Skip to main page content
U.S. flag

An official website of the United States government

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 May 8:15:375.
doi: 10.1186/s12885-015-1358-y.

Transcriptional profiling provides insights into metronomic cyclophosphamide-activated, innate immune-dependent regression of brain tumor xenografts

Joshua C Doloff  1 , David J Waxman  2
Affiliations

Transcriptional profiling provides insights into metronomic cyclophosphamide-activated, innate immune-dependent regression of brain tumor xenografts

Joshua C Doloff et al. BMC Cancer. .

Abstract

Background: Cyclophosphamide treatment on a six-day repeating metronomic schedule induces a dramatic, innate immune cell-dependent regression of implanted gliomas. However, little is known about the underlying mechanisms whereby metronomic cyclophosphamide induces innate immune cell mobilization and recruitment, or about the role of DNA damage and cell stress response pathways in eliciting the immune responses linked to tumor regression.

Methods: Untreated and metronomic cyclophosphamide-treated human U251 glioblastoma xenografts were analyzed on human microarrays at two treatment time points to identify responsive tumor cell-specific factors and their upstream regulators. Mouse microarray analysis across two glioma models (human U251, rat 9L) was used to identify host factors and gene networks that contribute to the observed immune and tumor regression responses.

Results: Metronomic cyclophosphamide increased expression of tumor cell-derived DNA damage, cell stress, and cell death genes, which may facilitate innate immune activation. Increased expression of many host (mouse) immune networks was also seen in both tumor models, including complement components, toll-like receptors, interferons, and cytolysis pathways. Key upstream regulators activated by metronomic cyclophosphamide include members of the interferon, toll-like receptor, inflammatory response, and PPAR signaling pathways, whose activation may contribute to anti-tumor immunity. Many upstream regulators inhibited by metronomic cyclophosphamide, including hypoxia-inducible factors and MAP kinases, have glioma-promoting activity; their inhibition may contribute to the therapeutic effectiveness of the six-day repeating metronomic cyclophosphamide schedule.

Conclusions: Large numbers of responsive cytokines, chemokines and immune regulatory genes linked to innate immune cell recruitment and tumor regression were identified, as were several immunosuppressive factors that may contribute to the observed escape of some tumors from metronomic CPA-induced, immune-based regression. These factors may include useful biomarkers that facilitate discovery of clinically effective immunogenic metronomic drugs and treatment schedules, and the selection of patients most likely to be responsive to immunogenic drug scheduling.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Top networks associated with U251 tumor human genes increased by metronomic CPA treatment on both day 12 and day 18 (late responses), as determined by IPA. A) Top network for the human chemokine CXCL10, involved in innate immune activation via toll-like receptor (TLR) and interferon (IFN) response pathways. B) Top network for the human chemokine CXCL11, involved in innate immune activation via DNA damage, TLR, IFN, and secretory chemokine/cytokine pathways. C) Top network for the human chemokine CXCL9, involved in innate immune activation via toll-like receptor, interleukin, and cell stress ligand MICB response pathways. Deeper shades of red-filled shapes indicate stronger up regulation of the gene by metronomic CPA treatment, as determined by microarray analysis. Solid arrows: protein-DNA interactions; solid lines: protein-protein; dashed arrows: regulation of gene expression; colored: related to highlighted factor(s). Shapes indicate protein family: rectangle: receptor; square: cytokine; triangle: kinase; diamond: enzyme; oval: factor (ie., transcription); concentric circles: complex; circle: other.
Figure 2
Figure 2
Interferon signaling upstream regulator pathway, with subcellular compartmentalization indicated. The activated upstream regulators identified (orange) include interferons IFNα (dark blue dashed lines), IFNα2 (pink dashed lines), IFNβ (teal blue dashed lines), IFNγ (green dashed lines), IFNL1 (orange dashed lines), and IRF1 (red solid lines), and regulate many immune responses. Shapes filled with deeper shades of red and green denote human tumor genes that are up regulated (red) or down-regulated (green) by metronomic CPA to a greater extent as compared to lighter shades, as indicated by microarray analysis. Key at the bottom: shapes used to indicate the molecular class of each factor.
Figure 3
Figure 3
Top networks associated with mouse (host) genes induced by metronomic CPA treatment, as determined by IPA. A) Top network showing connections between metronomic CPA-induced expression of innate immunological disease (many macrophage-related), adhesion, infiltration, scavenger, and cytolysis genes. B) Top networks for NK cell-related innate immune function: tumoricidal and infectious disease NK function, targeting via CXCR3 and FAS, and cytolysis via granzyme and perforin, and C), NK cell-related inflammatory disease network. Deeper shades of red indicate stronger up regulation of the gene by metronomic CPA treatment. Solid arrows: protein-DNA interactions; solid lines: protein-protein; dashed arrows: regulation of gene expression; colored: related to highlighted factor(s). Shapes indicate protein family: rectangle: receptor; square: cytokine; triangle: kinase; diamond: enzyme; oval: factor (i.e., transcription); concentric circles: complex; circle: other.
Figure 4
Figure 4
Downstream target network for the predicted upstream regulators of the mouse genes IL15 (dashed dark blue lines), IL18 (dashed red lines), TLR3 (dashed gold lines), TLR9 (dashed magenta lines), IKBKB (dashed green lines), and NFKB (dashed teal lines), showing multi-layer cell signaling and cross-talk between regulators, as well as downstream signaling and up- or down-regulation of genes identified on the mouse array as being responsive to metronomic CPA treatment. Genes and upstream regulators shown are only those that are common across tumor models at both late time points (U251 tumors on day 18 and 9L tumors on day 24). This network identifies potential signaling in tumor cell death-induced pathways, such as interferon, cytokine, tumor necrosis factor, TLR, and NFkB signaling. Deeper shades of red and green denote human tumor genes that are up-regulated (red) or down-regulated (green) by metronomic CPA to a greater extent as compared to lighter shades, as indicated by microarray analysis. Key at the bottom: shapes used to indicate the molecular class of each factor, as defined in Figure 3.
Figure 5
Figure 5
Downstream target network for the predicted mouse (host) upstream regulators DDX58 (magenta), FADD (dark blue), MAVS (red), STAT1 (green), and IRF7 (teal blue), showing multi-layer cell signaling and cross-talk amongst regulators, as well as downstream signaling and up- or down-regulation of genes identified on the mouse array following metronomic CPA treatment. Genes and upstream regulators show only those that are common to both late time points (day 18 and day 24) across the U251 and 9L models. This network identifies potential signaling in tumor cell death-induced immunogenic pathways, such as interferon, cytokine, tumor necrosis factor, and cytolysis (i.e., killer cell lectin, granzyme and perforin) signaling. Deeper shades of red and green denote human tumor genes that are up-regulated (red) or down-regulated (green) by metronomic CPA to a greater extent as compared to lighter shades, as indicated by microarray analysis. Key at the bottom: shapes used to indicate the molecular class of each factor.
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Browder T, Butterfield CE, Kraling BM, Shi B, Marshall B, O’Reilly MS, et al. Antiangiogenic scheduling of chemotherapy improves efficacy against experimental drug-resistant cancer. Cancer Res. 2000;60(7):1878–86. - PubMed
    1. Klement G, Baruchel S, Rak J, Man S, Clark K, Hicklin DJ, et al. Continuous low-dose therapy with vinblastine and VEGF receptor-2 antibody induces sustained tumor regression without overt toxicity. J Clin Invest. 2000;105(8):R15–24. - PMC - PubMed
    1. Pasquier E, Kavallaris M, Andre N. Metronomic chemotherapy: new rationale for new directions. Nat Rev Clin Oncol. 2010;7(8):455–65. - PubMed
    1. Hahnfeldt P, Hlatky L, Klement GL. Center of cancer systems biology second annual workshop–tumor metronomics: timing and dose level dynamics. Cancer Res. 2013;73(10):2949–54. - PMC - PubMed
    1. Lien K, Georgsdottir S, Sivanathan L, Chan K, Emmenegger U. Low-dose metronomic chemotherapy: a systematic literature analysis. Eur J Cancer. 2013;49(16):3387–95. - PubMed

Publication types