Abstract
We discuss the clinical characteristics and prognostic significance of adult individuals with PTPN11 mutations who have developed acute myeloid leukemia (AML) (none acute promyelocytic leukemia). Next generation sequencing and Sanger sequencing were used to detect 51 gene mutations, and multiplex-PCR was used to detect 41 fusion genes from 232 de novo adult AML patients retrospectively. About 7.76% patients harbored PTPN11 mutations, 20 PTPN11 alterations were identified, all of which were missense mutations in the N-SH2 (n = 16) and PTP (n = 4) domains located in exon 3. Patients with PTPN11 mut had significantly higher platelet counts and hemoglobin levels (p < 0.001), which were mainly detected in M5 (n = 12, 66.67%, p < 0.001) subtype. Patients with MLL-AF6 positive showed a higher frequency of PTPN11 mut (p = 0.018) in the 118 AML cases. PTPN11 mut were accompanied by other mutations, which were NPM1 (44.44%), DNMT3A (38.89%), FLT3 (38.89%), and NRAS (17.2%). PTPN11 mut had a negative impact on the complete remission rate in M5 subtype patients (p < 0.001). However, no statistically significant effect on overall survival (OS) with PTPN11 mut patients in the whole cohort and age group (p > 0.05) was observed. Further analysis revealed no significant difference in OS among NPM1 mut/PTPN11 mut, NPM1 mut/PTPN11 wt, DNMT3A mut/PTPN11 mut, and DNMT3A mut/PTPN11 wt patients (p > 0.05). Multivariate analysis showed the proportion of bone marrow blasts ≥65.4% was a factor significantly affecting OS in PTPN11 mut patients (p = 0.043).
1 Introduction
Acute myeloid leukemia (AML) is a clonal malignant proliferative disease of primitive cells in the hematopoietic system, and whole-genome sequencing has revealed the complexity and high heterogeneity of AML [1]. Previous studies have indicated that approximately 86% of AML patients carry two or more gene mutations [2]. Next-generation sequencing (NGS) technology has played a pivotal role in molecular diagnostics and is increasingly being utilized in the field of hematological malignancies, particularly in the detection of gene mutations in AML patients [3,4]. NGS has led to the discovery of a growing number of AML-associated gene mutations, such as FLT3, TP53, RUNX1, and so on [2]. High throughput, high sensitivity, and low cost of this technology make it a valuable tool for examining the molecular pathogenesis of hematological malignancy, assisting in clinical diagnosis and therapy, and facilitating the integration of precision medicine [3,4]. AML-associated gene mutations have become crucial determinants for AML diagnosis, risk stratification, and selection of treatment strategies [5]. However, the clinical relevance of some genes in AML is still unclear and requires exploration of their clinical characteristics and prognostic significance. This will be advantageous for gaining a deeper understanding of the biological characteristic in AML, identifying potential therapeutic targets, and ultimately improving patient prognosis.
The PTPN11 gene, identified as the first oncogene encoding a protein tyrosine phosphatase, has been found in numerous tissues and cells [6]. The PTPN11 gene, located on chromosome 12q24, serves as a crucial regulatory factor in the RAS signaling pathway [7,8]. It comprises exons 1–16 and encodes a non-receptor protein tyrosine kinase called SHP2. SHP2 has been discovered to play a key role in the development of normal hematopoietic cells [7,8]. Research has demonstrated that SHP2 promotes the signaling cascade of the ERK pathway, while inhibiting stem cell self-renewal and differentiation in the JAK/STAT3 pathway [6]. In cytokine-dependent hematopoietic cell lineages, SHP2 has been proven to be involved in signal transduction pathways triggered by interleukin-6 (IL-6), interleukin 3/granulocyte-macrophage colony-stimulating factor (GM-CSF), leukemia inhibitory factor, and other factors [9–11]. Furthermore, SHP2 augments the robustness and fidelity of IL-6-induced JAK/STAT signaling [11].
Mutations in the PTPN11 gene are associated with various developmental disorders, hematologic malignancies, and solid tumors, playing distinct biological roles in different mechanisms of cancer development [12,13]. Through the PI3K/AKT/GSK3β signaling pathway, PTPN11 has been shown to promote the proliferation of breast cancer cells, making it a potential factor in carcinogenesis or progression [14]. Additionally, mutations in PTPN11 have been found to be responsible for the development of Noonan syndrome (NS) and juvenile myelomonocytic leukemia (JMML) by triggering the RAS/MAPK signaling pathway [15,16]. The mechanism of PTPN11 mutations in adult AML is not well understood and may be related to mutation accumulation or disruption of intracellular signaling pathways [17].
The French–American–British (FAB) classification system categorizes AML into eight subtypes based on the morphology of leukemic cells, spanning from M0 (acute myeloblastic leukemia with minimal differentiation) to M7 (acute megakaryoblastic leukemia), alongside several intermediate subtypes. Notably, the treatment regimen and prognosis differ for the M3 subtype, known as acute promyelocytic leukemia (APL). When compared to other subtypes, APL exhibits a more favorable prognosis [18,19]. According to the literature, PTPN11 mutations are more commonly observed in the M5 subtype of pediatric AML [20,21]. The M5 subtype, also known as monocytic AML, is a specific subtype of AML characterized by the presence of abundant monocytic cells in both the bone marrow and peripheral blood [18]. PTPN11 mutations can also occur in other subtypes of adult AML or other types of leukemia, but they are relatively less common. Papaemmanuil et al. [2] found that PTPN11 mutations occur in less than 5% of adult AML cases, and are more frequently observed in patients with M4/M5 subtypes [22]. However, currently there is no reported evidence from domestic or international studies regarding the prognostic value of M5 subtype in patients with PTPN11 mutations. NPM1 is a protein widely expressed in the nucleolus, and NPM1 mutations are considered the most common genetic alterations in AML. Due to its unique clinical features, gene expression profile, and immunophenotype, NPM1 mutations were recognized as an independent disease subtype in the 2017 WHO classification of myeloid neoplasms and acute leukemia, with favorable prognostic significance [23,24]. Furthermore, a few studies have suggested a correlation between PTPN11 and NPM1 mutations, but the impact of this co-mutation on the prognosis of AML patients remains unclear [25,26]. DNMT3A, also known as DNA methyltransferase 3A, is a protein enzyme associated with genetic modifications. AML patients with mutations in the DNMT3A gene exhibit poor prognosis [27,28]. Additionally, while studies have shown that double mutations in PTPN11 and DNMT3A reduce survival in mice [29], there is no evidence to support a similar impact on clinical outcomes in adult AML patients. The specific role of PTPN11 gene mutations in adult AML remains inadequately explored. Understanding the significance of PTPN11 mutations in adult AML can help identify novel therapeutic targets and develop more effective treatment strategies for adult AML patients.
Therefore, in this study, we conducted a retrospective analysis of gene sequencing data from 232 adult AML (none APL) patients to examine the presence of PTPN11 mutations. We aimed to investigate the clinical characteristics of PTPN11 gene in adult newly diagnosed AML patients from both PTPN11 wild-type and PTPN11 mutant perspectives. Additionally, we analyzed the co-occurrence of PTPN11 mutations with NPM1 and DNMT3A mutations, as well as the impact of M5 subtype on the prognosis of patients with PTPN11 mutations in adult AML.
2 Patients and methods
2.1 Patients and gene sequencing
This was a retrospective analysis of gene mutations in 232 adult de novo AML patients (none APL) admitted to the Affiliated Hospital of Jiangnan University, Changzhou Second People’s Hospital, Wuxi People’s Hospital, and Wuxi Second People’s Hospital from January 2017 to July 2022. The study categorized the patients according to the FAB classification: M0 (n = 3), M1 (n = 23), M2 (n = 83), M4 (n = 50), M5 (n = 59), M6 (n = 3), and 11 cases were unknown. Bone marrow transplant patients were not included in the study. The sample comprised of 125 males and 107 females with a median age of 48 (18–72) years. All patients were diagnosed according to the 2016 revised World Health Organization classification criteria for hematopoietic and lymphoid tissue tumors [30,31].
To assess the gene mutations, 2 mL of bone marrow suspension was taken from each patient at the first diagnosis and extract intracellular DNA, use amplification method for library construction, bridge expansion using Illumina sequencing platform, generate a cluster, and then perform sequencing to detect AML related 51 gene mutations (the average sequencing depth was 1,000×): PTPN11, CBL, NRAS, KRAS, RUNX1, RUNX2, CEBPA, TP53, BCOR, BCOR1, BCORL2, GATA2, SETBP2, FLT3, JAK1, JAK2, JAK3, ABL1, C-KIT, NF1, TET2, WT1, IDH1, IDH2, ASXL1, ASXL2, NPM1, CSF3R, SETD2, KMT2A, EZH2, PHF6, DNMT3A, NOTCH1, U2AF1, ETV6, CSMD1, PDGFRB, MYC, IKZF1, SETBP1, EED, ETNK1, CSF1R, FAT1, KMT2C, APC, MPL, EP300, ARID2, SRSF2, STAG2. Data were read by selecting mutations on exons and removing both synonymous and polymorphic mutations. The first-generation PCR combined with Sanger sequencing was also utilized for supplemental testing of FLT3-ITD, exon 12 of the NPM1 gene, as well as the two functional domains (TAD and BZIP) of CEBPA.
We analyzed the patient’s chromosomal karyotype by extracting 2–4 mL of heparin anticoagulated bone marrow suspension at initial diagnosis, and performing short-term culture for 24 h followed by conventional R-banding technique. We examined an average of 20 metaphase spreads and named the cell karyotype according to the International System for Human Cytogenetic Nomenclature (ISCN 2009). The risk classification was performed based on the chromosomal karyotype analysis results according to the European LeukemiaNet (ELN 2017) risk categories. Furthermore, RNA was extracted from the bone marrow mononuclear cells of patients using TRIZOL method in order to detect 41 common fusion genes. The reaction solution was prepared according to the instructions of the leukemia fusion gene detection kit, and the Thermo Fisher ABI7500 amplification instrument was used for the amplification reaction.
2.2 First induction therapy
In this study, we evaluated the efficacy of Ara-C and IDA/DNR-based chemotherapy in the treatment of AML. Patients aged less than 60 years were treated with a standard dose of Ara-C 100–200 mg/(m2·d) × 7d combined with idarubicin (IDA) 12 mg/(m2·d) × 3d or DNR 60–90 mg/(m2·d) × 3d. Elderly patients aged 60 and above were treated with a standard dose of Ara-C 100 mg/(m2·d) × 7d combined with IDA 8–12 mg/(m2·d) × 3d or DNR 40–60 mg/(m2·d) × 3d. The dose was adjusted according to the patients’ actual condition. All patients underwent one course of chemotherapy followed by a repeat bone marrow aspiration to assess the efficacy. Due to the difference in treatment plan and prognosis between M3 and other types of AML, patients with M3 subtype were excluded in this study.
Complete remission (CR) was calculated after the first induction therapy, and patients were considered to be in CR if they met the following criteria: (i) no clinical manifestations of anemia, hemorrhage, infection, and leukemic cells infiltration; (ii) hemoglobin ≥100 g/L (male) or 90 g/L (female), absolute neutrophil value ≥1.5 × 109/L, platelets ≥100 × 109/L, and no leukemic cells in peripheral blood classification; (iii) bone marrow blasts plus early stage cells (or juvenile cells) <5%, normal red blood cells, and giant cells [32]. No remission (NR) was defined as failure to meet the above criteria in bone marrow, hemogram, and clinical index after treatment.
2.3 Statistical analysis
SPSS software version 25.0 and GraphPad PrismTM 8.02 were employed to analyze the data. While continuous variables were described using medians and ranges, categorical variables were summarized using frequency counts and percentages. The duration from the patient’s diagnosis to the last follow-up or death endpoint was called overall survival (OS). The Log-rank test was employed to assess group differences, and the Kaplan–Meier method was utilized to examine survival data. The data were analyzed using univariate and multivariate Cox proportional hazard regression models. The multivariate analysis to evaluate OS included variables with p < 0.05 in the univariate analysis. Statistical significance was determined by a two-sided p value < 0.05.
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Ethical approval: This research was approved by the Affiliated Hospital of Jiangnan University’s Ethics Committee.
3 Results
3.1 Mutation rate, type, and general characteristics of the PTPN11 mut AML
In a cohort of 232 adult AML patients, mutations in the PTPN11 gene were found in 7.76% (18/232). The median age of PTPN11 mut and PTPN11 wt patients were 46.5 years (19–66) and 48 years (18–72), respectively, with no significant difference (p = 0.7). ten male patients and eight female patients with PTPN11 mutation, 115 male and 99 female patients with wild type (p = 0.882). The white blood cell counts of PTPN11 mut and PTPN11 wt patients at the first diagnosis were 37.08 (2.58–156.1) × 109/L and 12.36 (0.5–350.75) × 109/L, respectively, with no significant difference (p = 0.094). However, hemoglobin and platelet counts of PTPN11 mut patients were significantly higher than those of PTPN11 wt patients (97.5(62–149) g/L vs 88.5(33–142) g/L, p = 0.032), (98(14–713) × 109/L vs 35.5(4–478) × 109/L, p < 0.001). No significant difference in bone marrow blasts was observed between the two groups (63.8 (30–95)% vs 55 (6–99.5)%, p = 0.052) (Table 1).
Eighteen PTPN11 gene mutation and clinical index in AML patients
| Case no./sex/age (year) | WBC (×109/L) | HB (g/L) | PLT (×109/L) | FAB | Karyotype | PTPN1 mut a.a.change |
|---|---|---|---|---|---|---|
| 1/Male/48 | 11.9 | 94 | 713 | M5 | 46, XY | G503A |
| 2/Female/53 | 63.46 | 76 | 33 | M5 | 45, XX, −7,9q- | E76G |
| 3/Female/19 | 156.1 | 90 | 303 | M5 | 46, XX | A72P |
| 4/Male/21 | 76.24 | 110 | 92 | M4 | 46, XY | T73I |
| 5/Female/22 | 25.5 | 80 | 51 | M2 | 46, XX | D61N |
| 6/Female/27 | 2.58 | 96 | 69 | M5 | 46, XX | E76Q |
| 7/Male/32 | 3.08 | 111 | 149 | M5 | 46, XY | T59A |
| 8/Male/33 | 34.16 | 62 | 59 | M5 | 45, XY, Inv(3) (q21q26), −7 | D61V |
| 9/Male/38 | 9.4 | 109 | 272 | M5 | 46, XY, t (9;21) (q21; q22) | S502L |
| 10/Male/38 | 89.19 | 101 | 14 | M1 | 46, XY, Del(9) (q13;q22) | A72T |
| 11/Female/45 | 62.77 | 95 | 332 | M4 | 46, XX | A72T |
| 12/Female/55 | 2.67 | 116 | 102 | M2 | 48, XX, +8, Inv(16) (p13;q22) | V45L |
| 13/Male/56 | 14.12 | 149 | 112 | M5 | 47, XY, +8, Inv(9) (p11q22) | F285S |
| 14/Male/56 | 86.0 | 106 | 119 | M5 | 46, XY | G503A |
| 15/Male/56 | 41.23 | 146 | 85 | M0 | 46, XY, t(6,11) | E76K |
| 16/Female/63 | 64.67 | 77 | 33 | M5 | 44, XX, t(2,8) (q35;q13), –21 | N58Y, E76K, E76G |
| 17/Female/65 | 40.0 | 99 | 94 | M5 | 47, XX, +21 | G60R |
| 18/Male/66 | 5.9 | 84 | 190 | M5 | 46, XY | Q79R |
WBC, white blood cell count; HB, hemoglobin; PLT, platelet; FAB, French–American–British classification systems.
In 18 PTPN11 mut patients, there were 20 mutation sites detected in exons 3, 8, and 13, and all of which were missense mutations. These included exon 3 (n = 16, 1 with A72P, 2 with A72T, 1 with D61N, 1 with D61V, 2 with E69G, 2 with E69K, 1 with E69Q, 1 with G60R, 1 with N58Y, 1 with Q79R, 1 with T59A, 1 with T73I, 1 with V45L), exon 8 (n = 1, 1 with F285S), and exon 13 (n = 3, 2 with G503A, 1 with S502L).The N-SH2 and PTP structural domains, respectively, had 16 and 4 mutant sites, and were mainly concentrated in exon 3. No.16 patient had three mutant sites, N58Y, E76K, and E76G mutations in exon 3 (Figure 1).
Schematic of PTPN11 mutation location found in AML patients.
3.2 FAB subtypes of PTPN11 mutAML
Among all patients, the rate of PTPN11 mutations was notably higher in M2, M4, and M5 subtypes than in other subtypes (Table 2). In particular, PTPN11 mutations occurred more frequently in patients with M5 subtype (p < 0.001). Out of the 18 PTPN11 mut patients, 11.1% (n = 2) and 66.67% (n = 12) were found in M2 and M5, respectively, whereas 5.56% (n = 3) and 5.56% (n = 1) were observed in M0 and M1, no PTPN11 mutations were found in the remaining M6 and M7 subtypes. The status of the remaining 11 patients was unknown.
Clinical features of PTPN11 mut and PTPN11 wt
| Variable | Total (n = 232) | PTPN11 mut (n = 18) | PTPN11 wt (n = 214) | p |
|---|---|---|---|---|
| Sex | ||||
| Male, n(%) | 125(53.9%) | 10(10/18, 55.6%) | 115(53.7%) | 0.882 |
| Female, n(%) | 107(46.1%) | 8(8/18, 44.4%) | 99(46.3%) | |
| Age (year) | ||||
| Median (range) | 48(18–72) | 46.5(19–66) | 48(18–72) | 0.7 |
| WBC (×10 9 /L) | ||||
| Median (range) | 13.8(0.5–350.75) | 37.08(2.58–156.1) | 12.36(0.5–350.75) | 0.094 |
| Hb (g/L) | ||||
| Median (range) | 90(33,149) | 97.5(62–149) | 88.5(33–142) | 0.032 |
| PLT (×10 9 /L) | ||||
| Median (range) | 38(4–713) | 98(14–713) | 35.5(4–478) | <0.001 |
| BM blasts (%) | ||||
| Median (range) | 55.75(6–99.5) | 63.8(30–95) | 55(6–99.5) | 0.052 |
| Cytogenetic karyotype | ||||
| Normal, n(n/N, %) | 134 | 9 | 125 | 0.489 |
| Abnormal, n(n/N, %) | 88 | 9 | 79 | 0.273 |
| NA | 10 | 0 | 10 | |
| FAB subtype | ||||
| M0 | 3(1.29%) | 1(5.56%) | 2(0.93%) | 0.096 |
| M1 | 23(9.91%) | 1(5.56%) | 22(10.28%) | 0.52 |
| M2 | 83(35.78%) | 2(11.11%) | 81(37.85%) | 0.022 |
| M4 | 50(21.55%) | 2(11.11%) | 48(22.43%) | 0.263 |
| M5 | 59(27.57%) | 12(66.67%) | 47(21.96%) | <0.001 |
| M6 | 3(1.29%) | 0 | 3(1.40%) | 0.614 |
| Undetermined | 11(4.74%) | 0 | 11(5.14%) | 0.325 |
| Fusion gene | ||||
| Negative | 169(72.84%) | 14(77.78%) | 155(72.43%) | 0.626 |
| Positive | 53(22.84%) | 4(22.22%) | 49(22.90%) | 0.948 |
| AML1-ETO | 20(8.62%) | 0 | 20(9.35%) | 0.176 |
| MLL-AF6 | 6(2.59%) | 2(11.11%) | 4(1.87%) | 0.018 |
| MLL-AF9 | 2(0.86%) | 0 | 2(0.93%) | 0.681 |
| MLL-AF10 | 2(0.86%) | 1(5.56%) | 1(0.47%) | 0.374 |
| CBFβ-MYH11 | 13(5.6%) | 1(5.56%) | 12(5.61%) | 0.933 |
| Other | 10(43.1%) | 0 | 10(4.67%) | 0.350 |
| NA | 10(43.1%) | 0 | 10(4.47%) | |
| Risk stratification (ELN 2017) | ||||
| Favorable | 75(32.33%) | 4(22.22%) | 71(33.18%) | 0.341 |
| Intermediate | 89(38.36%) | 10(55.56%) | 79(36.92%) | 0.119 |
| Adverse | 68(29.31%) | 4(22.22%) | 64(29.91%) | 0.492 |
WBC, white blood cell count; HB, hemoglobin; PLT, platelet; BM blasts, bone marrow blasts; FAB, French–American–British classification systems; NA, not available.
3.3 Chromosomal karyotype in PTPN11 mutAML
Among the 222 cases tested for karyotype, 134 had normal karyotypes and 88 had abnormal karyotypes, including one case of complex karyotype. The incidence of PTPN11 mutations in normal karyotypes was 6.72% (9/134), and in abnormal karyotypes was 10.23% (9/88). Cytogenetic risk stratification revealed no statistically significant difference in the distribution of PTPN11 mut among the favorable-risk (n = 4), intermediate-risk (n = 10), and adverse-risk (n = 4) groups (p > 0.05) (Table 2, Figure 2(a)).
(a) Comparison of the karyotype subgroups of AML patients with PTPN11 mut and PTPN11 wt and (b) comparison of fusion genes the of AML patients with PTPN11 mut and PTPN11 wt.
3.4 Fusion genes in PTPN11 mut AML
In this study, a total of 222 cases were examined for available fusion genes, of which 76.13% (169/222) tested negative and 23.87% (53/222) tested positive. All 18 PTPN11 mut patients underwent validated fusion gene testing, of which 77.78% (14/18) tested negative and 22.22% (4/18) tested positive. Specifically, MLL-AF6, MLL-AF10, and CBFβ-MYH11 accounted for 11.11% (2/18), 5.56% (1/18), and 5.56% (1/18), respectively. Of the 204 PTPN11 wt patients, 155 tested negative and 49 tested positive, yielding a positive rate of 24.02% (49/204). The difference between the two groups was not statistically significant (p > 0.05). However, AML patients with MLL-AF6 positive had a higher incidence of PTPN11 mutation (p = 0.018) (Table 2, Figure 2(b)).
3.5 Mutations in the PTPN11 and co-occurring genes
In our study, we analyzed the oncogene mutations in adult AML patients (Figure 3(a)), focusing on the PTPN11 wt and PTPN11 mut groups. Among PTPN11 wt patients, the top three genes were FLT3 (23.7%, 55/232), CEBPA (21.55%, 50/232), and NPM1 (18.97%, 44/232), followed by TET2 (15.95%, 37/232), DNMT3A (15.52%, 36/232), NRAS (13.36%, 31/232), WT1 (12.07%, 28/232), and IDH2 (11.64%, 27/232). In the PTPN11 mut group, the most frequent co-mutated genes were NPM1, DNMT3A, FLT3, NRAS, RUNX1, IDH2, TET2, KRAS, and BCORL1. Interestingly, 88.89% of the PTPN11 mut patients had co-existing mutations (Figure 3(c)), with NPM1 (44.44%, 8/18), DNMT3A (38.89%, 7/18), and FLT3 (38.89%, 7/18) being the most frequent. Five PTPN11 mut patients were simultaneously mutated in NPM1 and DNMT3A; however, no PTPN11 mutations were found to be co-mutated with KMT2D and CSF3R genes (Table S1).
Distribution and functional classification of co-existing mutation genes: (a) comparison of the number of mutations with PTPN11 mut and PTPN11 wt, (b) comparison of the number of mutations in functional genes with PTPN11 mut and PTPN11 wt, and (c) PTPN11 mutation with co-existing mutation genes in 18 patients (each small grid represents a patient).
In addition, 18 patients with PTPN11 mutations were identified, of which two had a single mutation, four had a double mutation, one had a triple mutation, five had a quadra mutation, and six had greater or equal to penta mutations. The frequency of gene mutation was 3.56 times. We functionally classified the genes in all patients and found that the most common co-mutations were those involved in the RAS Signaling Pathway (88.89%, 16/18), followed by Epigenetic Regulators (66.67%, 12/18), Transcription Factors (16.67%, 3/18), Spliceosomes (5.56%, 1/18), and no Oncogenes or Adhesion protein-related genes. NPM1 was a separate category with eight cases (44.44%, 8/18). In terms of PTPN11 wt patients, the most distributed functional genes were RAS Signaling Pathway related genes (75.23%, 161/214), followed by Epigenetic Regulators (62.15%, 133/214), Transcription Factors (45.79%, 98/214), Chromatin Modifiers (32.24%, 69/214), Oncogenes (21.03%, 45/214), NPM1 (20.56%, 44/214), Spliceosomes (10.28%, 22/214), and Adhesion Proteins (1.87%, 4/214) (Figure 3(b)).
3.6 Response to first induction therapy
We conducted a study to investigate the CR in 217 AML patients, of which 151 achieved CR and 10 cases had PTPN11 mutations. Among 66 patients who failed to achieve CR, 8 had PTPN11 mutations. The CR rate between patients with and without PTPN11 mutation did not show a statistically significant difference (55.56% vs 65.89%, p = 0.378). We further divided the patients into two age groups: <60 years old and ≥60 years old. In the <60 years old group (n = 194), 132 achieved CR, including 12 with PTPN11 mutation, while 6% (3/50) of the PTPN11 mutation patients failed to achieve CR. The CR rate between PTPN11 mut and PTPN11 wt with no CR showed no statistically significant difference (80% vs 67.04%, p = 0.395). In the ≥60 years old group (n = 38), 22 achieved CR, including one with PTPN11 mutation, and 13 failed to achieve CR, two of which were PTPN11 mutation. Similarly, the CR rate between PTPN11 mut and PTPN11 wt showed no statistically significant difference (33.33% vs 60%, p = 0.562) (Table 3).
Univariable outcome analyses according to PTPN11 mutation status
| Entire cohort clinical endpoint | Total (n = 232) | PTPN11 mut (n = 18) | PTPN11 wt (n = 214) | p |
|---|---|---|---|---|
| CR, n(%) | 151(65.09%) | 10(55.56%) | 141(65.89%) | 0.378 |
| NR, n(%) | 66(28.45%) | 8(44.44%) | 58(27.1%) | 0.118 |
| NA, n(%) | 15(6.47%) | 0 | 15(7.01%) | |
| OS | ||||
| Median, mo (95% CI) | 43(30.6–35.29) | 20.0(18.65–36.57) | 43(30.95–35.84) | 0.2 |
| 1-year OS (%) | 187(80.6) | 14(77.78) | 173(80.84) | |
| 3-year OS (%) | 123(53.01) | 7(38.89) | 116(54.21) | |
| 4.5-year OS (%) | 9(3.88) | 1(5.56) | 8(3.74) | |
| Younger adults Clinical endpoint (18 years ≤ age < 60 years) | Total (n = 194) | PTPN11 mut (n = 15) | PTPN11 wt (n = 179) | p |
| CR, n(%) | 132(68.04) | 12(80) | 120(67.04) | 0.395 |
| NR, n(%) | 50(25.77) | 3(20) | 47(26.26) | 0.764 |
| NA, n(%) | 12(6.19) | 0 | 12(6.7) | |
| OS | ||||
| Median, mo (95% CI) | 44(31.8–36.82) | 20(19.95–39.92) | 44(32.08–37.29) | 0.319 |
| 1-year OS (%) | 162(83.51) | 12(80) | 150(83.8) | |
| 3-year OS (%) | 110(56.7) | 7(46.67) | 103(57.54) | |
| 4.5-year OS (%) | 9(4.64) | 1(6.67) | 8(4.47) | |
| Older adults Clinical endpoint (age ≥ 60 years) | Total (n = 38) | PTPN11 mut (n = 3) | PTPN11 wt (n = 35) | p |
| CR, n(%) | 22(57.89) | 1(33.33) | 21(60) | 0.562 |
| NR, n(%) | 13(34.21) | 2(66.67) | 11(31.43) | 0.265 |
| NA, n(%) | 3(7.89) | 0 | 3(8.57) | |
| OS | ||||
| Median, mo (95% CI) | 22(19.63–32.21) | 15(22.56–54.56) | 26(20.12–33.42) | 0.401 |
| 1-year OS (%) | 25(65.79) | 2(66.67) | 23(65.71) | |
| 3-year OS (%) | 13(34.21) | 0 | 13(37.14) | |
| 4.5-year OS (%) | 0 | 0 | 0 | |
| M5 adults clinical endpoint | Total (n = 61) | PTPN11 mut (n = 12) | PTPN11 wt (n = 49) | p |
| CR, n(%) | 49(80.33) | 8(66.67) | 41(83.67) | <0.001 |
| NR, n(%) | 10(16.39) | 4(33.33) | 6(12.24) | 0.096 |
| NA, n(%) | 2(3.28) | 0 | 2(4.08) | |
| OS | ||||
| Median, mo (95% CI) | 32(26.92–36.07) | 19.5(14.05–38.12) | 33(27.78–37.85) | 0.305 |
| 1-year OS (%) | 47(77.05) | 9(75) | 38(77.55) | |
| 3-year OS (%) | 28(45.9) | 4(33.33) | 24(48.98) | |
| 4.5-year OS (%) | 1(1.64) | 1(8.33) | 0 | |
CR, first induction therapy complete remission; NR, no remission; NA, not available; mo, months; OS, overall survival; p, p-value.
3.7 Survival analysis
The median OS was 43 (95% CI: 30.6–35.29) months in all patients. There was no statistically significant difference between PTPN11 mut and PTPN11 wt patients (20 months, 95% CI: 18.65–36.57 vs 43 months, 95% CI: 30.95–35.84, p > 0.05) (Figure 4(a)). We analyzed the OS for the different groups of patients at 1, 3, and 4.5 years. Among all AML patients, 1-year OS was found to be 80.6% (187/232) and 6.03% (14/232) were PTPN11 mut patients. Three-year OS was 53.01%, of which 3.03% (7/232) of patients were with PTPN11 mutations. 3.88% (9/232) of AML patients surviving for 4.5 years, PTPN11 mut patients were only one. The median OS in 194 younger AML patients (18 years ≤ age < 60 years) was 44 months (95% CI: 31.8–36.82). Compared with PTPN11 mut and PTPN11 wt patients, the difference of OS was not significant (20 months, 95% CI: 19.95–39.92 vs 44 months, 95% CI: 32.08–37.29, p > 0.05) (Figure 4(b)). 83.51% (162/194) of AML patients had 1-year OS, PTPN11 mut patients were 6.19% (12/194). 56.7% (110/232) of patients with 3-year OS, and 3.61% (7/194) PTPN11 mut patients achieved 3-year OS. 4.64% (9/194) of AML patients obtained 4.5-year OS, while only one patient with PTPN11 mutation, less than PTPN11 wt patients (n = 8). 38 cases of older AML patients (age ≥ 60 years), the OS was 22 months (95% CI: 19.63–32.21). There was no significant difference between PTPN11 mut and PTPN11 wt patients (15 months, 95% CI: 22.56–54.56 vs 26 months, 95% CI: 20.12–33.42, p > 0.05) (Figure 4(c)). The 1-year OS and 3-year OS of the older group were, respectively, 65.79% (25/38) and 34.21% (13/38), while no AML patients with 4.5-year OS were identified. There was one case that achieved 1-year OS with PTPN11 mut significantly less than PTPN11 wt patients (n = 23). No PTPN11 mut patients were found with 3-year OS and 4.5-year OS (Table 3).
Influence of mutations in PTPN11 on survival: (a) Kaplan–Meier estimates of OS, (b) younger adult patients, (c) older adult patients, (d) NPM1 mut/PTPN11 mut, NPM1 mut/PTPN11 wt, (e) DNMT3A mut/PTPN11 mut, DNMT3A mut/PTPN11 wt, and (f) M5/PTPN11 mut, M5/PTPN11 wt with adult de novo AML.
We also performed a comparative analysis of OS between NPM1 mut/PTPN11 mut and NPM1 mut/PTPN11 wt, and finally showed that the median OS was not statistically different between the two groups (15 months vs 45 months, p = 0.112) (Figure 4(d)). DNMT3A mut/PTPN11 mut and DNMT3A mut/PTPN11 wt were also analyzed, the median OS was found to be with no statistically significant difference (15 months vs 45 months, p = 0.268) (Figure 4(e)).
In a univariate analysis of adult de novo PTPN11 mutation patients, platelet count ≥100 × 109/L, bone marrow blasts ratio ≥65.4%, and co-existence with DNMT3A or IDH2 mutations were found to influence survival (p < 0.05) (Table 4).
Univariate analysis of the OS analysis in adult AML patients with PTPN11 mutation
| Variables | χ 2 | p |
|---|---|---|
| Sex (male vs female) | 0 | 0.989 |
| Age (18–60 vs ≥60 years) | 2.301 | 0.129 |
| WBC (<50 vs ≥50 × 109/L) | 0 | 0.983 |
| HB (<110 vs ≥110 g/L) | 0.477 | 0.490 |
| PLT (<100 vs ≥100 × 109/L) | 1.716 | 0.019 |
| BM blasts (<65.4 vs ≥65.4%) | 4.938 | 0.026 |
| Cytogenetic karyotype (normal vs abnormal) | 3.805 | 0.051 |
| FAB subtype (n [%]) | 0.482 | 0.975 |
| M0 | 0.099 | 0.753 |
| M1 | 0.027 | 0.87 |
| M2 | 0.12 | 0.729 |
| M4 | 1.498 | 0.221 |
| M5 | 0.017 | 0.895 |
| Fusion gene | 0 | 0.992 |
| MLL-AF6 (positive vs negative) | 0.511 | 0.475 |
| MLL-AF10 (positive vs negative) | 0.099 | 0.753 |
| CBFβ-MYH11 (positive vs negative) | 2.503 | 0.114 |
| Risk stratification (adverse vs favorable/intermediate) | 1.798 | 0.18 |
| CR (yes vs no) | 0.187 | 0.665 |
| NPM1 (mutated vs wild type) | 0.645 | 0.422 |
| DNMT3A (mutated vs wild type) | 4.126 | 0.042 |
| FLT3 (mutated vs wild type) | 0.124 | 0.725 |
| NRAS (mutated vs wild type) | 0.373 | 0.541 |
| KRAS (mutated vs wild type) | 0.124 | 0.725 |
| RUNX1 (mutated vs wild type) | 0.288 | 0.591 |
| IDH2 (mutated vs wild type) | 4.985 | 0.026 |
| TET2 (mutated vs wild type) | 0.122 | 0.727 |
WBC, white blood cell; HB, hemoglobin; PLT, platelet; CR, first induction therapy complete remission; p, p-value.
Multivariate Cox proportional hazard regression model was conducted with survival as the outcome variable (no = 0, yes = 1), incorporating significant factors from the univariate analysis as predictors. These factors included platelet count (<100 × 109/L = 0, ≥100 × 109/L = 1), bone marrow blast percentage (<65.4% = 0, ≥65.4% = 1), DNMT3A mutation status (wild type = 0, mutated = 1), and IDH2 mutation status (wild type = 0, mutated = 1). The result revealed that bone marrow blasts percentage ≥65.4% was regarded as an independent predictor of prognosis (p < 0.05) (Table 5).
Multivariate analysis for OS in PTPN11 mutation
| Variables | HR (95% CI) | p |
|---|---|---|
| PLT (<100 vs ≥100 × 109/L) | 0.555 (0.211–1.458) | 0.232 |
| BM blasts (<65.4 vs ≥65.4%) | 3.192 (1.038–9.814) | 0.043 |
| DNMT3A (mutated vs wild type) | 0.443 (0.144–1.369) | 0.157 |
| IDH2 (mutated vs wild type) | 0.334 (0.057–1.950) | 0.223 |
OS, overall survival; HR, hazard ratio; CI, confidence interval; p, p-value.
3.8 Outcome of PTPN11 mutation with M5 subtypes
In our study, we found that the FAB typing of patients with PTPN11 mutation mostly showed M5 subtype (p < 0.05), so 61 patients with M5 subtype were further analyzed. Among them, 19.67% (n = 12, 12/61) had PTPN11 mut patients and 80.33% (n = 49, 49/61) had PTPN11 wt patients. The CR rate was lower in PTPN11 mut patients than in wild-type patients (66.67%, 8/12 vs 83.67%, 41/49, p < 0.001). Regarding OS with the M5 subtype patients, there was no statistically significant difference between PTPN11 mut patients and PTPN11 wt patients (19.5 months, 95% CI: 14.05–38.12 vs 33 months 95% CI: 27.78–37.85, p > 0.05). 77.05% (47/61) patients had 1-year OS, with 75% (9/12) of PTPN11 mut patients and 77.55% (38/49) of wild-type patients. Among all M5 subtypes, 3-year OS was 33.33% (4/12) and 48.98% (24/49) for PTPN11 mutant patients and wild-type patients, respectively. 8.33% (1/12) PTPN11 mut patients had 4.5-year OS while PTPN11 wt patients had none (Table 4, Figure 4(f)).
4 Discussion
This study revealed a mutation rate of 7.76% in the PTPN11 gene among AML patients (none APL). The majority of these mutations were observed in the M5 subtype according to FAB classification. Additionally, the PTPN11 mutations often co-existed with NPM1 and DNMT3A mutations. However, no significant impact on prognosis was observed as a result of these mutations. In M5 subtype AML patients, PTPN11 mutations do not affect the OS of the patients. Besides, a bone marrow blast percentage ≥65.4% was identified as an independent factor influencing the OS of patients with PTPN11 mutations. The innovation of this study lies in the grouping of AML patients into PTPN11 mut and PTPN11 wt groups, allowing for a comparison of the clinical characteristics between these two groups in adult AML (none APL) patients. In addition, the analysis of the co-occurrence of PTPN11 mutations with NPM1 and DNMT3A mutations, as well as the impact of the M5 subtype, on the prognosis of adult AML patients was performed. This research has clinical significance as it contributes to a better understanding of adult AML, improves prognostic assessment, and enhances OS outcomes for patients.
The PTPN11 gene encodes the Non-Receptor Tyrosine Kinase Protein SHP2 which is involved in key signaling functions in normal hematopoiesis, such as proliferation, differentiation, and apoptosis [7]. The molecular structure of SHP2 consists of two SH2 domains at the N-terminal and the PTP activity region at the C-terminal [33]. Studies have shown that mutations in the N-SH2/PTP domain can lead to leukemic transformation by up-regulating SHP2 activity and inducing hypersensitivity to GM-CSF, as well as over-activating the RAS signaling axis [34].
This study aimed to explore the clinical characteristics of adult PTPN11 gene mutation and its impact on the prognosis of adult AML patients. It has been found that PTPN11 mutations are not limited to adult AML, but are also associated with a range of hematological malignancies, such as JMML, childhood AML, myelodysplastic syndromes, and acute B-lymphocytic leukemia [21,35,36]. In addition, PTPN11 mutations have also been linked to the occurrence of solid tumors (e.g., carcinoma of the lungs, hepatic cell carcinoma, breast, ovarian, gastric, and prostate cancers) [12] and NS [37]. Furthermore, the PTPN11 gene has been identified as a drug target for the intrinsic and acquired drug resistance of cancer drugs, which has important implications for clinical treatment [38].
The incidence of PTPN11 mutations in adult AML patients in our study was 7.76%, comparable to the results from previous studies [26,39]. Of the 18 patients with PTPN11 mutations, 20 different mutation sites were identified, all of which were missense mutations. The majority (16/20) of mutation sites were located in the N-SH2 structural domain encoded by exon 3, with A72T, E69G, and E69K being the most frequent. G503 was found to be more frequent in exon 13, which is consistent with other research on AML [25,40]. The frequency of mutations in exons 8 and 13 was lower than that of N-SH2, at 20.6% (22/107) and 17.8% (19/107), respectively [37]. This suggested that the PTPN11 mutation in adult AML may be variable in terms of mutational sites.
In our study, PTPN11 mut and PTPN11 wt patients were compared in terms of white blood cell, hemoglobin, and platelet counts. The results showed that there was no statistically significant difference in white blood cell counts between the two groups (37.08 × 109/L vs 12.36 × 109/L, p > 0.05). However, PTPN11 mut patients had significantly higher hemoglobin levels than PTPN11 wt patients (97.5 g/L vs 88.5 g/L, p = 0.032). Additionally, platelet counts were significantly higher in PTPN11 mut patients than in PTPN11 wt patients (35.5 × 109/L vs 98 × 109/L, p < 0.001), which was in agreement with the former studies [26,41].There was no statistically significant difference in terms of gender, age, and bone marrow blasts between the two groups (p > 0.05). Moreover, the PTPN11 mutation was mainly detected in the M5 subtype of childhood AML [21], which is consistent with previous findings. These findings indicate that the PTPN11 mutation might be related to monocyte differentiation.
Our study showed that the median age of adult AML patients with PTPN11 mut and PTPN11 wt did not differ significantly (46.5(19–66) years vs 48(18–72) years, p > 0.05), which was consistent with previous research [26,41]. Moreover, the PTPN11 mutation in this study occurred mostly in the normal karyotype, and notably, one case of complex karyotype was found in PTPN11 mutation with an incidence of 5.56% [26]. This finding was in line with previous studies that identified one PTPN11 mutation associated with inv(3) (q21q26), which was associated with a marker of poor prognosis in AML patients concerning future malignant transformation [26,42].
Fusion genes have been identified as specific molecular markers of acute leukemia, and PTPN11 mutations have been observed to co-exist with MLL-AML (MLL-AF6, MLL-AF10) and CBFβ-MYH11, which is in accordance with previously reported findings in the literature [43,44]. Furthermore, evidence suggests that the RAS pathway is hyper-activated in childhood AML patients with MLL-AF6 positive, and that PTPN11, as an important regulator of the RAS pathway, may contribute to this activation by causing SHP2 to remain active in the RAS pathway [45]. Thus, a connection between PTPN11 mutation and MLL-AF6 is conceivable, although further confirmation is necessary.
Our study has revealed that PTPN11 mutations are often associated with other genes mutations with a rate lower than 5%, including TP53, CSF3R, and GATA2, which is consistent with the findings of Stasik et al. [39]. Similarly, Alfayez et al. [41] also identified that PTPN11 mutations are susceptible to co-exist with NPM1 and DNMT3A mutations. NPM1 is a protein ubiquitously expressed in the nucleolus and holds favorable prognostic significance [24]. This study demonstrated that, although PTPN11 mutations frequently co-occurred with NPM1 mutations, they did not have an impact on prognosis, which is consistent with the findings of Liu et al. [25]. Patients with DNMT3A gene mutations in AML have been associated with poorer prognosis. Furthermore, DNMT3A is another gene that is prone to co-occur with PTPN11 mutations [27,28]. To investigate this further, we analyzed the OS of AML patients with DNMT3A mut/PTPN11 mut and DNMT3A mut/PTPN11 wt, and found that DNMT3A gene mutation did not have an impact on the prognosis of PTPN11 mut patients (p ＞ 0.05).
Similar to the findings of Swoboda et al., our investigation showed that there was no discernible difference in the CR rate between patients with PTPN11 mut and PTPN11 wt [46]. However, the prognostic value of PTPN11 mutations in AML remains controversial. Alfayez et al. [41] reported that PTPN11 mut patients had lower overall remission rates (ORR) and CR rates than PTPN11 wt patients in de novo AML (67% vs 82%, p = 0.03; 44% vs 71%, p = 0.006), while no influence on ORR and CR was identified between PTPN11 mut and PTPN11 wt patients in refractory relapsing AML. Notably, our results showed that PTPN11 mutations were mainly located in the M5 subtype (p < 0.05). To further investigate the clinical significance of the M5 subtype in PTPN11 mut patients, we separately evaluated the CR and OS of AML patients with the M5 subtype. Consequently, we found that the CR rate of PTPN11 mut patients was lower than PTPN11 wt patients (66.67% vs 82.67%, p < 0.001). This indicates that the response to the first induction therapy in PTPN11 mut patients is associated with the M5 subtype. Moreover, the M5 subtype did not affect the OS of PTPN11 mut patients (p > 0.05). To the best of our knowledge, this is the first investigation into how PTPN11 mutations in the M5 subtype affect clinical outcomes.
Contrary to earlier research, there was no significant difference in median OS between PTPN11 mut and PTPN11 wt in this study (20 months, 95% CI: 19.95–39.92 vs 44 months, 95% CI: 32.08–37.29, p > 0.05) [39]. This discrepancy may be due to the limited sample size, resulting in an undetectable outcome. Additionally, we separated all the patients into two age groups: 18 ≤ y < 60 years and y ≥ 60 years. This finding contrasted those of Fobare et al. [26] and revealed that there was no statistically significant difference in median OS between PTPN11 mut and PTPN11 wt in the 18–60-year-old group (20 months, 95% CI: 19.95–39.92 vs 44 months, 95% CI: 32.08–37.29, p > 0.05). In the ≥60 years group, the difference was still not significant between PTPN11 mut and PTPN11 wt (15 months, 95% CI: 22.56–54.56 vs 26 months, 95% CI: 20.12–33.42, p > 0.05), which was in accordance with the results of Fobare et al. [26].
We sought to identify factors affecting OS in patients with PTPN11 mut associated AML. By analyzing relevant clinical features and concomitant gene mutations, we identified the bone marrow blasts ratio ≥65.4% as an independent prognostic factor, which can change how normally functioning hematopoietic stem cells behave and play a significant part in the genesis of AML [47]. Accordingly, consideration of the bone marrow blasts ratio is paramount in the clinical management of PTPN11 mut associated AML patients.
5 Conclusions
PTPN11 mutations were found to occur in 7.76% of adult de novo AML patients (none APL), all of which were missense mutations, with exon 3 mutations being the most frequent. Patients carrying PTPN11 mutations were more likely to be of the M5 subtype, and had higher hemoglobin and platelet levels, as well as a lower CR rate compared to PTPN11 wt patients. Furthermore, the frequency of PTPN11 mutations was higher in patients with MLL-AF6 positive AML. In addition, PTPN11 mutations were most often present in conjunction with NPM1 and DNMT3A mutations, though these had no prognostic impact. It was discovered that an independent factor affecting OS for PTPN11 mut individuals was the percentage of bone marrow blasts ratio 65.4%. In order to develop a theoretical framework for future clinical prognostic classification and treatment, future research should increase the sample size to further investigate the clinical significance and gene function of PTPN11 mutations.
Acknowledgements
The authors thank all the patients who participated in this study.
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Funding information: Not applicable.
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Author contributions: Li Sheng and Haiying Hua set the study conception and design. Li Sheng and Yajiao Liu collected the data. Yingying Zhu and Jingfen Zhou performed data analysis. All the authors participated in the interpretation of findings from the data analysis. Li Sheng and Yajiao Liu drafted the manuscript. All the authors contributed to the final version of the manuscript.
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Conflict of interest: The authors declare no conflicts of interest.
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Data availability statement: The analyzed data sets generated during the study are available from the corresponding author on reasonable request.
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