Dissection of stromal and cancer cell-derived signals in melanoma xenografts before and after treatment with DMXAA

Abstract

Background:The non-malignant cells of the tumour stroma have a critical role in tumour biology. Studies dissecting the interplay between cancer cells and stromal cells are required to further our understanding of tumour progression and methods of intervention. For proof-of-principle of a multi-modal approach to dissect the differential effects of treatment on cancer cells and stromal cells, we analysed the effects of the stromal-targeting agent 5,6-dimethylxanthenone-4-acetic acid on melanoma xenografts.Methods:Flow cytometry and multi-colour immunofluorescence staining was used to analyse leukocyte numbers in xenografts. Murine-specific and human-specific multiplex cytokine panels were used to quantitate cytokines produced by stromal and melanoma cells, respectively. Human and mouse Affymetrix microarrays were used to separately identify melanoma cell-specific and stromal cell-specific gene expression.Results:5,6-Dimethylxanthenone-4-acetic acid activated pro-inflammatory signalling pathways and cytokine expression from both stromal and cancer cells, leading to neutrophil accumulation and haemorrhagic necrosis and a delay in tumour re-growth of 26 days in A375 melanoma xenografts.Conclusion:5,6-Dimethylxanthenone-4-acetic acid and related analogues may potentially have utility in the treatment of melanoma. The experimental platform used allowed distinction between cancer cells and stromal cells and can be applied to investigate other tumour models and anti-cancer agents.

Vascular priming enhances chemotherapeutic efficacy against head and neck cancer

“…The results (shown in Supplementary Fig. 6 ) were consistent with DMXAA exerting its antivascular activity through cytokine induction and chemokine modulation, including induction of tumor necrosis factor (TNF-alpha) and interleukin (IL-6) canonical pathways (28-30). Analysis of the functional interactions between gene classes in the transcriptomes under study with Gene Ontology identified several annotated biomarkers including IL-8, MMP-10, STAT1, STC1, FSTL3, CXCL1 and CTSB.…”

Transposon mutagenesis identifies genetic drivers of BrafV600E melanoma

“…GFP fluorescence was visualized at the time of caliper measurement; loss of GFP signal was considered to indicate failed engraftment, and corresponding mice were removed from the study (take rates were ≥80% for all cohorts). Ellipsoid tumor volumes were calculated as volume (mm 3 ) = 0.52(length (mm) × width 2 (mm 2 )), where the two longest axes, length and width, were the major and minor diameter measurements, respectively; width 2 represents an assumption that the xenograft depth was equivalent to the diameter of the minor axis 98 . Statistical significance of tumor volumes at defined time points was determined by either one-way t test for all cohorts relative to shNTC or by two-way, repeated-measures ANOVA with Bonferroni correction for multiple comparisons, as indicated.…”

-Omics and Cancer Biomarkers: Link to the Biological Truth or Bear the Consequences

“…At this time, from a biomarker standpoint it is not clear what the clinical impact of tumor heterogeneity is, or even if the DNA mutation differences seen because of sampling are simply due to the lack of knowledge of which mutations are the causal driving mutations and which are passenger mutations. The need to eliminate bias caused by tissue cellular heterogeneity has certainly been recognized for over 15 years (14), and this problem has become more acute recently because of the surge of interest in the role of the tumor microenvironment (15–17) and potential for stromal therapy (18, 19). Any given piece of tumor often contains a hodgepodge of tumor epithelium, normal appearing epithelium, nerve cells, immune cells, extracellular matrix, stromal cells, and vascular cells.…”