Original Research

Mutational landscape of classical myeloproliferative neoplasms in the Western Cape Province, South Africa

Marthinus J. Dicks, Erica-Mari Nell, Carmen Swanepoel, Ibtisam Abdullah, Zivanai C. Chapanduka

Received: 07 Aug. 2025; Accepted: 04 Dec. 2025; Published: 20 Aug. 2026

Copyright: © 2026. The Author(s). Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: The classical myeloproliferative neoplasms (MPNs) are driven by somatic variants in Janus kinase 2 (JAK2), calreticulin (CALR) and thrombopoietin receptor (MPL) genes. The heterogeneity in mutational frequency of JAK2, CALR, MPL and triple-negative MPNs between regions indicates that epidemiological studies in sub-Saharan Africa are required.

Objective: The aim of this study was to describe the genetic variants seen in MPNs at a South African tertiary hospital.

Methods: A retrospective study was conducted at Tygerberg Hospital, Western Cape Province, South Africa. Patients investigated for a classical MPN driver variant (polycythaemia vera [PV], primary myelofibrosis [PMF] and essential thrombocythaemia [ET]) from 2009 to 2020 were included in the study. The associated MPN diagnosis was sought from full blood count and bone marrow reports. Janus kinase 2-positive and -negative groups were compared for each MPN using a two-tailed independent samples t-test.

Results: There were 128 patients diagnosed with an MPN over the 12-year study period. Polycythaemia vera was the most prevalent (38%), followed by PMF (33%), essential thrombocythaemia (20%), and MPN unclassifiable (9%). The most frequent variant was JAK2 p.V617F (78%) followed by CALR variants (8%). No MPL variants were detected among the patients tested. In PMF, patients with JAK2 p.V617F variants were older (mean age 65 years vs 58 years, p = 0.048) and had a higher haemoglobin (10.6 g/dL vs 8.1 g/dL, p = 0.013) at diagnosis when compared to patients without JAK2 p.V617F.

Conclusion: These data suggest that there are differences with regard to MPN epidemiology and variant frequency in South Africa, and further clinical studies are required to fully characterise MPNs in the South African context.

What this study adds: This retrospective study expanded the profiling of MPNs and driver variants of MPNs in a South African population. Primary myelofibrosis made up a higher percentage of MPN cases than reported in international studies. In addition, in PMF and essential thrombocythaemia, JAK2 p.V617F was more common and CALR variants were less common than reported internationally, while MPL variants were not detected.

Keywords: polycythaemia vera; essential thrombocythaemia; primary myelofibrosis; myeloproliferative neoplasms; mutational landscape.

Introduction

The classical myeloproliferative neoplasms (MPNs), namely polycythaemia vera (PV), essential thrombocythaemia (ET) and primary myelofibrosis (PMF), have overlapping clinical, morphological and molecular features. Primary myelofibrosis can be classified further into a pre-fibrotic and overt fibrotic stage. Cases with features of a MPN, which do not meet all criteria for a specific MPN entity, are classified as MPN unclassifiable.¹

The canonical MPN driver gene variants include specific variants in Janus kinase 2 (JAK2), calreticulin (CALR) and the thrombopoietin receptor gene (MPL).² Janus kinase 2 p.V617F accounts for 97% of PV and 55% of ET and PMF cases.³ Furthermore, JAK2 exon 12 variants are reported in the majority of PV patients who are negative for the JAK2 p.V617F variant.⁴ Calreticulin variants account for 25% of ET and 30% of PMF cases.³ Calreticulin variants can be subtyped as type 1 (52 bp deletion; c.1092_1143del52;p.Leu367Thrfs*46) and type 2 (5 bp insertion; c.1154_1155insTTGTC) CALR variants.⁵ In ET, type 1 and 2 CALR variants are more evenly distributed (51% for type 1 vs 39% for type 2) than in PMF (70% for type 1 vs 13% for type 2).⁶ Thrombopoietin receptor gene variants account for 5% of ET and 8% of PMF cases.³ The absence of MPL variants in some studies could indicate that MPL variants are not equally prevalent among all population groups.⁷

The absence of a classical driver gene variant in otherwise typical MPN suggests that there are alternative low-frequency non-canonical MPN variants which can result in a similar phenotype.^8,9 Cases of triple-negative MPNs (negative for the canonical variants in JAK2, CALR and MPL) occur in ET and PMF in 10% to 15% of cases.¹⁰

Driver variants in JAK2, CALR and MPL affect the MPN phenotype and prognosis. Primary myelofibrosis patients with JAK2 p.V617F are more likely to present with portal vein thrombosis, while those with CALR variants are younger, have a higher platelet count, and a lower leukocyte count when compared with other PMF patients.^11,12 The risk of blast transformation in CALR-mutated PMF is lower than in JAK2-mutated or triple-negative PMF.^11,12 There may be population-specific differences in the prognostic implications of a genetic driver. Calreticulin-mutated PMF was shown to have improved overall survival compared with JAK2-mutated PMF in the non-Asian population, while in the Asian group, JAK2-mutated PMF performed better.¹³ Such findings highlight the need for better description of the MPN mutational landscape in different populations.

The heterogeneity in variant frequency of JAK2, CALR, MPL and triple-negative MPNs between regions indicates that epidemiological studies in sub-Saharan Africa are required. The variant heterogeneity could be compounded in countries such as South Africa, where extensive genomic diversity is present.¹⁴ In addition, to our knowledge, there have been no published epidemiological studies assessing the frequency of JAK2, CALR or MPL variants in MPNs in South Africa. Understanding the genetic drivers has both diagnostic and therapeutic implications.

The aim of this study was, therefore, to describe the genetic variants found in MPNs in a South African population. The study objectives were to determine the frequency of PV, ET and PMF; to determine the frequency of JAK2 p.V617F, JAK2 exon 12, CALR and MPL variants in MPNs; and to compare full blood count parameters between variants within each MPN group.

Methods

Ethical considerations

This study was approved by the Human Research Ethics Committee of Stellenbosch University (Approval number: HREC1-2020-17308). A waiver of individual patient consent was granted because of the retrospective nature of the study and the fact that patients were de-identified. Collected data were entered on a REDCap® data entry sheet.¹⁵ Each data set was allocated a unique study number and de-identified for any subsequent analyses. The patient identifiers remained only on the REDCap® data entry sheet, which was protected with both a password and an encryption key. The anonymity of the patients was upheld throughout the study and no patient identifying information was made public during the data collection, data analysis, and final output of this study.

Study setting

A retrospective cross-sectional descriptive study was conducted at Tygerberg Hospital, a tertiary academic hospital in South Africa. The hospital serves a catchment area of 3.4 million people. All sample testing was conducted at the National Health Laboratory Service.

Data collection and interpretation

All patients aged 18 years or older who were investigated for the presence of a classical MPN variant (JAK2 p.V617F, JAK2 exon 12, CALR or MPL variants) at Tygerberg Hospital from January 2009 to December 2020 were included in the study. Patients who required a diagnostic bone marrow examination for MPN diagnosis, but did not have one, were excluded.

Patients were obtained from the database of patients tested for classical MPN variants at the Molecular Haematology Laboratory. The data extraction was performed between July and September 2021. Patient information was entered on a REDCap® data entry sheet.¹⁵ The National Health Laboratory Service Laboratory Information System was used to assess full blood count, erythropoietin, and bone marrow examination reports. Age at diagnosis and sex were also retrieved. Results from before August 2015 were obtained from the DisaLab Laboratory Information System (DisaLab, Laboratory System Technologies, Johannesburg, South Africa), while results from after August 2015 were obtained from the TrakCare Laboratory Information System (TrakCare, InterSystems Corporation, Cambridge, Michigan, United States).

Janus kinase 2 variant testing for p.V617F and exon 12 variants commenced at Tygerberg Hospital in 2009, and CALR and MPL variant testing in 2015. The workflow for MPN testing at Tygerberg Hospital entailed first testing for JAK2 p.V617F. If the result was negative, JAK2 exon 12 variant testing was performed for patients with suspected PV, while for ET and PMF, CALR and MPL variant testing was performed. Janus kinase 2 p.V617F testing was performed by allele-specific polymerase chain reaction. This method employs variant- and wild-type-specific forward primers with a common reverse primer. Genotype is determined by the presence or absence of the corresponding allele-specific amplicons. Janus kinase 2 exon 12, CALR and MPL variant analysis was performed by bidirectional Sanger sequencing.

Data analysis

Statistical analysis was performed using Microsoft Excel® (Microsoft, Redmond, Washington, United States). Results were summarised and analysed in association with the Biostatistics Unit, Division of Epidemiology and Biostatistics, at Stellenbosch University in South Africa. The Shapiro–Wilk test was used to determine whether the data deviated from a normal distribution. All variables (age at diagnosis, haemoglobin, white cell count, and platelet count) were parametric, and therefore mean and standard deviation were calculated. Variables were compared using the two-tailed independent samples t-test. The JAK2 p.V617F-positive group was compared to the JAK2 p.V617F-negative group for each classical MPN. For PV, the JAK2 p.V617F-negative group consists of all patients negative for JAK2 V617F. For ET and PMF, the JAK2 V617F-negative group consists of CALR variant positive, MPL variant positive, and triple-negative patients. Pre-PMF and overt-PMF were analysed as one group (PMF). A p-value less than 0.05 was considered statistically significant.

Results

A total of 757 patients were tested for variants in JAK2 p.V617F, JAK2 exon 12, CALR and/or MPL over the 12-year period (Figure 1). All patients were initially tested for JAK2 p.V617F. Of these, 143 (19%) were positive for the variant and were not assessed for other variants based on the workflow of the testing laboratory.

FIGURE 1: Summary of sample population by diagnosis and myeloproliferative neoplasm mutation status, Tygerberg Hospital, Cape Town, Western Cape, South Africa, January 2009 to December 2020.

Diagnostic bone marrow examination was not performed in 420 (55%) of the patients who had genetic analysis. Of these, 16 met the diagnostic criteria for PV without a bone marrow examination.¹ Bone marrow examination was performed on 337 (45%) patients (Figure 1). In 63% of these (212/337), an MPN-associated variant was not detected and the final diagnosis on bone marrow examination was not in keeping with a classical MPN. In 4% (13/337), a variant for a classical MPN was detected; however, on bone marrow examination, the diagnostic criteria for a classical MPN were not met.

There were 128 patients diagnosed with an MPN and included for further analysis, with 16 of these meeting diagnostic criteria for PV without bone marrow aspiration and trephine (Figure 1). The average age of MPN diagnosis was 62 ± 14 years with a male to female ratio of 1:1 (64 male patients to 64 female patients). Of the 128 patients diagnosed with an MPN on bone marrow examination, 49 (39%) had PV, 26 (20%) had ET, 17 (13%) had pre-PMF, and 25 (19%) had overt-PMF. In addition, 11 patients (9%) were classified as MPN unclassifiable. The ages at presentation of PV, ET and PMF were similar (Table 1).

In PV, JAK2 p.V617F was seen in the majority of patients (96%). The remaining two (4%) JAK2 p.V617F-negative patients with PV were also negative for JAK2 exon 12 variants (Figure 2). The diagnosis of PV was based on the minor criterion of low erythropoietin level in these cases. In ET and PMF, the most common variant was JAK2 p.V617F, seen in 65% (ET) and 71% (PMF) (Figure 2). Patients who were JAK2 p.V617F negative were tested for CALR and MPL variants; that accounted for seven of the nine ET patients and six of the 12 PMF patients. The patients who were not tested for CALR or MPL variants were investigated for an MPN before testing for CALR and MPL variants became available at our centre. Three patients (2%) had a CALR 52 bp deletion (Type 1 mutation) – all of these were PMF cases. Five patients (5%) had a CALR 5 bp insertion (Type 2 mutation) – four were in patients with ET and the other one in a patient with PMF. A novel CALR frameshift variant was detected in one patient with ET [NM_004343.3(CALR):c.1104_1143del40 (p.E369Qfs)]. All tested patients were negative for an MPL variant. There were five triple-negative cases, two of which were ET, two PMF, and one case was MPN unclassifiable (Figure 2).

FIGURE 2: Genetic variant profile categorised by myeloproliferative neoplasm diagnoses for (a) all myeloproliferative neoplasms (n = 128); (b) polycythaemia vera (n = 49); (c) essential thrombocythaemia (n = 26); (d) primary myelofibrosis (n = 42); (e) myeloproliferative neoplasm unclassifiable (n = 11), Tygerberg Hospital, Cape Town, Western Cape, South Africa, January 2009 to December 2020.

In PMF, haemoglobin was significantly higher in those patients positive for JAK2 p.V617F compared to those negative for JAK2 p.V617F (p = 0.013). In addition, patients diagnosed with PMF who lack the JAK2 p.V617F variant were significantly younger than the JAK2 p.V617F-positive group (p = 0.048). There were no other significant differences in ET or PMF between the JAK2 p.V617F-positive and -negative groups (Table 1). There were too few PV patients who were negative for both JAK2 p.V617F and exon 12 (n = 2) for meaningful comparison between groups.

Discussion

We found that PV was the most common MPN subtype, accounting for 38% of MPNs, followed by PMF in 33%. Essential thrombocythaemia was the least common MPN, at 20%. We found that JAK2 p.V617F was the most common variant across all MPNs, seen in 96% of PV, 65% of ET and 71% of PMF. No MPL variants were detected among the patients tested. In PMF, JAK2 p.V617F was associated with older age at diagnosis and higher haemoglobin.

The proportion of PV, PMF and ET cases found in our study compared well to a seven-year retrospective study which examined JAK2 p.V617F variants in the Gauteng Province of South Africa.¹⁶ Primary myelofibrosis was diagnosed in 43.7% of the Gauteng patients, and ET in 11.5%.¹⁶ In contrast, PMF is typically the least frequent of the three classical MPNs outside of South Africa.⁷ In a large meta-analysis of 52 studies, which included 5300 MPN patients from the United States, China, Brazil and Europe, only 18% of MPN cases were diagnosed with PMF and 49% with ET.⁷ The reason for this difference in the frequency of the MPNs between South African and international studies is unclear. It may reflect a true population-specific difference in MPN frequencies; however, it may also be that patients with PMF are more likely than those with ET both to seek medical care and to be referred from primary care facilities for further investigation because of the more pronounced symptom severity seen in PMF.

In our 49 patients with PV, 96% had the JAK2 p.V617F. The frequency of JAK2 p.V617F variant ranges from 37.8% to 100% in PV across different studies (Table 2). The average frequency of JAK2 p.V617F-negative PV has been reported as 5% in literature from Europe and the United States, although the number varies slightly between studies (Table 2).¹⁷ This may be related to sensitivity of testing modality and sample study size, rather than differing driver variants. Of note, many studies did not perform a test for JAK2 exon 12 variants. The only African studies investigating the frequency of JAK2 exon 12 variants in PV patients were a Sudanese study that reported a JAK2 exon 12 frequency of 8.1% and an Egyptian study with a frequency of 0% (Table 2).^18,19 The frequency of PV driver variants in sub-Saharan African countries has not yet been determined. We only had two PV patients who were negative for JAK2 p.V617F and both patients were negative for JAK2 exon 12 variants. Further large-scale South African studies are required to more accurately characterise the frequency of JAK2 exon 12 mutations within the local population.

Our findings showed that there were no MPL variants detected in the JAK2 p.V617F-negative ET and PMF patients. The only other African studies, which were performed in Egypt, also failed to detect MPL variants in ET and PMF patients.^18,20 Of note, in our study, there were 11 patients who did not undergo MPL testing after testing negative for JAK2 p.V617F. Their mutational status is therefore unknown. Our findings support revising our institutional standard operating procedure to perform JAK2 p.V617F testing upfront, given its high prevalence, followed by next-generation sequencing when JAK2 p.V617F is negative. This strategy will improve detection of non-canonical mutations and, importantly, enhance identification of low allele frequency CALR variants that are currently under-recognised in South Africa.

Janus kinase 2 p.V617F or CALR variants were present in the majority of ET and PMF patients in our study, a finding frequently reported in the literature (Table 3 and Table 4). The frequency of CALR variants in our study was on the lower end of the frequency distribution range, with the majority of our patients having a JAK2 p.V617F variant. In our study, the prevalence of JAK2 p.V617F is higher in PMF patients (71%) than ET patients (65%) (Table 3 and Table 4). Calreticulin 5 bp insertion mutations (n = 6) were more common in our patients than CALR 52 bp deletion mutations (n = 3), which contrasts with Europe (32% vs. 56%).⁶ There were only 10 CALR variant-positive patients in our study and larger studies are required to confirm this finding.

Triple-negative ET and PMF were relatively infrequent in our patients at only 6%, which is less than the 10% to 15% reported in international studies.¹⁰ The number of triple-negative patients in this study may be higher than reported if all the ET and PMF patients who tested negative for JAK2 p.V617F were also tested for other variants, namely those affecting CALR and MPL.

Our study showed that patients with PMF were statistically more likely to present with a higher haemoglobin level if they were positive for the JAK2 p.V617F variant. The JAK2 p.V617F positive PMF patients were also significantly older at presentation than the JAK2 p.V617F negative group. These findings correlate with the international literature.³⁵ Haemoglobin level and age in PMF were the only phenotypic parameters where a statistically significant difference was associated with a specific variant, despite the fact that laboratory features of JAK2 p.V617F have been distinguished from those of other variants in PV, ET and PMF.^8,35,36 Future studies on prognosis of different variants in PMF are required in a South African context.

Limitations

A limitation was that there were 31 patients who were JAK2 p.V617F positive who did not meet the criteria for PV and did not have a diagnostic bone marrow examination. They were excluded from analysis, limiting the characterisation of JAK2 p.V617F MPNs, but also highlighting that investigation of cytoses may be incomplete in our setting. Another limitation was that Sanger sequencing might not be able to detect mutant alleles below 10% to 15%, which could lead to false-negative results.³⁷ The MPL, CALR and JAK2 exon 12 variants should be investigated with more sensitive techniques in future South African MPN studies to validate these findings.³⁸

Conclusion

In conclusion, this study highlights the frequency of the MPN subtypes and the mutational landscape of MPNs in a South African hospital. We found no MPL variants among the ET and PMF patients tested and no JAK2 exon 12 variants among the PV patients tested. Polycythaemia vera and PMF were common, while ET was less frequent. This study has thus demonstrated that the proportion of MPN subtypes and mutation frequency in subtypes differ from international studies. Patient outcomes may also differ. Future studies exploring survival based on driver mutations within the South African context could prove valuable.

Acknowledgements

We acknowledge Dr Merga Feyasa (Department of Biostatistics, Stellenbosch University) for assistance with statistical analysis.

This article partially based on research originally conducted as part of Marthinus J. Dicks’s Master of Medicine (MMed) degree titled ‘Mutational landscape of classical myeloproliferative neoplasms in the Western Cape province, South Africa’, in Haematopathology submitted to the Faculty of Medicine and Health Sciences at the Stellenbosch University 16 September 2022. The thesis was supervised by Dr Ibtisam Abdullah and co-supervised by Dr Carmen Swanepoel and Prof Zivanai Chapanduka. Portions of the data, analysis, and discussion have been revised, updated, and adapted for publication as a journal article.

During the preparation of this work, the authors used ChatGPT (OpenAI) to assist with language, formatting and internal-consistency checks. All suggested corrections were independently reviewed and verified by the authors, who retain full responsibility for the content of the article.

The authors, Marthinus J. Dicks, Erica-Mari Nell, Carmen Swanepoel, Ibtisam Abdullah, and Zivanai C. Chapanduka, declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Marthinus J. Dicks: Conceptualisation, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft. Erica-Mari Nell: Data curation, Supervision, Writing – review & editing. Carmen Swanepoel: Supervision, Writing – review & editing. Ibtisam Abdullah: Conceptualisation, Methodology, Supervision, Writing – review & editing. Zivanai C. Chapanduka: Supervision, Writing – review & editing. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication, and take responsibility for the integrity of its findings.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The data that support the findings of this study are not openly available due to reasons of sensitivity, for example, human health data and are available from the corresponding author, Marthinus J. Dicks, upon reasonable request. Data are housed on the Stellenbosch University REDCap® platform.

The views and opinions expressed in this article are those of the authors and are the product of professional research. The article does not necessarily reflect the official policy or position of any affiliated institution, funder, agency, or that of the publisher. The authors are responsible for this article’s results, findings, and content.

References