Cytokine profiling of tumor interstitial fluid of the breast and its relationship with lymphocyte infiltration and clinicopathological characteristics

Espinoza, Jaime A.; Jabeen, Shakila; Batra, Richa; Papaleo, Elena; Haakensen, Vilde Drageset; Wielenga, Vera Timmermans; Talman, Maj Lis Møller; Brünner, Nils; Børresen-Dale, Anne Lise; Gromov, Pavel; Helland, Åslaug; Kristensen, Vessela N.; Gromova, Irina

doi:10.1080/2162402x.2016.1248015

Cited by 53 publications

(63 citation statements)

References 75 publications

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“…cytokines (Espinoza et al, 2016). Interestingly, Picon-Ruiz et al (2016) identified the same five cytokines to be upregulated in BC-educated adipocytes and showed their protumorigenic influence.…”

Section: Discussionmentioning

confidence: 90%

“…We showed that upon S100A4 stimulation, basal‐like BCCs secrete factors that trigger monocyte‐to‐macrophage differentiation and polarization. This is in line with previous studies demonstrating that basal‐like/TNBC, compared to luminal BC, have superior abilities to recruit macrophages (Espinoza et al ., 2016; Sousa et al ., 2015), modulate their polarization, and stimulate protumorigenic functions (Hollmen et al ., 2015; Sousa et al ., 2015; Stewart et al ., 2012; Su et al ., 2014). The current study adds to the previous knowledge by revealing a strong potentiating influence of S100A4, which is expressed at elevated levels in basal‐like/TNBC as also reported previously (Egeland et al ., 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Thereby, BC‐educated macrophages could function as amplifiers of cytokine production. This observation is in concordance with previous reports from TNBC, where it was shown that tumor‐infiltrating immune cells contribute to the total pool of tumor cytokines (Espinoza et al ., 2016). Interestingly, Picon‐Ruiz et al .…”

Section: Discussionmentioning

confidence: 99%

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Basal‐like breast cancer engages tumor‐supportive macrophages via secreted factors induced by extracellular S100A4

et al. 2018

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The tumor microenvironment (TME) may influence both cancer progression and therapeutic response. In breast cancer, particularly in the aggressive triple‐negative/basal‐like subgroup, patient outcome is strongly associated with the tumor's inflammatory profile. Tumor‐associated macrophages (TAMs) are among the most abundant immune cells in the TME, shown to be linked to poor prognosis and therapeutic resistance. In this study, we investigated the effect of the metastasis‐ and inflammation‐associated microenvironmental factor S100A4 on breast cancer cells (BCCs) of different subtypes and explored their further interactions with myeloid cells. We demonstrated that extracellular S100A4 activates BCCs, particularly the basal‐like subtype, to elevate secretion of pro‐inflammatory cytokines. The secreted factors promoted conversion of monocytes to TAM‐like cells that exhibited protumorigenic activities: stimulated epithelial–mesenchymal transition, proliferation, chemoresistance, and motility in cancer cells. In conclusion, we have shown that extracellular S100A4 instigates a tumor‐supportive microenvironment, involving a network of cytokines and TAM‐like cells, which was particularly characteristic for basal‐like BCCs and potentiated their aggressive properties. The S100A4–BCC–TAM interaction cascade could be an important contributor to the aggressive behavior of this subtype and should be further explored for therapeutic targeting.

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

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Basal‐like breast cancer engages tumor‐supportive macrophages via secreted factors induced by extracellular S100A4

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“…IL6 is of interest thanks to its role in the immune response and the complement system [51], as well as considering that it is down-regulated in LUSC. We also recently identified IL6 as the only down-regulated cytokine in breast cancer samples using cytokine assays [52]. However, IL6 downregulation could be also associated with the chemotherapeutic treatment as previously reported [53].…”

Section: Resultsmentioning

confidence: 56%

Different molecular signatures in lung cancer types from integrative bioinformatic analyses of RNASeq data

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Piedade

Mounir

et al. 2018

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BackgroundGenomic initiatives such as The Cancer Genome Atlas (TCGA) project contain data on profiling of thousands of tumors with different-omics approaches, providing a valuable source of information which may be used to decipher cancer signaling and related alterations. Managing and analyzing data from large-scale projects such as TCGA is a demanding task. Indeed, it is difficult to dissect the high complexity hidden in genomic data and to adequately account for tumor heterogeneity.ResultsIn this study, we used a robust statistical framework along with the integration of diverse bioinformatic tools to analyze next-generation sequencing data from more than 1000 patient samples from two different lung cancer subtypes, i.e., the lung adenocarcinoma (LUAD) and the squamous cell carcinoma (LUSC). In particular, we used RNA-Seq gene expression data to identify both co-expression modules and differentially expressed genes to accurately discriminate between LUAD and LUSC. Moreover, we identified a group of genes which could act as specific oncogenes or tumor suppressor genes in one of the two lung cancer types, as well as two dual role genes. Our results have also been cross-validated against other transcriptomics data of lung cancer patients.ConclusionsOur integrative approach allowed to identify two key features: a substantial up-regulation of genes involved in O-glycosylation of mucins in LUAD, and a compromised immune response in LUSC. The immune-profile associated with LUSC is linked to the activation of three specific oncogenic pathways which promote the evasion of antitumor immune response, providing new future directions for the design of target therapies.

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“…The tumor microenvironment encloses cellular and non-cellular units that play a critical role in the initiation, progression, and metastasis of the tumor [30,47,48].…”

Section: Design and Implementationmentioning

confidence: 99%

Analyses of cancer data in the Genomic Data Commons Data Portal with new functionalities in the TCGAbiolinks R/Bioconductor package

Mounir

Silva

Lucchetta

et al. 2018

Preprint

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The advent of Next Generation Sequencing (NGS) technologies has opened new perspectives in deciphering the genetic mechanisms underlying complex diseases. Nowadays, the amount of genomic data is massive and substantial efforts and new tools are required to unveil the information hidden in the data.The Genomic Data Commons (GDC) Data Portal is a large data collection platform that includes different genomic studies included the ones from The Cancer Genome Atlas (TCGA) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) initiatives, accounting for more than 40 tumor types originating from nearly 30000 patients. Such platforms, although very attractive, must make sure the stored data are easily accessible and adequately harmonized. Moreover, they have the primary focus on the data storage in a unique place, and they do not provide a comprehensive toolkit for analyses and interpretation of the data. To fulfill this urgent need, comprehensive but easily accessible computational methods for integrative analyses of genomic data without renouncing a robust statistical and theoretical framework are needed. In this context, the R/Bioconductor package TCGAbiolinks was developed, offering a variety of bioinformatics functionalities. Here we introduce new features and enhancements of TCGAbiolinks in terms of i) more accurate and flexible pipelines for differential expression analyses, ii) different methods for tumor purity estimation and filtering, iii) integration of normal samples from the Genotype-Tissue-Expression (GTEx) platform iv) support for other genomics datasets, here exemplified by the TARGET data.Evidence has shown that accounting for tumor purity is essential in the study of tumorigenesis, as these factors promote confounding behavior regarding differential expression analysis. Henceforth, we implemented these filtering procedures in TCGAbiolinks. Moreover, a limitation of some of the TCGA datasets is the unavailability or paucity of corresponding normal samples. We thus integrated into TCGAbiolinks the possibility to use normal samples from the Genotype-Tissue Expression (GTEx) project, which is another large-scale repository cataloging gene expression from healthy individuals. The new functionalities are available in the TCGABiolinks v 2.8 and higher released in Bioconductor version 3.7.

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Cytokine profiling of tumor interstitial fluid of the breast and its relationship with lymphocyte infiltration and clinicopathological characteristics

Cited by 53 publications

References 75 publications

Basal‐like breast cancer engages tumor‐supportive macrophages via secreted factors induced by extracellular S100A4

Basal‐like breast cancer engages tumor‐supportive macrophages via secreted factors induced by extracellular S100A4

Different molecular signatures in lung cancer types from integrative bioinformatic analyses of RNASeq data

Analyses of cancer data in the Genomic Data Commons Data Portal with new functionalities in the TCGAbiolinks R/Bioconductor package

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