Retrospective Study Open Access
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Jul 16, 2024; 12(20): 4121-4129
Published online Jul 16, 2024. doi: 10.12998/wjcc.v12.i20.4121
Transforming growth factor-β1 and vascular endothelial growth factor levels in senile acute myeloid leukemia and correlation with prognosis
Wan Li, Sheng-Yu Ma, Hui-Ying Zhao, Department of Hematology, Suzhou Hospital of Anhui Medical University, Suzhou 234000, Anhui Province, China
ORCID number: Hui-Ying Zhao (0009-0003-7349-5315).
Author contributions: Wan L, Ma SY, and Zhao HY designed the study and were involved in the data acquisition and writing of this article; Wan L and Zhao HY contributed to the analysis of the manuscript; and all authors have read and approved the final manuscript.
Institutional review board statement: This study was approved by the Ethic Committee of Suzhou Hospital of Anhui Medical University (Approval No. C2024003).
Informed consent statement: All patients provided written informed consent for participation in the study.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No additional data are available.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Hui-Ying Zhao, Doctor, Associate Chief Physician, Department of Hematology, Suzhou Hospital of Anhui Medical University, No. 229 Bianhe Middle Road, Suzhou 234000, Anhui Province, China. 18155785701@163.com
Received: March 21, 2024
Revised: April 30, 2024
Accepted: May 17, 2024
Published online: July 16, 2024
Processing time: 101 Days and 15.3 Hours

Abstract
BACKGROUND

Acute myeloid leukemia (AML) is a disease in which immature hematopoietic cells accumulate in the bone marrow and continuously expand, inhibiting hematopoiesis. The treatment and prognosis of this disease have always been unsatisfactory.

AIM

To investigate the correlation between vascular endothelial growth factor (VEGF) and transforming growth factor-β1 (TGFβ1) expression and prognosis in older adults with AML.

METHODS

This study enrolled 80 patients with AML (AML group), including 36 with complete response (AML-CR), 23 with partial response (AML-PR), and 21 with no response (AML-NR). The expression levels of VEGF and TGFβ1 were detected by reverse transcription polymerase chain reaction in bone marrow mononuclear cells isolated from 56 healthy controls. Kaplan-Meier analysis was performed to assess overall survival (OS) and progression- or disease-free survival (DFS). Prognostic risk factors were analyzed using a Cox proportional hazards model.

RESULTS

The AML group showed a VEGF level of 2.68 ± 0.16. VEGF expression was lower in patients with AML-CR than those with AML-PR or AML-NR (P < 0.05). TGFβ1 expression in the AML group was 0.33 ± 0.05. Patients with AML-CR showed a higher TGFβ1 expression than those with AML-PR or AML-NR (P < 0.05). VEGF and TGFβ1 expression in patients with AML was significantly correlated with the counts of leukocytes, platelets, hemoglobin, and peripheral blood immature cells (P < 0.05); Kaplan-Meier survival analysis revealed that patients with high TGFβ1 expression had better OS and DFS than those with low TGFβ1 expression (P < 0.05), whereas patients with low VEGF levels showed better OS and DFS than those with high VEGF levels (P < 0.05). VEGF, TGFβ1, and platelet count were identified by the Cox proportional hazards model as independent risk factors for OS (P < 0.05), while VEGF, TGFβ1, and white blood cell count were independent risk factors for DFS (P < 0.05).

CONCLUSION

Decreased VEGF expression and increased TGFβ1 expression in patients with AML provide valuable references for determining and individualizing clinical treatment strategies.

Key Words: Acute myeloid leukemia; Transforming growth factor-β1; Vascular endothelial growth factor; Expression level; Prognostic correlation

Core Tip: At present, the prognosis and survival of acute myeloid leukemia (AML) remain unsatisfactory. In this paper, vascular endothelial growth factor and transforming growth factor-β1 expression in patients with AML was investigated to fully understand the molecular mechanism of angiogenesis and immunomodulation in AML to enhance treatment strategies for targeted therapy, thereby improving prognosis in patients with AML.



INTRODUCTION

Acute myeloid leukemia (AML) is the abnormal aggregation and proliferation of immature leukemia cells in body organs, which causes impaired hematopoietic function in vivo. It is a highly common hematological malignancy that produces malignant lesions in myeloid progenitors or hematopoietic stem cells, which result in the abnormal proliferation of immature and primitive myeloid cells in the bone marrow and peripheral blood[1]. According to various statistical data, approximately 50% of patients with AML are elderly, with a median age of 68 years and approximately 35% of patients ≥ 75 years[2]. AML mainly presents with hemorrhage, anemia, infection, metabolic abnormalities, and organ infiltration and can be life-threatening with disease progression[3]. In the 20th and early 21st centuries, chemotherapy, immunotherapy, and biotherapy were still the preferred clinical treatments. Studies on disease inheritance and variation have shown that targeted and new chemotherapeutic drugs and regimens are ineffective[4]. Especially elderly patients with declining body function and multiple complications, they cannot tolerate the toxic and other side effects of chemotherapeutic drugs. Therefore, the requirements for the clinical treatment of elderly patients with AML are more stringent[5]. Based on the treatment course for elderly patients with AML, internationally accepted standard-dose chemotherapy, allogeneic hematopoietic stem cell transplantation, and molecularly targeted drugs have become the primary treatment methods[6]. However, although the improvement of chemotherapy regimens and development of new drugs have improved survival[7], early death, short survival, significant adverse reactions, and poor prognosis remain unresolved.

The occurrence, development, and metastasis of tumors depend on neovascularization. Vascular endothelial growth factor (VEGF) induces vascular permeability, thereby promoting angiogenesis and mitosis in vivo and enhancing the proliferation of the vascular endothelium to form new blood vessels. It has a strong effect and induces high permeability. VEGF is the main prognostic indicator reflecting the biological behavior of tumors[8]. Angiogenesis and its regulators are strongly associated with the occurrence, development, and outcomes of hematologic malignancies[9]. Transforming growth factor-β1 (TGF-β1) is a polypeptide cell growth factor that is essential in cell growth[10], proliferation[11], differentiation[12], and apoptosis[13]. Decreased TGFβ1 expression may affect immune system function and increase the susceptibility of patients to infection and other complications[14]. Therefore, studying the changes in VEGF and TGFβ1 expression facilitates an in-depth understanding of the pathogenesis of AML, which could generate new ideas and methods for future treatment. VEGF and TGFβ1 expression in patients with AML were investigated, and their correlation with prognosis and therapeutic efficacy in AML was analyzed to provide data support for subsequent clinical treatment.

MATERIALS AND METHODS
General data

This study enrolled 40 patients with AML (23 male, 17 female) aged > 60 years who visited our hospital between January 2019 and January 2023. The age range was 61-69 years (mean: 65.98 ± 3.81 years). All patients underwent 1-2 cycles of induction therapy followed by 4-6 cycles of consolidation therapy (including at least 3 cycles of medium- and high-dose Ara-C regimen). The patients were grouped according to treatment response: 36 cases with complete response (CR), 23 cases with partial response (PR), and 21 cases with no response (NR). In addition, 56 healthy subjects were included as a healthy control group.

Criteria for patient inclusion and exclusion

Inclusion criteria: (1) Underwent physical, blood, and bone marrow examination and met the AML diagnostic criteria described previously[15]; (2) Aged ≥ 60 years; and (3) Eastern Cooperative Oncology performance status score of 0-2 points. Exclusion criteria: (1) Myelodysplastic syndrome and AML transformed from myeloproliferative tumors; (2) Other malignant tumor(s), or liver and kidney dysfunction; (3) Severe infection; (4) Pregnant, lactating or on the menstrual period; and (5) Mental dysfunction. Elimination criteria: (1) Lack of clinical information; (2) Sudden aggravation during treatment and transfer to other departments for treatment; (3) Subjective willingness of patients to withdraw from this investigation; and (4) Poor compliance during participation in the investigation.

Methods

Isolation of bone marrow mononuclear cells: Lidocaine hydrochloride injection (Shanghai Zhaohui Pharmaceutical Co., Ltd.; SFDA Approval No. H31021071; specifications: 20 mL; 0.4 g) was used for local anesthesia. Bone marrow fluid (400 mL) was collected from the patient’s iliac spine using a bone marrow puncture needle. Cells were then isolated on a 100-grade clean bench as follows: The separation solution was slowly added dropwise to the human lymphocyte separation solution at a ratio of 1:1. The mixture was centrifuged at 2000 r/min for 20 min. The centrifuge was kept in a horizontal position, and then the speed was slowly reduced. After centrifugation, the intermediate interface, the milky white membrane layer (mononuclear cell layer), was slowly removed using a pipette. The cells were washed twice with 0.9% saline and stored at -80 °C until further testing.

TGFβ1 and VEGF expression determined by reverse transcription polymerase chain reaction: The TRIzoI sample of total RNA to be extracted from the environment was removed at -80 °C, and placed on ice for thawing. Chloroform was added at 200 μL after complete thawing, and the mixture was shaken violently for 15 s, then centrifuged at 12000 r/s for 15 min at 4 °C. The supernatant (500 μL) was extracted and transferred into a 1.5-mL EP tube. Isopropanol of the same volume was added and mixed well, and the mixture was placed on ice for 10 min. The mixture was centrifuged at 12000 r/s and 4 °C for 10 min, after which the supernatant was removed, and 1000 μL of 75% ethanol was added for cooling. The mixture was again centrifuged at 12000 r/s and 4 °C for 5 min. The supernatant was removed, the precipitate was dried with filter paper until it was transparent, and 30 μL diethyl pyrocarbonate-treated water was added. The quality of the RNA obtained was evaluated using a Nanodrop spectrophotometer, and cDNA was synthesized by reverse transcription polymerase chain reaction. The reaction system was as follows: 4 μL of 5 × PrimeScript Buffer, 10 μL RNase-free H2O, and 1 μL PrimeScript RT Enzyme Mix. The mixture was first placed in a water bath for 5 min at 37 °C, then in another water bath for 10 s for 85 °C. The final product obtained was stored at -80 °C for later use. The cycle was reversed 30 times at 94 °C for 5 min; 94 °C for 30 s; 56 °C for 30 s; 72 °C for 30 s; and ended at 70 °C for 10 min. The test was performed in replicates for each sample, with GAPDH as the internal reference. VEGF expression 2-ΔΔCt = 2.1 was the cutoff value for gene expression. A TGFβ1 expression 2-ΔΔCt = 0.3 indicates that the gene expression is higher than the low cutoff value (Table 1).

Table 1 Primer sequences.
Genes

Primer sequence
VEGFUpstream primer5’-AACACAGACTCGCGTTGCAA-3’
Downstream primer5’-ACCGCCTCGGCTTGTCA-3’
TGFβ1Upstream primer5’-GAGAAGAACYGCTGCGTGCGG-3’
Downstream primer5’-GCGTGTCCAGGCTCCAAATGT-3’
GAPDHUpstream primer5’-GATGACCTTGCCCACAGCCT-3’
Downstream primer5’-GGGTCATTGATGGCAACAATATC-3’

Clinical efficacy: After 2 months of treatment, the therapeutic efficacy was evaluated by the attending physician. The clinical efficacy was rated as CR, PR, or NR. CR refers to the disappearance of symptoms and signs caused by myeloid leukemia cell infiltration; platelet count (Plt) > 100 × 109 g/L; hemoglobin (Hb) > 90 g/L; bone marrow primitive cells ≤ 5%, and normal peripheral and white blood cell (WBC) classification, megakaryocyte series, and red blood cells. PR features any abnormality in clinical symptoms and peripheral red and WBC classification; bone marrow primitive cells > 5%; and platelet count ≤ 100 × 109 g/L. NR refers to two or more of clinical symptoms, bone marrow primitive cells > 5%, and Plt ≤ 100 × 109 g/L. The critical values of WBC, Hb, lactate dehydrogenase (LDH), and Plt were 10 × 109/L, 80 g/L, 250 U/L and 80 × 109 g/L, respectively. The above indicators were measured in peripheral blood collected for testing.

Quality control and data collection

The medical staff who participated in this study underwent a 4-wk training before performing measurements. After the training, the staff were assessed. Those with an assessment score ≥ 95 were deemed as qualified, whereas those who fail continued to receive the training until they passed the assessment.

Statistical analysis

All data were analyzed using SPSS 26.0. Measurement data were validated for normal distribution using the Kolmogorov-Smirnov test. Normally distributed data were expressed as mean ± SD, with between-group comparisons performed using the independent t-test. Data with a skewed distribution were expressed as median and quartile [M(P25, P75)], and between-group comparisons were performed using the Mann-Whitney U test. Enumeration data are expressed as number and percentage [n (%)] and were analyzed using the χ2 test. Overall survival (OS) and disease-free survival (DFS) were assessed using the Kaplan-Meier analysis. Independent risk factors affecting prognosis were determined using the Cox proportional hazards model. P < 0.05 was considered statistically significant.

RESULTS
VEGF and TGFβ1 expression

The VEGF expression in patients with AML was 2.68 ± 0.16, which was higher than that in healthy controls (P < 0.055). The TGFβ1 expression was 0.33 ± 0.05, which was lower than that in healthy controls (P < 0.05) (Table 2). Taking the ordinate as reference, VEGF expression in healthy controls was lower than that in patients with AML (P < 0.05), whereas TGFβ1 expression was lower in the AML group than that in the control group (P < 0.05) (Figure 1).

Figure 1
Figure 1 Expression levels of vascular endothelial growth factor and transforming growth factor-β1. A: Expression levels of vascular endothelial growth factor; B: Expression levels of transforming growth factor-β1. AML: Acute myeloid leukemia; VEGF: Vascular endothelial growth factor; TGF-β1: Transforming growth factor-β1.
Table 2 Expression levels of vascular endothelial growth factor and transforming growth factor-β1.
Group
Number of cases
VEGF
TGFβ1
AML group802.68 ± 0.160.33 ± 0.05
Healthy control group562.41 ± 0.120.45 ± 0.09
t10.6939.943
P value0.0000.000
Correlation between clinical characteristics and VEGF and TGFβ1 expression

Sex (male, female), age (< 60 years old, ≥ 60 years old), WBC (< 10 × 109/L, ≥ 10 × 109/L), Hb (< 80 g/L, ≥ 80 g/L), LDH (< 250 U/L, ≥ 250 U/L), and peripheral blood blasts (< 80%, ≥ 80%) were used as independent variables, whereas VEGF and TGFβ1 expression levels were used as the dependent variables for correlation analysis. WBC, Hb, and Plt were significantly correlated with VEGF and TGFβ1 expression in patients with AML (P < 0.05) (Table 3).

Table 3 Correlations between clinical characteristics and vascular endothelial growth factor and transforming growth factor-β1 expression in patients with acute myeloid leukemia.
Characteristic
Item
VEGF
χ2
P value
TGFβ1
χ2
P value
Low
High
Low
High
SexMale27300.5490.45929170.4170.518
Female13101915
Age (yr)< 6023290.2440.62221221.4270.232
≥ 6014142314
WBC (× 109/L)< 1014266.0540.01428118.6730.003
≥ 1025151625
Hb (g/L)< 8025165.0310.02516236.0040.014
≥ 8014252813
LDH (U/L)< 25013111.1640.2812192.5070.113
≥ 25023332624
Plt (%)< 8013287.1550.0071874.2460.039
≥ 8024152629
VEGF and TGFβ1 expression in patients with AML with different treatment responses

Significantly better OS and DFS were observed in patients with AML who exhibited high TGFβ1 expression than those with low TGFβ1 expression (P < 0.05). Conversely, patients with low VEGF expression had significantly better OS and DFS than those with high VEGF expression (P < 0.05) (Table 4). Using the mid-coordinate as a reference, VEGF expression was lower and TGFβ1 expression was higher in healthy controls than in patients with AML with different treatment responses (P < 0.05) (Figure 2).

Figure 2
Figure 2 Expression levels of vascular endothelial growth factor and transforming growth factor-β1 in patients with acute myeloid leukemia with different treatment responses and healthy controls. A: Expression levels of vascular endothelial growth factor; B: Expression levels of transforming growth factor-β1. AML: Acute myeloid leukemia; VEGF: Vascular endothelial growth factor; TGF-β1: Transforming growth factor-β1; CR: Complete response; PR: Partial response; NR: No response.
Table 4 Vascular endothelial growth factor and transforming growth factor-β1 expression in patients with acute myeloid leukemia with different treatment responses.
Item
VEGF
TGFβ1
Healthy control (n = 56)2.41 ± 0.120.45 ± 0.09
Complete response (n = 36)2.42 ± 0.10a0.43 ± 0.11a
Partial response (n = 23)2.58 ± 0.13a0.37 ± 0.13a
No response (n = 21)2.67 ± 0.11a0.34 ± 0.09a
t35.92711.439
P value< 0.001< 0.001
Factors influencing the prognosis of patients with AML

Kaplan-Meier survival analysis showed significantly higher OS and DFS in patients with AML with low VEGF expression and high TGFβ1 expression than those with high VEGF expression and low TGFβ1 expression (P < 0.05); Plt, VEGF, and TGFβ1 were identified by multivariate Cox regression analysis as independent risk factors for OS (P < 0.05), whereas WBC, VEGF, and TGFβ1 were identified as independent risk factors for DFS (P < 0.05) (Table 5). The DFS and OS at low VEGF and high TGFβ1 expression were significantly better than those at high VEGF and low TGFβ1 expression (P < 0.05) (Figure 3).

Figure 3
Figure 3 Correlation between disease-free or overall survival rate and transforming growth factor-β1 or vascular endothelial growth factor expression analyzed using the Kaplan-Meier survival curve. A: Correlation between disease-free survival (DFS) rate and vascular endothelial growth factor (VEGF) expression analyzed using the Kaplan-Meier survival curve; B: Correlation between overall survival (OS) rate and VEGF expression analyzed using the Kaplan-Meier survival curve; C: Correlation between disease-free survival rate and transforming growth factor-β1 (TGF-β1) expression analyzed using the Kaplan-Meier survival curve; D: Correlation between OS rate and TGF-β1 expression analyzed using the Kaplan-Meier survival curve. AML: Acute myeloid leukemia; VEGF: Vascular endothelial growth factor; TGF-β1: Transforming growth factor-β1; DFS: Disease-free survival; OS: Overall survival.
Table 5 Factors influencing the prognosis of patients with acute myeloid leukemia.
Item
OS
P value
DFS
P value
HR
95%CI
HR
95%CI
WBC0.3260.19-1.3510.0640.2410.091-0.8290.039
Plt0.5290.134-1.1310.0350.3910.109-0.8360.067
VEGF0.5090.206-1.6410.0190.4150.132-1.7290.034
TGFβ10.4310.221-1.4350.0260.3150.175-1.6350.027
DISCUSSION

AML is mainly caused by excessive proliferation of WBCs in the bone marrow and clonal inhibition of the body’s hematopoietic function, resulting in damage to other organs with disease progression[16]. AML is difficult to treat, given the scarcity and high cost of bone marrow transplantation. Therefore, chemotherapy and biotherapy are commonly administered in clinical practice to mitigate the disease. However, some patients still exhibit poor disease control and even exacerbation, especially elderly patients (> 60 years old), for whom age is the main factor for poor prognosis in AML[17]. The standard 3 + 7 regimen (daunorubicin 60-90 mg/m2 dl-3 and cytarabine 100-200 mg/m2 dl-7) for AML, was followed by sequential maintenance of high-dose cytarabine for 4-6 courses and sequential allogeneic hematopoietic stem cell inhibition with approximately 60%-80% of patients attaining CR with a 5-year survival rate of 30%[18]. However, most older patients with high-risk chromosomes[19], complex karyotype abnormalities[20], and an increased likelihood of high-risk gene mutations are intolerant to the standard regimen. Their immune system would be unable to recover from the drug toxicity during treatment, although the immune system would have been able to handle the treatment of solid tumors. Few relevant studies on the blood system have been conducted, but B, T, and natural killer cells have gradually gained research attention and have been found to play key roles in AML disease progression[21]. Therefore, prolonging survival time, increasing the remission rate, and improving quality of life in AML have become an outstanding concern and pressing research goal.

This study identified a significant correlation between VEGF and TGFβ1 expression with WBC, Hb, and Plt in patients with AML (P < 0.05). This is mainly because VEGF is an important angiogenetic factor that can stimulate the formation of new blood vessels, which thus promotes tumor growth and spread. TGFβ1 is a multifunctional cytokine capable of modulating cell growth, differentiation, migration, and apoptosis[22]. Abnormal expression of VEGF and TGFβ1 enable AML cells to escape immune attack by suppressing the immune response[23].

The occurrence, development, and metastasis of tumors depend on neovascularization. VEGF is a vascular permeability factor that can promote angiogenesis and mitosis in vivo and enhance the proliferation of the vascular endothelium to form new blood vessels. It is potent and exhibits high permeability and is thus the main parameter reflecting the biological behavior of tumors[24]. The oxygen and nutrient supply for angiogenesis comes from the exudative deposition of plasma macromolecules outside blood vessels caused by high VEGF levels, which can also regulate hematopoietic stem cell development and inflammatory cytokine production[25]. Therefore, inhibiting tumor angiogenesis and blocking the nutrient supply for angiogenesis has become a new opportunity for treatment[26]. Chen et al[27] showed that leukemia cells in patients with AML can autonomously secrete VEGF. After combining with VEGFR, the cells promote micro-angiogenesis and cell proliferation in the body, creating a pathway for leukemia cells to metastasize to other organs. Blocking this metastasis pathway can effectively control disease progression and improve the survival of patients during their lifetime. Multivariate Cox regression analysis revealed an association between high VEGF expression and poor survival in AML (P < 0.05), indicating the potential of VEGF as a prognostic predictor in AML. In addition to being a therapeutic target, Song et al[28] found that VEGF expression can also be used as a prognostic indicator for AML. Low level VEGF expression is associated with OS, whereas high VEGF expression indicates a worse prognosis. Standard drug therapy for reducing VEGF levels can reduce the supply of intravascular oxygen and nutrients and avoid vascular endothelial hyperplasia. In turn, drug therapy may alleviate the progression or worsening of AML, which is consistent with our findings. Therefore, VEGF can serve as a biomarker for assessing outcomes in AML and help guide clinical treatment and prognostic evaluation.

Zhao et al[29] reported that TGFβ1 is a multifunctional cytokine involved in various biological processes, including cell growth, differentiation, apoptosis, and the immune response. TGFβ1 can inhibit leukemia cell proliferation by inhibiting cyclin synthesis and promoting apoptosis. TGFβ1 can enhance leukemia cell invasion and metastasis, thereby contributing to disease progression and worse prognosis. According to Stefaniuk et al[30], TGFβ1 can promote leukemia cell motility and adhesion, as well as extracellular matrix degradation and angiogenesis, thereby promoting metastasis in leukemia. By modulating immune responses, TGFβ1 can also facilitate the survival and progression of leukemia cells. TGFβ1 can inhibit T cell activation and proliferation while promoting the expansion and function of regulatory T cells, thereby suppressing antitumor immune responses. TGFβ1 expression is low in patients with AML, which correlates with poor prognosis. Moreno Vanegas and Badar[31] found that low TGFβ1 expression is associated with lower DFS and OS, indicating that TGFβ1 can be used to predict patient outcomes. Therefore, reasonable and effective drug treatments for increasing TGFβ1 levels can effectively alleviate AML activity, enhance immune function, and reduce the inflammatory response, which is consistent with the results of this study. The results of multivariate Cox regression analysis indicated TGFβ1 as an independent risk factor for DFS (P < 0.05). It primarily activated the downstream Smad signaling pathway by binding to its receptor to exert its biological effects[31]. In AML, TGFβ1 can promote the growth and survival of leukemia cells in a Smad-dependent or -independent manner[32]. In addition, Yao et al[33] found that TGFβ1 can also interact with other signaling pathways, such as MAPK and PI3K, to jointly regulate the biological behavior of leukemia cells, which suggest a new treatment direction for patients after tolerance therapy.

CONCLUSION

Understanding the expression of VEGF and TGFβ1 in elderly patients with AML offers insights into the pathogenesis and progression of the disease. Evaluating VEGF and TGFβ1 expression can help clinicians more accurately assess patients’ condition and prognosis. Abnormal VEGF and TGFβ1 expression may indicate rapid disease progression or poor prognosis, whereas changes in the patient’s condition should be closely monitored for the prompt adjustment of the treatment regimen. Therapeutic targets of new drugs and treatment regimens can be developed based on VEGF and TGFβ1 expression. Drugs targeting VEGF can inhibit tumor angiogenesis, thereby reducing nutrient and oxygen supply to tumor cells and inhibiting tumor growth and spread. Drugs that target TGFβ1 can regulate the immune system and enhance its cytotoxicity against tumor cells.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Medicine, research and experimental

Country of origin: China

Peer-review report’s classification

Scientific Quality: Grade C

Novelty: Grade C

Creativity or Innovation: Grade B

Scientific Significance: Grade B

P-Reviewer: Murthy R, United States S-Editor: Wang JJ L-Editor: A P-Editor: Yuan YY

References
1.  Kim S, Yoon SS, Hong J, Shin DY, Koh Y, Byun JM, Kim I. Characterization and Prognosis of Secondary Acute Myeloid Leukemia in an Asian Population: AML With Antecedent Hematological Disease Confers Worst Outcomes, Irrespective of Cytogenetic Risk. Anticancer Res. 2020;40:2917-2924.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Cited by in F6Publishing: 7]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
2.  Lu J, Dong Q, Zhang S, Feng Y, Yang J, Zhao L. Acute myeloid leukemia (AML)-derived mesenchymal stem cells induce chemoresistance and epithelial-mesenchymal transition-like program in AML through IL-6/JAK2/STAT3 signaling. Cancer Sci. 2023;114:3287-3300.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 1]  [Reference Citation Analysis (0)]
3.  Othman J, Meggendorfer M, Tiacci E, Thiede C, Schlenk R, Dillon R, Stasik S, Venanzi A, Bertoli S, Delabesse E, Dumas PY, Pigneux A, Bidet A, Gilkes AF, Thomas I, Voso MT, Rambaldi A, Brunetti L, Perriello VM, Andresen V, Gjertsen BT, Martelli MP, Récher C, Röllig C, Bornhäuser M, Serve H, Müller-Tidow C, Baldus CD, Haferlach T, Russell N, Falini B. Overlapping features of therapy-related and de novo NPM1-mutated AML. Blood. 2023;141:1846-1857.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 15]  [Cited by in F6Publishing: 16]  [Article Influence: 16.0]  [Reference Citation Analysis (0)]
4.  Cao W, Li X, Zhang R, Bian Z, Zhang S, Li L, Xing H, Liu C, Xie X, Jiang Z, Fang X, Wan D, Yu J. Prognostic prediction of novel risk scores (AML-DRG and AML-HCT-CR) in acute myeloid leukemia patients with allogeneic hematopoietic stem cell transplantation. Sci Rep. 2022;12:19024.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
5.  Cao Z, Shu Y, Wang J, Wang C, Feng T, Yang L, Shao J, Zou L. Super enhancers: Pathogenic roles and potential therapeutic targets for acute myeloid leukemia (AML). Genes Dis. 2022;9:1466-1477.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 3]  [Article Influence: 1.5]  [Reference Citation Analysis (0)]
6.  Shimony S, Chen EC. Tri-ing to decipher trisomy AML. Br J Haematol. 2024;204:751-752.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
7.  Chan O, Al Ali N, Tashkandi H, Ellis A, Ball S, Grenet J, Hana C, Deutsch Y, Zhang L, Hussaini M, Song J, Yun S, Talati C, Kuykendall A, Padron E, Walker A, Roboz G, Desai P, Sallman D, Sweet K, Komrokji R, Lancet J. Mutations highly specific for secondary AML are associated with poor outcomes in ELN favorable risk NPM1-mutated AML. Blood Adv. 2024;8:1075-1083.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 4]  [Reference Citation Analysis (0)]
8.  Song Y, Zhuang G, Li J, Zhang M. BAIAP2L2 facilitates the malignancy of prostate cancer (PCa) via VEGF and apoptosis signaling pathways. Genes Genomics. 2021;43:421-432.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 4]  [Article Influence: 1.3]  [Reference Citation Analysis (0)]
9.  Liu L, Liu H, Liu L, Huang Q, Yang C, Cheng P, Ren S, Zhang J, Yu M, Ma X, Song W, Chen L, Zhang H, Chen M, Zhang X. Apicidin confers promising therapeutic effect on acute myeloid leukemia cells via increasing QPCT expression. Cancer Biol Ther. 2023;24:2228497.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 1]  [Reference Citation Analysis (0)]
10.  Syed YY. Perindopril/Indapamide/Amlodipine in Hypertension: A Profile of Its Use. Am J Cardiovasc Drugs. 2022;22:219-230.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
11.  Mohamed Jiffry MZ, Kloss R, Ahmed-Khan M, Carmona-Pires F, Okam N, Weeraddana P, Dharmaratna D, Dandwani M, Moin K. A review of treatment options employed in relapsed/refractory AML. Hematology. 2023;28:2196482.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
12.  Wachter F, Pikman Y. Pathophysiology of Acute Myeloid Leukemia. Acta Haematol. 2024;147:229-246.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Reference Citation Analysis (0)]
13.  de Oliveira Lisboa M, Brofman PRS, Schmid-Braz AT, Rangel-Pozzo A, Mai S. Chromosomal Instability in Acute Myeloid Leukemia. Cancers (Basel). 2021;13.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 5]  [Cited by in F6Publishing: 16]  [Article Influence: 5.3]  [Reference Citation Analysis (0)]
14.  Wang R, Xu P, Chang LL, Zhang SZ, Zhu HH. Targeted therapy in NPM1-mutated AML: Knowns and unknowns. Front Oncol. 2022;12:972606.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 7]  [Reference Citation Analysis (0)]
15.  Cho CH, Cha J. Analysis of neutrophil gelatinase-associated lipocalin, vascular endothelial growth factor, and soluble receptor for advanced glycation end-products in bone marrow supernatant in hematologic malignancies. Clin Biochem. 2020;80:19-24.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 7]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
16.  Zhang J, Qi L, Wang T, An J, Zhou B, Fang Y, Liu Y, Shan M, Hong D, Wu D, Xu Y, Liu T. FEV Maintains Homing and Expansion by Activating ITGA4 Transcription in Primary and Relapsed AML. Front Oncol. 2022;12:890346.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
17.  Huang L, Huang L, Ming X, Wu J, Liu W, Xiao Y. CircNFIX knockdown inhibited AML tumorigenicity by the miR-876-3p/TRIM31 axis. Hematology. 2022;27:1046-1055.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 5]  [Reference Citation Analysis (0)]
18.  Arber DA, Erba HP. Diagnosis and Treatment of Patients With Acute Myeloid Leukemia With Myelodysplasia-Related Changes (AML-MRC). Am J Clin Pathol. 2020;154:731-741.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 7]  [Cited by in F6Publishing: 10]  [Article Influence: 2.5]  [Reference Citation Analysis (0)]
19.  Cluzeau T, Lemoli RM, McCloskey J, Cooper T. Measurable Residual Disease in High-Risk Acute Myeloid Leukemia. Cancers (Basel). 2022;14.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 7]  [Article Influence: 3.5]  [Reference Citation Analysis (0)]
20.  Maffeo B, Panuzzo C, Moraca A, Cilloni D. A Leukemic Target with a Thousand Faces: The Mitochondria. Int J Mol Sci. 2023;24.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
21.  Tseng S, Lee ME, Lin PC. A Review of Childhood Acute Myeloid Leukemia: Diagnosis and Novel Treatment. Pharmaceuticals (Basel). 2023;16.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
22.  Tomasoni C, Arsuffi C, Donsante S, Corsi A, Riminucci M, Biondi A, Pievani A, Serafini M. AML alters bone marrow stromal cell osteogenic commitment via Notch signaling. Front Immunol. 2023;14:1320497.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
23.  Sahasrabudhe KD, Mims AS. Novel investigational approaches for high-risk genetic subsets of AML: TP53, KMT2A, FLT3. Hematology Am Soc Hematol Educ Program. 2022;2022:15-22.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 1]  [Article Influence: 0.5]  [Reference Citation Analysis (0)]
24.  Chen Z, Guo Q, Huang S, Li L, Wu F, Liu Z, Li Z, Chen T, Song G, Xu S, Chen J, Hou Y. Overcoming adaptive resistance in AML by synergistically targeting FOXO3A-GNG7-mTOR axis with FOXO3A inhibitor Gardenoside and rapamycin. Genes Dis. 2024;11:397-412.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
25.  Mounier M, Romain G, Callanan M, Alla AD, Boussari O, Maynadié M, Colonna M, Jooste V. Flexible Modeling of Net Survival and Cure by AML Subtype and Age: A French Population-Based Study from FRANCIM. J Clin Med. 2021;10.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
26.  Arwanih EY, Louisa M, Rinaldi I, Wanandi SI. Resistance Mechanism of Acute Myeloid Leukemia Cells Against Daunorubicin and Cytarabine: A Literature Review. Cureus. 2022;14:e33165.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 5]  [Reference Citation Analysis (0)]
27.  Chen B, Wang L, Wang Z, Zhang H, Chen L, Zhang L, Li J, Yan X, Zhao M, Lin Y, Ru K. An NGS based MRD evaluation from acute myeloid leukemia patients. Int J Lab Hematol. 2023;45:353-359.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 3]  [Reference Citation Analysis (0)]
28.  Song M, Wang H, Ye Q. Increased circulating vascular endothelial growth factor in acute myeloid leukemia patients: a systematic review and meta-analysis. Syst Rev. 2020;9:103.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Cited by in F6Publishing: 8]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]
29.  Zhao D, Zarif M, Eladl E, Capo-Chichi JM, Smith AC, Atenafu EG, Tierens A, Minden MD, Schuh A, Chang H. NPM1-mutated AML-MRC diagnosed on the basis of history of MDS or MDS/MPN frequently harbours secondary-type mutations and confers inferior outcome compared to AML with mutated NPM1. Leuk Res. 2022;118:106869.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
30.  Stefaniuk P, Szymczyk A, Podhorecka M. In Pursuit of Genetic Prognostic Factors and Treatment Approaches in Secondary Acute Myeloid Leukemia-A Narrative Review of Current Knowledge. J Clin Med. 2022;11.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
31.  Moreno Vanegas Y, Badar T. Clinical Utility of Azacitidine in the Management of Acute Myeloid Leukemia: Update on Patient Selection and Reported Outcomes. Cancer Manag Res. 2022;14:3527-3538.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 3]  [Reference Citation Analysis (0)]
32.  Zhang Y, Li N, Chang Z, Wang H, Pei H, Zhang D, Zhang Q, Huang J, Guo Y, Zhao Y, Pan Y, Chen C, Chen Y. The Metabolic Signature of AML Cells Treated With Homoharringtonine. Front Oncol. 2022;12:931527.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
33.  Yao Y, Chai X, Gong C, Zou L. WT1 inhibits AML cell proliferation in a p53-dependent manner. Cell Cycle. 2021;20:1552-1560.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 1]  [Cited by in F6Publishing: 6]  [Article Influence: 2.0]  [Reference Citation Analysis (0)]