Triple-negative myeloproliferative neoplasms (TN-MPN): A meta-analysis of clinical and molecular characteristics

Abstract

Abstract Triple-negative myeloproliferative neoplasms (TN-MPN), defined by the absence of canonical driver mutations in JAK2, CALR, and MPL, are a biologically heterogeneous subset of BCR-ABL1-negative MPNs. The disease is not well characterized due to rarity of the disease. Non-canonical mutations in TN-MPNs, including rare variants in JAK2, CALR, or MPL not covered by standard assays, as well as somatic alterations in epigenetic regulators and spliceosome components, have been identified in over 50% of cases. A distinct subset of TN-MPN patients, referred to as truly triple-negative (TTN-MPN), lack any mutation, raising the possibility of alternative pathogenicity. The clinical relevance of these molecular subgroups remains underexplored. We conducted a meta-analysis to comprehensively evaluate the clinical, molecular, and thrombotic features of TN-MPNs, with an exploratory sub-analysis comparing TTN-MPNs, mutated TN-MPNs, and driver-mutated MPNs.A literature search was conducted of PubMed, EMBASE and Scopus (updated July 2025) involving observational studies of TN-MPN cohorts with available clinical or molecular data. Eligible studies included ≥2 TN-MPN patients and reported distinct clinical characteristics, thrombotic outcomes or mutation data beyond driver mutations. Results from the literature search were independently reviewed by two authors. Subgroup analysis was performed evaluating patients from Karmanos Cancer Institute, UT Southwestern, Wisconsin School of Medicine and were included as pooled analysis along with other studies. Random-effects model was used to calculate effect size in terms of pooled proportions and comparative risk (odds ratios [ORs] or hazard ratios [HRs]) for thrombotic events. Median age and survival data were analyzed using a meta-analysis of medians with a random effects model to calculate pooled estimates using R software (McGrath et al., 2023). From 406 screened records, 14 studies met inclusion criteria. These studies had a total 623 TN-MPN patients with diagnosis distribution as follows: ET: 363; MF: 157; MPN 239(mix of ET, PV and MF). Pooled estimate for males with ET by random effects model was 40%, (95% CI 23-57%) with I2of 90.2%(p<0.0001), and for males with MF was 58% with CI ( 46-70%) I2of 37.7%,(p<0.15). Pooled estimate of thrombotic events in pts with ET was 17% (CI 9-27%) with I2of 69%(p<0.02). Thrombotic events for MF and all diagnosis MPN was scarcely reported and hence uncomparable. For pts with ET, Pooled weighted median age was 50 yrs,( 95% CI 47-53 yrs), Hb was 13.6(95% CI 13.2-14), WBC median was 8.3(95% CI 8-8.5) and for platelet count median was 635(95% CI 595-854). For pts with MF, Pooled weighted median age was 67(95% CI 47-69 yrs), Hb 9.8(95% CI 9-11.5), WBC median was 8.5(6.7-14) and for platelet count 157(147-1345). We analyzed TN, Truly triple negative(TTN) and Positive group, there was a significant difference in gender distribution(p<0.05) with female predominance in TTN and TN group. There was difference in diagnosis among the three groups(p<0.02), TTN had predominant ET pts. TN had higher Hb count compared to others(p<0.001), highest platelet in TTN(p<0.0001). Based on NGS analysis, TET2 was enriched in TN compared to other groups(43% vs 22 vs 18% in TN, TTN and in positive group), similarly ASXL1 was enriched in TN (29% vs 18 vs 17%), and EZH2 enriched in TN (14% vs 4% vs 5%), similarly DNMT3A enriched in TN (14% vs 11% vs 10%). TP53, U2AF1 was enriched in positive group. Jak2 was 71%, CALR was 26% and MPL was 5% in the positive group. This meta-analysis of 623 TN-MPN patients revealed that TTN-MPNs (truly triple-negative) were predominantly female and had an ET phenotype with thehighest platelet counts, while mutated TN-MPNs showed enrichment in epigenetic and spliceosome mutations (e.g., TET2, ASXL1, EZH2, DNMT3A). These findings highlight the need for routine NGS testing in TN-MPNs and support the notion that TTN-MPNs may represent a biologically distinct subgroup warranting further investigation. To further delineate clonal evolution and uncover cryptic drivers, we plan to analyze serially sequenced samples, which may provide deeper insight into disease dynamics and mutation acquisition over time.