Correlation between Duffy blood group phenotype and breast cancer incidence

Involvement in Tumorigenesis and Clinical Significance of CXCL1 in Reproductive Cancers: Breast Cancer, Cervical Cancer, Endometrial Cancer, Ovarian Cancer and Prostate Cancer

C-X-C motif chemokine ligand 1 (CXCL1) is a member of the CXC chemokine subfamily and a ligand for CXCR2. Its main function in the immune system is the chemoattraction of neutrophils. However, there is a lack of comprehensive reviews summarizing the significance of CXCL1 in cancer processes. To fill this gap, this work describes the clinical significance and participation of CXCL1 in cancer processes in the most important reproductive cancers: breast cancer, cervical cancer, endometrial cancer, ovarian cancer, and prostate cancer. The focus is on both clinical aspects and the significance of CXCL1 in molecular cancer processes. We describe the association of CXCL1 with clinical features of tumors, including prognosis, ER, PR and HER2 status, and TNM stage. We present the molecular contribution of CXCL1 to chemoresistance and radioresistance in selected tumors and its influence on the proliferation, migration, and invasion of tumor cells. Additionally, we present the impact of CXCL1 on the microenvironment of reproductive cancers, including its effect on angiogenesis, recruitment, and function of cancer-associated cells (macrophages, neutrophils, MDSC, and T_reg). The article concludes by summarizing the significance of introducing drugs targeting CXCL1. This paper also discusses the significance of ACKR1/DARC in reproductive cancers.

Prospects for targeting ACKR1 in cancer and other diseases

The chemokine network is comprised of a family of signal proteins that encode messages for cells displaying chemokine G-protein coupled receptors (GPCRs). The diversity of effects on cellular functions, particularly directed migration of different cell types to sites of inflammation, is enabled by different combinations of chemokines activating signal transduction cascades on cells displaying a combination of receptors. These signals can contribute to autoimmune disease or be hijacked in cancer to stimulate cancer progression and metastatic migration. Thus far, three chemokine receptor-targeting drugs have been approved for clinical use: Maraviroc for HIV, Plerixafor for hematopoietic stem cell mobilization, and Mogalizumab for cutaneous T-cell lymphoma. Numerous compounds have been developed to inhibit specific chemokine GPCRs, but the complexity of the chemokine network has precluded more widespread clinical implementation, particularly as anti-neoplastic and anti-metastatic agents. Drugs that block a single signaling axis may be rendered ineffective or cause adverse reactions because each chemokine and receptor often have multiple context-specific functions. The chemokine network is tightly regulated at multiple levels, including by atypical chemokine receptors (ACKRs) that control chemokine gradients independently of G-proteins. ACKRs have numerous functions linked to chemokine immobilization, movement through and within cells, and recruitment of alternate effectors like β-arrestins. Atypical chemokine receptor 1 (ACKR1), previously known as the Duffy antigen receptor for chemokines (DARC), is a key regulator that binds chemokines involved in inflammatory responses and cancer proliferation, angiogenesis, and metastasis. Understanding more about ACKR1 in different diseases and populations may contribute to the development of therapeutic strategies targeting the chemokine network.

Duffy antigen receptor for chemokines (DARC) expressing in cancer cells inhibits tumor progression by suppressing CXCR2 signaling in human pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis. Chemokines play important roles in the progression of many malignancies; however, the role of chemokine receptor expression in clinical cases of PDAC is unclear. Moreover, little is known about DARC, a decoy receptor of CXC chemokines, in the regulation of tumor progression.

METHODS

Functions of chemokine receptors were evaluated using surgical specimens collected from PDAC patients, and PDAC cell lines.

RESULTS

CXCR2 expression had no impacts on predicting prognosis, but low DARC expression in cancer cells was an independent risk factor for poor prognosis. In PDAC with low DARC expression, tumor sizes were larger and vascular invasion was increased. High CXCR2 expression was a significant predictor for poor prognosis, only in PDAC patients with low DARC expression. CXCR2 signaling induced STAT3 activation in PDAC, resulting in promoting cell cycle progression, inhibiting apoptosis, inducing angiogenesis, and enhancing invasiveness. DARC inhibited STAT3 activation by down-regulating CXCR2 signaling. These effects were confirmed by EMSA in vitro. DARC knockdown significantly increased cell proliferation in CFPAC-1 cells with high DARC expression, by activating STAT3. In contrast, CXCR2 knockdown inhibited the proliferative effects of IL-8 in MIA PaCa-2 cells with low DARC expression. Moreover, the inhibitory effect of CXCR2 antagonist on PDAC cell proliferation was more powerful in MIA PaCa-2 cells than CFPAC-1 cells.

CONCLUSIONS

DARC expressing in cancer cells inhibits PDAC progression by suppressing STAT3 activation through the inhibition of CXCR2 signaling. Therefore, DARC is a novel prognostic predictor and a potential therapeutic target for PDAC.

Overview and potential unifying themes of the atypical chemokine receptor family

Chemokines modulate immune responses through their ability to orchestrate the migration of target cells. Chemokines directly induce cell migration through a distinct set of 7 transmembrane domain G protein-coupled receptors but are also recognized by a small subfamily of atypical chemokine receptors, characterized by their inability to support chemotactic activity. Atypical chemokine receptors are now emerging as crucial regulatory components of chemokine networks in a wide range of physiologic and pathologic contexts. Although a new nomenclature has been approved recently to reflect their functional distinction from their conventional counterparts, a systematic view of this subfamily is still missing. This review discusses their biochemical and immunologic properties to identify potential unifying themes in this emerging family.

Distinct Transcript Isoforms of the Atypical Chemokine Receptor 1 (ACKR1)/Duffy Antigen Receptor for Chemokines (DARC) Gene Are Expressed in Lymphoblasts and Altered Isoform Levels Are Associated with Genetic Ancestry and the Duffy-Null Allele

The Atypical ChemoKine Receptor 1 (ACKR1) gene, better known as Duffy Antigen Receptor for Chemokines (DARC or Duffy), is responsible for the Duffy Blood Group and plays a major role in regulating the circulating homeostatic levels of pro-inflammatory chemokines. Previous studies have shown that one common variant, the Duffy Null (Fy-) allele that is specific to African Ancestry groups, completely removes expression of the gene on erythrocytes; however, these individuals retain endothelial expression. Additional alleles are associated with a myriad of clinical outcomes related to immune responses and inflammation. In addition to allele variants, there are two distinct transcript isoforms of DARC which are expressed from separate promoters, and very little is known about the distinct transcriptional regulation or the distinct functionality of these protein isoforms. Our objective was to determine if the African specific Fy- allele alters the expression pattern of DARC isoforms and therefore could potentially result in a unique signature of the gene products, commonly referred to as antigens. Our work is the first to establish that there is expression of DARC on lymphoblasts. Our data indicates that people of African ancestry have distinct relative levels of DARC isoforms expressed in these cells. We conclude that the expression of both isoforms in combination with alternate alleles yields multiple Duffy antigens in ancestry groups, depending upon the haplotypes across the gene. Importantly, we hypothesize that DARC isoform expression patterns will translate into ancestry-specific inflammatory responses that are correlated with the axis of pro-inflammatory chemokine levels and distinct isoform-specific interactions with these chemokines. Ultimately, this work will increase knowledge of biological mechanisms underlying disparate clinical outcomes of inflammatory-related diseases among ethnic and geographic ancestry groups.

The Discovery of Novel Biomarkers Improves Breast Cancer Intrinsic Subtype Prediction and Reconciles the Labels in the METABRIC Data Set

BACKGROUND

The prediction of breast cancer intrinsic subtypes has been introduced as a valuable strategy to determine patient diagnosis and prognosis, and therapy response. The PAM50 method, based on the expression levels of 50 genes, uses a single sample predictor model to assign subtype labels to samples. Intrinsic errors reported within this assay demonstrate the challenge of identifying and understanding the breast cancer groups. In this study, we aim to: a) identify novel biomarkers for subtype individuation by exploring the competence of a newly proposed method named CM1 score, and b) apply an ensemble learning, as opposed to the use of a single classifier, for sample subtype assignment. The overarching objective is to improve class prediction.

METHODS AND FINDINGS

The microarray transcriptome data sets used in this study are: the METABRIC breast cancer data recorded for over 2000 patients, and the public integrated source from ROCK database with 1570 samples. We first computed the CM1 score to identify the probes with highly discriminative patterns of expression across samples of each intrinsic subtype. We further assessed the ability of 42 selected probes on assigning correct subtype labels using 24 different classifiers from the Weka software suite. For comparison, the same method was applied on the list of 50 genes from the PAM50 method.

CONCLUSIONS

The CM1 score portrayed 30 novel biomarkers for predicting breast cancer subtypes, with the confirmation of the role of 12 well-established genes. Intrinsic subtypes assigned using the CM1 list and the ensemble of classifiers are more consistent and homogeneous than the original PAM50 labels. The new subtypes show accurate distributions of current clinical markers ER, PR and HER2, and survival curves in the METABRIC and ROCK data sets. Remarkably, the paradoxical attribution of the original labels reinforces the limitations of employing a single sample classifiers to predict breast cancer intrinsic subtypes.