9 research outputs found
Histone-3 methylation marks in cancer progression.
<p>(A) Western blot of H3K4 tri-methyl, H3K9 tri-methyl, H3K27 tri-methyl and actin control in tumor lysates from adenomas (5 week outgrowth), carcinomas (18 week outgrowth), and lung metastasis; n = 3 per group. (B) Western blot of H3K4 tri-methyl, H3K4 di-methyl, H3K4 mono-methyl and Histone 3 control performed with serial dilutions of tumor lysates (1 ug, 5 ug, 10 ug total protein loaded per well). (C) Fluidigm RT-PCR analysis of Il-6, Il-6ra, and Prdm1 in the indicated tumor populations. GFP-positive tumor populations were FACS-sorted from the indicated groups and mRNA was harvested for the analysis; mean ± s.e.m., n = 5 per group. Data was normalized to Gapdh expression.</p
Gene families enriched in residual MMTV-PyMT tumors after chemotherapy.
<p>Gene families enriched in residual MMTV-PyMT tumors after chemotherapy.</p
Profiling of disseminated cells and metastases in MMTV-PyMT hyperplasia transplant model.
<p>Representative brightfield (A) and GFP fluorescence (A′) images of the lungs of mice with advanced carcinoma (18 week outgrowths). Disseminated tumors cells were detected as single, GFP-positive cells in the lungs as early as 8-weeks post-transplant. (B) Representative image of a single disseminated tumor cell in the lung of an 18-week-tumor-bearing mouse. Green indicates GFP and blue indicates DAPI. (C) Whole mount image of lung metastases. Mice with 18-week tumor outgrowths were anesthetized and the primary tumor was surgically removed. Mice were sacrificed when they developed the first signs of respiratory distress, indicating the growth of lung metastases (typically 8–10 weeks after primary tumor removal). (D) Number of genes differentially expressed by 2-fold (light blue) and 4-fold (dark blue) in microarray dataset comparisons. (E) Hierarchical clustering of chromatin modifying genes in tumor populations. Tumor populations from adenoma (red), carcinoma (green), disseminated cells (blue), and metastases (purple) were FACS-sorted for profiling. Inset shows clustering of H3K4, H3K9, and H3K27 methyltransferases. Scale bars correspond to 1 mm (A, C) and 5 um (B).</p
Biomarkers of Residual Disease, Disseminated Tumor Cells, and Metastases in the MMTV-PyMT Breast Cancer Model
<div><p>Cancer metastases arise in part from disseminated tumor cells originating from the primary tumor and from residual disease persisting after therapy. The identification of biomarkers on micro-metastases, disseminated tumors, and residual disease may yield novel tools for early detection and treatment of these disease states prior to their development into metastases and recurrent tumors. Here we describe the molecular profiling of disseminated tumor cells in lungs, lung metastases, and residual tumor cells in the MMTV-PyMT breast cancer model. MMTV-PyMT mice were bred with actin-GFP mice, and focal hyperplastic lesions from pubertal MMTV-PyMT;actin-GFP mice were orthotopically transplanted into FVB/n mice to track single tumor foci. Tumor-bearing mice were treated with TAC chemotherapy (docetaxel, doxorubicin, cyclophosphamide), and residual and relapsed tumor cells were sorted and profiled by mRNA microarray analysis. Data analysis revealed enrichment of the Jak/Stat pathway, Notch pathway, and epigenetic regulators in residual tumors. Stat1 was significantly up-regulated in a DNA-damage-resistant population of residual tumor cells, and a pre-existing Stat1 sub-population was identified in untreated tumors. Tumor cells from adenomas, carcinomas, lung disseminated tumor cells, and lung metastases were also sorted from MMTV-PyMT transplant mice and profiled by mRNA microarray. Whereas disseminated tumors cells appeared similar to carcinoma cells at the mRNA level, lung metastases were genotypically very different from disseminated cells and primary tumors. Lung metastases were enriched for a number of chromatin-modifying genes and stem cell-associated genes. Histone analysis of H3K4 and H3K9 suggested that lung metastases had been reprogrammed during malignant progression. These data identify novel biomarkers of residual tumor cells and disseminated tumor cells and implicate pathways that may mediate metastasis formation and tumor relapse after therapy.</p> </div
Ifn-γ/Jak/Stat signaling in MMTV-PyMT residual tumor cells after chemotherapy.
<p>(A) Ingenuity pathway analysis of genes up-regulated in chemotherapy-treated residual tumors in the MMTV-PyMT transplant model. (B) Microarray expression values of Ifn-γ/Jak/Stat-associated genes in untreated (green), residual (red) and relapsed (blue) tumors; mean, n = 5 per group. (C) Fluidigm RT-PCR analysis of Ifn-γ/Jak/Stat-associated genes. GFP-positive tumor populations were FACS-sorted from the indicated groups and mRNA was harvested for the analysis; mean ± s.e.m., n = 5 per group. Data was normalized to Gapdh expression.</p
Enrichment of a Stat1-positive tumor sub-population in MMTV-PyMT residual tumor cells after chemotherapy.
<p>(A–A″) Immunohistochemistry of Stat1 in untreated tumors (A), residual tumors (A’) and relapsed tumors (A″). (B) Immunofluorescence of Stat1 (red), F4-80 (green), and DAPI (blue) in untreated tumors sample. (C–C′) Immunohistochemistry of p-Stat1 in untreated (C) and residual tumor samples (C′). (D) Western blot of p-Stat1, Stat1, p-Stat3, p-Stat6, and actin control in MMTV-PyMT whole tumor lysates. Mice were treated with TAC chemotherapy and tumors harvested on the indicated number of days after treatment. (E) Immunohistochemistry of Stat1 and phospho-H2A.X in residual tumor sample. Scale bars correspond to 200 um (A–A″), 300 um (G) and 25 um (B–E′).</p
Up-regulation of Notch family members in MMTV-PyMT residual tumors.
<p>(A) Taqman RT-PCR analysis of untreated, residual and relapsed tumors. Whole tumor lysates were harvested and mRNA purified for RT-PCR. Individual tumor samples were analyzed in triplicate; mean ± s.e.m, red line indicates average Ct value. M100 sample was negative control. (B) Fluidigm RT-PCR analysis of Notch1 and Dll1 in tumor populations. GFP-positive tumor populations were FACS-sorted from indicated groups and mRNA was harvested for the analysis; mean ± s.e.m., n = 5 per group. All data were normalized to Gapdh expression.</p
Modeling breast cancer residual disease in the MMTV-PyMT hyperplasia transplant model.
<p>(A) Representative images of a focal hyperplastic tumor in the No. 4 mammary gland of a female, 3 week-old MMTV-PyMT;actin-GFP mouse (left panel). The tumor was microdissected from mammary gland, placed in PBS (middle image), and then transplanted into the mammary fat pad of a wild-type mouse (right panel). (B) and (C) Representative fluorescent and H&E images of tumor outgrowths after transplantation. (D) Tumor response curve of MMTV-PyMT transplant mice treated with TAC chemotherapy (docetaxel, doxorubicin, cyclophosphamide); mean ± s.e.m., n = 10. Arrows indicate chemotherapy dosing. Scale bars correspond to 1 mm (A) and 100 um (C).</p
Up-regulation of chromatin modifying gene in MMTV-PyMT residual tumors.
<p>Fluidigm RT-PCR analysis of H3K4 methyltransferases (A), H3K9 methyltransferases (B) and other chromatin-modifying enzymes (C) in various tumor populations. GFP-positive tumor populations were FACS-sorted from indicated groups and mRNA was harvested for the analysis; mean ± s.e.m., n = 5 per group. Data were normalized to Gapdh expression.</p