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Analysis of tumor vascularization in a mouse model of metastatic lung cancer.

ABSTRACT: Therapies targeting tumor vasculature would improve the treatment of lung metastasis, although the early changes in vascular structure are incompletely understood. Here, we show that obstructive metastatic foci in lung arterioles decrease the pulmonary vascular network. To generate a mouse model of lung metastasis activation, luciferase-expressing tumor cells were inoculated into the subiliac lymph node (SiLN) of an MXH10/Mo-lpr/lpr mouse, and metastatic tumor cells in the lungs were activated by SiLN resection. Activation of metastases was monitored by in vivo bioluminescence imaging. Pulmonary blood vessel characteristics were analyzed using ex vivo micro-computed tomography. The enhanced permeability and retention (EPR) effect in neovasculature after tumor cell activation was evaluated from the accumulation of intravenously injected indocyanine green (ICG) liposomes. Metastatic foci in lung arterioles were investigated histologically. Micro-computed tomography revealed decreases in pulmonary blood vessel length, volume and number of branching nodes during the early stage of metastasis caused by metastatic foci. ICG liposome accumulation by the EPR effect was not detected. Histology identified metastatic foci in lung arterioles. The lack of an EPR effect after the formation of metastatic foci in lung arterioles makes conventional systemic chemotherapy ineffective for lung metastasis. Thus, alternative therapeutic methods of drug delivery are needed.

SUBMITTER: Sukhbaatar A

PROVIDER: S-EPMC6831815 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Analysis of tumor vascularization in a mouse model of metastatic lung cancer.

Sukhbaatar Ariunbuyan A Sakamoto Maya M Mori Shiro S Kodama Tetsuya T

Scientific reports 20191105 1

Therapies targeting tumor vasculature would improve the treatment of lung metastasis, although the early changes in vascular structure are incompletely understood. Here, we show that obstructive metastatic foci in lung arterioles decrease the pulmonary vascular network. To generate a mouse model of lung metastasis activation, luciferase-expressing tumor cells were inoculated into the subiliac lymph node (SiLN) of an MXH10/Mo-lpr/lpr mouse, and metastatic tumor cells in the lungs were activated b ...[more]

PMID: 31690726

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Project description:BACKGROUND:Current preclinical osteosarcoma (OS) models largely focus on quantifying primary tumor burden. However, most fatalities from OS are caused by metastatic disease. The quantification of metastatic OS currently relies on CT, which is limited by motion artifact, requires intravenous contrast, and can be technically demanding in the preclinical setting. We describe the ability for indocyanine green (ICG) fluorescence angiography to quantify primary and metastatic OS in a previously validated orthotopic, immunocompetent mouse model. QUESTIONS/PURPOSES:(1) Can near-infrared ICG fluorescence be used to attach a comparable, quantitative value to the primary OS tumor in our experimental mouse model? (2) Will primary tumor fluorescence differ in mice that go on to develop metastatic lung disease? (3) Does primary tumor fluorescence correlate with tumor volume measured with CT? METHODS:Six groups of 4- to 6-week-old immunocompetent Balb/c mice (n = 6 per group) received paraphyseal injections into their left hindlimb proximal tibia consisting of variable numbers of K7M2 mouse OS cells. A hindlimb transfemoral amputation was performed 4 weeks after injection with euthanasia and lung extraction performed 10 weeks after injection. Histologic examination of lung and primary tumor specimens confirmed ICG localization only within the tumor bed. RESULTS:Mice with visible or palpable tumor growth had greater hindlimb fluorescence (3.5 ± 2.3 arbitrary perfusion units [APU], defined as the fluorescence pixel return normalized by the detector) compared with those with a negative examination (0.71 ± 0.38 APU, -2.7 ± 0.5 mean difference, 95% confidence interval -3.7 to -1.8, p < 0.001). A strong linear trend (r = 0.81, p < 0.01) was observed between primary tumor and lung fluorescence, suggesting that quantitative ICG tumor fluorescence is directly related to eventual metastatic burden. We did not find a correlation (r = 0.04, p = 0.45) between normalized primary tumor fluorescence and CT volumetric measurements. CONCLUSIONS:We demonstrate a novel methodology for quantifying primary and metastatic OS in a previously validated, immunocompetent, orthotopic mouse model. Quantitative fluorescence of the primary tumor with ICG angiography is linearly related to metastatic burden, a relationship that does not exist with respect to clinical tumor size. This highlights the potential utility of ICG near-infrared fluorescence imaging as a valuable preclinical proof-of-concept modality. Future experimental work will use this model to evaluate the efficacy of novel OS small molecule inhibitors. CLINICAL RELEVANCE:Given the histologic localization of ICG to only the tumor bed, we envision the clinical use of ICG angiography as an intraoperative margin and tumor detector. Such a tool may be used as an alternative to intraoperative histology to confirm negative primary tumor margins or as a valuable tool for debulking surgeries in vulnerable anatomic locations. Because we have demonstrated the successful preservation of ICG in frozen tumor samples, future work will focus on blinded validation of this modality in observational human trials, comparing the ICG fluorescence of harvested tissue samples with fresh frozen pathology.

Project description:BackgroundCancer metastasis is a complex process involving the spread of malignant cells from a primary tumor to distal organs. Understanding this cascade at a mechanistic level could provide critical new insights into the disease and potentially reveal new avenues for treatment. Transcriptome profiling of spontaneous cancer models is an attractive method to examine the dynamic changes accompanying tumor cell spread. However, such studies are complicated by the underlying heterogeneity of the cell types involved. The purpose of this study was to examine the transcriptomes of metastatic breast cancer cells using the well-established MMTV-PyMT mouse model.MethodsOrgan-derived metastatic cell lines were harvested from 10 female MMTV-PyMT mice. Cancer cells were isolated and sorted based on the expression of CD44low/EpCAMhigh or CD44high/EpCAMhigh surface markers. RNA from each cell line was extracted and sequenced using the NextSeq 500 Illumina platform. Tissue-specific genes were compared across the different metastatic and primary tumor samples. Reads were mapped to the mouse genome using STAR, and gene expression was quantified using RSEM. Single-cell RNA-seq (scRNA-seq) was performed on select samples using the ddSeq platform by BioRad and analyzed using Seurat v3.2.3. Monocle2 was used to infer pseudo-time progression.ResultsComparison of RNA sequencing data across all cell populations produced distinct gene clusters. Differential gene expression patterns related to CD44 expression, organ tropism, and immunomodulatory signatures were observed. scRNA-seq identified expression profiles based on tissue-dependent niches and clonal heterogeneity. These cohorts of data were narrowed down to identify subsets of genes with high expression and known metastatic propensity. Dot plot analyses further revealed clusters expressing cancer stem cell and cancer dormancy markers. Changes in relevant genes were investigated across pseudo-time and tissue origin using Monocle2. These data revealed transcriptomes that may contribute to sub-clonal evolution and treatment evasion during cancer progression.ConclusionsWe performed a comprehensive transcriptome analysis of tumor heterogeneity and organ tropism during breast cancer metastasis. These data add to our understanding of metastatic progression and highlight targets for breast cancer treatment. These markers could also be used to image the impact of tumor heterogeneity on metastases.

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Analysis of tumor vascularization in a mouse model of metastatic lung cancer.

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Analysis of tumor vascularization in a mouse model of metastatic lung cancer.

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