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.
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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
Introduction
Owing to recent remarkable advances in our understanding of the molecular and genetic basis of disease, it is now known that colorectal carcinoma (CRC) is a heterogenous clinical entity characterized by multiple molecular subtypes [1]. One such molecular pathway involved in CRC pathogenesis is the microsatellite instability (MSI) pathway, where a deficient mismatch repair (dMMR) system leads to unchecked errors in DNA replication [2]. These errors result in a propensity for abnormal insertion or deletion of short, repetitive sequences of DNA (microsatellites), resulting in mutations in cancer-related genes and ultimately neoplasia. Up to 15–20% of colorectal carcinomas are of MSI phenotype. An inherited predisposition to dMMR cancers, particularly CRC, is present in Lynch syndrome, the most common heritable cancer syndrome. It is due to autosomal dominant mutations in four mismatch repair (MMR) genes (MLH1, MSH2, MSH6, PMS2) or more rarely by mutations in EPCAM, a gene upstream of MSH2. Patients present at an earlier age and have an increased incidence of synchronous and metachronous CRCs. Histologically, tumours are poorly differentiated, frequently exhibiting a mucinous or signet ring cell morphology. Tumour infiltrating lymphocytes are often prominent and a Crohn’s-like inflammatory response may be present at the tumour periphery. However, the majority of dMMR CRCs arise sporadically and are a result of MLH1 promoter hypermethylation. Unlike in Lynch syndrome, these tumours affect the right side of the colon, are diagnosed at advanced age and have a female preponderance. They are, however, histologically similar to Lynch syndrome CRCs. Mutation of the BRAF V600E gene is present in 60–70% of sporadic dMMR tumours and is almost never seen in Lynch syndrome. As such, incorporating BRAF and/or MLH1 methylation status into MMR diagnostic algorithms offers potential exclusion criteria for genetic testing [3–5].
Why is it important to identify dMMR in colorectal carcinoma?
Diagnosing a patient with a dMMR cancer has a number of advantages:
1. Identification of patients with Lynch syndrome
Once diagnosed, these patients benefit from increased surveillance, prophylactic aspirin therapy and more radical surgery in order to facilitate the prevention and/or early detection of potential tumours (both colonic and extracolonic) [5].
2. It provides prognostic information
Several studies have shown that dMMR CRC has a better prognosis than MMR proficient (pMMR) CRC. dMMR tumours are less likely to develop lymph node and liver metastases. However, in advanced disease (stage IV) dMMR status can portend a poorer prognosis [6–8].
3. It provides predictive information
dMMR tumours likely have a reduced response to 5-flurouracil based chemotherapy. In addition, advanced dMMR tumours have been shown to have a better response rate and progression free survival to the anti PD-1 drug pembrolizumab when compared to pMMR tumours [7–9].
Reliance by clinicians on clinical criteria such as the revised Bethesda guidelines to determine which patients should undergo screening for Lynch syndrome results in inaccurate determination of eligibility for screening in up to 28% of cases [10]. Consequently, a number of organizations have recently published guidelines endorsing reflex MMR testing of all diagnosed CRCs, including the National Institute for Health and Care Excellence (NICE), the American Society for Clinical Pathology (ASCP) and the American Society for Clinical Oncology (ASCP), among others [11–12]. The cost effectiveness of such a screening approach has been proven by several studies [13].
Diagnosis
Diagnosis of dMMR tumours is either via PCR amplification of specific microsatellite repeats in formalin-fixed, paraffin-embedded tumour tissue or by immunohistochemistry (IHC) which confirms the absence or presence of MMR proteins. Both MSI testing and IHC have virtually equivalent informative value in predicting germline mutation [3, 14]. Given that IHC is more widely available in general pathology laboratories and is a rapid, efficient and cost-effective method of testing, it is the more frequently used test. It also has the added benefit of directing germline testing to the particular mutated gene.
A number of commercially available MMR IHC antibodies are available for laboratory use. A protocol using a panel of four immunohistochemical antibodies to the four mismatch repair gene proteins (MLH1, MSH2, MSH6, PMS2) is recommended (Fig. 1). Complete loss of expression of one or more MMR protein is suggestive of dMMR. Loss of MLH1 often occurs in conjunction with loss of PMS2. This is due to the fact that MLH1 protein forms a heterodimer complex with PMS2. Isolated loss of PMS2 Is indicative of a defect in the PMS2 gene. However, combined loss of PMS2 and MLH1 indicates the defect lies in MLH1, as MLH1 confers stability to PMS2. A similar situation is seen with MSH2 and MSH6; isolated loss of MSH6 indicating defective MSH6, whereas loss of expression of both proteins indicates the defect involves MSH2. Background positive IHC staining in intratumoural lymphocytes or of adjacent normal colonic epithelium, if present, serve as reliable internal positive controls [5].
Once loss of expression of any IHC MMRP is confirmed, further testing is required. In cases where there is loss of MLH1, testing for the presence of BRAF V600E mutation and MLH1 hypermethylation, as mentioned previously, can further stratify those patients who likely have sporadic dMMR tumours. Patients demonstrating loss of MSH2, MSH6 or PMS2, and patients demonstrating loss of MLH1 who are BRAF V600E negative and MLH hypermethylation negative, should undergo germline testing to confirm Lynch syndrome (Fig. 2).
MMR IHC testing is typically performed on CRC resection specimens. Data has recently begun to accumulate that the yield of IHC testing performed on endoscopic biopsy material may be as good as that performed on surgical resections. We recently published a study evaluating the reliability of MMR IHC in CRC from preoperative endoscopic biopsy tissue when compared to matched surgical resection specimens and demonstrated 100% concordance in 53 cases of dMMR (n=10) and pMMR (n=43) tumours [14]. Our results corroborate the results of other studies that indicate endoscopic biopsies are a suitable source of tissue for MMR IHC analysis [15–17].
Preferential testing of MMR status on endoscopic biopsy samples over resection specimens carries a number of advantages. Immunostaining is highly sensitive to the degree of tissue fixation; given the small size of biopsy samples, faster and more thorough fixation may result in superior quality staining. Additionally, neoadjuvant chemoradiotherapy used in the standard treatment of locally advanced rectal tumours may result in a complete pathologic response, with no residual tumour available for testing. Neoadjuvant treatment can also occasionally alter the MMRP status of the tumour. In these two scenarios, the pretreatment biopsy could provide reliable testing material.
Endoscopic biopsies could also be used to initiate earlier and indeed preoperative genetic testing, allowing informed clinical decisions regarding the extent of resection to be made before surgery in those patients confirmed as having Lynch syndrome. The option of total colectomy as an alternative to segmental colectomy could be discussed, particularly with younger patients, to reduce the risk of metachronous CRC and the need for intense postoperative surveillance. In addition, females identified as having Lynch syndrome, who have completed their families, could be considered for concurrent hysterectomy, with/without bilateral salpingo-oophorectomy, in order to prevent the development of a gynecological tract malignancy and spare them a potential additional future procedure.
Recent studies suggest that dMMR tumours may respond well to immunotherapy in patients with advanced disease [9]. In the instance that an advanced tumour is inoperable at diagnosis, metastatic or endoscopic biopsy tissue could be used to screen for dMMR and Lynch syndrome, and direct immunotherapy.
Despite these advantages, some limitations exist in the use of IHC to determine MMR status which are not just specific to biopsy tissue. Rare missense mutations have been reported in MLH1 and MSH6 genes that affect MMR protein function but not translation and antigenicity – in this scenario the tumour harbours a defective protein, but one which demonstrates retention of IHC staining, giving a false result [19].
Intratumoural heterogeneity, where there is heterogeneity of MMR protein expression within a single tumour, also represents a potential pitfall [20]. This may be of particular concern in biopsy samples as they represent only a small proportion of a tumour and could erroneously misclassify the MMR status by virtue of inadequate sampling. Another issue is the small size of endoscopic biopsies; adequate material may not be available for IHC. Encouraging generous tumour sampling at the time of biopsy could reduce the risk of such limitations. Heterogeneity in the MMR status of CRC is rare and is thought in many instances to be a result of suboptimal tissue fixation. Given biopsies are usually of small size, adequate fixation of tissue can be assured.
Conclusion
Up to 15–20% of CRCs are of MSI phenotype, secondary to either sporadic methylation-induced silencing or inherited mutations in MMR-related genes. IHC is an effective and reliable testing modality for determining MMR status in CRC. Colorectal endoscopic biopsy and resection specimens are both suitable sources of testing material, with resection specimens currently the preferred specimen type. Endoscopic biopsy samples may become increasingly important as a testing material as the potential of tailored approaches to surgery, chemotherapy and immunotherapy becomes a standard of care in this era of personalized medicine.
References
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2. Poulogiannis G, Frayling IM, Arends MJ. 2010. DNA mismatch repair deficiency in sporadic colorectal cancer and Lynch syndrome. Histopathology 2010; 56(2): 167–179.
3. Lindor NM, Burgart LJ, Leontovich O, Goldberg RM, Cunningham JM, Sargent DJ, Walsh-Vockley C, Petersen GM, Walsh MD, et al. Immunohistochemistry versus microsatellite instability testing in phenotyping colorectal tumors. J Clin Oncol 2002; 20(4): 1043–1048.
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The authors
Dr Odharnaith O’Brien* MB BCh BAO, Dr Éanna Ryan MB BCh BAO, and Prof. Kieran Sheahan MB BCh BAO
Department of Pathology, St. Vincent’s
University Hospital, Dublin, Ireland
*Corresponding author
E-mail: odharnaithobrien@ gmail.com
Modern hematology emphasizes a multiparametric diagnostic approach and the basic parameters, beside history of the disease and clinical examination, are morphological, immunophenotypic and genetic evaluation. Flow cytometry plays an important role in diagnosis of a large group of hematological diseases. This article reviews the basic principles of flow cytometry and its use in hematology diagnosis, with emphasis on chronic lymphoproliferations.
by Dr Nataša Lazić
Introduction
In modern diagnostics, flow cytometry has an important place as one of the basic and irreplaceable tools for diagnosis, classification, monitoring and prediction of malignant hematological disease [1]. The extreme complexity of these diseases, on one hand, and the availability of the different therapeutic protocols for the different types of these diseases on the other, makes accurate and precise diagnosis imperative. Contributing to this is the fact that the World Health Organization (WHO), in the Classification of Tumours of Hemopoietic and Lymphoid Tissues, suggests a multiparametric approach in diagnosing these diseases; basic parameters required are morphological, immunophenotypic and genetic analysis for each entity of the disease, in addition to a detailed history of the disease and clinical examination [2, 3]. The clinical picture and cell morphology, as a well-known and traditionally-used means of examination, are insufficient in many cases; quite often, because of a similar clinical presentation and cell morphology, it is not possible to draw a diagnostic conclusion based on these findings or a wrong diagnosis may be reached in some cases.
Coulter’s principle of measuring the change in the electrical impedance of the individual cells flowing through the measuring cell, in the late 1940s, was the basis for construction of the first hematologic counter and later for the flow cytometer. Later inventions added new detection capabilities, such as light scatter and fluorescence detection. Fluorescent activated cell sorting (FACS) was invented in the late 1960s by Herzenberg, Bonner, Sweet and Hullet. Introduced as a commercial machine in the early 1970s, this is the class of instruments now commonly referred to as flow cytometer [4]. The invention of monoclonal antibodies by Milstein and colleagues in 1977 opened new perspective for flow cytometry. Further developments, especially in electronics, led to modern cytometers with multiple lasers, detectors, better performance characteristics, and the ability to measure larger amounts of data.
Flow cytometry principles
Flow cytometry is a powerful technology that simultaneously measures many aspects of single particles, usually cells. Any suspended particle or cell from 0.2–150 μm is suitable for analysis. However, it can also measure soluble molecules if trapped onto a particulate surface and bound by fluorochromes. Virtually any component or function of a cell can be measured if the fluorescent probe can be made to detect it.
Sample preparation should provide a homogeneous suspension of cells with monoclonal antibodies conjugated with fluorochromes of a different emission spectrum. Depending on the sample, it most often includes incubation, erythrocyte lysis, centrifugation, washing and fixation.
The cytometer needs to be adjusted to have the appropriate performance characteristics (linearity, sensitivity, CV, electronic and optical background noise, fluorescence detector efficiency, etc). This is achieved by adjusting voltages on the detectors and by spectral overlap compensation (Fig. 1).
The three main systems of flow cytometer are fluidics, optics and electronics (Fig. 2). Parameters measured include forward scatter (FSC) corresponding to cell size, side scatter (SSC) depending on internal complexity and fluorescence intensity for different fluorochromes.
Becoming more available in clinical laboratories, a wide range of clinical applications of flow cytometry are constantly expanding and the most common among them are in, for example, lymphoma and leukemia diagnosis, stem cell enumeration for transplantation, estimation of minimal residual disease, paroxysmal nocturnal hemoglobinuria diagnosis, immunodeficiencies, HIV infection.
Flow cytometry in hematology
Flow cytometric immunophenotyping enables examination of the phenotype of the separate cells in the suspension and summarizing of the results, which gives data about the presence or absence of antigen expression as well as the expression intensity [5]. Hence, an immunophenotypic pattern is obtained on the cell population of interest for the examined disease. Meanwhile, there are no separate antigens specific for the particular disease. Instead, their mutual relation is observed and analysed, which makes the analysis of the flow cytometry results very demanding and complex, but usually very useful and precise owing to the huge amount of data that can be collected from the cells [6]. Therefore, flow cytometry helps with determining the cell line, the degree of cell maturity, abnormal patterns of expression and provides a detailed immunophenotype of the pathological cell population [7]. From information on all the aforementioned factors, a diagnostic conclusion is drawn if there is a phenotype characteristic for some disease. In the case of an atypical phenotype, the disease is assigned to the appropriate group and additional tests should be done to gain a precise diagnosis (such as immunohistochemical, FISH, molecular tests).
CD markers (clusters of differentiation) are blood cell antigens that enable their characterization. CD nomenclature was developed and reviewed by HLDA (Human Leukocyte Differentiation Antigen) workshops started in 1982. There were 10 such workshops and the nomenclature now encompasses about 400 CD markers. Monoclonal antibodies against those antigens are used for immunophenotype characterization.
The antibody panel for the analysis of the sample to be tested by flow cytometry depends, to a large extent, on the available information of other findings made for that patient. According to the Bethesda Group recommendations from 2006, which were aimed at regulating a more systematic approach in this field (and are still valid today), before sending a sample to flow cytometry, a detailed history of the disease, clinical examination, microscopic examination of cell morphology, and other laboratory tests should be carried out, and based on this, diagnosis or differential diagnosis determined. In this way significant rationalization and cost reduction can be achieved [8].
Immunophenotype characterization for chronic lymphoproliferative disorders
For both of the two major groups of malignant hematologic diseases, those derived from mature and from immature cells, flow cytometry is of a great importance. Neoplasms of mature lymphoid cells, according to the WHO Classification, include chronic lymphoid leukemia and non-Hodgkin’s lymphoma. Their basic characteristic is that they have an immunophenotype similar to mature lymphoid cells and, accordingly, they show an absence of immaturity indicators (CD34, TdT). According to the origin, in relation to the cell line, they can be divided into T, B and NK neoplasms. [7]
Mature B-cell lymphoproliferations make up most of the malignant blood diseases: 90 % of the total lymphoid malignancies, according to WHO data. They present 4 % of the newly discovered carcinomas per year. As already known, the malignant cell derived from B-cell lineage in most cases imitates the normal B-cells stopped at a certain maturity level. The classification of this disease group mostly relies on this fact. The most common in this group are chronic lymphocytic leukemia (CLL), hairy cell leukemia (HCL), follicular lymphoma, splenic marginal zone lymphoma, mantle cell lymphoma (MCL), plasma cell leukemia [12]. Immunophenotype characterization in the diagnosis of B-cell chronic lymphoproliferative diseases is an irreplaceable method and, together with morphology, it presents the essential search that should be undertaken in the diagnosis of these diseases[2, 9]. Based on the finding of the immunophenotype characterization it is possible to discover aberrant expression patterns and establish the phenotypic characteristics related to particular diseases. The application of a scoring system as an additional tool is the result of a need for some standardization and quantification in the diagnosis of B-cell chronic lymphoproliferative diseases. In order to increase the precision of the scoring system, different studies with different CD markers are taken [10–12]. The most common scoring system of 5 points includes CD5, CD23, FMC7, CD79b and surface immunoglobulin chains with an accuracy of 96.6 % if a three-point cut-off is used [10].
In most cases of CLL, cell morphology is characteristic and typical for this disease. However, in a number of cases, flow cytometry has a huge and decisive significance for diagnosis (Fig. 3) [13]. CLL and MCL share many morphological and immunophenotypic features [14]. As a result of their partial overlap, a differential diagnosis of MCL is most considered when making a diagnosis of CLL. Because of the different therapeutic approach and prognoses of the diseases, their diagnostic differentiation is very important. For that purpose cyclin D1 testing is recommended [15, 16]. Unlike the other chronic lymphoproliferations, HCL cells do not match any stage of the normal lymphoid cells development. Morphologically typical HCL cells have fine, hair-like, cytoplasmic projections, which are sometimes difficult to find in the peripheral blood smear. Because of this and a very specific immunophenotype, flow cytometry is essential for HCL diagnosis [14, 17].
Advantages
The possibility of combining more antibodies in the same tube and analysing their interactions on the population of interest for the given disease is the greatest advantage of multiparametric flow cytometry, which involves simultaneously collecting and analysing a large amount of data from cells or particles.
Considerations
Comprehensive analysis involves considering possible causes of false-positive or false-negative results, thus avoiding an incomplete or incorrect interpretation of flow cytometry data (Fig. 4).
Other difficulties, such as non-standardized methods, particularly the issue of regulation in cytometry, different antibody panels, cut-off values, analysis subjectivity – recommended visual approach, result analysis complexity, report form, etc., are the subject of work by various associations dealing with cytometry in order to achieve harmonization in this area [13].
References
1. Paiva A, Alves GVA, Sales VSF, Silva ASJ, Silva DGKC, Alves E, Bahia F, Freitas RV, De Oliveira Paiva HD, Cavalcanti GB, Jr. Utility of flow cytometry immunophenotyping and hematological profile in chronic lymphoproliferative disorders. Blood 2017; 130: 5326 [poster abstract].
2. Swerdlow SH, Campo E, Harris NL, Jaffe ES, Pileri SA, Stein H, Thiele J, Vardiman J (eds). WHO classification of tumors of haematopoietic and lymphoid tissues. IARC 2008; Chapters 1, 8, 10. ISBN 978-9283224310.
3. Boyd SD, Natkunam Y, Allen JR, Warnke R. Selective immunophenotyping for diagnosis of B-cell neoplasms: immunohistochemistry and flow cytometry strategies and results. Appl Immunohistochem Mol Morphol 2013; 21: 116–131.
4. Herzenberg LA, Parks D, Sahaf B, Perez O, Roederer M, Herzenberg LA. The history and future of the fluorescence activated cell sorter and flow cytometry: a view from Stanford. Clin Chem 2002; 48: 1819–1827.
5. Braylan RC. Impact of flow cytometry on the diagnosis and characterization of lymphomas, chronic lymphoproliferative disorders and plasma cell neoplasias. Cytometry A 2004; 58: 57–61.
6. Brown M, Wittwer C. Flow cytometry: principles and clinical applications in hematology. Clin Chem 2000; 4: 1221–1229.
7. Craig FE, Foon FA. Flow cytometric immunophenotyping for hematologic neoplasms. Blood 2008; 111: 3941–3967.
8. Oberley MJ, Fitzgerald S, Yang DT, Morgan A, Johnson J, Leith C. Value-based flow testing of chronic lymphoproliferative disorders: a quality improvement project to develop an algorithm to streamline testing and reduce costs. Am J Clin Pathol 2014; 142: 411–418.
9. D’Arena G, Keating MJ, Carotenuto M. Chronic lymphoproliferative disorders: an integrated point of view for the differential diagnosis. Leuk Lymphoma 2000; 36: 225–237.
10. Matutes E, Wotherspoon A, Catovsky D. Differential diagnosis in chronic lymphocytic leukemia. Best Pract Res Clin Haematol 2007; 20: 367–384.
11. Matutes E, Owusu-Ankomah K, Morilla R, Garcia Marco J, Houlihan A, Que TH, Catovsky D. The immunological profile of B cell disorders and proposal of a scoring system for the diagnosis of CLL. Leukemia 1994; 8: 1640–1645.
12. Moreau EJ, Matutes E, A’Hern RP, Morilla AM, Morilla RM, Owusu-Ankomah KA, Seon BK, Catovsky D. Improvement of the chronic lymphocytic leukemia scoring system with the monoclonal antibody SN8 (CD79b). Am J Clin Pathol 1997; 108: 378–382.
13. Rawstron AC, at al. Reproducible diagnosis of chronic lymphocytic leukemia by flow cytometry: an European Research Initiative on CLL (ERIC) & European Society for Clinical Cell Analysis (ESCCA) Harmonisation project. Cytometry B Clin Cytom 2018; 9: 121–128.
14. Asaad NY, Abd El-Wahed MM, Dawoud MM. Diagnosis and prognosis of B-cell chronic lymphocytic leukemia/small lymphocytic lymphoma (B-CLL/SLL) and Mantle cell lymphoma (MCL). J Egypt Natl Canc Inst 2005; 17: 279–290.
15. Matutes E, Polliack A. Morphological and immunophenotypic features of chronic lymphocytic leukemia. Rev Clin Exp Hematol 2000; 4: 22–47.
16. Vose JM. Mantle cell lymphoma; update on diagnosis, risk stratification and clinical management. Am J Hematol 2015; 90: 739–745.
17. Bacal NS, Mantovani E, Grossl S, Nozawa ST, Kanayama RH, Brito ACM, Albers CEM, de Campos Guerra JC, Mangueira CLP. Flow cytometry: immunophenotyping in 48 hairy cell leukemia cases and relevance of fluorescence intensity in CDs expression for diagnosis. Einstein 2007; 5: 123–128.
The authors
Nataša Lazić MD
Institute for Clinical Laboratory Diagnostics, University Clinical Centre of the Republika Srpska, Republika Srpska, Bosnia and Herzegovina
*Corresponding author
E-mail: natasa.lazic.bl@gmail.com
In May it was reported that, owing to an IT error, from 2009 to 2018, approximately 450,000 women aged between 68 and 71 were not recalled for their final mammogram appointments in England. Jeremy Hunt, the health secretary has been quoted as saying that between 135 and 270 women “may have had their lives shortened as a result”. The panic-quelling response came very quickly. The Guardian newspaper reported that Sir
Richard Peto, a professor of medical statistics at Oxford University, had written that there is still substantial uncertainty about the exact ages that mammographic screening should start and end. Additionally, a group of academics and GPs wrote a letter to The Times newspaper saying that the women should not be concerned unless they notice a lump or other symptoms and that the breast cancer screening programme mostly causes more unintended harm than good; many women and doctors avoid breast screening as it has no impact on all-cause death; and that the most dangerous and advanced cancers are not prevented by screening programmes. Breast cancer charities retorted that mammographic screening remains the best tool available for detecting breast cancer at an early and therefore more easily treatable stage and we must not forget that the programme does save lives. The UK’s NHS breast screening programme began in 1988 and national coverage was reached in the mid-1990s. However, over twenty years on, there seems to be an increasing body of data to suggest that the ‘accidental’ harm resulting from mammography because of over-detection and over-treatment of clinically unimportant lumps has been underestimated. The often-quoted figure is that for every woman whose life is extended, three receive unnecessary surgery, chemotherapy or radiotherapy. Hence our ‘best tool available’ seems to be a rather blunt tool. Biomarkers, surely, could provide the refinement needed to stratify patients according to therapy response. This will enable the delivery of individually tailored treatment plans and so will, crucially, prevent the unnecessary administration of chemotherapy and radiotherapy. Work on this is, of course, underway. The EU-funded RESPONSIFY study in Germany has already led to two parameters being included into German breast cancer guidelines for the treatment of HER2-positive breast cancer. Additionally, a gene-expression panel that predicts whether chemotherapy will be beneficial for preventing recurrence is already being used, with some success for the low and high scores. Further work is needed, but perhaps the day is in sight where women will no longer undergo unnecessary chemotherapy.
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