03 / Nature · 2019
An underestimated mutation. A consequential mechanism.
Revisit accepted results and follow the evidence to mechanism.
AN ASSUMPTION PUT TO THE TEST
The assumption I challenged
The flagship TCGA AML study reported SRSF2 mutations in fewer than 1% of patients. Taken at face value, that made the mutation appear uncommon and easy to give less attention.
What we showed
Reanalysis revealed SRSF2 mutations that the original report had largely missed. The collaborative study connected SRSF2 and IDH2 mutations to faulty INTS3 RNA processing.
My contribution
I recognized the mismatch in the RNA evidence, led the computational reanalysis, and checked the result across patient cohorts.
The evidence we established
Three cohorts converged on roughly one in nine patients. Restoring INTS3 slowed leukemia progression in an experimental mouse model.
Why it matters
The study corrected an underestimated mutation frequency and provided functional evidence that mutations in the machinery that splices RNA can drive myeloid blood cancers. Identifying the INTS3 mechanism—and showing that restoring INTS3 slowed leukemia in a mouse model—connected a missed mutation signal to how the disease develops and where future treatments might intervene.
A published frequency depends on the analysis behind it.
A rare finding became a consistent signal.
Evidence & why this changed the research question
The 2019 paper states that the original TCGA AML publication reported one SRSF2-mutant case. Reanalysis identified 19 of 179 patients with RNA-sequencing data. The other two cohorts independently showed similar frequencies; these are cohort estimates, not a universal frequency for all AML patients.
The discovery led to a biological question: how does this mutation help drive leukemia? The collaborative study linked abnormal INTS3 RNA processing to loss of its protein. Restoring INTS3 slowed leukemia progression in a mouse model.
2019 study · Figure 1b–d ↗Explore the evidence & discovery process
- 01Following a mismatch in the RNA
- RNA-processing patterns suggested that the original mutation calls did not capture all affected patients. That discrepancy prompted a re-examination of the underlying data.
- 02Connecting mutations to mechanism
- The collaborative work identified cooperation between SRSF2 and IDH2 mutations. Abnormal INTS3 splicing triggered RNA degradation and reduced protein expression, disrupting the Integrator complex.
- 03Testing biological consequence
- Forced INTS3 expression promoted differentiation and slowed progression in IDH2/SRSF2 double-mutant HL-60 xenografts. This was experimental rescue evidence, not a treatment trial in patients.
- 04The next question
- Which parts of this mechanism are therapeutically tractable, and which patient groups would be most informative for testing them?
Supporting analysis: age at diagnosis
Age context comes from a separate calculation using cBioPortal’s OHSU Nature 2018 study (aml_ohsu_2018), accessed 10 September 2026. Among mutation-profiled patients with age at diagnosis ≥70, 34/148 unique patients carried an SRSF2 mutation (23.0%). Counting samples instead gives 36/171 (21.1%), because some patients contributed multiple samples. Patients without recorded age were excluded. This portal subset differs from the 498-patient RNA analysis in our paper; it is not an additional independent cohort. The U.S. median age at AML diagnosis is 70 (SEER, 2019–2023).
Beat AML dataset · cBioPortal ↗Age at diagnosis · NCI SEER ↗Why this matters today
Four studies connect SRSF2 alterations with rapid growth of mutant blood-cell populations, leukemia, future malignant disease, and earlier mortality. Population-scale UK Biobank analyses complement long-term tracking of individual clones.
Clonal expansion
>50% / yearSRSF2 P95H was associated with exceptionally rapid growth of mutant blood-cell populations, compared with about 5% for DNMT3A and TP53.
385 people · median 13-year follow-up
Fabre et al. · Nature · 2022 ↗Disease association
82× oddsMyeloid leukemia odds: 82× for SRSF2, compared with 18× for ASXL1 in the same study.
454,787 UK Biobank exomes · population-scale study
Backman et al. · Nature · 2021 ↗Future progression
HR 17.24Future myeloid neoplasm: HR 17.24 for SRSF2, compared with 1.84 for TET2 and 1.87 for ASXL1.
438,890 UK Biobank participants screened
Weeks et al. · NEJM Evidence · 2023 ↗Human lifespan
Mortality HR 5.8Mortality HR 5.8 for SRSF2, compared with 1.5 for both DNMT3A and TET2 in the same predicted-pathogenic missense analysis.
393,833 UK Biobank participants · discovery analysis
Park et al. · Nature Communications · 2025 ↗HR = hazard ratio, a comparison of event rates over time. These relative measures describe different study populations and outcomes, not individual absolute risk.
Human studies connect SRSF2 alterations with rapid clonal expansion, myeloid malignancy, future progression, and earlier mortality. Our 2019 work identified INTS3 mis-splicing as one biologically consequential route to leukemia development—giving researchers a mechanism to investigate and potential vulnerabilities to test.
Study details, comparison groups & interpretation
Clonal expansion
Fabre et al. tracked 697 clones in 385 SardiNIA participants aged 55 or older. Estimated growth ranged from about 5% per year for DNMT3A and TP53 to more than 50% for SRSF2 P95H. This is relative clonal expansion, not a yearly probability of leukemia, and concerns this specific SRSF2 mutation.
Fabre et al. · Nature · 2022 ↗Disease association
Backman et al. sequenced 454,787 participants. The SRSF2 rare-variant burden association with myeloid leukemia (ICD-10 C92) had an odds ratio of 82 (95% CI 44–150; P = 1.96 × 10⁻⁴³) in the European-ancestry analysis. This is a gene-burden association, not a prospective progression estimate for every SRSF2 mutation. For the same myeloid leukemia outcome, Supplementary Table 14 reports ASXL1 OR 18 (95% CI 11–28). These are each gene’s carrier-versus-non-carrier associations, not a direct comparison between carriers of the two genes. The reported burdens use different variant masks: SRSF2 M3.01 and ASXL1 M1.01. Supplementary Tables 6 and 14 report the results; the authors identify evidence consistent with somatic mutations in blood-derived DNA.
Backman et al. · Nature · 2021 ↗Future progression
The study screened 438,890 participants; this estimate comes from 11,337 CHIP/CCUS participants in the derivation cohort. Among participants with CHIP/CCUS, SRSF2 mutation was associated with a hazard ratio of 17.24 (95% CI 12.44–23.87) for subsequent myeloid neoplasms, compared with CHIP/CCUS participants without that mutation. Figure 1C reports these univariate associations: TET2 HR 1.838 (95% CI 1.413–2.397), ASXL1 HR 1.869 (1.340–2.606), and SRSF2 HR 17.24. Each compares CHIP/CCUS participants with the named mutation against those without it; these are not direct comparisons between gene groups. SRSF2 was among the high-risk genes, but JAK2 had a higher estimate (HR 32.30). It is not an estimate for an isolated mutation independent of all other risk factors. CHIP/CCUS refers to acquired mutant blood-cell populations, without or with unexplained low blood counts.
Weeks et al. · NEJM Evidence · 2023 ↗Human lifespan
The discovery analysis included 393,833 European-ancestry participants. Park et al. reported mortality HR 5.8 for carriers of AlphaMissense-predicted pathogenic SRSF2 variants versus non-carriers (Cox-analysis P = 3.3 × 10⁻⁶¹). The same AlphaMissense analysis reported DNMT3A HR 1.5 and TET2 HR 1.5, each against its own non-carrier group. These point estimates provide context rather than a formal test of differences between genes. SRSF2 had the largest HR among the significant AlphaMissense gene burdens reported in that analysis. The separate lifespan burden test gave P = 1.8 × 10⁻⁹⁴. These are distinct analyses, not a single HR/P-value pair; HR 5.8 does not mean a lifespan 5.8 times shorter.
Park et al. · Nature Communications · 2025 ↗These studies examine different populations and outcomes; the UK Biobank analyses also draw on overlapping participants. Cross-gene comparisons within a study provide context; they are not head-to-head estimates or proof that the effects differ statistically. Their estimates cannot be multiplied or treated as one inevitable disease trajectory. Clonal growth, relative odds, and hazards do not by themselves establish an individual’s absolute risk.
Technical context & publication
AML means acute myeloid leukemia. Figure 1 reports SRSF2 mutations in 19/179 TCGA, 57/498 Beat AML, and 28/263 Leucegene patients. INTS3 mis-splicing triggered nonsense-mediated decay and reduced protein expression. Forced INTS3 expression promoted differentiation and slowed progression in IDH2/SRSF2 double-mutant HL-60 xenografts, not a clinical trial. The separate cBioPortal estimate uses age at diagnosis ≥70 and unique mutation-profiled patients; accessed 10 September 2026. Clinical frequency depends on the cohort, measurement, and analysis.
Read the Nature paper ↗