Intratumoral expression of CCR3 in breast cancer is associated with improved relapse-free survival in luminal-like disease

The Identification by Exome Sequencing of Candidate Genes in BRCA-Negative Tunisian Patients at a High Risk of Hereditary Breast/Ovarian Cancer

(1) Background: Germline variants in BRCA1/BRCA2 genes explain about 20% of hereditary breast/ovarian cancer (HBOC) cases. In the present paper, we aim to identify genetic determinants in BRCA-negative families from the South of Tunisia. (2) Methods: Exome Sequencing (ES) was performed on the lymphocyte DNA of patients negative for BRCA mutations from each Tunisian family with a high risk of HBOC. (3) Results: We focus on the canonical genes associated with HBOC and identified missense variants in DNA damage response genes, such as ATM, RAD52, and RAD54; however, no variants in PALB2, Chek2, and TP53 genes were found. To identify novel candidate genes, we selected variants harboring a loss of function and identified 17 stop-gain and 11 frameshift variants in genes not commonly known to be predisposed to HBOC. Then, we focus on rare and high-impact genes shared by at least 3 unrelated patients from each family and selected 16 gene variants. Through combined data analysis from MCODE with gene ontology and KEGG pathways, a short list of eight candidate genes (ATM, EP300, LAMA1, LAMC2, TNNI3, MYLK, COL11A2, and LAMB3) was created. The impact of the 24 selected genes on survival was analyzed using the TCGA data resulting in a selection of five candidate genes (EP300, KMT2C, RHPN2, HSPG2, and CCR3) that showed a significant association with survival. (4) Conclusions: We identify novel candidate genes predisposed to HBOC that need to be validated in larger cohorts and investigated by analyzing the co-segregation of selected variants in affected families and the locus-specific loss of heterozygosity to highlight their relevance for HBOC risk.

Chemokine receptors differentially expressed by race category and molecular subtype in the breast cancer TCGA cohort

Racial disparities in mortality due to metastasis remain significant among breast cancer patients. Chemokine receptors contribute to breast tumors and metastatic outcome. We explored for significant differences in chemokine receptor expression in breast tumors from Black, Asian, and White patients in The Cancer Genome Atlas. We show that despite sharing the same molecular subtype, expression of the chemokine receptors ACKR1, CCR3, CCR6, CCRL1, CCRL2, CXCR1, CXCR2, CXCR4, CXCR6, and CXC3CR1 was significantly different depending on racial group. For patients with triple negative breast cancer, CCR3 was higher in Black versus White and CCRL2 was higher in Asian versus White. In luminal A tumors, ACKR1 was lower in Asian versus White, CCR3 was higher in Black versus White, and CCR6 and CXC3CR1 were lower in Black versus White. In luminal B tumors, CCRL2 was lower in Black versus White, CXCR1 and CXC3CR1 were lower in Asian versus White, and CXCR2 was lower in Black and Asian versus White. In HER2 enriched tumors, CCR3 was higher in Black versus White and CXCR4 lower in Asian versus White. CCR3, CCR6, and CXCR6 associated with worse patient survival. These findings can inform improved treatment strategies to decrease racial disparities in breast cancer burden.

DeCompress: tissue compartment deconvolution of targeted mRNA expression panels using compressed sensing

Targeted mRNA expression panels, measuring up to 800 genes, are used in academic and clinical settings due to low cost and high sensitivity for archived samples. Most samples assayed on targeted panels originate from bulk tissue comprised of many cell types, and cell-type heterogeneity confounds biological signals. Reference-free methods are used when cell-type-specific expression references are unavailable, but limited feature spaces render implementation challenging in targeted panels. Here, we present DeCompress, a semi-reference-free deconvolution method for targeted panels. DeCompress leverages a reference RNA-seq or microarray dataset from similar tissue to expand the feature space of targeted panels using compressed sensing. Ensemble reference-free deconvolution is performed on this artificially expanded dataset to estimate cell-type proportions and gene signatures. In simulated mixtures, four public cell line mixtures, and a targeted panel (1199 samples; 406 genes) from the Carolina Breast Cancer Study, DeCompress recapitulates cell-type proportions with less error than reference-free methods and finds biologically relevant compartments. We integrate compartment estimates into cis-eQTL mapping in breast cancer, identifying a tumor-specific cis-eQTL for CCR3 (C-C Motif Chemokine Receptor 3) at a risk locus. DeCompress improves upon reference-free methods without requiring expression profiles from pure cell populations, with applications in genomic analyses and clinical settings.

Stromal CCL5 Promotes Breast Cancer Progression by Interacting with CCR3 in Tumor Cells

Chemokines secreted from stromal cells have important roles for interactions with carcinoma cells and regulating tumor progression. C-C motif chemokine ligand (CCL) 5 is expressed in various types of stromal cells and associated with tumor progression, interacting with C-C chemokine receptor (CCR) 1, 3 and 5 expressed in tumor cells. However, the expression on CCL5 and its receptors have so far not been well-examined in human breast carcinoma tissues. We therefore immunolocalized CCL5, as well as CCR1, 3 and 5, in 111 human breast carcinoma tissues and correlated them with clinicopathological characteristics. Stromal CCL5 immunoreactivity was significantly correlated with the aggressive phenotype of breast carcinomas. Importantly, this tendency was observed especially in the CCR3-positive group. Furthermore, the risk of recurrence was significantly higher in the patients with breast carcinomas positive for CCL5 and CCR3 but negative for CCR1 and CCR5, as compared with other patients. In summary, the CCL5-CCR3 axis might contribute to a worse prognosis in breast cancer patients, and these findings will contribute to a better understanding of the significance of the CCL5/CCRs axis in breast carcinoma microenvironment.

Mechanisms of Tumor-Lymphatic Interactions in Invasive Breast and Prostate Carcinoma

During the last few years, diverse studies have shown that tumors can actively interact with the lymphatic system and promote metastases development. In order to examine the molecular mechanisms involved in this interaction, we co-cultured tumor and lymphatic endothelial cells (LEC) and subsequently analyzed the molecular alterations of LECs. Therefore, LECs were co-cultivated with either a highly or weakly metastatic breast cancer cell line using contact (mixture) and non-contact (transwell) co-cultures. mRNA profiles from LECs were subsequently analyzed for genes specifically induced by highly metastatic tumor cells (“metastatic specific”). Among the up-regulated “metastatic specific” genes, we found candidates involved in cell cycle, cell adhesion and motility (BST2, E-selectin, and HMMR), cytokines (CCL7, CXCL6, CXCL1, and CSF2) and factors of the complement system (C1R, C3, and CFB). Among the down-regulated genes, we detected the hyaluronan receptor STAB2, angiogenic factor apelin receptor (APLNR), and the glycosylation enzyme MAN1A1. In an additional prostate cancer co-culture model, we could confirm a “metastatic specific” upregulation of E-selectin and CCL7 in LECs after interaction with the prostate cancer cell lines LNCAP (highly metastatic) and DU145 (weakly metastatic). These data allowed us to identify a set of genes regulated in LECs during in vitro communication with cancer cells, which might subsequently facilitate lymphatic metastasis.

Paracrine Crosstalk between Fibroblasts and ER+ Breast Cancer Cells Creates an IL1β-Enriched Niche that Promotes Tumor Growth

Breast cancer-induced activated fibroblasts support tumor progression. However, the role of normal fibroblasts in tumor progression remains controversial. In this study, we used modified patient-derived organoid cultures and demonstrate that constitutively secreted cytokines from normal breast fibroblasts initiate a paracrine signaling mechanism with estrogen receptor-positive (ER⁺) breast cancer cells, which results in the creation of an interleukin (IL)-1β-enriched microenvironment. We found that this paracrine signaling mechanism is shared between normal and activated fibroblasts. Interestingly, we observed that in reconstructed tumor microenvironment containing autologous ER⁺ breast cancer cells, activated fibroblasts, and immune cells, tamoxifen is more effective in reducing tumor cell proliferation when this paracrine signaling is blocked. Our findings then suggest that ER⁺ tumor cells could create a growth-promoting environment without activating stromal fibroblasts and that in breast-conserving surgeries, normal fibroblasts could be a significant modulator of tumor recurrence by enhancing the proliferation of residual breast cancer cells in the tumor-adjacent breast tissue.

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Normal fibroblast-cancer cell interaction promotes tumor progression

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Paracrine signaling common to normal and activated fibroblasts promotes drug resistance

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Fibroblast-secreted factors create an IL1β-enriched niche for ER⁺ breast cancer cell growth

Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer

Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer.

Transcriptomic analyses reveal the underlying pro-malignant functions of PTHR1 for osteosarcoma via activation of Wnt and angiogenesis pathways

BACKGROUND

Increasing evidence has indicated parathyroid hormone type 1 receptor (PTHR1) plays important roles for the development and progression of osteosarcoma (OS). However, its function mechanisms remain unclear. The goal of this study was to further illuminate the roles of PTHR1 in OS using microarray data.

METHODS

Microarray data were available from the Gene Expression Omnibus database under the accession number GSE46861, including six tumors from mice with PTHR1 knockdown (PTHR1.358) and six tumors from mice with control knockdown (Ren.1309). Differentially expressed genes (DEGs) between PTHR1.358 and Ren.1309 were identified using the LIMMA method, and then, protein-protein interaction (PPI) network was constructed using data from STRING database to screen crucial genes associated with PTHR1. KEGG pathway enrichment analysis was performed to investigate the underlying functions of DEGs using DAVID tool.

RESULTS

A total of 1163 genes were identified as DEGs, including 617 downregulated (Lef1, lymphoid enhancer-binding factor 1) and 546 upregulated genes (Dkk1, Dickkopf-related protein 1). KEGG enrichment analysis indicated upregulated DEGs were involved in Renin-angiotensin system (e.g., Agt, angiotensinogen) and Wnt signaling pathway (e.g., Dkk1), while downregulated DEGs participated in Basal cell carcinoma (e.g., Lef1). A PPI network (534 nodes and 2830 edges) was constructed, in which Agt gene was demonstrated to be the hub gene and its interactive genes (e.g., CCR3, CC chemokine receptor 3; and CCL9, chemokine CC chemokine ligand 9) were inflammation related.

CONCLUSIONS

Our present study preliminarily reveals the pro-malignant effects of PTHR1 in OS cells may be mediated by activating Wnt, angiogenesis, and inflammation pathways via changing the expressions of the crucial enriched genes (Dkk1, Lef1, Agt-CCR3, and Agt-CCL9).

Evaluation of the TRPM2 channel as a biomarker in breast cancer using public databases analysis

BACKGROUND

Breast cancer is one of the most common malignancies affecting women. Recent investigations have revealed a major role of ion channels in cancer. The transient receptor potential melastatin-2 (TRPM2) is a plasma membrane and lysosomal channel with important roles in cell migration and cell death in immune cells and tumor cells.

METHODS

In this study, we investigated the prognostic value of TRPM2 channel in breast cancer, analyzing public databases compiled in Oncomine™ (Thermo Fisher, Ann Arbor, MI) and online Kaplan-Meier Plotter platforms.

RESULTS

The results revealed that TRPM2 mRNA overexpression is significant in situ and invasive breast carcinoma compared to normal breast tissue. Furthermore, multi-gene validation using Oncomine™ showed that this channel is coexpressed with proteins related to cellular migration, transformation, and apoptosis. On the other hand, Kaplan-Meier analysis exhibited that low expression of TRPM2 could be used to predict poor outcome in ER- and HER2+ breast carcinoma patients.

CONCLUSIONS

TRPM2 is a promising biomarker for aggressiveness of breast cancer, and a potential target for the development of new therapies.