Dataset Information

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum.

ABSTRACT: Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical samples as training and validation sets and using independent training algorithms, and determine their accuracy in identifying IBC samples in three independent datasets. We show that these gene lists have little to no mutual overlap, and have limited predictive accuracy in identifying IBC samples. Despite this inconsistency, single-sample gene set enrichment analysis (ssGSEA) of IBC samples correlate with their position on the epithelial-hybrid-mesenchymal spectrum. This positioning, together with ssGSEA scores, improves the accuracy of IBC identification across the three independent datasets. Finally, we observed that IBC samples robustly displayed a higher coefficient of variation in terms of EMT scores, as compared to non-IBC samples. Pending verification that this patient-to-patient variability extends to intratumor heterogeneity within a single patient, these results suggest that higher heterogeneity along the epithelial-hybrid-mesenchymal spectrum can be regarded to be a hallmark of IBC and a possibly useful biomarker.

SUBMITTER: Chakraborty P

PROVIDER: S-EPMC7851345 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum.

Chakraborty Priyanka P George Jason T JT Woodward Wendy A WA Levine Herbert H Jolly Mohit Kumar MK

Translational oncology 20210131 4

Inflammatory breast cancer (IBC) is a highly aggressive breast cancer that metastasizes largely via tumor emboli, and has a 5-year survival rate of less than 30%. No unique genomic signature has yet been identified for IBC nor has any specific molecular therapeutic been developed to manage the disease. Thus, identifying gene expression signatures specific to IBC remains crucial. Here, we compare various gene lists that have been proposed as molecular footprints of IBC using different clinical sa ...[more]

PMID: 33535154

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Project description:The Epithelial-mesenchymal transition (EMT) is a cellular process implicated in embryonic development, wound healing, and pathological conditions such as cancer metastasis and fibrosis. Cancer cells undergoing EMT exhibit enhanced aggressive behavior characterized by drug resistance, tumor-initiation potential, and the ability to evade the immune system. Recent in silico, in vitro, and in vivo evidence indicates that EMT is not an all-or-none process; instead, cells can stably acquire one or more hybrid epithelial/mesenchymal (E/M) phenotypes which often can be more aggressive than purely E or M cell populations. Thus, the EMT status of cancer cells can prove to be a critical estimate of patient prognosis. Recent attempts have employed different transcriptomics signatures to quantify EMT status in cell lines and patient tumors. However, a comprehensive comparison of these methods, including their accuracy in identifying cells in the hybrid E/M phenotype(s), is lacking. Here, we compare three distinct metrics that score EMT on a continuum, based on the transcriptomics signature of individual samples. Our results demonstrate that these methods exhibit good concordance among themselves in quantifying the extent of EMT in a given sample. Moreover, scoring EMT using any of the three methods discerned that cells can undergo varying extents of EMT across tumor types. Separately, our analysis also identified tumor types with maximum variability in terms of EMT and associated an enrichment of hybrid E/M signatures in these samples. Moreover, we also found that the multinomial logistic regression (MLR)-based metric was capable of distinguishing between "pure" individual hybrid E/M vs. mixtures of E and M cells. Our results, thus, suggest that while any of the three methods can indicate a generic trend in the EMT status of a given cell, the MLR method has two additional advantages: (a) it uses a small number of predictors to calculate the EMT score and (b) it can predict from the transcriptomic signature of a population whether it is comprised of "pure" hybrid E/M cells at the single-cell level or is instead an ensemble of E and M cell subpopulations.

Project description:The carcinogenesis process is associated with inflammation, which can be modified by diet. There is limited evidence regarding the inflammatory status and diet in association with breast cancer (BC). The aim of this study was to investigate the association of hybrid dietary-blood inflammatory profiles (HD-BIPs) with postmenopausal breast cancer occurrence. The case-control study was conducted among 420 women (230 controls, 190 primary BC cases) aged 40-79 years from north-eastern Poland. Blood levels of C-reactive protein (CRP), interleukin-6 (IL-6) and leukocyte count were marked in 129 postmenopausal women (82 controls, 47 cases). The 62-item food frequency questionnaire (FFQ-6) was used to the dietary data collection. Two HD-BIPs were found using the Principal Component Analysis (PCA). The "Pro-healthy/Neutral-inflammatory" profile was characterized by the frequent consumption of wholemeal cereals/coarse groats, legumes, vegetables, fruits, nuts/seeds and fish. The "Unhealthy/Pro-inflammatory" profile was characterized by the frequent consumption of red/processed meats, animal fats, sugar/honey/sweets, refined cereals/fine groats, and an increased concentration of CRP, IL-6 and granulocyte-to-lymphocyte ratio. The lower odds ratio (OR) of breast cancer was associated with the higher adherence to the "Pro-healthy/Neutral-inflammatory" profile (OR = 0.38; 95% Cl: 0.18-0.80; p < 0.01 for the higher level vs. lower level, crude model; OR for one-point score increment: 0.61; 95% Cl: 0.42-0.87; p < 0.01, adjusted model). The higher OR of breast cancer was associated with the higher adherence to the "Unhealthy/Pro-inflammatory" profile (OR = 3.07; 95%Cl: 1.27-7.44; p < 0.05 for the higher level v.s. lower level, adjusted model; OR for one-point score increment: 1.18; 95%Cl: 1.02-1.36; p < 0.05, adjusted model). This study revealed that the consumption of highly processed, high in sugar and animal fat foods should be avoided because this unhealthy diet was positively associated with postmenopausal breast cancer occurrence through its pro-inflammatory potential. Instead, the frequent consumption of low-processed plant foods and fish should be recommended since this pro-healthy diet was inversely associated with the cancer occurrence even though its anti-inflammatory potential has not been confirmed in this study sample.

Dataset Information

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum.

Publications

Gene expression profiles of inflammatory breast cancer reveal high heterogeneity across the epithelial-hybrid-mesenchymal spectrum.

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