Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2009 Aug 18;2(3):138-45.
doi: 10.1593/tlo.09106.

Cancer abolishes the tissue type-specific differences in the phenotype of energetic metabolism

Affiliations

Cancer abolishes the tissue type-specific differences in the phenotype of energetic metabolism

Paloma Acebo et al. Transl Oncol. .

Abstract

Nowadays, cellular bioenergetics has become a central issue of investigation in cancer biology. Recently, the metabolic activity of the cancer cell has been shown to correlate with a proteomic index that informs of the relative mitochondrial activity of the cell. Within this new field of investigation, we report herein the production and characterization of high-affinity monoclonal antibodies against proteins of the "bioenergetic signature" of the cell. The use of recombinant proteins and antibodies against the mitochondrial beta-F1-ATPase and Hsp60 proteins and the enzymes of the glycolytic pathway glyceraldehyde-3-phosphate dehydrogenase and pyruvate kinase M2 in quantitative assays provide, for the first time, the actual amount of these proteins in normal and tumor surgical specimens of breast, lung, and esophagus. The application of this methodology affords a straightforward proteomic signature that quantifies the variable energetic demand of human tissues. Furthermore, the results show an unanticipated finding: tumors from different tissues and/or histological types have the same proteomic signature of energetic metabolism. Therefore, the results indicate that cancer abolishes the tissue-specific differences in the bioenergetic phenotype of mitochondria. Overall, the results support that energetic metabolism represents an additional hallmark of the phenotype of the cancer cell and a promising target for the treatment of diverse neoplasias.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Expression and purification of recombinant proteins and characterization of the monoclonal antibodies produced. (A) The M15 E. coli strain was used for the expression of recombinant proteins. Samples were collected before (-) and after 2 hours of 0.1 mM IPTG induction (+) and the cellular proteins analyzed by SDS-PAGE. The recombinant proteins were affinity-purified using the streptavidin tag (Hsp60) or the His tag (β-F1 ATPase, GAPDH, and PK) and the purity of the eluted protein estimated by SDS-PAGE (RP). (B) Western blot analysis showing the reactivity of the different antibodies produced. The antibodies (0.4 µg/ml) exclusively recognized the recombinant (RP; 1 ng of protein) as well as the native cellular protein in normal and/or tumor breast (B), esophagus (E), gastric (G), and lung (L) tissues or cell lines (HepG2; 10–30 µg of protein). (C) Immunofluorescence microscopy using the antibodies produced (0.4 µg/ml) revealed (green) the mitochondrial (β-F1 and Hsp60) or cytoplasmic (GAPDH and PK) localization of the cellular proteins in human liver (HepG2) and breast (Hs578T) cancer cells. Nuclear DNA (blue) was stained with ToPro3. Original magnification, x60. (D) Representative slot-blots with the antibodies produced for the quantification of the amount of the different biomarkers. A linear increase in the signal is observed as the amount of recombinant protein (RP in ng) or protein from cellular extracts (E in µg) is augmented. (E) Graphs of the experiments in panel D for both the recombinant protein (○, RP) and the cellular antigen (▪, CA) within the linear range of protein. The equations and correlation coefficients are as follows: β-F1 ATPase [RP: y = 1.7372x - 0.284/R2 = 0.9823; CA: y = 0.7228x + 0.0542/R2 = 0.9571], Hsp60 [RP: y = 0.3224x - 0.0161/R2 = 9879; CA: y = 0.4594x + 0.9/R2 = 0.9632], GAPDH [RP: y = 0.243x - 0.0404/R2 = 0.9804; CA: y = 0.8742x + 0.1839/R2 = 0.992], and PK [RP: y = 0.6673x + 0.179/R2 = 0.9664; CA: y = 1.3235x + 0.3378/R2 = 0.9803].
Figure 2
Figure 2
Graphical hierarchical clustering analysis of the bioenergetic signature as quantitatively determined by slot-blot procedures. Rows indicate type of sample; columns, proteins and derived ratios. Protein expression scores are shown normalized to the mean value of the normal lung samples that accompany squamous lung carcinomas (LSC-N) in panels A, E, and F and to the corresponding normal tissue in panels B, C and D, according to a color scale (below panel F): red indicates high; black, normal; and green, low. The dendogram (to the right of the matrix) represents overall similarities in expression profiles. The maximum and minimum values of the markers for each cluster are shown in brackets. (A) Clustering of normal breast (B-N, light blue), esophageal (ESO-N, orange), and normal lung samples from adenocarcinomas (LAC-N, yellow) and squamous carcinomas (LSC-N, light green). (B) Clustering of normal (B-N, light blue) and adenocarcinomas (B-T, black) of the breast. (C) Clustering of normal (ESO-N, orange) and squamous carcinomas (ESO-T, green) of the esophagus. (D) Clustering of normal (LAC-N, yellow) and adenocarcinomas of the lung (LAC-T, blue). (E) Clustering of normal (LSC-N, light green) and squamous carcinomas of the lung (LSC-T, red). (F) Clustering of breast, esophageal, and lung tumors.

Similar articles

Cited by

References

    1. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100:57–70. - PubMed
    1. DeBerardinis RJ, Lum JJ, Hatzivassiliou G, Thompson CB. The biology of cancer: metabolic reprogramming fuels cell growth and proliferation. Cell Metab. 2008;7:11–20. - PubMed
    1. Kim JW, Dang CV. Cancer's molecular sweet tooth and the Warburg effect. Cancer Res. 2006;66:8927–8930. - PubMed
    1. Semenza GL, Artemov D, Bedi A, Bhujwalla Z, Chiles K, Feldser D, Laughner E, Ravi R, Simons J, Taghavi P, et al. “The metabolism of tumours”: 70 years later. Novartis Found Symp. 2001;240:251–260. - PubMed
    1. Gogvadze V, Orrenius S, Zhivotovsky B. Mitochondria in cancer cells: what is so special about them? Trends Cell Biol. 2008;18:165–173. - PubMed

LinkOut - more resources