scholarly journals BCL(X)L and BCL2 increase the metabolic fitness of breast cancer cells: a single-cell imaging study

Author(s):  
Federico Lucantoni ◽  
Manuela Salvucci ◽  
Heiko Düssmann ◽  
Andreas U. Lindner ◽  
Diether Lambrechts ◽  
...  
2021 ◽  
Vol 22 (14) ◽  
pp. 7279
Author(s):  
Paulina Natalia Osuchowska ◽  
Przemysław Wachulak ◽  
Wiktoria Kasprzycka ◽  
Agata Nowak-Stępniowska ◽  
Maciej Wakuła ◽  
...  

Understanding cancer cell adhesion could help to diminish tumor progression and metastasis. Adhesion mechanisms are currently the main therapeutic target of TNBC-resistant cells. This work shows the distribution and size of adhesive complexes determined with a common fluorescence microscopy technique and soft X-ray contact microscopy (SXCM). The results presented here demonstrate the potential of applying SXCM for imaging cell protrusions with high resolution when the cells are still alive in a physiological buffer. The possibility to observe the internal components of cells at a pristine and hydrated state with nanometer resolution distinguishes SXCM from the other more commonly used techniques for cell imaging. Thus, SXCM can be a promising technique for investigating the adhesion and organization of the actin cytoskeleton in cancer cells.


2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A799-A799
Author(s):  
Dhiraj Kumar ◽  
Sreeharsha Gurrapu ◽  
Hyunho Han ◽  
Yan Wang ◽  
Seongyeon Bae ◽  
...  

BackgroundLong non-coding RNAs (lncRNAs) are involved in various biological processes and diseases. Malat1 (metastasis-associated lung adenocarcinoma transcript 1), also known as Neat2, is one of the most abundant and highly conserved nuclear lncRNAs. Several studies have shown that the expression of lncRNA Malat1 is associated with metastasis and serving as a predictive marker for various tumor progression. Metastatic relapse often develops years after primary tumor removal as a result of disseminated tumor cells undergoing a period of latency in the target organ.1–4 However, the correlation of tumor intrinsic lncRNA in regulation of tumor dormancy and immune evasion is largely unknown.MethodsUsing an in vivo screening platform for the isolation of genetic entities involved in either dormancy or reactivation of breast cancer tumor cells, we have identified Malat1 as a positive mediator of metastatic reactivation. To functionally uncover the role of Malat1 in metastatic reactivation, we have developed a knock out (KO) model by using paired gRNA CRISPR-Cas9 deletion approach in metastatic breast and other cancer types, including lung, colon and melanoma. As proof of concept we also used inducible knockdown system under in vivo models. To delineate the immune micro-environment, we have used 10X genomics single cell RNA-seq, ChIRP-seq, multi-color flowcytometry, RNA-FISH and immunofluorescence.ResultsOur results reveal that the deletion of Malat1 abrogates the tumorigenic and metastatic potential of these tumors and supports long-term survival without affecting their ploidy, proliferation, and nuclear speckles formation. In contrast, overexpression of Malat1 leads to metastatic reactivation of dormant breast cancer cells. Moreover, the loss of Malat1 in metastatic cells induces dormancy features and inhibits cancer stemness. Our RNA-seq and ChIRP-seq data indicate that Malat1 KO downregulates several immune evasion and stemness associated genes. Strikingly, Malat1 KO cells exhibit metastatic outgrowth when injected in T cells defective mice. Our single-cell RNA-seq cluster analysis and multi-color flow cytometry data show a greater proportion of T cells and reduce Neutrophils infiltration in KO mice which indicate that the immune microenvironment playing an important role in Malat1-dependent immune evasion. Mechanistically, loss of Malat1 is associated with reduced expression of Serpinb6b, which protects the tumor cells from cytotoxic killing by the T cells. Indeed, overexpression of Serpinb6b rescued the metastatic potential of Malat1 KO cells by protecting against cytotoxic T cells.ConclusionsCollectively, our data indicate that targeting this novel cancer-cell-initiated domino effect within the immune system represents a new strategy to inhibit tumor metastatic reactivation.Trial RegistrationN/AEthics ApprovalFor all the animal studies in the present study, the study protocols were approved by the Institutional Animal Care and Use Committee(IACUC) of UT MD Anderson Cancer Center.ConsentN/AReferencesArun G, Diermeier S, Akerman M, et al., Differentiation of mammary tumors and reduction in metastasis upon Malat1 lncRNA loss. Genes Dev 2016 Jan 1;30(1):34–51.Filippo G. Giancotti, mechanisms governing metastatic dormancy and reactivation. Cell 2013 Nov 7;155(4):750–764.Gao H, Chakraborty G, Lee-Lim AP, et al., The BMP inhibitor Coco reactivates breast cancer cells at lung metastatic sites. Cell 2012b;150:764–779.Gao H, Chakraborty G, Lee-Lim AP, et al., Forward genetic screens in mice uncover mediators and suppressors of metastatic reactivation. Proc Natl Acad Sci U S A 2014 Nov 18; 111(46): 16532–16537.


RSC Advances ◽  
2021 ◽  
Vol 11 (16) ◽  
pp. 9076-9085
Author(s):  
Kanchan Yadav ◽  
Megha Das ◽  
Nurul Hassan ◽  
Archana Mishra ◽  
Jayeeta Lahiri ◽  
...  

A novel nanodot-using protein has been synthesized for the live cell imaging and drug delivery of melatonin in breast cancer cells. Its unique properties hold potential for various biomedical applications in the field of bioimaging and drug delivery.


2020 ◽  
Author(s):  
Santosh Kumar Paidi ◽  
Vaani Shah ◽  
Piyush Raj ◽  
Kristine Glunde ◽  
Rishikesh Pandey ◽  
...  

AbstractIdentification of the metastatic potential represents one of the most important tasks for molecular imaging of cancer. While molecular imaging of metastases has witnessed substantial progress as an area of clinical inquiry, determining precisely what differentiates the metastatic phenotype has proven to be more elusive underscoring the need to marry emerging imaging techniques with tumor biology. In this study, we utilize both the morphological and molecular information provided by 3D optical diffraction tomography and Raman spectroscopy, respectively, to propose a label-free route for optical phenotyping of cancer cells at single-cell resolution. By using an isogenic panel of cell lines derived from MDA-MB-231 breast cancer cells that vary in their metastatic potential, we show that 3D refractive index tomograms can capture subtle morphological differences among the parental, circulating tumor cells, and lung metastatic cells. By leveraging the molecular specificity of Raman spectroscopy, we demonstrate that coarse Raman microscopy is capable of rapidly mapping a sufficient number of cells for training a random forest classifier that can accurately predict the metastatic potential of cells at a single-cell level. We also leverage multivariate curve resolution – alternating least squares decomposition of the spectral dataset to demarcate spectra from cytoplasm and nucleus, and test the feasibility of identifying metastatic phenotypes using the spectra only from the cytoplasmic and nuclear regions. Overall, our study provides a rationale for employing coarse Raman mapping to substantially reduce measurement time thereby enabling the acquisition of reasonably large training datasets that hold the key for label-free single-cell analysis and, consequently, for differentiation of indolent from aggressive phenotypes.


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

Nature ◽  
2015 ◽  
Vol 526 (7571) ◽  
pp. 131-135 ◽  
Author(s):  
Devon A. Lawson ◽  
Nirav R. Bhakta ◽  
Kai Kessenbrock ◽  
Karin D. Prummel ◽  
Ying Yu ◽  
...  

2018 ◽  
Author(s):  
Detu Zhu ◽  
Xianglan Zhaozu ◽  
Guimei Cui ◽  
Shiehong Chang ◽  
Yi Xiang See ◽  
...  

AbstractEstrogen regulates diverse physiological effects and drives breast tumor progression by directly activating estrogen receptor α (ERα). However, due to the stochastic nature of gene transcription and the resulting heterogeneous cellular response, it is important to investigate estrogen-stimulated gene expression profiles at the single-cell level in order to fully understand how ERα regulates transcription in breast cancer cells. In this study, we performed single-cell transcriptome analysis on ERα-positive breast cancer cell lines following 17β-estradiol stimulation. Overall, we observed robust gene expression diversity between individual cells. Moreover, we found over two thirds of the genes in breast cancer cells displayed a bimodal expression pattern, which caused averaging artifacts and masked the identification of potential estrogen-regulated genes. We overcame this issue by reconstructing a dynamic estrogen-responsive transcriptional network from discrete time points into a pseudotemporal continuum. Pathway analysis of the differentially expressed genes derived from the pseudotemporal analysis showed an estrogen-stimulated metabolic switch that favored biosynthesis and cell proliferation but reduced estrogen degradation. In addition, we identified folate-mediated one-carbon metabolism as a novel estrogen-regulated pathway in breast cancer cells. Notably, estrogen stimulation reprogramed this pathway through the mitochondrial folate pathway to coordinately fuel polyamine and de novo purine synthesis. Finally, we showed AZIN1 and PPAT, key regulators in the above pathways, are direct ERα target genes and essential for breast cancer cell survival and growth. In summary, our single-cell study illustrated a dynamic transcriptional heterogeneity in ERα-positive breast cancer cells in response to estrogen stimulation and uncovered a novel mechanism of an estrogen-mediated metabolic switch.


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