Analysis of Treg cell population in patients with breast cancer with respect to progesterone receptor status

Dziobek, Konrad; Biedka, Marta; Nowikiewicz, Tomasz; Szymankiewicz, Maria; Lukaszewska, Ewelina; Dutsch-Wicherek, Magdalena

doi:10.5114/wo.2018.80038

Cited by 10 publications

(9 citation statements)

References 21 publications

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“…Unlike Trm cells, the presence of immune-suppressing Treg cells in the micro-environment has been associated with poor prognosis in breast cancer 49–51 . After identifying TNFRSF4 as heterogeneously expressed across the Treg cell subgroup, we showed that TNFRSF4 expression was associated with worse patient survival in the METABRIC data set when adjusted for CCL5 expression, which was down-regulated among all Treg cells.…”

Section: Discussionmentioning

confidence: 99%

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data

Reed

Monti

2020

Preprint

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As high-throughput genomics assays become more efficient and cost effective, their utilization has become standard in large-scale biomedical projects. These studies are often explorative, in that relationships between samples are not explicitly defined a priori, but rather emerge from data-driven discovery and annotation of molecular subtypes, thereby informing hypotheses and independent evaluation. Here, we present K2Taxonomer, a novel unsupervised recursive partitioning algorithm and associated R package that utilize ensemble learning to identify robust subgroups in a "taxonomy-like" structure (https://github.com/montilab/K2Taxonomer). K2Taxonomer was devised to accommodate different data paradigms, and is suitable for the analysis of both bulk and single-cell transcriptomics data. For each of these data types, we demonstrate the power of K2Taxonomer to discover known relationships in both simulated and human tissue data. We conclude with a practical application on breast cancer tumor infiltrating lymphocyte (TIL) single-cell profiles, in which we identified co-expression of translational machinery genes as a dominant transcriptional program shared by T cells subtypes, associated with better prognosis in breast cancer tissue bulk expression data.

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Section: Discussionmentioning

confidence: 99%

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data

Reed

Monti

2020

Preprint

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“…Although many studies have described the correlation between gene expression and survival in breast cancer patients, the results of most of these studies have been verified in animal tumor models, in vitro cell models or small numbers of human samples. The infiltration of immune cells (regulatory T cells, M2 tumor-related macrophages and CD20+ B cells) in the microenvironment of breast cancer is an important predictor of prognosis [37–39]. Retrospective studies have indicated that higher expression of immune checkpoint molecules (PD-L1, PD-1, CTLA-4 and LAG3) is associated with a higher survival rate in TNBC patients [40].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment

Bai

Jin

Zhang

et al. 2019

Aging

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In the microenvironment of breast cancer, immune cell infiltration is associated with an improved prognosis. To identify immune-related prognostic markers and therapeutic targets, we determined the lymphocyte-specific kinase (LCK) metagene scores of samples from breast cancer patients in The Cancer Genome Atlas. The LCK metagene score correlated highly with other immune-related scores, as well as with the clinical stage, prognosis and tumor suppressor gene mutation status (BRCA2, TP53, PTEN) of patients in the four breast cancer subtypes. A weighted gene co-expression network analysis was performed to detect representative genes from LCK metagene-related gene modules. In two of these modules, the levels of the co-expressed genes correlated highly with LCK metagene levels, so we conducted an enrichment analysis to discover their functions. We also identified differentially expressed genes in samples with high and low LCK metagene scores. By examining the overlapping results from these analyses, we obtained 115 genes, and found that 22 of them were independent predictors of overall survival in breast cancer patients. These genes were validated for their prognostic and diagnostic value with external data sets and paired tumor and non-tumor tissues. The genes identified herein could serve as diagnostic/prognostic markers and immune-related therapeutic targets in breast cancer.

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“…Recently, different prognostic factors including survivin, mitochondrial-derived activator of caspase, androgen receptor expression, lymphoid environment, and Treg cell population have been used in breast cancer [15,16,17,19]. Adamkov et al [15] examined the survivin expression patterns in malignant and benign breast masses.…”

Section: Discussionmentioning

confidence: 99%

Clinical importance of fibulin-5 immunohistochemical staining in breast lesions

Karanis

Köksal

Ates

et al. 2019

pjp

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The aim of this study was to evaluate the clinical importance of fibulin-5, which has been shown to display tumour-promoting and tumour-protective functions in breast lesions. Sixty-two breast cancer patients, 19 patients with fibroadenoma, and 15 healthy breast tissues were enrolled. Forty-seven patients had invasive ductal carcinoma (IDC) (12 of them also had in situ carcinoma DCIS), and 15 had invasive lobular carcinoma (ILC). A scoring system from 0 to 4 was used to evaluate the fibulin-5 staining according to the percentage of stained cells. The median values of fibulin-5 staining scores of the breast cancer, fibroadenoma, and healthy breast tissues were 2 (range: 0-4), 3 (range: 3-4), and 4 (range: 1-4), respectively, and the difference is statistically significant (p = 0.0001). There was no significant difference between the fibulin-5 scores of IDC, ILC, and DCIS. Fifteen patients with triple-negative breast cancer (TNBC) had the lowest fibulin-5 score (p < 0.0001). The median fibulin-5 scores of the patients according to Ki-67 index ≥ 14% and < 14% were 2 (range: 1-5) and 4 (range: 1-5), respectively, and the difference is statistically significant (p = 0.001). These data can be explained by the inhibitory effect of fibulin-5 on epithelial cell proliferation, which is closely related to differentiation and prognosis.

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Analysis of Treg cell population in patients with breast cancer with respect to progesterone receptor status

Cited by 10 publications

References 21 publications

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data

Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data

Bioinformatic profiling of prognosis-related genes in the breast cancer immune microenvironment

Clinical importance of fibulin-5 immunohistochemical staining in breast lesions

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