¹ Division of Hematology and Medical Oncology, Dharmais Cancer Hospital, Jakarta, Indonesia
² Department of Hematology and Cellular Therapy, Dharmais Cancer Hospital, Jakarta, Indonesia
³ Division of Hematology and Medical Oncology, Department of Internal Medicine, Faculty of Medicine, Diponegoro University, Semarang, Indonesia
⁴ Department of Pharmacology and Therapeutics, Faculty of Medicine, Indonesia University, Jakarta, Indonesia
⁵ Department of Biochemistry and Molecular Biology, Faculty of Medicine, Indonesia University, Jakarta, Indonesia
⁶ Division of Hematology and Medical Oncology, Cipto Mangunkusumo National General Hospital, Faculty of Medicine, Indonesia University, Jakarta, Indonesia

Resti Mulya Sari
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Lyana Setiawan
Roles: Conceptualization, Funding Acquisition, Methodology, Resources, Supervision, Validation

Damai Santosa
Roles: Resources, Supervision, Validation, Visualization

Syarifah Dewi
Roles: Methodology, Supervision, Visualization

Melva Louisa
Roles: Methodology, Supervision, Visualization

Ikhwan Rinaldi
Roles: Formal Analysis, Methodology, Resources, Supervision

Noorwati Sutandyo
Roles: Conceptualization, Formal Analysis, Methodology, Supervision, Validation, Visualization

This study was conducted using a prospective cohort design at Dharmais National Cancer Center, Jakarta, Indonesia. Patients were recruited consecutively between March–December 2025. Eligible patients were aged >18 years and had newly diagnosed acute myeloid leukemia (AML) confirmed according to WHO diagnostic criteria 2022. Patients with acute promyelocytic leukemia corresponding to the M3 FAB subtype, a previous diagnosis of myelodysplastic syndrome, severe clinical conditions that precluded intensive chemotherapy, death before completion of induction chemotherapy, unavailable post-induction bone marrow evaluation, or non-evaluable biomarker laboratory results were excluded from the biomarker-evaluable analysis. Pediatric patients were not included because the parent study was specifically designed for adults treated within adult hematology-oncology services. Pediatric AML differs from adult AML in its cytogenetic and molecular landscape, treatment protocols, chemotherapy dose intensity, supportive-care requirements, treatment-related toxicity, and long-term outcomes. Combining pediatric and adult patients could therefore introduce substantial biological and therapeutic heterogeneity.

Initially, 109 adult patients with newly diagnosed AML were assessed for eligibility. Seven patients were excluded prior to induction chemotherapy due to early mortality (n = 4) and loss to follow-up (n = 3). Among the 102 patients who received induction chemotherapy, 31 patients were excluded from the final analysis due to death during induction chemotherapy (n = 25), loss to follow-up (n = 2), and incomplete clinical data (n = 4). Finally, 71 patients were included in the final analysis ( Figure 1).

The 71-patient cohort should be interpreted as an evaluable-patient biomarker cohort rather than the entire population initiating induction chemotherapy. Induction mortality among the 102 treated patients is reported separately to provide a transparent description of treatment attrition.

The sample size of the parent prospective cohort was calculated using a single diagnostic-sensitivity formula:

Nsen=Zα2×Sen(1−Sen)/(d2×P)

The calculation assumed an expected biomarker sensitivity of 70%, an anticipated prevalence of successful induction response of 55%, a precision of 15%, and a two-sided alpha level of 5%, corresponding to a Zα value of 1.96. The minimum calculated sample size was 66 participants. Ultimately, 71 patients had complete induction-response and biomarker data and were included in the final analysis, thereby exceeding the minimum required sample size.

Peripheral blood samples were collected at baseline before initiation of induction chemotherapy. Plasma or serum was separated according to the requirements of each biomarker assay and stored at −80°C until analysis.

Total RNA, including microRNAs, was extracted from peripheral blood samples using the miRNeasy Mini Kit (Qiagen, Hilden, Germany; Cat. No. 217004) according to the manufacturer’s instructions. Reverse transcription was performed using the miRCURY LNA RT Kit (Qiagen, Hilden, Germany; Cat. No. 339340). Expression levels of miR-181a-3p and miR-181b-5p were quantified using the miRCURY LNA miRNA PCR Assay (Qiagen, Hilden, Germany; Cat. No. 339306) in combination with the QIAcuity EG PCR Kit (Qiagen, Hilden, Germany; Cat. No. 250111). Absolute quantification was performed using the QIAcuity Digital PCR System (Qiagen, Hilden, Germany) according to the manufacturer’s protocol.

Serum ATM protein levels were measured using a Human ATM ELISA Kit (Colorimetric) (Novus Biologicals, Centennial, CO, USA; Cat. No. NBP2–69891). Serum ATR protein levels were measured using a Human Serine/Threonine-Protein Kinase ATR ELISA Kit (Abbexa Ltd., Cambridge, United Kingdom; Cat. No. abx555473). Serum HMGB-1 protein levels were measured using a Human HMGB1 ELISA Kit (Colorimetric) (Novus Biologicals, Centennial, CO, USA; Cat. No. NBP2–62766).

All ELISA measurements were performed according to the manufacturers’ instructions. Optical density was measured at 450 nm using a microplate reader, and protein concentrations were calculated from standard calibration curves generated using the supplied standards. One kit was used for ATM and HMGB-1 measurements, while two ATR ELISA kits were required to accommodate all study samples.

Patients who met the inclusion criteria received induction chemotherapy using the D3A7 regimen, daunorubicin 60–90 mg/m² for 3 days and cytarabine 100–200 mg/m² for seven days. Bone marrow aspiration evaluation was done at a minimum of day 21 after the initiation of induction chemotherapy.

Continuous variables were summarized as mean (standard deviation) or median (interquartile range), as appropriate, and categorical variables as frequencies and percentages. Exploratory biomarker cut-offs were determined using receiver operating characteristic curve analysis and the Youden index. HMGB-1 was categorized as low (≤28.59 pg/mL) or high (>28.59 pg/mL). Because the cut-off was derived and evaluated in the same cohort, the corresponding categorical analyses were considered exploratory.

Associations between categorical variables and induction response were evaluated using Pearson’s chi-square or Fisher’s exact test, as appropriate, and reported as relative risks with 95% confidence intervals. Continuous variables were compared using appropriate parametric or non-parametric tests. Spearman’s rank correlation was used to evaluate the relationships between baseline HMGB-1 and bone marrow and peripheral blood blast percentages, miR-181a-3p, miR-181b-5p, ATM, and ATR.

Variables with p < 0.25 in bivariable analysis were considered for multivariable analysis using backward elimination. The initial clinical-biomolecular model included platelet count >22,500/μL, serum creatinine >0.74 mg/dL, HMGB-1 > 28.59 pg/mL, and ATR >29.16 pg/mL. Serum creatinine was removed during backward elimination, leaving platelet count, HMGB-1, and ATR in the final model. Adjusted relative risks with 95% confidence intervals were reported, and multicollinearity was assessed using variance inflation factors. All tests were two-sided, with p < 0.05 considered statistically significant. Analyses were performed using IBM SPSS Statistics version 26.0.

The median age at diagnosis was 39 years (IQR, 27–46 years), and 37 patients (52.1%) were female. AML M2 was the most frequent FAB subtype, accounting for 34 patients (47.9%). Forty patients (56.3%) achieved a successful induction response, whereas 31 patients (43.7%) did not. The patients’ characteristics are presented in Table 1.

Among the 40 patients who achieved a successful induction response, 21 (52.5%) were male, 34 (85.0%) had an ECOG performance status of 0–1, and 30 (75.0%) had at least one comorbidity. AML M2 was the most frequent FAB subtype in both the successful- and unsuccessful-response groups, accounting for 47.5% and 48.4% of patients, respectively.

There were no significant differences between the successful- and unsuccessful-response groups in age, sex, FAB subtype, comorbidity, ECOG performance status, febrile neutropenia, duration of febrile neutropenia, baseline bone marrow blast percentage, hemoglobin concentration, leukocyte count, or platelet count. Serum creatinine differed significantly between the two groups, with a median concentration of 0.80 mg/dL (IQR, 0.70–1.00) in the successful-response group and 0.70 mg/dL (IQR, 0.50–0.80) in the unsuccessful-response group (p = 0.023). Complete comparisons are presented in Table 2.

Among the evaluated baseline biomolecular markers, only circulating HMGB-1 was significantly associated with successful induction response. Low baseline HMGB-1 levels, defined as ≤28.59 pg/mL, were observed in 33 patients. Of these patients, 14 (42.4%) achieved a successful response and 19 (57.6%) did not. Among the 38 patients with high baseline HMGB-1 levels, 26 (68.4%) achieved a successful response and 12 (31.6%) did not.

The ROC analysis of baseline circulating HMGB-1 for predicting successful induction response yielded an AUC of 0.615 (95% CI 0.480–0.749). The Youden index identified an optimal cut-off value of 28.59 pg/mL, with a sensitivity of 65.0% and a specificity of 61.3%. HMGB-1 concentrations ≤28.59 pg/mL were categorized as low, whereas concentrations >28.59 pg/mL were categorized as high (Figure 2).

Patients with low baseline HMGB-1 had a lower probability of achieving a successful induction response than patients with high HMGB-1 levels (RR 0.620; 95% CI 0.394–0.975; p = 0.038), corresponding to an approximately 38% lower probability of successful response.

Baseline miR-181a-3p, miR-181b-5p, ATM, and ATR categories were not significantly associated with induction response. The association for high ATR approached but did not reach the predefined level of statistical significance (RR 1.532; 95% CI 0.987–2.376; p = 0.057). The results of the biomarker analyses are presented in Table 3.

The correlations between baseline circulating HMGB-1 and the evaluated morphologic and biomolecular characteristics are presented in Table 4. Baseline HMGB-1 concentration was not significantly correlated with bone marrow blast percentage at diagnosis (Spearman’s r = −0.090; p = 0.457) or peripheral blood blast percentage (r = 0.118; p = 0.331). These findings indicate that baseline circulating HMGB-1 was not detectably associated with morphologic blast burden in this cohort.

No statistically significant correlations were identified between baseline HMGB-1 and circulating miR-181a-3p (r = −0.031; p = 0.797), miR-181b-5p (r = −0.068; p = 0.576), or ATM concentration (r = −0.034; p = 0.781). Baseline HMGB-1 was also not significantly correlated with ATR concentration observed in the cohort and included in the analysis (r = 0.148; p = 0.217; n = 71). Overall, the correlations were weak, and none of the evaluated morphologic or biomolecular characteristics demonstrated a statistically significant correlation with baseline circulating HMGB-1.

Variables meeting the predefined criterion of p < 0.25 in the bivariable analysis were considered for the multivariable clinical-biomolecular model. The initial model included platelet count >22,500/μL, serum creatinine >0.74 mg/dL, high baseline HMGB-1 > 28.59 pg/mL, and high baseline ATR >29.16 pg/mL. In the initial model, platelet count (RR 1.926; 95% CI 1.149–3.229; p = 0.013) and high ATR (RR 1.534; 95% CI 1.042–2.257; p = 0.030) were significantly associated with successful induction response. The association with high HMGB-1 approached statistical significance (RR 1.529; 95% CI 0.993–2.354; p = 0.054), whereas serum creatinine was not significantly associated with response (RR 0.697; 95% CI 0.454–1.072; p = 0.101).

After serum creatinine was removed through backward elimination, platelet count >22,500/μL, high baseline HMGB-1, and high baseline ATR were retained in the final model. High baseline HMGB-1 was associated with a higher probability of successful induction response after adjustment for platelet count and ATR (adjusted RR 1.666; 95% CI 1.092–2.541; p = 0.018). Platelet count >22,500/μL (adjusted RR 1.947; 95% CI 1.151–3.293; p = 0.013) and high baseline ATR (adjusted RR 1.514; 95% CI 1.026–2.263; p = 0.037) were also associated with successful response. No relevant multicollinearity was identified among the variables included in the model. The findings of the multivariable biomarker analysis are presented in Table 5.

The median age at diagnosis was 39 years (IQR, 27–46 years), and 52.1% of the patients were female. Forty patients (56.3%) achieved a successful induction response. Among these patients, most had an ECOG performance status of 0–1 and at least one comorbidity.

Previous studies have reported varying response rates following AML induction chemotherapy. Lee et al. reported complete remission in 61% of 132 patients receiving induction chemotherapy in South Korea.¹⁶ Zahrani et al. reported remission in 84% of patients treated in Saudi Arabia, although 41% subsequently experienced relapse.¹⁷ In Indonesia, Hadisantoso et al. reported complete remission in 55.4% of evaluable patients treated with standard 7 + 3 induction chemotherapy.² Shireen et al. reported complete remission in 54% of patients receiving standard 3 + 7 induction therapy.¹⁸ Whereas Zaidi et al. reported a post-induction response rate of approximately 65.5%.¹⁹ Differences among studies may be related to patient age, performance status, AML subtype, molecular risk, treatment intensity, supportive care, and response definitions.

In the present study, 25 of 102 patients who initiated induction chemotherapy died during induction or early post-induction care. These patients could not undergo standardized post-induction bone marrow evaluation and were therefore excluded from the final biomarker analysis. Consequently, the response rate reported among the 71 evaluable patients should not be interpreted as the response rate among all patients who initiated induction chemotherapy.

HMGB-1 protein is a non-histone nuclear protein included in the High Mobility Group Box subgroup, an important protein that has antiapoptotic and pro-autophagic properties.²⁰ HMGB-1 protein is a multifunctional molecule that is involved especially in inflammatory disorders and malignancies.^21,22 HMGB-1 contributes to leukemia progression through regulation of proliferation, survival signaling, inflammation, and resistance to cell death.²² HMGB-1 protein has a higher expression level in bone marrow mononuclear cells of AML patients and contributes to the pathogenesis and progression of AML by inhibiting apoptosis, facilitating proliferation, and inducing inhibition of myeloid differentiation in AML cells.^23–27

Among the evaluated baseline biomolecular markers, circulating HMGB-1 was significantly associated with successful induction response. Patients with low baseline HMGB-1 had a lower probability of successful response than those with high levels. This direction was consistent with the final clinical-biomolecular model, in which high baseline HMGB-1 remained associated with successful induction response after adjustment for platelet count and ATR. These findings suggest that baseline circulating HMGB-1 may provide complementary information regarding early treatment response alongside the clinical and biomolecular variables included in the model.

Baseline HMGB-1 was not significantly correlated with bone marrow or peripheral blood blast percentages, miR-181a-3p, miR-181b-5p, ATM, or ATR. Thus, circulating HMGB-1 was not detectably associated with morphologic blast burden or the other evaluated baseline biomolecular markers in this cohort. Nevertheless, the absence of statistically significant correlations does not establish biological independence because circulating HMGB-1 may originate from multiple cellular and tissue sources.

The direction of the association observed in this study appears to differ from that reported in several previous AML studies, in which higher HMGB-1 expression has generally been associated with more aggressive disease biology and chemotherapy resistance. This apparent discrepancy may partly reflect differences in the biological compartment and timing of HMGB-1 measurement. Many previous studies evaluated intracellular HMGB-1 or its expression in bone marrow cells, where HMGB-1 is associated with leukemic-cell survival, autophagy activation, inhibition of apoptosis, and chemoresistance.^{25,26,28,30,31} In contrast, the present study measured circulating HMGB-1 in peripheral blood before induction chemotherapy, which may represent a different aspect of leukemic and host biology.

This context-dependent activity is consistent with the “double-edged sword” nature of HMGB-1.^22,28 Intracellular HMGB-1 may promote leukemic-cell survival and treatment resistance through regulation of autophagy, apoptosis, ferroptosis, pyroptosis, and DNA-damage-related signaling. Its extracellular activity is also not uniform but depends on its molecular form and redox state. Fully reduced HMGB-1 primarily exhibits chemotactic activity, disulfide HMGB-1 can induce cytokine signaling through the TLR4/MD-2 complex, whereas terminal oxidation may abolish these extracellular activities.¹² Therefore, a higher total circulating HMGB-1 concentration cannot automatically be interpreted as evidence of an immune-stimulatory or antitumor effect.^21,27

During immunogenic cell death, extracellular HMGB-1 released from damaged or dying malignant cells may activate TLR4- and RAGE-related signaling in antigen-presenting cells.^13–15 This process may promote dendritic-cell activation, antigen processing, and adaptive antitumor immune responses.^{21,29,32–34} Therefore, higher circulating HMGB-1 could hypothetically reflect spontaneous leukemic-cell turnover or subclinical cell death and an immune microenvironment that is more responsive to subsequent cytotoxic treatment.^13–15 The proposed model presented in Figure 3 illustrates this possible link between leukemic-cell stress, extracellular HMGB-1 signaling, immune activation, and induction-treatment response.

However, HMGB-1 was measured before initiation of chemotherapy. Therefore, the measured concentration cannot be interpreted as HMGB-1 released directly in response to chemotherapy-induced leukemic-cell death. Baseline circulating HMGB-1 may reflect spontaneous leukemic-cell turnover, inflammatory activity, tissue injury, immune-cell activation, or other host- and disease-related processes. Consequently, the proposed relationship between baseline HMGB-1, immunogenic cell death, and subsequent chemotherapy response remains biologically plausible but was not directly demonstrated in this study.

The findings support further investigation of circulating HMGB-1 as an accessible biomolecular marker associated with early induction response in AML. Nevertheless, HMGB-1 should currently be considered an exploratory complementary biomarker rather than a substitute for established clinical assessment, cytogenetic and molecular risk classification, or measurable residual disease evaluation.

This study has several limitations. First, although patients were recruited at two national referral hospitals, the final biomarker-evaluable cohort was relatively small. The 71 included patients exceeded the minimum calculated sample size of 66. Second, excluding patients who died before post-induction response assessment may have introduced survivor-selection bias. Third, HMGB-1 was measured only once before induction chemotherapy; therefore, changes during and after treatment could not be evaluated.

Fourth, the assay measured total circulating HMGB-1 without distinguishing its cellular source or redox isoforms. Fifth, the HMGB-1 cut-off was derived and evaluated in the same cohort and therefore requires external validation. Sixth, comprehensive cytogenetic and molecular risk profiling was not systematically available. Finally, OS and EFS could not be estimated because complete dates of death, relapse, and last follow-up were unavailable. The findings should therefore be interpreted as associations with early induction response rather than evidence of the long-term prognostic significance of HMGB-1.

Despite these limitations, this study provides prospective biomarker data from an Indonesian adult AML population. Larger multicenter prospective studies incorporating serial HMGB-1 measurements, HMGB-1 redox-state characterization, comprehensive molecular profiling, measurable residual disease assessment, OS, EFS, and mechanistic validation are required to confirm these findings and define their clinical relevance.

The datasets generated and analysed during the current study contain individual-level clinical and laboratory information from patients with acute myeloid leukemia. Public deposition of these data is restricted due to ethical and privacy considerations and in accordance with the conditions approved by the Health Research Ethics Committee of Dr. Cipto Mangunkusumo National General Hospital, Faculty of Medicine Universitas Indonesia.

The Ethics Committee approved the study on the condition that participant confidentiality and privacy are protected. Therefore, raw patient-level data cannot be made publicly available. Researchers who wish to access de-identified data for legitimate academic purposes may submit a written request to the corresponding author ([email protected]).

Requests will be reviewed by the corresponding author and the relevant institutional authorities. Access may be granted following ethical review, execution of a data-sharing agreement, and confirmation that the proposed use is consistent with the original informed consent and applicable regulations.

The Authors wish to thank Dharmais Cancer Hospital and Cipto Mangunkusumo Hospital for the support given during this study.

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This study was supported by a research grant from the Clinical Research Unit (CRU), National Cancer Center Dharmais Cancer Hospital Research Centre, Jakarta, Indonesia (Grant Notification No. DP.04.03/D.XII.2.3/163/2026).

This manuscript represents a secondary analysis derived from a larger prospective research project entitled “Predictors of Treatment Success in Patients with Acute Myeloblastic Leukemia Receiving Induction Chemotherapy: An Analysis of CD7 Cell Surface Antigen Expression, miRNA 181a-3p, miRNA 181b-5p, ATM Protein, ATR Protein, and HMGB-1 Protein”, which was funded by the Clinical Research Unit.

The funder had no role in the study design, data collection, data analysis, interpretation of results, manuscript preparation, or the decision to publish.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Current Reviewer Status: ?

VERSION 1

PUBLISHED 11 Jul 2026

Reviewer Report 28 Jul 2026

Deniz Ozmen, Istanbul University Cerrahpaşa, Istanbul, Turkey 

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Reviewer Report 22 Jul 2026

Harsh Goel, All India Institute of Medical Sciences, New Delhi, India 

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