Abstract GS6-05: A joint atlas of single-cell and bulk RNA-seq in metastatic breast cancer allows inference of oncogenic and drug-resistant transcriptional programs in malignant cells and the tumor microenvironment

Author(s):  
Ofir Cohen ◽  
Daniel Abravanel ◽  
Michal Slyper ◽  
Johanna Klughammer ◽  
Judit Jane-Valbuena ◽  
...  
2021 ◽  
Author(s):  
Karla Helvie ◽  
Laura DelloStritto ◽  
Lori Marini ◽  
Nelly Oliver ◽  
Miraj Patel ◽  
...  

This standard operating procedure was established by the Center for Cancer Genomics at Dana-Farber Cancer Institute, the Brigham and Women's Hospital and the Klarman Cell Observatory at the Broad Institute, to standardize the collection of fresh metastatic breast cancer biopsies and their allocation to various bulk and single cell assays, including whole exome and bulk RNA-sequencing, single-cell RNA sequencing, and spatial profiling of RNA and protein. The use of a well defined workflow has allowed us to generate high quality data from these different assays, by implementing efficient modes of communication, minimizing the time elapsed from sample collection to preservation or processing, and ensuring optimal transportation conditions. Visual Abstract


2021 ◽  
Author(s):  
SANJAY MISHRA ◽  
Manish Charan ◽  
Rajni Kant Shukla ◽  
Pranay Agarwal ◽  
Swati Misri ◽  
...  

Abstract Background: Metastasis is the major cause of mortality in breast cancer; however, the molecular mechanisms remain elusive. In our previous study, we demonstrated that S100A7/RAGE mediates breast cancer growth and metastasis by recruitment of tumor-associated macrophages. However, the downstream S100A7-mediated inflammatory oncogenic signaling cascade that enhances breast tumor growth and metastasis by generating the immunosuppressive tumor microenvironment (iTME) has not been studied. In this present study, we aimed to investigate the S100A7 and cPLA2 cross-talk in enhancing tumor growth and metastasis through enhancing the iTME.Methods: Human breast cancer tissue and plasma samples were used to analyze the expression of S100A7, cPLA2, and PGE2 titer. S100A7-overexpressing or downregulated human metastatic breast cancer cells were used to evaluate the S100A7-mediated downstream signaling mechanisms. Bi-transgenic mS100a7a15 overexpression, TNBC C3(1)/Tag transgenic, and humanized patient-derived xenograft mouse models and cPLA2 inhibitor (AACOCF3) were used to investigate the role of S100A7/cPLA2/PGE2 signaling in tumor growth and metastasis. Additionally, CODEX, a highly advanced multiplexed imaging was employed to delineate the effect of S100A7/cPLA2 inhibition on the recruitment of various immune cells.Results: S100A7 and cPLA2 are highly expressed and positively correlated in malignant breast cancer patients. S100A7/RAGE upregulates cPLA2/PGE2 axis in aggressive breast cancer cells. Furthermore, S100A7 is positively correlated with PGE2 in breast cancer patients. Moreover, cPLA2 pharmacological inhibition suppressed S100A7-mediated tumor growth and metastasis in multiple pre-clinical models. Mechanistically, S100A7-mediated activation of cPLA2 enhances the recruitment of immunosuppressive myeloid cells by increasing PGE2 to fuel breast cancer growth and its secondary spread. We revealed that cPLA2 inhibitor mitigates S100A7-mediated breast tumorigenicity by suppressing the iTME. Furthermore, CODEX imaging data showed that cPLA2 inhibition increased the infiltration of CD4+/CD8+ T cells in the TME. Analysis of metastatic breast cancer samples revealed a positive correlation between S100A7/cPLA2 with CD163+ tumor-associated M2-macrophages.Conclusions: Our study shows that cross-talk between S100A7 and cPLA2 plays an important role in enhancing breast tumor growth and metastasis by generating an immunosuppressive tumor microenvironment and reducing infiltration of T cells. Furthermore, S100A7 could be used as a novel non-invasive prognostic marker and cPLA2 inhibitors as promising drugs against S100A7-overexpressing metastatic breast cancer.


2019 ◽  
Vol 64 (2) ◽  
pp. 91-100 ◽  
Author(s):  
Tianqun Lang ◽  
Xinyue Dong ◽  
Zhong Zheng ◽  
Yiran Liu ◽  
Guanru Wang ◽  
...  

2018 ◽  
Vol 5 (12) ◽  
pp. 1801158 ◽  
Author(s):  
Jialang Zhuang ◽  
Yongjian Wu ◽  
Liang Chen ◽  
Siping Liang ◽  
Minhao Wu ◽  
...  

2014 ◽  
Vol 9 (4) ◽  
pp. 749-757 ◽  
Author(s):  
Marta Pestrin ◽  
Francesca Salvianti ◽  
Francesca Galardi ◽  
Francesca De Luca ◽  
Natalie Turner ◽  
...  

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