E. Clarke, Robert B. Sotgia, Federica Lisanti, Michael P. |
author_sort | Lamb, Rebecca |
collection | PubMed |
description | Tumor cell metabolic heterogeneity is thought to contribute to tumor recurrence, distant metastasis and chemo-resistance in cancer patients, driving poor clinical outcome. To better understand tumor metabolic heterogeneity, here we used the MCF7 breast cancer line as a model system to metabolically fractionate a cancer cell population. First, MCF7 cells were stably transfected with an hTERT-promoter construct driving GFP expression, as a surrogate marker of telomerase transcriptional activity. To enrich for immortal stem-like cancer cells, MCF7 cells expressing the highest levels of GFP (top 5%) were then isolated by FACS analysis. Notably, hTERT-GFP(+) MCF7 cells were significantly more efficient at forming mammospheres (i.e., stem cell activity) and showed increased mitochondrial mass and mitochondrial functional activity, all relative to hTERT-GFP(−) cells. Unbiased proteomics analysis of hTERT-GFP(+) MCF7 cells directly demonstrated the over-expression of 33 key mitochondrial proteins, 17 glycolytic enzymes, 34 ribosome-related proteins and 17 EMT markers, consistent with an anabolic cancer stem-like phenotype. Interestingly, MT-CO2 (cytochrome c oxidase subunit 2; Complex IV) expression was increased by >20-fold. As MT-CO2 is encoded by mt-DNA, this finding is indicative of increased mitochondrial biogenesis in hTERT-GFP(+) MCF7 cells. Importantly, most of these candidate biomarkers were transcriptionally over-expressed in human breast cancer epithelial cells in vivo. Similar results were obtained using cell size (forward/side scatter) to fractionate MCF7 cells. Larger stem-like cells also showed increased hTERT-GFP levels, as well as increased mitochondrial mass and function. Thus, this simple and rapid approach for the enrichment of immortal anabolic stem-like cancer cells will allow us and others to develop new prognostic biomarkers and novel anti-cancer therapies, by specifically and selectively targeting this metabolic sub-population of aggressive cancer cells. Based on our proteomics and functional analysis, FDA-approved inhibitors of protein synthesis and/or mitochondrial biogenesis, may represent novel treatment options for targeting these anabolic stem-like cancer cells. |
format | Online Article Text |
id | pubmed-4673134 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-46731342015-12-23 Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells Lamb, Rebecca Ozsvari, Bela Bonuccelli, Gloria Smith, Duncan L. Pestell, Richard G. Martinez-Outschoorn, Ubaldo E. Clarke, Robert B. Sotgia, Federica Lisanti, Michael P. Oncotarget Research Paper Tumor cell metabolic heterogeneity is thought to contribute to tumor recurrence, distant metastasis and chemo-resistance in cancer patients, driving poor clinical outcome. To better understand tumor metabolic heterogeneity, here we used the MCF7 breast cancer line as a model system to metabolically fractionate a cancer cell population. First, MCF7 cells were stably transfected with an hTERT-promoter construct driving GFP expression, as a surrogate marker of telomerase transcriptional activity. To enrich for immortal stem-like cancer cells, MCF7 cells expressing the highest levels of GFP (top 5%) were then isolated by FACS analysis. Notably, hTERT-GFP(+) MCF7 cells were significantly more efficient at forming mammospheres (i.e., stem cell activity) and showed increased mitochondrial mass and mitochondrial functional activity, all relative to hTERT-GFP(−) cells. Unbiased proteomics analysis of hTERT-GFP(+) MCF7 cells directly demonstrated the over-expression of 33 key mitochondrial proteins, 17 glycolytic enzymes, 34 ribosome-related proteins and 17 EMT markers, consistent with an anabolic cancer stem-like phenotype. Interestingly, MT-CO2 (cytochrome c oxidase subunit 2; Complex IV) expression was increased by >20-fold. As MT-CO2 is encoded by mt-DNA, this finding is indicative of increased mitochondrial biogenesis in hTERT-GFP(+) MCF7 cells. Importantly, most of these candidate biomarkers were transcriptionally over-expressed in human breast cancer epithelial cells in vivo. Similar results were obtained using cell size (forward/side scatter) to fractionate MCF7 cells. Larger stem-like cells also showed increased hTERT-GFP levels, as well as increased mitochondrial mass and function. Thus, this simple and rapid approach for the enrichment of immortal anabolic stem-like cancer cells will allow us and others to develop new prognostic biomarkers and novel anti-cancer therapies, by specifically and selectively targeting this metabolic sub-population of aggressive cancer cells. Based on our proteomics and functional analysis, FDA-approved inhibitors of protein synthesis and/or mitochondrial biogenesis, may represent novel treatment options for targeting these anabolic stem-like cancer cells. Impact Journals LLC 2015-08-27 /pmc/articles/PMC4673134/ /pubmed/26323205 Text en Copyright: © 2015 Lamb et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Lamb, Rebecca Ozsvari, Bela Bonuccelli, Gloria Smith, Duncan L. Pestell, Richard G. Martinez-Outschoorn, Ubaldo E. Clarke, Robert B. Sotgia, Federica Lisanti, Michael P. Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
title | Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
title_full | Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
title_fullStr | Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
title_full_unstemmed | Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
title_short | Dissecting tumor metabolic heterogeneity: Telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
title_sort | dissecting tumor metabolic heterogeneity: telomerase and large cell size metabolically define a sub-population of stem-like, mitochondrial-rich, cancer cells |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4673134/ https://www.ncbi.nlm.nih.gov/pubmed/26323205 |
work_keys_str_mv | AT lambrebecca dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT ozsvaribela dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT bonuccelligloria dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT smithduncanl dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT pestellrichardg dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT martinezoutschoornubaldoe dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT clarkerobertb dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT sotgiafederica dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells AT lisantimichaelp dissectingtumormetabolicheterogeneitytelomeraseandlargecellsizemetabolicallydefineasubpopulationofstemlikemitochondrialrichcancercells |