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1.
Mol Oncol ; 17(10): 1953-1961, 2023 10.
Artigo em Inglês | MEDLINE | ID: mdl-37666492

RESUMO

The role of the tumor microenvironment (TME) in immuno-oncology has driven demand for technologies that deliver in situ, or spatial, molecular information. Compartmentalized heterogeneity that traditional methods miss is becoming key to predicting both acquired drug resistance to targeted therapies and patient response to immunotherapy. Here, we describe a novel method for assay-agnostic spatial profiling and demonstrate its ability to detect immune microenvironment signatures in breast cancer patients that are unresolved by the immunohistochemical (IHC) assessment of programmed cell death ligand-1 (PD-L1) on immune cells, which represents the only FDA microenvironment-based companion diagnostic test that has been approved for triple-negative breast cancer (TNBC). Two distinct physiological states were found that are uncorrelated to tumor mutational burden (TMB), microsatellite instability (MSI), PD-L1 expression, and intrinsic cancer subtypes.


Assuntos
Neoplasias de Mama Triplo Negativas , Humanos , Neoplasias de Mama Triplo Negativas/diagnóstico , Neoplasias de Mama Triplo Negativas/genética , Neoplasias de Mama Triplo Negativas/tratamento farmacológico , Microambiente Tumoral/genética , Antígeno B7-H1/metabolismo , Biomarcadores Tumorais/genética , Oncologia
2.
Biol Methods Protoc ; 1(1): bpw005, 2016 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-32161782

RESUMO

Gene expression studies which utilize lipopolysaccharide (LPS)-stimulated macrophages to model immune signaling are widely used for elucidating the mechanisms of inflammation-related disease. When expression levels of target genes are quantified using Real-Time quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR), they are analyzed in comparison to reference genes, which should have stable expression. Judicious selection of reference genes is, therefore, critical to interpretation of qRT-PCR results. Ideal reference genes must be identified for each experimental system and demonstrated to remain constant under the experimental conditions. In this study, we evaluated the stability of eight common reference genes: Beta-2-microglobulin (B2M), Cyclophilin A/Peptidylprolyl isomerase A, glyceraldehyde-3-phosphatedehydrogenase (GAPDH), Hypoxanthine Phosphoribosyltransferase 1, Large Ribosomal Protein P0, TATA box binding protein, Ubiquitin C (UBC), and Ribosomal protein L13A. Expression stability of each gene was tested under different conditions of LPS stimulation and compared to untreated controls. Reference gene stabilities were analyzed using Ct value comparison, NormFinder, and geNorm. We found that UBC, closely followed by B2M, is the most stable gene, while the commonly used reference gene GAPDH is the least stable. Thus, for improved accuracy in evaluating gene expression levels, we propose the use of UBC to normalize PCR data from LPS-stimulated macrophages.

3.
Biol Proced Online ; 16: 9, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-24834016

RESUMO

BACKGROUND: Heterogeneity within cell populations is relevant to the onset and progression of disease, as well as development and maintenance of homeostasis. Analysis and understanding of the roles of heterogeneity in biological systems require methods and technologies that are capable of single cell resolution. Single cell gene expression analysis by RT-qPCR is an established technique for identifying transcriptomic heterogeneity in cellular populations, but it generally requires specialized equipment or tedious manipulations for cell isolation. RESULTS: We describe the optimization of a simple, inexpensive and rapid pipeline which includes isolation and culture of live single cells as well as fluorescence microscopy and gene expression analysis of the same single cells by RT-qPCR. We characterize the efficiency of single cell isolation and demonstrate our method by identifying single GFP-expressing cells from a mixed population of GFP-positive and negative cells by correlating fluorescence microscopy and RT-qPCR. CONCLUSIONS: Single cell gene expression analysis by RT-qPCR is a convenient means for investigating cellular heterogeneity, but is most useful when correlating observations with additional measurements. We demonstrate a convenient and simple pipeline for multiplexing single cell RT-qPCR with fluorescence microscopy which is adaptable to other molecular analyses.

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