scholarly journals Genomic landscape of the immune microenvironments of brain metastases in breast cancer

2020 ◽  
Author(s):  
Wei-cheng Lu ◽  
Hui Xie ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Brain Metastases ◽  
Plasma Cells ◽  
Function Analysis ◽  
Immune Microenvironment ◽  
Metastatic Recurrence ◽  
Genomic Landscape ◽  
Tumor Immune Microenvironment ◽  
Immune Related Genes

Abstract Background This study was intended to investigate the genomic landscape of the immune microenvironments of brain metastases in breast cancer. Methods Three gene expression profile datasets (GSE76714, GSE125989 and GSE43837) of breast cancer with brain metastases were downloaded from Gene Expression Omnibus (GEO) database. After differential expression analysis, the tumor immune microenvironment and immune cell infiltration were analyzed. Then immune-related genes were identified, followed by function analysis, transcription factor (TF)-miRNA-mRNA co-regulatory network analysis, and survival analysis of metastatic recurrence. Results The present results showed that the tumor immune microenvironment in brain metastases was immunosuppressed compared with primary caner. Compared with primary cancer samples, the infiltration ratio of plasma cells in brain metastases samples was significantly higher, while the infiltration ratio of macrophages M2 cells in brain metastases samples was significantly lower. Total 42 immune-related genes were identified, such as THY1 and NEU2. CD1B and THY1 were found to be implicated in the metastatic recurrence of breast cancer. Conclusions Targeting macrophages or plasma cells may be new strategies for immunotherapy of breast cancer with brain metastases. THY1 and NEU2 may be potential therapeutic targets for breast cancer with brain metastases, and THY1 and CD1B may serve as potential prognostic markers for improvement of brain metastases survival.

scholarly journals Genomic landscape of the immune microenvironments of brain metastases in breast cancer

2020 ◽  
Author(s):  
Wei-cheng Lu ◽  
Hui Xie ◽  
Ce Yuan ◽  
Jin-jiang Li ◽  
Zhao-yang Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Brain Metastases ◽  
Plasma Cells ◽  
Function Analysis ◽  
Immune Microenvironment ◽  
Metastatic Recurrence ◽  
Genomic Landscape ◽  
Tumor Immune Microenvironment ◽  
Immune Related Genes

Abstract Background: This study was intended to investigate the genomic landscape of the immune microenvironments of brain metastases in breast cancer. Methods: Three gene expression profile datasets (GSE76714, GSE125989 and GSE43837) of breast cancer with brain metastases were downloaded from Gene Expression Omnibus (GEO) database. After differential expression analysis, the tumor immune microenvironment and immune cell infiltration were analyzed. Then immune-related genes were identified, followed by function analysis, transcription factor (TF)-miRNA-mRNA co-regulatory network analysis, and survival analysis of metastatic recurrence. Results: The present results showed that the tumor immune microenvironment in brain metastases was immunosuppressed compared with primary caner. Compared with primary cancer samples, the infiltration ratio of plasma cells in brain metastases samples was significantly higher, while the infiltration ratio of macrophages M2 cells in brain metastases samples was significantly lower. Total 42 immune-related genes were identified, such as THY1 and NEU2. CD1B, THY1 and DOCK2 were found to be implicated in the metastatic recurrence of breast cancer. Conclusions: Targeting macrophages or plasma cells may be new strategies for immunotherapy of breast cancer with brain metastases. THY1 and NEU2 may be potential therapeutic targets for breast cancer with brain metastases, and THY1, CD1B and DOCK2 may serve as potential prognostic markers for improvement of brain metastases survival.

scholarly journals EPEN-10. UNRAVELLING THE TUMOR IMMUNE MICROENVIRONMENT OF POSTERIOR FOSSA A EPENDYMOMAS ON RNA AND PROTEIN EXPRESSION LEVELS

2021 ◽  
Vol 23 (Supplement_1) ◽  
pp. i15-i15
Author(s):  
Fenna F. Feenstra ◽  
Friso Calkoen ◽  
Johan M Kros ◽  
Lennart Kester ◽  
Mariëtte Kranendonk ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Expression ◽  
Posterior Fossa ◽  
Antigen Processing ◽  
Sequence Data ◽  
Expression Profiles ◽  
Immune Microenvironment ◽  
Expression Levels ◽  
Tumor Immune Microenvironment ◽  
Immune Related Genes

Abstract Background Ependymomas account for 8–10% of pediatric brain tumors, and the standard therapy of surgery and radiation has not changed for the past two decades. Characterization of the tumor immune microenvironment (TIME) is of great importance in order to find better therapies. However, the TIME of ependymomas is still not defined. In this retrospective observational study we aimed to unravel the TIME of ependymomas at mRNA and protein expression levels. Methods Ependymoma samples from two locations were selected: Posterior Fossa (PF-A, n=8), and supratentorial (ST, n=5). Targeted gene expression profile using the PanCancer immune profile panel of NanoString technology was performed. Data were analyzed using the nSolver software. In addition, 8 samples were subjected to RNA bulk sequencing, and the sequenced data were connected to the expression data of the same samples. To validate some of the findings, immunohistochemistry was performed. Results Unsupervised hierarchical clustering showed that PF-A ependymomas can be divided into two groups based on the expression of their immune-related genes. PF-A that showed high immune-expression clustered closely to the ST ependymomas. Significant expressions of genes related to “antigen-processing” and “adhesion” pathways were found in the immune-active groups. On the contrary, the PF-A that had low expressions of immune-related genes showed a high expression of BMI1 that has a prognostic and therapeutic value. Connecting gene expression to bulk sequence data validated the findings. In addition, immunohistochemical analysis confirmed that protein expression for some of the findings. Conclusion The TIME varies in ependymomas based on the location of the tumor. Moreover, the immune-related expression profiles indicated that PF-A ependymomas can be divided into two groups: immune-active and immune-not active PF-A. The prognostic and therapeutic values of the immune activity of PF-A should be further studied.

Characterization of the tumor immune microenvironment of triple-negative breast cancer (TNBC) patients who self-identify as African American (AA) or non-African American (NonAA).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 564-564
Author(s):  
Kim Blenman ◽  
Michal Marczyk ◽  
Tao Qing ◽  
Tess O'Meara ◽  
Vesal Yaghoobi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
African American ◽  
Triple Negative Breast Cancer ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Immune Microenvironment ◽  
Gene Level ◽  
Tumor Immune Microenvironment ◽  
Pathway Level

564 Background: What tumor biological differences, if any, contribute to the higher incidence and worse prognosis of triple negative breast cancer (TNBC) in African American (AA) compared to NonAA patients are unknown. We hypothesized that differences in the tumor immune microenvironment may contribute to the outcome disparities. The purpose of this study was to characterize and compare the immune microenvironment of TNBC between patients self-identified as NonAA or AA. Methods: Formalin fixed paraffin embedded surgically resected cancer and paired normal tissues collected before any systemic therapy and the corresponding clinical data were collected for NonAA (n = 56) and AA (n = 54) stage I-III TNBC treated at Yale Cancer Center between 2000-2017. The two cohorts were matched for clinical stage, age of diagnosis, and year of diagnosis. We performed somatic and germline whole exome sequencing (WES), bulk RNA sequencing, and immunohistochemistry to assess PD-L1 expression (SP142). Stromal tumor infiltrating lymphocytes (sTILs) were assessed on H&E slides. Mutation load, mutation frequencies, and gene expression differences were compared at gene and pathway level. Immune cell composition was estimated through gene expression deconvolution analyses (TIDE). Results: Tumor mutational burden was similar between the two cohorts. At gene level, few genes had significantly different somatic mutation frequencies, or differential mRNA expression between AA and NonAA samples. Pathway level alterations showed inflammation, immunity (adaptive; innate), antigen presentation, and allograft rejection pathways were more affected by somatic mutations in AA samples. The affected genes differed from cancer to cancer and were not recurrent and therefore were missed at gene level analysis. Gene set enrichment and co-expression analysis also showed higher immune related pathway expression in AA samples. Unsupervised co-expression cluster analysis confirmed coordinated overexpression of genes involved in immunity, inflammation, and cytokine/chemokine signaling in AA patients. Two immunotherapy response predictive signatures, immune inflamed and the IFNG as well as sTILs score and PD-L1 positivity were also higher in AA samples. These findings raise the possibility that immune checkpoint inhibitors might be particularly effective in AA patients. In NonAA samples, the EMT transition, angiogenesis, adipogenesis, myogenesis, fatty acid metabolism, TGFβ signaling, UV-response, and hypoxia pathways were overexpressed. TIDE analysis suggested higher levels of TAM M2, overall TIDE score, and the Immune Exclusion score in NonAA samples. Conclusions: TNBC in AA patients more frequently harbor somatic mutations in genes involved with immune functions and overexpress immune and inflammatory genes compared to NonAA patients.

scholarly journals Prognostic Significance and Tumor Immune Microenvironment Heterogenicity of m5C RNA Methylation Regulators in Triple-Negative Breast Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhidong Huang ◽  
Junfan Pan ◽  
Helin Wang ◽  
Xianqiang Du ◽  
Yusheng Xu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Triple Negative Breast Cancer ◽  
Prognostic Value ◽  
Triple Negative ◽  
Gene Set Enrichment Analysis ◽  
Immune Microenvironment ◽  
Data Set ◽  
Rna Methylation ◽  
Tumor Immune Microenvironment

PurposeThe m5C RNA methylation regulators are closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the gene expression, clinicopathological characteristics, and prognostic value of m5C regulators in triple-negative breast cancer (TNBC) and their correlation with the tumor immune microenvironment (TIM).MethodsThe TNBC data, Luminal BC data and HER2 positive BC data set were obtained from The Cancer Genome Atlas and Gene Expression Omnibus, and 11 m5C RNA methylation regulators were analyzed. Univariate Cox regression and the least absolute shrinkage and selection operator regression models were used to develop a prognostic risk signature. The UALCAN and cBioportal databases were used to analyze the gene characteristics and gene alteration frequency of prognosis-related m5C RNA methylation regulators. Gene set enrichment analysis was used to analyze cellular pathways enriched by prognostic factors. The Tumor Immune Single Cell Hub (TISCH) and Timer online databases were used to explore the relationship between prognosis-related genes and the TIM.ResultsMost of the 11 m5C RNA methylation regulators were differentially expressed in TNBC and normal samples. The prognostic risk signature showed good reliability and an independent prognostic value. Prognosis-related gene mutations were mainly amplified. Concurrently, the NOP2/Sun domain family member 2 (NSUN2) upregulation was closely related to spliceosome, RNA degradation, cell cycle signaling pathways, and RNA polymerase. Meanwhile, NSUN6 downregulation was related to extracellular matrix receptor interaction, metabolism, and cell adhesion. Analysis of the TISCH and Timer databases showed that prognosis-related genes affected the TIM, and the subtypes of immune-infiltrating cells differed between NSUN2 and NSUN6.ConclusionRegulatory factors of m5C RNA methylation can predict the clinical prognostic risk of TNBC patients and affect tumor development and the TIM. Thus, they have the potential to be a novel prognostic marker of TNBC, providing clues for understanding the RNA epigenetic modification of TNBC.

scholarly journals Immune microenvironment and intrinsic subtyping in hormone receptor-positive/HER2-negative breast cancer

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Gaia Griguolo ◽  
Maria Vittoria Dieci ◽  
Laia Paré ◽  
Federica Miglietta ◽  
Daniele Giulio Generali ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Gene Expression Data ◽  
Hormone Receptor ◽  
Tumor Biology ◽  
Expression Data ◽  
Immune Microenvironment ◽  
Immune Infiltrate ◽  
Hormone Receptor Positive ◽  
Her2 Breast Cancer

AbstractLittle is known regarding the interaction between immune microenvironment and tumor biology in hormone receptor (HR)+/HER2− breast cancer (BC). We here assess pretreatment gene-expression data from 66 HR+/HER2− early BCs from the LETLOB trial and show that non-luminal tumors (HER2-enriched, Basal-like) present higher tumor-infiltrating lymphocyte levels than luminal tumors. Moreover, significant differences in immune infiltrate composition, assessed by CIBERSORT, were observed: non-luminal tumors showed a more proinflammatory antitumor immune infiltrate composition than luminal ones.

scholarly journals Relapsed multiple myeloma demonstrates distinct patterns of immune microenvironment and malignant cell-mediated immunosuppression

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Alissa Visram ◽  
Surendra Dasari ◽  
Emilie Anderson ◽  
Shaji Kumar ◽  
Taxiarchis V. Kourelis
Keyword(s):  
Multiple Myeloma ◽  
T Cells ◽  
Plasma Cells ◽  
Malignant Cell ◽  
Immune Microenvironment ◽  
Cytokine Analysis ◽  
Tumor Immune Microenvironment ◽  
Early Memory ◽  
E2f Transcription Factors ◽  
Cluster 2

AbstractImmunotherapy has shown efficacy in relapsed multiple myeloma (MM). However, these therapies may depend on a functional tumor immune microenvironment (iTME) for their efficacy. Characterizing the evolution of the iTME over the disease course is necessary to optimize the timing of immunotherapies. We performed mass cytometry, cytokine analysis, and RNA sequencing on bone marrow samples from 39 (13 newly diagnosed [NDMM], 11 relapsed pre-daratumumab exposure [RMM], and 13 triple-refractory [TRMM]) MM patients. Three distinct cellular iTME clusters were identified; cluster 1 comprised mainly of NDMM and RMM patients; and clusters 2 and 3 comprised primarily of TRMM patients. We showed that naive T cells were decreased in clusters 2 and 3, cluster 2 was characterized by increased senescent T cells, and cluster 3 by decreased early memory T cells. Plasma cells in clusters 2 and 3 upregulated E2F transcription factors and MYC proliferation pathways, and downregulated interferon, TGF-beta, interleuking-6, and TNF-αlpha signaling pathways compared to cluster 1. This study suggests that the MM iTME becomes increasingly dysfunctional with therapy whereas the MM clone may be less dependent on inflammation-mediated growth pathways and less sensitive to IFN-mediated immunosurveillance. Our findings may explain the decreased sensitivity of TRMM patients to novel immunotherapies.

Can Intratumoral neutrophil lymphocyte ratio (NLR) be a prognostic biomarker in breast cancer patients?

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12573-e12573
Author(s):  
Yoshihisa Tokumaru ◽  
Masanori Oshi ◽  
Vijayashree Murthy ◽  
Eriko Katsuta ◽  
Nobuhisa Matsuhashi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Cancer Patients ◽  
Immune Cells ◽  
Breast Cancer Patients ◽  
Immune Microenvironment ◽  
High Group ◽  
Anti Cancer ◽  
Tumor Immune Microenvironment ◽  
Er Positive

e12573 Background: In breast cancer patients, it is well known that the elevation of neutrophil lymphocyte ratio (NLR) in the blood are reported to associate with poor prognosis based on the notion that neutrophils represent pro-cancer, and lymphocytes represent anti-cancer immune cells. Tumor immune microenvironment has been demonstrated to play critical roles in the outcome of breast cancer patients. However, there is scarce evidence on the clinical relevance of intratumoral NLR in breast cancer patients. In the current study, we hypothesized that intratumoral NLR high tumors are associated with worse survival particularly in TNBC that is known to have high immune cell infiltration. Methods: A total of 1904 breast cancer patients’ data from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium) and analyzed. NLR was calculated by the gene expressions of CD66b (CEACAM8) and CD8 (CD8A). NLR high and low were divided by the median. Overall Survival (OS) and Disease-Free Survival were calculated utilizing Kaplan Meier method between intratumoral NLR high and low groups. xCell algorithm was used to analyze the infiltrated immune cells within the tumor immune microenvironment as we have previously published. Results: Intratumoral NLR high group was associated with worse OS in whole, ER-positive/HER2-negative, and triple negative (TN) subtypes, in agreement with the previous studies. TN subtype alone demonstrated worse DFS of NLR high group. Surprisingly, gene set enrichment analysis (GSEA) demonstrated no gene set enrichment to NLR high group, which implicates that there is no distinctive mechanism that associate with worse survival. Whereas, immune response-related gene sets significantly enriched to NLR low group in TN subtype. This enrichment was consistent in ER-positive/HER2-negative. Compared with ER-positive/HER2-negative subtype, anti-cancer immune cells such as CD4+ T cells, CD8+ T cells, M1 macrophage, and helper T helper type 1 cells were significantly infiltrated in TN patients (p < 0.001 for all genes), where M2 macrophages and neutrophils were less and regulatory T cells and T helper type 2 cells were more infiltrated in TN subtype. Furthermore, intratumoral NLR was significantly lower in TN compared with ER-positive/HER2-negative subtype (p < 0.001). These results suggest that intratumoral NLR low group is associated with better survival due to favorable tumor immune microenvironment in TN subtype rather than NLR high group has worse survival. Conclusions: Intratumoral NLR low tumor demonstrated more favorable OS and more favorable DFS in TN patients. Intratumoral NLR low breast cancer was associated with enhanced immune response and higher infiltration of anti-cancer immune cells were observed in TN subtype compared to ER-positive/HER2-negative which may contribute to the favorable outcome of in TN breast cancer.

scholarly journals P02.03 Automated cell type specific PD-L1 quantification by artificial intelligence using high throughput bleach & stain 15-marker multiplex fluorescence immunohistochemistry in human cancers

2021 ◽  
Vol 9 (Suppl 1) ◽  
pp. A8.2-A9
Author(s):  
NC Blessin ◽  
E Bady ◽  
T Mandelkow ◽  
C Yang ◽  
J Raedler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Tumor Cells ◽  
Immune Cells ◽  
T Cell Subsets ◽  
Immune Microenvironment ◽  
L1 Data ◽  
Tumor Immune Microenvironment ◽  
Immune Phenotypes ◽  
Fluorescence Immunohistochemistry ◽  
Tumor Entities

BackgroundThe quantification of PD-L1 (programmed cell death ligand 1) has been used to predict patient’s survival, to characterize the tumor immune microenvironment, and to predict response to immune checkpoint therapies. However, a framework to assess the PD-L1 status with a high interobserver reproducibility on tumor cells and different types of immune cells has yet to be established.Materials and MethodsTo study the impact of PD-L1 expression on the tumor immune microenvironment and patient outcome, a framework for fully automated PD-L1 quantification on tumor cells and immune cells was established and validated. Automated PD-L1 quantification was facilitated by incorporating three different deep learning steps for the analysis of more than 80 different neoplasms from more than 10’000 tumor specimens using a bleach & stain 15-marker multiplex fluorescence immunohistochemistry panel (i.e., PD-L1, PD-1, CTLA-4, panCK, CD68, CD163, CD11c, iNOS, CD3, CD8, CD4, FOXP3, CD20, Ki67, CD31). Clinicopathological parameter were available for more than 30 tumor entities and overall survival data were available for 1517 breast cancer specimens.ResultsComparing the automated deep-learning based PD-L1 quantification with conventional brightfield PD-L1 data revealed a high concordance in tumor cells (p<0.0001) as well as immune cells (p<0.0001) and an accuracy of the automated PD-L1 quantification ranging from 90% to 95.2%. Across all tumor entities, the PD-L1 expression level was significantly higher in distinct macrophage/dendritic cell (DC) subsets (identified by CD68, CD163, CD11c, iNOS; p<000.1) and in macrophages/DCs located in the Stroma (p<0.0001) as compared to intratumoral macrophages/DC subsets. Across all different tumor entities, the PD-L1 expression was highly variable and distinct PD-L1 driven immune phenotypes were identified based on the PD-L1 intensity on both tumor and immune cells, the distance between non-exhausted T-cell subsets (i.e. PD-1 and CTLA-4 expression on CD3+CD8+ cytotoxic T-cells, CD3+CD4+ T-helper cells, CD3+CD4+FOXP3+ regulatory T-cells) and tumor cells as well as macrophage/(DC) subtypes. In breast cancer, the PD-L1 fluorescence intensity on tumor cells showed a significantly higher predictive performance for overall survival with an area under receiver operating curves (AUC) of 0.72 (p<0.0001) than the percentage of PD-L1+ tumor cells (AUC: 0.54). In PD-L1 positive as well as negative breast cancers a close spatial relationship between T- cell subsets (CD3+CD4±CD8±FOXP3±PD-1±CTLA-4±) and Macrophage/DC subsets (CD68±CD163±CD11c±iNOS) was found prognostic relevant (p<0.0001).ConclusionsIn conclusion, multiplex immunofluorescence PD-L1 assessment provides cutoff-free/continuous PD-L1 data which are superior to the conventional percentage of PD-L1+ tumor cells and of high prognostic relevance. The combined analysis of spatial PD-L1/PD-1 data and more than 20 different immune cell subtypes of the immune tumor microenvironment revealed distinct PD-L1 immune phenotypes.Disclosure InformationN.C. Blessin: None. E. Bady: None. T. Mandelkow: None. C. Yang: None. J. Raedler: None. R. Simon: None. C. Fraune: None. M. Lennartz: None. S. Minner: None. E. Burandt: None. D. Höflmayer: None. G. Sauter: None. S.A. Weidemann: None.

scholarly journals RNA N6-Methyladenosine Regulators Contribute to Tumor Immune Microenvironment and Have Clinical Prognostic Impact in Breast Cancer

2022 ◽  
Vol 12 ◽  
Author(s):  
Lan-Xin Mu ◽  
You-Cheng Shao ◽  
Lei Wei ◽  
Fang-Fang Chen ◽  
Jing-Wei Zhang
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Impact ◽  
Immune Microenvironment ◽  
Model Based ◽  
Tumor Immune Microenvironment

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p &lt; 0.001) and m6aRiskscore (p &lt; 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.

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