Metagenomic NGS and Targeted NGS Driven Precision Therapy in Pediatric Chemotherapy-Associated Infections: A Single-Center Retrospective Study

Metagenomic NGS and Targeted NGS Driven Precision Therapy in Pediatric Chemotherapy-Associated Infections: A Single-Center Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Metagenomic NGS and Targeted NGS Driven Precision Therapy in Pediatric Chemotherapy-Associated Infections: A Single-Center Retrospective Study Jianxin Dun, Ai Zhang, Aiguo Liu, Yaqin Wang, Qun Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8485427/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Infections in immunocompromised pediatric hematology-oncology patients present a major challenge. This study utilized pathogen NGS (metagenomic next generation sequencing (mNGS) / targeted next generation sequencing (tNGS)) to characterize the microbial spectrum in this population, thereby enhancing detection and enabling targeted antimicrobial therapy. Methods This retrospective study enrolled pediatric patients with hematologic malignancies. The analysis employed descriptive statistics for pathogen profiles and comparative statistics to assess variations by clinical stage and outcome, and to evaluate NGS against traditional pathogen detection (TPD). Results This study included 72 children with a median age of 8 years. A total of 83 NGS tests were performed. Microbial organisms were detected by NGS in 70 samples, yielding 26 bacterial, 14 viral, and 12 fungal species. No statistically significant difference in NGS positivity was observed between the non-agranulocytosis (A1) and agranulocytosis (A2) groups ( P = 0.374). Escherichia coli (n = 5), Candida albicans (n = 5), and Human beta herpesvirus 5 (CMV, n = 21) were the most prevalent bacterial, fungal, and viral pathogens, respectively. Analysis of blood samples revealed that Escherichia coli, Aspergillus flavus , and Human gamma herpesvirus 4 (EBV) were the predominant bacterial, fungal, and viral pathogens, respectively. Statistical comparison revealed comparable rates of viremia between groups A1 and A2 ( P >0.999), whereas group A2 had a greater risk of bloodstream infection ( P = 0.023). Among the 61 blood samples, 49 (80.3%) were positive by mNGS, whereas only 7 were positive by TPD)(all of which were also mNGS-positive). All 11 pulmonary samples tested by tNGS were positive, while TPD was positive in only 1 specimen. tNGS identified Pneumocystis jirovecii in 3 samples, all of which were missed by TPD. NGS-guided antibiotic adjustment in 53.5% of patients with bacterial/fungal infections led to a favorable outcome, with an 88.4% cure rate after a median treatment of 12.1 days. Conclusions This study identified predominant pathogens ( Escherichia coli . Candida albicans s, CMV) and demonstrated that NGS, which is agranulocytosis, enhances detection of bacterial/fungal infections, enabling precision antimicrobial therapy in pediatric chemotherapy patients. Clinical trial number: not applicable. Trial registration: not applicable. Pediatric hematology-oncology Next-generation sequencing Pathogen spectrum Bloodstream infection Figures Figure 1 Figure 2 Background Advances in chemotherapy have significantly improved the cure rates of various pediatric hematological cancer particularly in acute lymphoblastic leukemia, and the 5-year OS can reach more than 90% [ 1 ] . However, the efficacy of chemotherapy is accompanied by notable side effects that cannot be overlooked. Most chemotherapy regimens induce bone marrow suppression and compromised immunity in pediatric blood cancer patients, rendering them more susceptible to infections than healthy children [ 2 ] . Infections are more likely to progress to sepsis, which can lead to severe complications such as septic shock, multiple organ failure, and potentially death, thereby impacting the prognosis of children with hematological cancer [ 2 , 3 ] . In the absence of a definitive pathogen, indiscriminate administration of broad-spectrum antibiotics may promote the emergence of multidrug-resistant bacteria [ 4 ] . Hence, a targeted antibiotic approach based on pathogen identification is preferable for promptly managing infections and mitigating the development of drug resistance. Metagenomic next-generation sequencing(mNGS) is a new method for detecting pathogenic microorganisms. By sequencing the DNA or RNA of clinical samples, a variety of pathogenic microorganisms can be detected simultaneously, with a short detection time and high sensitivity [ 5 ] . For children with blood cancer, it is important to identify whether fever is caused by infection early or identify pathogens early in infection to control complications and avoid delaying chemotherapy [ 6 ] . Furthermore, target next-generation sequencing (tNGS) offers distinct advantages for sputum and bronchoalveolar lavage fluid (BLAF) specimen analysis [ 7 ] . Unlike mNGS, it does not require host depletion and directly sequences targeted genomic regions, which reduces the required data volume. More importantly, tNGS employs targeted primers or probes to enrich microbial nucleic acids prior to sequencing, enabling the detection of low-abundance pathogens and thereby providing higher sensitivity than mNGS dose [ 8 ] . This study collected the clinical data of children with cancer who underwent mNGS or tNGS, analyzed the susceptibility pathogen spectrum of children with blood cancer, and explored the application value of NGS (mNGS/ tNGS) in children with cancer. Methods 1.Patient This study retrospectively collected data from tumorous children who visited our hospital for chemotherapy from January 1, 2022 to July 1, 2025, and NGS examination was performed during chemotherapy. Hematological cancers include acute lymphoblastic leukemia, acute myelogenous leukemia, and lymphoma. Children aged ≥ 1 and < 18 years. ANC < 0.5×10 9 /L is defined as agranulocytosis [ 9 ] . All the samples were processed for traditional pathogen detection (TPD). TPD included: cultures of blood, urine, stool, BLAF, sputum, pleural/ascitic fluid, and cerebrospinal fluid; cerebrospinal fluid smear and India ink staining; viral DNA detection; multiplex respiratory pathogen testing from throat swabs; and the T-SPOT assay. 2. Metagenomic NGS and targeted NGS mNGS: Samples (2 mL of EDTA blood; tissue/secretions/body fluids/CSF in sterile containers) were analyzed via a database of 25,863 pathogens (12,142 bacteria, 2,680 fungi, 206 mycobacteria, 120 mycoplasma/chlamydia, 7,369 DNA viruses, 2,692 RNA viruses, and 654 parasites). tNGS: Samples (deep sputum/BALF in sterile containers) were analyzed via a panel covering 302 pathogens (133 bacteria, 46 fungi, 110 DNA/RNA viruses, and 13 parasites) and 35 key resistance/virulence genes 3. Statistical analysis Statistical analyses were performed using SPSS 26.0. Continuous data were presented as median (interquartile range, IQR), and categorical data as n (%). Group comparisons for categorical variables were conducted using Fisher’s exact test, with a P < 0.05 considered statistically significant. 4. Ethical considerations This study was conducted in accordance with the ethical standards stipulated in the Declaration of Helsinki of 1975. This study was approved by Tongji Medical College, Huazhong University of Science and Technology (Approval No. [2020] Lun Shen Zi (S278)). Written informed consent was obtained from all guardians, and the confidentiality of patient information was strictly maintained throughout the study. Results 1.Demographic and Clinical Characteristics of the Patients This study enrolled 72 pediatric patients, among whom 49 were male and 23 were female. The cohort included 54 patients with acute leukemia and 18 patients with lymphoma. The median age of the patients was 8.0 years (IQR: 5.6 ~ 11.7 years). These patients underwent a total of 71 mNGS and 11 tNGS examinations. A total of 61 blood samples, 11 pulmonary-derived samples (including deep sputum and BLAF), 8 body fluid samples, and 2 tissue-derived samples were collected (Table 1 ). On the day of NGS examination, the median white blood cell count was 2.09×10⁹/L, and the median neutrophil count was 0.48×10⁹/L. With respect to the patients' immunologic status during NGS testing, 51.2% were in a stage of agranulocytosis. Patients were stratified into Group A1 (non-agranulocytosis) and Group A2 (agranulocytosis). Table 1 Patients and characteristics Characteristics N (%) SEX Male 49(68.1%) Female 23(31.9%) Underlying disease Acute lymphoblastic leukemia 45(62.5%) Acute myeloid leukemia 9(12.5%) Lymphoma 18(25.0%) Samples Blood samples 61(74.4%) Pulmonary-derived samples deep sputum bronchoalveolar lavage fluid 11(13.4%) 7(8.5%) 4(4.9%) Body fluid samples secretion cerebrospinal-fluid pleural/ascitic-fluid 8(9.8%) 3(3.7%) 3(3.7%) 2(2.4%) Tissue-derived samples 2(2.4%) Neutrophil count Non- agranulocytosis 40(48.8%) Agranulocytosis 42(51.2%) 2. Pathogen Detection by NGS (mNGS/tNGS) NGS detected microbial nucleic acids in 70 of the 82 samples (85.4%). NGS revealed the presence of multiple pathogens, including 26 species of bacteria, 12 species of fungi, and 14 species of viruses (Fig. 1 ). In the positive samples, pathogens were identified as follows: 66 with viruses, 42 with bacteria, and 21 with fungi. Among the samples tested, 43 were positive for bacteria and/or fungi. Analysis of the NGS-positive samples revealed that a single pathogen type (bacterial, fungal, or viral) ( n = 47, 67.1%) was more common than co-infections with two or more pathogen types ( n = 23, 32.9%), which included 5 cases (7.1%) of bacterial-fungal co-injection. In terms of pathogen composition, single-bacterial infections ( n = 20,28.6%) were more common than multi-bacterial infections ( n = 8,11.4%), and single-fungal infections ( n = 11, 15.7%) outnumbered multi-fungal infections ( n = 2,2.9%). A Fisher's exact test was conducted to compare the NGS positivity rates between groups A1 and A2, which demonstrated no statistically significant difference( P = 0.374) (Fig. 2 ). Among the bacterial isolates, 16 were gram-positive and 22 were gram-negative. Among the gram-positive isolates, Enterococcus faecium was the most prevalent( n = 4), followed by Staphylococcus aureus ( n = 3). Of the gram-negative bacteria, Enterobacteriaceae were the most frequently detected ( n = 10), with Escherichia coli being the most common species ( n = 5). This was followed by Halomonas ( n = 6), 5 of which were Pseudomonas aeruginosa . Candida was the predominant fungis( n = 8), with Candida albicans being the most prevalent species( n = 5). Among all the detected viruses, the most prevalent was Human beta herpesvirus 5 (CMV, n = 21), followed by T orque teno virus ( n = 15) and Human gamma herpesvirus 4 (EBV, n = 10). 2.Pathogen Composition of Bloodstream Bacterial/Fungal Infections by mNGS Evidence of bloodstream infections (BSI, bacterial/fungal) was found in 28 cases, and viremia was identified in 34 cases. The main bacterial isolate in blood samples was gram negative bacillus( n = 15). Among these the most common pathogens identified were Escherichia coli ( n = 5) and Pseudomonas aeruginosa ( n = 3) for bacteria; Aspergillus flavus ( n = 3) for fungi; and EBV ( n = 7) for viruses, respectively. A Fisher's exact test was conducted to compare viremia positivity between groups A1 and A2, which demonstrated no statistically significant difference( P >0.999). In contrast, a Fisher's exact test on the disparity of BSI between groups A1 and A2 indicated that BSI was detected more frequently in group A2, and this difference was statistically significant( P = 0.023). Interestingly, a further comparison within BSI revealed no statistically significant difference in the distribution of monomicrobial versus polymicrobial infections between groups A1 and A2( P = 0.319) (Fig. 2 ). 3. Pathogen Composition of Pulmonary Infections Detected by tNGS Of the 11 pulmonary-derived samples subjected to tNGS, the following pathogenic sources were identified as follows: viruses in 4 cases (EBV( n = 1), SARS-CoV-2( n = 1), Respiratory Syncytial Virus ( n = 1), and Rhinovirus ( n = 1)); fungi in 4 cases ( Candida albicans ( n = 1) and Pneumocystis jirovecii ( n = 3)); and bacteria in 3 cases ( Pseudomonas aeruginosa ( n = 1), Klebsiella pneumoniae ( n = 1), and Streptococcus pneumoniae ( n = 1)). One case was coinfected with Haemophilus parainfluenzae ( n = 1) and Candida krusei ( n = 1). Furthermore, concomitant chest CT scans were obtained in all cases during tNGS testing, and the radiographic findings demonstrated evidence of pulmonary infection of varying severity. 4.Diagnostic Performance of NGS (mNGS/tNGS) mNGS detected microbial nucleic acids in 49 of the 61 blood samples, yielding a positivity rate of 80.3%. Conventional blood culture was positive in only 7 cases (11.5%) (both of which were mNGS-positive). Similarly, all 11 pulmonary-derived samples were positive by tNGS. However, only 1 case was positive case by TPD. Notably, Pneumocystis jirovecii was detected by tNGS in 3 cases, all of which were missed by TPD. Furthermore, mNGS/tNGS provides results within 48h with high sensitivity, whereas conventional culture typically requires approximately 5d and has a low positivity rate. 5. Clinical Outcomes and Therapeutic Impact Among the 43 samples with bacterial and/or fungal infections, 53.5% ( n = 23) had their antimicrobial therapy adjusted based on the basis of the test results. The median treatment duration following this NGS-guided adjustment was 12.1 days (IQR:8 ~ 15d). The clinical outcomes were as follows: 88.4% ( n = 38) achieved cure, 9.3% ( n = 4) died from septic shock, and 2.3%( n = 1) were lost to follow-up after treatment withdrawal due to severe infection. Discussion The success of modern therapies for pediatric hematologic malignancies is tempered by the challenge of treatment-related complications. Myelosuppression, a near-universal adverse effect, entails a substantial clinical burden by prolonging hospitalization and risking mortality from severe infection [ 10 ] . Furthermore, in the context of severe infection, any delay in providing targeted antimicrobial therapy may lead to worse clinical outcomes, including extended hospitalization and increased mortality, alongside a significant economic burden [ 11 ] . For children on chemotherapy, delays in infection control inevitably lead to postponement of chemotherapy, with potential consequences for the primary disease outcome. This study analyzed the pathogenic findings from NGS in pediatric hematology-oncology patients during chemotherapy, with the aim of improving pathogen diagnosis and guiding precise antimicrobial therapy for these immunocompromised children. This study revealed diverse pathogen profiles of 52 species (26 bacterial, 14 viral, and 12 fungal) in pediatric hematological cancer patients during chemotherapy. The spectrum included common pathogens such as Escherichia coli and Candida albicans alongside rare organisms such as Finegoldia magna and Cunninghamella elegans , reflecting the profound immunosuppression from multiagent chemotherapy that enables opportunistic infections. In this study, Escherichia coli was the most frequently detected bacterium in both overall and blood samples, aligning with previous reports that gram-negative bacteria (particularly Pseudomonas aeruginosa and E. coli ) predominate in neutropenic patients, and that E. coli is the most common pathogen in blood cultures [ 12 ] . A total of 51.2% of patients had agranulocytosis at the time of NGS testing. The overall NGS positivity rate was comparable between the and non-agranulocytosis groups ( P = 0.374). However, further analysis of pathogen-specific profiles revealed that while the incidence of viremia in blood was similar between the groups, the agranulocytosis group had a significantly greater risk of bacterial and/or fungal infections( P = 0.023). For pulmonary infections, tNGS provides a rapid, accurate, and cost-effective diagnostic solution [ 13 ] . Previous studies in immunocompromised children have shown that tNGS has greater detection efficacy than mNGS does; tNGS most frequently detects Pseudomonas aeruginosa , Pneumocystis jirovecii , CMV and EBV [ 13 ] . Our tNGS results identified Pneumocystis jirovecii and EBV as the predominant fungal and viral pathogens, which is consistent with prior reports. Moreover, TPD failed to identify Pneumocystis jirovecii . mNGS demonstrates superior performance over TPD in providing rapid, comprehensive, and accurate pathogen identification [ 14 ] . In this study, mNGS achieved a positivity rate of 80.3%, which was significantly higher than the 11.5% rate obtained by TPD, whereas mNGS detected a significant number of additional pathogens, notably missing all cases of viremia owing to the inherent limitations of TPD. Studies have established that infection represents the most frequent cause of treatment-related mortality in pediatric oncology patients, particularly those with hematologic malignancies [ 15 ] . This finding underscores the critical importance of early pathogen identification and targeted antimicrobial therapy. In the present study, over half of the patients received antimicrobial regimen adjustments on the basis of NGS findings, suggesting that NGS testing can guide appropriate early intervention, especially when current anti-infective therapy is ineffective. While 88.4% patients in our cohort were successfully cured, 4 children unfortunately died due to progressive infection. Conclusions In this study, pediatric hematological cancer patients who underwent mNGS/tNGS most frequently exhibited Escherichia coli , Candida albicans , and CMV. While the distribution of monomicrobial versus polymicrobial infections was not significantly different between agranulocytic and non-agranulocytic patients, the former demonstrated a higher detection rate of bacterial and/or fungal pathogens. mNGS/tNGS findings prove valuable in guiding appropriate antimicrobial therapy. Abbreviations BLAF Bronchoalveolar lavage fluid mNGS Metagenomic next generation sequencing tNGS Targeted next generation sequencing TPD Traditional pathogen detection CMV Human beta herpesvirus 5 EBV Human gamma herpesvirus 4 IQR Interquartile range Declarations Clinical trial number not applicable. Ethics approval and consent to participate The procedures followed in this study were in accordance with principles of the Declaration of Helsinki (1964, amended most recently in 2008) of the World Medical Association and informed consent was obtained from all participants/parents/guardians. This study was approved by Tongji Medical College, Huazhong University of Science and Technology (Approval No. [2020] Lun Shen Zi (S207)). Consent for publication Written informed consent was obtained from all guardians, and the confidentiality of patient information was strictly maintained throughout the study. Competing interests The authors declare that they have no competing interests Funding Not applicable Author Contribution Jianxin Dun: Conceptualization and writing the manuscriptAi Zhang: Investigation and methodologyAiguo Liu: Data CurationYaqin Wang: Data CurationQun Hu: Writing - Review & Editing Acknowledgements We extend our sincere gratitude to all individuals who contributed to the completion of this research. Special thanks to the patient's family. Thank you to the editors for their meticulous attention to detail and invaluable contributions throughout the editing process. Your expertise and dedication have greatly enhanced the clarity and quality of this work. Data Availability The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request References MALARD F, MOHTY M. Acute lymphoblastic leukaemia [J]. Lancet (London, England), 2020, 39510230 HäRTEL C, DEUSTER M, LEHRNBECHER T,et al. Current approaches for risk stratification of infectious complications in pediatric oncology [J]. Pediatric Blood & Cancer, 2007, 496 VAN DE GEER A, ZANDSTRA J, TANCK MWT,et al. Biomarkers to predict infection and infection-related complications during chemotherapy‐induced neutropenia in acute myeloid leukaemia: a pilot study [J]. British Journal of Haematology, 2021, 1935 IRFAN M, ALMOTIRI A, ALZEYADI ZA. Antimicrobial Resistance and Its Drivers—A Review [J]. Antibiotics, 2022, 1110 WENSEL CR, PLUZNICK JL, SALZBERG SL,et al. Next-generation sequencing: insights to advance clinical investigations of the microbiome [J]. The Journal of Clinical Investigation, 2022, 1327 VOULGARIDOU A, ATHANASIADOU KI, ATHANASIADOU E,et al. Pulmonary Infectious Complications in Children with Hematologic Malignancies and Chemotherapy-Induced Neutropenia [J]. Diseases, 2020, 83 YIN Y, ZHU P, GUO Y,et al. Enhancing lower respiratory tract infection diagnosis: implementation and clinical assessment of multiplex PCR-based and hybrid capture-based targeted next-generation sequencing [J]. EBioMedicine, 2024, 107 SUN W, ZHENG L, KANG L,et al. Comparative analysis of metagenomic and targeted next-generation sequencing for pathogens diagnosis in bronchoalveolar lavage fluid specimens [J]. Front Cell Infect Microbiol, 2024, 14 DALE DC. How I manage children with neutropenia [J]. British Journal of Haematology, 2017, 1783 BOCCIA R, GLASPY J, CRAWFORD J,et al. Chemotherapy-Induced Neutropenia and Febrile Neutropenia in the US: A Beast of Burden That Needs to Be Tamed? [J]. The Oncologist, 2022, 278 BONINE NG, BERGER A, ALTINCATAL A,et al. Impact of Delayed Appropriate Antibiotic Therapy on Patient Outcomes by Antibiotic Resistance Status From Serious Gram-negative Bacterial Infections [J]. Am J Med Sci, 2018, 3572 ZHU J, ZHOU K, JIANG Y,et al. Bacterial Pathogens Differed Between Neutropenic and Non-neutropenic Patients in the Same Hematological Ward: An 8-Year Survey [J]. Clinical Infectious Diseases: an Official Publication of the Infectious Diseases Society of America, 2018, 67suppl_2 GASTON DC, MILLER HB, FISSEL JA,et al. Evaluation of Metagenomic and Targeted Next-Generation Sequencing Workflows for Detection of Respiratory Pathogens from Bronchoalveolar Lavage Fluid Specimens [J]. Journal of Clinical Microbiology, 2022, 607 DIAO Z, HAN D, ZHANG R,et al. Metagenomics next-generation sequencing tests take the stage in the diagnosis of lower respiratory tract infections [J]. J Adv Res, 2021, 38 LOEFFEN EAH, KNOPS RRG, BOERHOF J,et al. Treatment-related mortality in children with cancer: Prevalence and risk factors [J]. European Journal of Cancer (Oxford, England: 1990), 2019, 121 Additional Declarations No competing interests reported. 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09:11:20","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":67730,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8485427/v1/80bd7ed98021ed2d6eeb64a0.html"},{"id":100367110,"identity":"e2023429-95e0-4158-ad72-e60de2e67ccd","added_by":"auto","created_at":"2026-01-16 07:56:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":374152,"visible":true,"origin":"","legend":"\u003cp\u003eSpectrum of pathogens detected pathogens by mNGS. (A) Spectrum of detected fungi by mNGS:\u003cem\u003e E.faecium(n=4), S.blood(n=1), S.pneumoniae(n=2), S.pyogenes(n=1), S.mitis(n=1), S.aureus(n=1), F.magna(n=1), K.rhizophila(n=1), N.farcinica(n=1), M.abscessus (n=1), A.pittii (n=1), A.baumannii(n=2), E.coli(n=5), E. asburiae(n=1), E.cloacae(n=2), P.mirabilis(n=1), Morganella, S.maltophilia(n=1), P.aeruginosa(n=5), L. pneumophila(n=1), K.oxytoca(n=1), K.aerogenes(n=1), K.Pneumoniae(n=1), H.segnis(n=1), H.parainfluenzae(n=1) , F.periodonticum(n=1)\u003c/em\u003e (B) Spectrum of fungi detected by mNGS: \u003cem\u003eC.albicans(n=5), C.parapsilosis(n=1), C.krusei(n=1), C.tropicalis(n=1), PJ:Pneumocystis jirovecii(n=3), Rhizopus microspores(n=2), S.cerevisiae(n=1), Mucor(n=1), C.elegans(n=1), A.flavus(n=3), A. fumigatus(n=1), and A.terreus(n=1)\u003c/em\u003e. (C) Spectrum of detected fungi by mNGS: TTV: \u003cem\u003eTorque teno virus\u003c/em\u003e, CMV\u003cem\u003e: Human betaherpesvirus5\u003c/em\u003e, HPV B19: \u003cem\u003eHuman parvovitus 19\u003c/em\u003e, JCPyV: \u003cem\u003eJC polyomavirus, \u003c/em\u003eEBV: \u003cem\u003eHuman gammaherpesvirus 4\u003c/em\u003e, HHV6: \u003cem\u003eRoseolovirus\u003c/em\u003e, HHV7: \u003cem\u003eHuman herpesvirus 7\u003c/em\u003e, BKPyV: \u003cem\u003eBK polyomavirus, \u003c/em\u003eGBV-C\u003cem\u003e: GB virus type C, SARS-CoV-2:\u003c/em\u003e \u003cem\u003eSevere acute respiratory syndrome coronavirus 2, RSV: Respiratory syncytial virus\u003c/em\u003e, HRV‑A: \u003cem\u003eHuman rhinovirus A, \u003c/em\u003eHSV1\u003cem\u003e: Human alphaherpesvirus1\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8485427/v1/04d5c806f28de12a8a8d95f9.png"},{"id":100124503,"identity":"8a69f00b-9661-4bf1-bd31-33f1679b1a18","added_by":"auto","created_at":"2026-01-13 09:11:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":234780,"visible":true,"origin":"","legend":"\u003cp\u003eComparative pathogen profiles in Groups A1 and A2: mNGS positivity, viremia, and bloodstream infections. A: NGS positivity. B: Viremia. C: Bacterial/Fungal. D: Monomicrobial or polymicrobial bacterial/fungal infections\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8485427/v1/5292e3c5f5cc78e93222f25e.png"},{"id":104779540,"identity":"790889fe-ab67-46ef-916d-136bf9c11140","added_by":"auto","created_at":"2026-03-17 07:41:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1326593,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8485427/v1/3502a69b-0981-44bc-9104-89e0645e5348.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Metagenomic NGS and Targeted NGS Driven Precision Therapy in Pediatric Chemotherapy-Associated Infections: A Single-Center Retrospective Study","fulltext":[{"header":"Background","content":"\u003cp\u003eAdvances in chemotherapy have significantly improved the cure rates of various pediatric hematological cancer particularly in acute lymphoblastic leukemia, and the 5-year OS can reach more than 90%\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. However, the efficacy of chemotherapy is accompanied by notable side effects that cannot be overlooked. Most chemotherapy regimens induce bone marrow suppression and compromised immunity in pediatric blood cancer patients, rendering them more susceptible to infections than healthy children\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. Infections are more likely to progress to sepsis, which can lead to severe complications such as septic shock, multiple organ failure, and potentially death, thereby impacting the prognosis of children with hematological cancer \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In the absence of a definitive pathogen, indiscriminate administration of broad-spectrum antibiotics may promote the emergence of multidrug-resistant bacteria\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Hence, a targeted antibiotic approach based on pathogen identification is preferable for promptly managing infections and mitigating the development of drug resistance.\u003c/p\u003e \u003cp\u003eMetagenomic next-generation sequencing(mNGS) is a new method for detecting pathogenic microorganisms. By sequencing the DNA or RNA of clinical samples, a variety of pathogenic microorganisms can be detected simultaneously, with a short detection time and high sensitivity\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. For children with blood cancer, it is important to identify whether fever is caused by infection early or identify pathogens early in infection to control complications and avoid delaying chemotherapy\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Furthermore, target next-generation sequencing (tNGS) offers distinct advantages for sputum and bronchoalveolar lavage fluid (BLAF) specimen analysis\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Unlike mNGS, it does not require host depletion and directly sequences targeted genomic regions, which reduces the required data volume. More importantly, tNGS employs targeted primers or probes to enrich microbial nucleic acids prior to sequencing, enabling the detection of low-abundance pathogens and thereby providing higher sensitivity than mNGS dose\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. This study collected the clinical data of children with cancer who underwent mNGS or tNGS, analyzed the susceptibility pathogen spectrum of children with blood cancer, and explored the application value of NGS (mNGS/ tNGS) in children with cancer.\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003e1.Patient\u003c/h3\u003e\n\u003cp\u003eThis study retrospectively collected data from tumorous children who visited our hospital for chemotherapy from January 1, 2022 to July 1, 2025, and NGS examination was performed during chemotherapy. Hematological cancers include acute lymphoblastic leukemia, acute myelogenous leukemia, and lymphoma. Children aged\u0026thinsp;\u0026ge;\u0026thinsp;1 and \u0026lt;\u0026thinsp;18 years.\u003c/p\u003e \u003cp\u003eANC\u0026thinsp;\u0026lt;\u0026thinsp;0.5\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L is defined as agranulocytosis\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. All the samples were processed for traditional pathogen detection (TPD). TPD included: cultures of blood, urine, stool, BLAF, sputum, pleural/ascitic fluid, and cerebrospinal fluid; cerebrospinal fluid smear and India ink staining; viral DNA detection; multiplex respiratory pathogen testing from throat swabs; and the T-SPOT assay.\u003c/p\u003e\n\u003ch3\u003e2. Metagenomic NGS and targeted NGS\u003c/h3\u003e\n\u003cp\u003emNGS: Samples (2 mL of EDTA blood; tissue/secretions/body fluids/CSF in sterile containers) were analyzed via a database of 25,863 pathogens (12,142 bacteria, 2,680 fungi, 206 mycobacteria, 120 mycoplasma/chlamydia, 7,369 DNA viruses, 2,692 RNA viruses, and 654 parasites).\u003c/p\u003e \u003cp\u003etNGS: Samples (deep sputum/BALF in sterile containers) were analyzed via a panel covering 302 pathogens (133 bacteria, 46 fungi, 110 DNA/RNA viruses, and 13 parasites) and 35 key resistance/virulence genes\u003c/p\u003e\n\u003ch3\u003e3. Statistical analysis\u003c/h3\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS 26.0. Continuous data were presented as median (interquartile range, IQR), and categorical data as n (%). Group comparisons for categorical variables were conducted using Fisher\u0026rsquo;s exact test, with a \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e\n\u003ch3\u003e4. Ethical considerations\u003c/h3\u003e\n\u003cp\u003e This study was conducted in accordance with the ethical standards stipulated in the Declaration of Helsinki of 1975. This study was approved by Tongji Medical College, Huazhong University of Science and Technology (Approval No. [2020] Lun Shen Zi (S278)). Written informed consent was obtained from all guardians, and the confidentiality of patient information was strictly maintained throughout the study.\u003c/p\u003e"},{"header":"Results","content":"\n\u003ch3\u003e1.Demographic and Clinical Characteristics of the Patients\u003c/h3\u003e\n\u003cp\u003eThis study enrolled 72 pediatric patients, among whom 49 were male and 23 were female. The cohort included 54 patients with acute leukemia and 18 patients with lymphoma. The median age of the patients was 8.0 years (IQR: 5.6\u0026thinsp;~\u0026thinsp;11.7 years). These patients underwent a total of 71 mNGS and 11 tNGS examinations. A total of 61 blood samples, 11 pulmonary-derived samples (including deep sputum and BLAF), 8 body fluid samples, and 2 tissue-derived samples were collected (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOn the day of NGS examination, the median white blood cell count was 2.09\u0026times;10⁹/L, and the median neutrophil count was 0.48\u0026times;10⁹/L. With respect to the patients' immunologic status during NGS testing, 51.2% were in a stage of agranulocytosis. Patients were stratified into Group A1 (non-agranulocytosis) and Group A2 (agranulocytosis).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatients and characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSEX\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49(68.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23(31.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnderlying disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute lymphoblastic leukemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45(62.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute myeloid leukemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9(12.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18(25.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSamples\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61(74.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary-derived samples\u003c/p\u003e \u003cp\u003edeep sputum\u003c/p\u003e \u003cp\u003ebronchoalveolar lavage fluid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11(13.4%)\u003c/p\u003e \u003cp\u003e7(8.5%)\u003c/p\u003e \u003cp\u003e4(4.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fluid samples\u003c/p\u003e \u003cp\u003esecretion\u003c/p\u003e \u003cp\u003ecerebrospinal-fluid\u003c/p\u003e \u003cp\u003epleural/ascitic-fluid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8(9.8%)\u003c/p\u003e \u003cp\u003e3(3.7%)\u003c/p\u003e \u003cp\u003e3(3.7%)\u003c/p\u003e \u003cp\u003e2(2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTissue-derived samples\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2(2.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutrophil count\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon- agranulocytosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40(48.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgranulocytosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42(51.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003e2. Pathogen Detection by NGS (mNGS/tNGS)\u003c/h3\u003e\n\u003cp\u003eNGS detected microbial nucleic acids in 70 of the 82 samples (85.4%). NGS revealed the presence of multiple pathogens, including 26 species of bacteria, 12 species of fungi, and 14 species of viruses (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the positive samples, pathogens were identified as follows: 66 with viruses, 42 with bacteria, and 21 with fungi. Among the samples tested, 43 were positive for bacteria and/or fungi. Analysis of the NGS-positive samples revealed that a single pathogen type (bacterial, fungal, or viral) (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47, 67.1%) was more common than co-infections with two or more pathogen types (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;23, 32.9%), which included 5 cases (7.1%) of bacterial-fungal co-injection. In terms of pathogen composition, single-bacterial infections (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20,28.6%) were more common than multi-bacterial infections (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8,11.4%), and single-fungal infections (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;11, 15.7%) outnumbered multi-fungal infections (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2,2.9%). A Fisher's exact test was conducted to compare the NGS positivity rates between groups A1 and A2, which demonstrated no statistically significant difference(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.374) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the bacterial isolates, 16 were gram-positive and 22 were gram-negative. Among the gram-positive isolates, \u003cem\u003eEnterococcus faecium\u003c/em\u003e was the most prevalent(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4), followed by \u003cem\u003eStaphylococcus aureus\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3). Of the gram-negative bacteria, \u003cem\u003eEnterobacteriaceae\u003c/em\u003e were the most frequently detected (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10), with \u003cem\u003eEscherichia coli\u003c/em\u003e being the most common species (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5). This was followed by \u003cem\u003eHalomonas\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6), 5 of which were \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e. \u003cem\u003eCandida\u003c/em\u003e was the predominant fungis(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8), with \u003cem\u003eCandida albicans\u003c/em\u003e being the most prevalent species(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5). Among all the detected viruses, the most prevalent was \u003cem\u003eHuman beta herpesvirus 5\u003c/em\u003e (CMV, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;21), followed by T\u003cem\u003eorque teno virus\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15) and \u003cem\u003eHuman gamma herpesvirus 4\u003c/em\u003e(EBV, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cb\u003e2.Pathogen Composition of Bloodstream Bacterial/Fungal Infections by mNGS\u003c/b\u003e\u003c/div\u003e \u003cp\u003eEvidence of bloodstream infections (BSI, bacterial/fungal) was found in 28 cases, and viremia was identified in 34 cases. The main bacterial isolate in blood samples was gram negative bacillus(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15). Among these the most common pathogens identified were \u003cem\u003eEscherichia coli\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5) and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) for bacteria; \u003cem\u003eAspergillus flavus\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3) for fungi; and EBV (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7) for viruses, respectively. A Fisher's exact test was conducted to compare viremia positivity between groups A1 and A2, which demonstrated no statistically significant difference(\u003cem\u003eP\u003c/em\u003e\u0026gt;0.999). In contrast, a Fisher's exact test on the disparity of BSI between groups A1 and A2 indicated that BSI was detected more frequently in group A2, and this difference was statistically significant(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023). Interestingly, a further comparison within BSI revealed no statistically significant difference in the distribution of monomicrobial versus polymicrobial infections between groups A1 and A2(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.319) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003e3. Pathogen Composition of Pulmonary Infections Detected by tNGS\u003c/h3\u003e\n\u003cp\u003eOf the 11 pulmonary-derived samples subjected to tNGS, the following pathogenic sources were identified as follows: viruses in 4 cases (EBV(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), SARS-CoV-2(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), \u003cem\u003eRespiratory Syncytial Virus\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), and \u003cem\u003eRhinovirus\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1)); fungi in 4 cases (\u003cem\u003eCandida albicans\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) and \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3)); and bacteria in 3 cases (\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1), and \u003cem\u003eStreptococcus pneumoniae\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1)). One case was coinfected with \u003cem\u003eHaemophilus parainfluenzae\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) and \u003cem\u003eCandida krusei\u003c/em\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1). Furthermore, concomitant chest CT scans were obtained in all cases during tNGS testing, and the radiographic findings demonstrated evidence of pulmonary infection of varying severity.\u003c/p\u003e\n\u003ch3\u003e4.Diagnostic Performance of NGS (mNGS/tNGS)\u003c/h3\u003e\n\u003cp\u003emNGS detected microbial nucleic acids in 49 of the 61 blood samples, yielding a positivity rate of 80.3%. Conventional blood culture was positive in only 7 cases (11.5%) (both of which were mNGS-positive). Similarly, all 11 pulmonary-derived samples were positive by tNGS. However, only 1 case was positive case by TPD. Notably, \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e was detected by tNGS in 3 cases, all of which were missed by TPD. Furthermore, mNGS/tNGS provides results within 48h with high sensitivity, whereas conventional culture typically requires approximately 5d and has a low positivity rate.\u003c/p\u003e\n\u003ch3\u003e5. Clinical Outcomes and Therapeutic Impact\u003c/h3\u003e\n\u003cp\u003eAmong the 43 samples with bacterial and/or fungal infections, 53.5% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;23) had their antimicrobial therapy adjusted based on the basis of the test results. The median treatment duration following this NGS-guided adjustment was 12.1 days (IQR:8\u0026thinsp;~\u0026thinsp;15d). The clinical outcomes were as follows: 88.4% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;38) achieved cure, 9.3% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4) died from septic shock, and 2.3%(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1) were lost to follow-up after treatment withdrawal due to severe infection.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe success of modern therapies for pediatric hematologic malignancies is tempered by the challenge of treatment-related complications. Myelosuppression, a near-universal adverse effect, entails a substantial clinical burden by prolonging hospitalization and risking mortality from severe infection\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Furthermore, in the context of severe infection, any delay in providing targeted antimicrobial therapy may lead to worse clinical outcomes, including extended hospitalization and increased mortality, alongside a significant economic burden\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. For children on chemotherapy, delays in infection control inevitably lead to postponement of chemotherapy, with potential consequences for the primary disease outcome. This study analyzed the pathogenic findings from NGS in pediatric hematology-oncology patients during chemotherapy, with the aim of improving pathogen diagnosis and guiding precise antimicrobial therapy for these immunocompromised children.\u003c/p\u003e \u003cp\u003eThis study revealed diverse pathogen profiles of 52 species (26 bacterial, 14 viral, and 12 fungal) in pediatric hematological cancer patients during chemotherapy. The spectrum included common pathogens such as \u003cem\u003eEscherichia coli\u003c/em\u003e and \u003cem\u003eCandida albicans\u003c/em\u003e alongside rare organisms such as \u003cem\u003eFinegoldia magna\u003c/em\u003e and \u003cem\u003eCunninghamella elegans\u003c/em\u003e, reflecting the profound immunosuppression from multiagent chemotherapy that enables opportunistic infections. In this study, \u003cem\u003eEscherichia coli\u003c/em\u003e was the most frequently detected bacterium in both overall and blood samples, aligning with previous reports that gram-negative bacteria (particularly \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and \u003cem\u003eE. coli\u003c/em\u003e) predominate in neutropenic patients, and that \u003cem\u003eE. coli\u003c/em\u003e is the most common pathogen in blood cultures\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. A total of 51.2% of patients had agranulocytosis at the time of NGS testing. The overall NGS positivity rate was comparable between the and non-agranulocytosis groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.374). However, further analysis of pathogen-specific profiles revealed that while the incidence of viremia in blood was similar between the groups, the agranulocytosis group had a significantly greater risk of bacterial and/or fungal infections(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023).\u003c/p\u003e \u003cp\u003eFor pulmonary infections, tNGS provides a rapid, accurate, and cost-effective diagnostic solution\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Previous studies in immunocompromised children have shown that tNGS has greater detection efficacy than mNGS does; tNGS most frequently detects \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e, \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e, CMV and EBV\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Our tNGS results identified \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e and EBV as the predominant fungal and viral pathogens, which is consistent with prior reports. Moreover, TPD failed to identify \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e.\u003c/p\u003e \u003cp\u003emNGS demonstrates superior performance over TPD in providing rapid, comprehensive, and accurate pathogen identification\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In this study, mNGS achieved a positivity rate of 80.3%, which was significantly higher than the 11.5% rate obtained by TPD, whereas mNGS detected a significant number of additional pathogens, notably missing all cases of viremia owing to the inherent limitations of TPD. Studies have established that infection represents the most frequent cause of treatment-related mortality in pediatric oncology patients, particularly those with hematologic malignancies\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. This finding underscores the critical importance of early pathogen identification and targeted antimicrobial therapy. In the present study, over half of the patients received antimicrobial regimen adjustments on the basis of NGS findings, suggesting that NGS testing can guide appropriate early intervention, especially when current anti-infective therapy is ineffective. While 88.4% patients in our cohort were successfully cured, 4 children unfortunately died due to progressive infection.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, pediatric hematological cancer patients who underwent mNGS/tNGS most frequently exhibited \u003cem\u003eEscherichia coli\u003c/em\u003e, \u003cem\u003eCandida albicans\u003c/em\u003e, and CMV. While the distribution of monomicrobial versus polymicrobial infections was not significantly different between agranulocytic and non-agranulocytic patients, the former demonstrated a higher detection rate of bacterial and/or fungal pathogens. mNGS/tNGS findings prove valuable in guiding appropriate antimicrobial therapy.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBLAF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBronchoalveolar lavage fluid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003emNGS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMetagenomic next generation sequencing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003etNGS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTargeted next generation sequencing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTPD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTraditional pathogen detection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCMV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eHuman beta herpesvirus 5\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEBV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003e \u003cem\u003eHuman gamma herpesvirus 4\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003enot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The procedures followed in this study were in accordance with principles of the Declaration of Helsinki (1964, amended most recently in 2008) of the World Medical Association and informed consent was obtained from all participants/parents/guardians. This study was approved by Tongji Medical College, Huazhong University of Science and Technology (Approval No. [2020] Lun Shen Zi (S207)).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eWritten informed consent was obtained from all guardians, and the confidentiality of patient information was strictly maintained throughout the study.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJianxin Dun: Conceptualization and writing the manuscriptAi Zhang: Investigation and methodologyAiguo Liu: Data CurationYaqin Wang: Data CurationQun Hu: Writing - Review \u0026amp; Editing\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eWe extend our sincere gratitude to all individuals who contributed to the completion of this research. Special thanks to the patient's family. Thank you to the editors for their meticulous attention to detail and invaluable contributions throughout the editing process. Your expertise and dedication have greatly enhanced the clarity and quality of this work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMALARD F, MOHTY M. Acute lymphoblastic leukaemia [J]. Lancet (London, England), 2020, 39510230\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eH\u0026auml;RTEL C, DEUSTER M, LEHRNBECHER T,et al. Current approaches for risk stratification of infectious complications in pediatric oncology [J]. Pediatric Blood \u0026amp; Cancer, 2007, 496\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVAN DE GEER A, ZANDSTRA J, TANCK MWT,et al. Biomarkers to predict infection and infection-related complications during chemotherapy‐induced neutropenia in acute myeloid leukaemia: a pilot study [J]. British Journal of Haematology, 2021, 1935\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIRFAN M, ALMOTIRI A, ALZEYADI ZA. Antimicrobial Resistance and Its Drivers\u0026mdash;A Review [J]. Antibiotics, 2022, 1110\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWENSEL CR, PLUZNICK JL, SALZBERG SL,et al. Next-generation sequencing: insights to advance clinical investigations of the microbiome [J]. The Journal of Clinical Investigation, 2022, 1327\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVOULGARIDOU A, ATHANASIADOU KI, ATHANASIADOU E,et al. Pulmonary Infectious Complications in Children with Hematologic Malignancies and Chemotherapy-Induced Neutropenia [J]. Diseases, 2020, 83\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYIN Y, ZHU P, GUO Y,et al. Enhancing lower respiratory tract infection diagnosis: implementation and clinical assessment of multiplex PCR-based and hybrid capture-based targeted next-generation sequencing [J]. EBioMedicine, 2024, 107\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSUN W, ZHENG L, KANG L,et al. Comparative analysis of metagenomic and targeted next-generation sequencing for pathogens diagnosis in bronchoalveolar lavage fluid specimens [J]. Front Cell Infect Microbiol, 2024, 14\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDALE DC. How I manage children with neutropenia [J]. British Journal of Haematology, 2017, 1783\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBOCCIA R, GLASPY J, CRAWFORD J,et al. Chemotherapy-Induced Neutropenia and Febrile Neutropenia in the US: A Beast of Burden That Needs to Be Tamed? [J]. The Oncologist, 2022, 278\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBONINE NG, BERGER A, ALTINCATAL A,et al. Impact of Delayed Appropriate Antibiotic Therapy on Patient Outcomes by Antibiotic Resistance Status From Serious Gram-negative Bacterial Infections [J]. Am J Med Sci, 2018, 3572\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZHU J, ZHOU K, JIANG Y,et al. Bacterial Pathogens Differed Between Neutropenic and Non-neutropenic Patients in the Same Hematological Ward: An 8-Year Survey [J]. Clinical Infectious Diseases: an Official Publication of the Infectious Diseases Society of America, 2018, 67suppl_2\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGASTON DC, MILLER HB, FISSEL JA,et al. Evaluation of Metagenomic and Targeted Next-Generation Sequencing Workflows for Detection of Respiratory Pathogens from Bronchoalveolar Lavage Fluid Specimens [J]. Journal of Clinical Microbiology, 2022, 607\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDIAO Z, HAN D, ZHANG R,et al. Metagenomics next-generation sequencing tests take the stage in the diagnosis of lower respiratory tract infections [J]. J Adv Res, 2021, 38\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLOEFFEN EAH, KNOPS RRG, BOERHOF J,et al. Treatment-related mortality in children with cancer: Prevalence and risk factors [J]. European Journal of Cancer (Oxford, England: 1990), 2019, 121\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Pediatric hematology-oncology, Next-generation sequencing, Pathogen spectrum, Bloodstream infection","lastPublishedDoi":"10.21203/rs.3.rs-8485427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8485427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eInfections in immunocompromised pediatric hematology-oncology patients present a major challenge. This study utilized pathogen NGS (metagenomic next generation sequencing (mNGS) / targeted next generation sequencing (tNGS)) to characterize the microbial spectrum in this population, thereby enhancing detection and enabling targeted antimicrobial therapy.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis retrospective study enrolled pediatric patients with hematologic malignancies. The analysis employed descriptive statistics for pathogen profiles and comparative statistics to assess variations by clinical stage and outcome, and to evaluate NGS against traditional pathogen detection (TPD).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study included 72 children with a median age of 8 years. A total of 83 NGS tests were performed. Microbial organisms were detected by NGS in 70 samples, yielding 26 bacterial, 14 viral, and 12 fungal species. No statistically significant difference in NGS positivity was observed between the non-agranulocytosis (A1) and agranulocytosis (A2) groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.374). \u003cem\u003eEscherichia coli (n\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5), \u003cem\u003eCandida albicans (n\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5), and \u003cem\u003eHuman beta herpesvirus 5\u003c/em\u003e (CMV, \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;21) were the most prevalent bacterial, fungal, and viral pathogens, respectively. Analysis of blood samples revealed that \u003cem\u003eEscherichia coli, Aspergillus flavus\u003c/em\u003e, and \u003cem\u003eHuman gamma herpesvirus 4\u003c/em\u003e(EBV) were the predominant bacterial, fungal, and viral pathogens, respectively. Statistical comparison revealed comparable rates of viremia between groups A1 and A2 (\u003cem\u003eP\u003c/em\u003e\u0026gt;0.999), whereas group A2 had a greater risk of bloodstream infection (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.023). Among the 61 blood samples, 49 (80.3%) were positive by mNGS, whereas only 7 were positive by TPD)(all of which were also mNGS-positive). All 11 pulmonary samples tested by tNGS were positive, while TPD was positive in only 1 specimen. tNGS identified \u003cem\u003ePneumocystis jirovecii\u003c/em\u003e in 3 samples, all of which were missed by TPD. NGS-guided antibiotic adjustment in 53.5% of patients with bacterial/fungal infections led to a favorable outcome, with an 88.4% cure rate after a median treatment of 12.1 days.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study identified predominant pathogens (\u003cem\u003eEscherichia coli\u003c/em\u003e. \u003cem\u003eCandida albicans\u003c/em\u003e s, CMV) and demonstrated that NGS, which is agranulocytosis, enhances detection of bacterial/fungal infections, enabling precision antimicrobial therapy in pediatric chemotherapy patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical trial number:\u003c/b\u003e\u003c/p\u003e \u003cp\u003enot applicable.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTrial registration:\u003c/b\u003e\u003c/p\u003e \u003cp\u003enot applicable.\u003c/p\u003e","manuscriptTitle":"Metagenomic NGS and Targeted NGS Driven Precision Therapy in Pediatric Chemotherapy-Associated Infections: A Single-Center Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-13 09:11:15","doi":"10.21203/rs.3.rs-8485427/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a69ce76-3279-4067-a076-5760154f13b4","owner":[],"postedDate":"January 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-07T21:23:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-13 09:11:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8485427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8485427","identity":"rs-8485427","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}