An agent-based model of triple-negative breast cancer: the interplay between chemokine receptor CCR5 expression, cancer stem cells, and hypoxia

Norton, Kerri-Ann; Wallace, Travis; Pandey, Niranjan B.; Popel, Aleksander S.

doi:10.1186/s12918-017-0445-x

Cited by 53 publications

(51 citation statements)

References 87 publications

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“…Lymph endothelial cells secrete chemokines including chemokine (C-X-C motif) ligand 12 (CXCL12) and chemokine (C-C motif) ligand 21 (CCL21) to recruit tumor cells that express chemokine (C-C motif) receptor 7 (CCR7) and chemokine (C-X-C motif) receptor 4 (CXCR4) [ 95 , 96 ]. Lymph endothelial cells also secrete C-C chemokine ligand 5 (CCL5), which increases the migratory capacity of TNBC cells that express C-C chemokine receptor 5 (CCR5) [ 97 , 98 ].…”

Section: Vascular Endothelial and Lymph Endothelial Cellsmentioning

confidence: 99%

Stromal cells in breast cancer as a potential therapeutic target

et al. 2018

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Breast cancer in the United States is the second most commonly diagnosed cancer in women. About 1 in 8 women will develop invasive breast cancer over the course of her lifetime and breast cancer remains the second leading cause of cancer-related death. In pursuit of novel therapeutic strategies, researchers have examined the tumor microenvironment as a potential anti-cancer target. In addition to neoplastic cells, the tumor microenvironment is composed of several critical normal cell types, including fibroblasts, vascular and lymph endothelial cells, osteoclasts, adipocytes, and immune cells. These cells have important roles in healthy tissue stasis, which frequently are altered in tumors. Indeed, tumor-associated stromal cells often contribute to tumorigenesis, tumor progression, and metastasis. Consequently, these host cells may serve as a possible target in anti-tumor and anti-metastatic therapeutic strategies. Targeting the tumor associated host cells offers the benefit that such cells do not mutate and develop resistance in response to treatment, a major cause of failure in cancer therapeutics targeting neoplastic cells. This review discusses the role of host cells in the tumor microenvironment during tumorigenesis, progression, and metastasis, and provides an overview of recent developments in targeting these cell populations to enhance cancer therapy efficacy.

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Section: Vascular Endothelial and Lymph Endothelial Cellsmentioning

confidence: 99%

Stromal cells in breast cancer as a potential therapeutic target

et al. 2018

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“…Gene-gene interactions were detected in the relapse group (Fig. 9 ); CCL5 , GZMB , IL2RA , SELE , and CCL8 interacted with CCR5 in both the pCR and relapse groups and were associated with tumour progression [ 14 ], and metastasis [ 10 ]. In patients with breast cancer, CCR5 and its ligand CCL5 were found to be upregulated among DEGs in the pCR group [ 10 ].…”

Section: Resultsmentioning

confidence: 99%

Prediction of prognostic signatures in triple-negative breast cancer based on the differential expression analysis via NanoString nCounter immune panel

et al. 2020

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Background Triple-Negative Breast Cancer (TNBC) is an aggressive and complex subtype of breast cancer. The current biomarkers used in the context of breast cancer treatment are highly dependent on the targeting of oestrogen receptor, progesterone receptor, or HER2, resulting in treatment failure and disease recurrence and creating clinical challenges. Thus, there is still a crucial need for the improvement of TNBC treatment; the discovery of effective biomarkers that can be easily translated to the clinics is essential. Methods We report an approach for the discovery of biomarkers that can predict tumour relapse and pathologic complete response (pCR) in TNBC on the basis of mRNA expression quantified using the NanoString nCounter Immunology Panel. To overcome the limited sample size, prediction models based on random Forest were constructed using the differentially expressed genes (DEGs) as selected features. We also evaluated the differences between pre- and post-treatment groups aiming for the combinatorial assessment of pCR and relapse using additive models in edgeR. Results We identify nine and 13 DEGs strongly associated with pCR and relapse, respectively, from 579 immune genes in a small number of samples (n = 55) using edgeR. An additive model for the comparison of pre- and post-treatment groups via the adjustment of the independent subject in the relapse group revealed associations for 41 genes. Comprehensive analysis indicated that our prediction models outperformed those constructed using features extracted from the existing feature selection model Elastic Net in terms of accuracy. The prediction models were assessed using a randomization test to validate the robustness (empirical P for the model of pCR = 0.015 and empirical P for the model of relapse = 0.018). Furthermore, three DEGs (FCER1A, EDNRB, and TGFBI) in the model of relapse showed prognostic significance for predicting the survival of patients with cancer through Cox proportional hazards regression model-based survival analysis. Conclusion Gene expression quantified via the NanoString nCounter Immunology Panel can be seamlessly analysed using edgeR, even considering small sample sizes. Our approach provides a scalable framework that can easily be applied for the discovery of biomarkers based on the NanoString nCounter Immunology Panel. Data availability The source code will be available from github at https://github.com/sungheep/nanostring.

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“…The presence of cancer stem cells can be an important indicator of tumor growth and recurrence ( 23 ). We find expression of the stem-like marker CD71 is significantly modeled by the interaction of GSC line with transport condition (X 2 =64.68, p<0.0001), glia components (X 2 =86.62, p<0.0001), and all three covariates (X 2 =40.26, p<0.0019).…”

Section: Resultsmentioning

confidence: 99%

A patient-designed tissue-engineered model of the infiltrative glioblastoma microenvironment

Cornelison

Yuan

Tate

et al. 2020

Preprint

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Glioblastoma is an aggressive brain cancer characterized by diffuse infiltration. Infiltrated glioma cells persist in the brain post-resection where they interact with glial cells and experience interstitial fluid flow. We recreate this infiltrative microenvironment in vitro based on resected patient tumors and examine malignancy metrics (invasion, proliferation, and stemness) in the context of cellular and biophysical factors and therapies. Our 3D tissue-engineered model comprises patient-derived glioma stem cells, human astrocytes and microglia, and interstitial fluid flow. We found flow contributes to all outcomes across seven patient-derived lines, and glial effects are driven by CCL2 and differential glial activation. We conducted a six-drug screen using four outcomes and find expression of putative stemness marker CD71, opposed to viability IC50, significantly predicts murine xenograft survival. Our results dispute the paradigm of viability as predictive of drug efficacy. We posit this patient-centric, infiltrative tumor model is a novel advance towards translational personalized medicine.

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An agent-based model of triple-negative breast cancer: the interplay between chemokine receptor CCR5 expression, cancer stem cells, and hypoxia

Cited by 53 publications

References 87 publications

Stromal cells in breast cancer as a potential therapeutic target

Stromal cells in breast cancer as a potential therapeutic target

Prediction of prognostic signatures in triple-negative breast cancer based on the differential expression analysis via NanoString nCounter immune panel

A patient-designed tissue-engineered model of the infiltrative glioblastoma microenvironment

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