Although considerable progress has been made in our understanding of the role of platelets in hemostasis, the analytical methods clinically available for investigating platelet function defects remain limited. Herein, we describe an initiative at Linköping University Hospital, Sweden, to use flow cytometry for measuring platelet function in patients with a suspected bleeding disorder.

by Dr Niklas Boknäs, Dr Sofia Ramström and Prof. Tomas Lindahl

Introduction
Although many patients seek professional help for bleeding problems, very few end up receiving an informative diagnosis, even when the presenting symptoms are clearly abnormal [1]. At present, our diagnostic tools for the investigation of bleeding symptoms are tailored for identifying serious disorders with dramatic symptoms such as hemophilia and Glanzmann’s thrombastenia, but often fail to identify the underlying defect in mild bleeding disorders (MBD) [2]. Ironically, the reverse is also often true, as the clinical significance of many tests performed during conventional laboratory investigations of MBDs is ill-defined [3].

Platelet function disorders (PFDs) represent a subcategory of MBDs where the underlying hemostatic defect is caused by abnormally low platelet pro-hemostatic activity. As PFDs produce virtually identical clinical symptoms to many other conditions causing bleeding problems, diagnosing PFDs necessitates access to reliable laboratory testing of platelet function. Ideally, such tests could provide important guidance in a number of clinical situations, such as when deciding on whether to give pharmaceutical prophylaxis in the event of frequent bleeding or surgery and when assessing the risks associated with the use of thromboprophylaxis after thrombosis and surgery in the individual patient.

Unfortunately, clinical tests evaluating platelet function have evolved poorly during recent decades, despite the introduction of new promising techniques. Light transmission aggregometry (LTA), the method currently considered gold standard for evaluating platelet function, has been used for more than five decades and comprises continuous measurement of the optical density of stirred platelet-rich plasma after stimulation with agonists. LTA gives information about how platelets aggregate upon stimulation, but does not enable measurement of other aspects of platelet pro-hemostatic activity such as platelet adhesion, granule secretion and alterations of platelet membrane structure to accelerate coagulation. From our experience, the clinical value of LTA in terms of explaining patient symptoms is limited, and this is supported by studies failing to show an association between results from LTA and the severity of bleeding problems among patients with MBD [1, 4]. In addition to this limitation, LTA remains poorly standardized and labour-intensive, making performance of LTA only feasible in specialized hemostasis laboratories.

Flow cytometry for the diagnosis of PFD in patients with MBD
In an effort to overcome these problems with the methods currently used for diagnosing PFD, we and others have switched to employing whole-blood flow cytometry for the diagnosis of PFD among patients with MBD. Whole-blood flow cytometry for platelet function testing (FC-PFT) was developed in the 1980s [5, 6]. A description of the analytical principle behind flow cytometry is outside the scope of this article, but in this context, the technique can extremely briefly be described as a powerful method to quantify the presence of different epitopes on the surface of platelets after platelet activation by the use of fluorescent probes that bind to the cell surface. Compared to LTA, FC-PFT confers the following practical advantages [7]:

• Samples can be analysed in anticoagulated whole blood, eliminating the need for pre-analytical manipulation of blood components.
• Sample volumes can be reduced drastically, which is especially advantageous in children.
• Results are not influenced by platelet count, enabling assessment of platelet function in patients with thrombocytopenia [8].
• The work load is reduced considerably as many samples can be analysed in rapid sequence.
• Flow cytometry is a very common technique, and appropriate instruments are widely available in most clinical and research laboratories.

In addition to these practical benefits with FC-PFT, the method confers several other advantages. For example, it produces numerical results that are easy to interpret, and can give information about several different aspects of platelet activation by the employment of different fluorescent probes detecting distinct events during platelet activation [9]. The ability to measure different aspects of platelet function also allows the direct diagnosis of rare disorders, such as Bernard-Soulier syndrome, Glanzmann’s thrombastenia and Scott syndrome, without the need for sequential testing [10].

Unfortunately, until recently no studies had addressed the clinical utility of FC-PFT for diagnosing clinically relevant PFDs. To address this issue, we recently published a clinical study comparing the results from FC-PFT with symptom severity in a cohort of bleeders [11]. The study was performed on 105 patients referred to Linköping University for evaluation of platelet function. Only patients wherein a complete diagnostic work-up including a full blood cell count, APTT (activated partial thromboplastin time), PT (prothrombin time), FVIII (factor 8) and von Willebrand factor (antigen and ristocetin cofactor activity) had excluded the presence of von Willebrand disease or a coagulation disorder were included in the study. Bleeding symptoms were assessed by a single experienced clinician blinded to the laboratory results of the study. In our panel for FC-PFT, we included analysis of fibrinogen binding (indicating activation of the fibrinogen receptor glycoprotein (GP)IIb/IIIa responsible for platelet aggregations) as well as P-selectin exposure (indicating release of platelet alpha granules) after platelet stimulation with a panel of four different agonists that specifically activate the most important platelet receptors: P2Y12 and P2Y1 (ADP); the thrombin receptors PAR1 and PAR4 [PAR1-activating peptide (AP), PAR4-AP]; and the collagen receptor GPVI (CRP-XL). To assess the contribution of dense granules to platelet activation, we designed an indirect test wherein the effects of pre-incubation with apyrase (which degrades ADP) was used as a measure of functional dense granule release. A flow chart illustrating the flow cytometry protocol is provided in Figure 1.

Our results clearly demonstrate that abnormal test results using FC-PFT are associated with a more severe bleeding phenotype in patients with MBDs. In fact, a high symptom burden was 5–8 times more common among patients with more than two abnormal test results in our study as compared to patients with two or fewer abnormal test results (Fig. 2), depending on which method that was used for calculating the reference range for the different tests. When results pertaining to the fifth percentile of the patient material was classified as abnormal and more than two abnormal test results were used as a predictor for bleeding symptom severity, a high symptom burden was predicted with as specificity of 95 % and a positive predictive value of 80 %. It should be noted however, that the clinical material was insufficient to allow for a prospective validation of these estimates in a separate patient cohort.

Discussion
In our opinion, FC-PFT for clinical use should as a minimum comprise: (a) testing of platelet integrin activation, either directly by the use of the anti-PAC-1 antibody (recognizing GPIIb/IIIa) or indirectly by measuring fibrinogen binding or microaggregate formation; (b) a marker of alpha granule secretion, preferably by using an antibody directed towards P-selectin; and (c) a test of dense granule secretion to accurately assess the clinically most important hemostatic functions of platelets. Ideally, a clinical protocol for FC-PFT should also include a marker of platelet procoagulant platelet activity and a fluorescent marker binding to GPIbα, in order to provide a more complete assessment of the platelet hemostatic repertoire and diagnose the rare hereditary disorders Scott syndrome and Bernard-Soulier syndrome. In our own protocol, we have recently incorporated these two additional functionalities. We have also improved our protocol by incorporating the use of fixatives and pre-preparation of frozen reagents in order to improve reproducibility and increase the time- and cost-efficiency of the protocol. Recently, very promising methodological improvements have been made by other researchers, such as the use of fluorescent beads as an internal control for standardizing results and facilitating comparisons between different instruments [12] and the use of a modular diagnostic algorithm to ensure efficient and exact diagnosis [13]. Thus, continuous efforts are being made to firmly establish FC-PFT as an attractive alternative for platelet function testing in the setting of MBDs.

References
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11. Boknäs N, Ramström S, Faxälv L, Lindahl TL. Flow cytometry-based platelet function testing is predictive of symptom burden in a cohort of bleeders. Platelets 2017; doi: https://doi.org/10.1080/09537104.2017.1349305
12. Huskens D, Sang Y, Konings J, van der Vorm L, de Laat B, Kelchtermans H, Roest M. Standardization and reference ranges for whole blood platelet function measurements using a flow cytometric platelet activation test. PLoS One 2018; 13(2): 1–16.
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The authors
Niklas Boknäs*^1,2 MD, PhD; Sofia Ramström^3,4 PhD; Tomas Lindahl³ MD, PhD
¹Department of Hematology and Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
²Australian Centre for Blood Diseases, Monash University, Melbourne, Australia
³Department of Clinical Chemistry and Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
⁴School of Medical Sciences, Örebro University, Örebro, Sweden

*Corresponding author
E-mail: niklas.boknas@gmail.com

Over the last twenty-five years, breast cancer genetics has moved from linkage in high-risk families to association in population-based studies. Accordingly, the genetic variants that have been identified range from rare high-penetrance mutations to common low-penetrance markers. We summarize current knowledge and consider whether understanding how these that variants influence risk could help to refine risk prediction and develop targeted therapies.

by Dr Olivia Fletcher and Dr Syed Haider

Rare high-penetrance mutations
The earliest evidence for genetic susceptibility to cancer came from epidemiological studies in the 1940s and 1950s showing increased cancer risk in the relatives of cancer patients. It was not until the 1990s that linkage analysis, i.e. the genotyping of genetic markers in large family pedigrees, led to the identification of the first breast cancer susceptibility gene, BRCA1, at 17q21 [1]. Identification of the second breast cancer susceptibility gene, BRCA2, at 13q12-13 followed relatively quickly [2]. Mutations in BRCA1 and BRCA2 are present at a frequency of approximately 1 in 800 for BRCA1 and 1 in 500 for BRCA2, they confer high relative risks of breast cancer in carriers (more than tenfold) and are associated with early onset disease [3, 4].
Moderate-risk variants
The next milestone in breast cancer genetics came in 2002 with the discovery of frameshift alteration in the checkpoint kinase 2 gene, CHEK2*1100delC. This variant was discovered using a combination of linkage and mutation screening in a large multiple-case breast cancer family from the Netherlands, followed by analysis of the CHEK2*110delC variant in high-risk breast cancer families, ‘unselected’ breast cancer cases and controls [5]. The CHEK2*1100delC variant occurs on a single haplotype indicating that all CHEK2*1100delC-carrying chromosomes arise from a single founder; this variant is confined to Northern European populations with a prevalence in controls that varies significantly between Northern European populations. Compared to truncating mutations in BRCA1 and BRCA2, the relative risk associated with CHEK2*1100delC is moderate – approximately twofold.

Subsequent to the discovery of CHEK2*1100delC, additional moderate-risk variants were identified in candidate genes including ataxia telangiectasia mutated (ATM), partner and localiser of BRCA2 (PALB2) and BRCA1 interacting protein C-terminal helicase 1 (BRIP1). These variants were discovered by sequencing of exons and exon/intron boundaries of DNA damage repair genes in breast cancer cases from high- and moderate-risk families. Variants in these genes occur in the population at combined frequencies (per gene) of around 1% and are predominantly protein-truncating mutations.

Common low-penetrance variants
It was not until 2007 that the first genome-wide association study (GWAS) of breast cancer successfully identified five common low-penetrance variants; minor allele frequencies of these variants ranged from 25 to 40% and they were associated with relative risks of 1.07 to 1.26 [6]. Detecting relative risks of this magnitude required three stages of genotyping and a total of 26 258 cases and 26 894 controls. This study was an order of magnitude larger than any previous study marking the beginning of the era of GWAS as well as large consortia. Since 2007 many more breast cancer GWASs have been published, but the major advances in identifying and cataloguing additional low-penetrance variants have come from large collaborative efforts led by the Breast Cancer Association Consortium (http://bcac.ccge.medschl.cam.ac.uk/); in particular two large analyses – the Collaborative Oncological Gene-environment study (COGS) and OncoArray [7, 8]. To date, more than 150 low-penetrance variants conferring relative risks of approximately 0.81–1.35 have been identified. Not surprisingly, the more common variants with the (relatively) more extreme breast cancer odds ratios were identified first, by the GWASs (shown in deep blue, Fig. 1); less common variants and variants with less extreme odds ratios were identified most recently, by the largest pooled analysis, OncoArray (shown in green, Fig. 1).

Contribution to the excess familial relative risk
Breast cancer, like most common cancers, shows familial aggregation; the risk of breast cancer in the first-degree relative of a breast cancer case is about twice that of the risk in the general population [3]. The proportion of this ‘familial relative risk’ that is explained by one or more variants is the metric used to quantify the relative contributions of the different classes of variants – and to estimate the number of variants that have not yet been identified. Relative proportions of all three types of variants are shown in Figure 2; mutations in BRCA1 and BRCA2 account for approximately the same proportion of the familial relative risk as the sum of the common low-penetrance variants.
Differences between coding variants and non-coding variants
One fundamental difference between the high-penetrance mutations in BRCA1 and BRCA2, the moderate-risk variants in DNA damage repair genes and the low-penetrance variants identified by GWAS is that the vast majority of low-penetrance GWAS variants map to non-coding DNA. Estimating the risk of breast cancer for individual BRCA1 and BRCA2 mutation carriers is not trivial; there is some evidence that breast cancer risks differ according to the position of the mutation within the gene [4] and for BRCA2, there is evidence of effect modification by common low-penetrance variants [9]. For the low-penetrance GWAS variants, however, the problem is rather different; while the relative risks associated with the marker single nucleotide polymorphisms (SNPs) are fairly precisely estimated, the underlying ‘causal’ variants and the genes that these variants influence remain – largely – unknown. Approaches to the functional characterisation of GWAS risk loci include fine-scale mapping of potentially large genomic regions, the analysis of SNP genotypes in relation to expression of nearby genes (eQTL) and the use of chromatin association methods [chromosome conformation capture (3C) and Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET)] of regulatory regions to determine the identities of target genes. Regulatory elements have been shown to form physical interactions with the genes that they regulate, often over long distances and frequently ‘skipping over’ proximal genes; chromatin association methods capture these interactions and use them to infer likely target genes. We have recently carried out a high-throughput, high resolution analysis of 63 breast cancer risk loci using Capture Hi-C [10]. We were able to identify 110 putative target genes mapping to 33 risk loci. Although some of these putative target genes were well-known cancer genes others were not; in depth follow-up studies will be required to determine which of these putative target genes truly influence breast cancer risk and the mechanisms by which they do so.

Causal variants and target genes can inform risk prediction and therapy
NICE guidelines for the classification, care and management of breast cancer, based on an individual’s family history of breast and other cancers, are used to classify women into three categories: population risk (<17% lifetime risk), moderate risk (17–30% lifetime risk) and high risk (≥30% lifetime risk; https://www.nice.org.uk/guidance/CG164). The options that are available to a woman – increased surveillance, genetic testing, chemoprevention and prophylactic surgery – depend on which category she falls within. A longer-term aim of GWAS is the development of polygenic risk scores (PRS) that can be incorporated into risk prediction algorithms to refine risk estimates. A recent analysis based on 77 breast cancer-associated SNPs, estimated lifetime risks of breast cancer for women in the lowest and highest quintiles of the PRS as 5.3% (population risk) and 17.2% (moderate risk), respectively [11]. Inclusion of larger numbers of SNPs and incorporating causal variants rather than tag SNPs should improve the discriminatory power of the PRS.

In this era of stratified medicine, identifying the genes that underlie GWAS associations and hence – presumably – contribute to defining disease subgroups, also offers the potential for targeted therapies. For instance, metastatic breast cancer patients with germline BRCA1 or BRCA2 mutations who also lack HER2 expression are eligible for Olaparib [a targeted cancer drug that inhibits poly-ADP ribose polymerase (PARP)] as of January 2018. A recent study demonstrated that Olaparib-treated patients have significantly improved progression-free survival (PFS) compared to patients treated with standard-therapy (median PFS of 7 months vs 4.2 months respectively) [12]. Breast cancer patients with germline BRCA1 or BRCA2 mutations already have a defect in their DNA repair mechanisms; by blocking PARP proteins, Olaparib acts to exacerbate DNA damage and trigger cell death, specifically in cancer cells (synthetic lethality). Although defects in DNA repair can be a consequence of germline BRCA mutations, some breast cancer patients manifest defects in DNA repair in the absence of germline BRCA mutations; these patients are also regarded as BRCA deficient – a characteristic often termed as ‘BRCAness’ [13]. Scientists are actively searching for biomarkers of BRCAness in order to assess the suitability of existing PARP inhibitors for patients exhibiting BRCAness [14]. Additional clinical trials on studying efficacy of PARP inhibitors for treating other breast cancer subgroups are underway.

The associations between GWAS SNPs and disease are very modest, and this is often cited as a disadvantage when it comes to considering the genes that map to these loci as putative drug targets. However, an individual non-coding ‘causal’ SNP will usually explain only a small proportion of variation in expression of the gene(s) that it regulates; chemically targeting these genes could have a much more profound effect on disease incidence or outcome. In support of this prediction, a recent investigation by scientists from GlaxoSmithKline estimated that selecting genetically supported targets (including those identified by GWAS) could double the success rate of drugs in clinical development. Although this estimate may be less applicable to cancer drugs, where the somatic genome is as important – or more important – than the germline genome [15,] it leaves open the possibility of new therapies targeting the genes that underlie GWAS associations.

Acknowledgements
We thank Breast Cancer Now for funding this work as part of Programme Funding to the Breast Cancer Now Toby Robins Research Centre.

References
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The authors
Olivia Fletcher* PhD, Syed Haider PhD
Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London SW3 6JB, UK

*Corresponding author
E-mail: Olivia.fletcher@icr.ac.uk