Onco-mNGS Facilitates Rapid and Precise Identification of The Etiology of Fever of Unknown Origin: A Single-centre Prospective Study in North China

Onco-mNGS Facilitates Rapid and Precise Identification of The Etiology of Fever of Unknown Origin: A Single-centre Prospective Study in North China | 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 Onco-mNGS Facilitates Rapid and Precise Identification of The Etiology of Fever of Unknown Origin: A Single-centre Prospective Study in North China Bingbing LIU, Tengfei Yu, Ruotong Ren, Na wu, Nanshu xing, Jingya wang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4463841/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Dec, 2024 Read the published version in BMC Infectious Diseases → Version 1 posted 10 You are reading this latest preprint version Abstract Objectives Delayed diagnosis of patients with Fever of Unknown Origin has long been a daunting clinical challenge. Onco-mNGS, which can accurately diagnose infectious agents and identify suspected tumor signatures by analyzing host chromosome copy number changes, has been widely used to assist identifying complex etiologies. However, the application of Onco-mNGS to improve FUO etiological screening has never been studied before. Methods In this single-centre prospective study, we included 65 patients with classic FUO, who were randomly divided into control group (sample cultivation) and mNGS group (cultivation + Onco-mNGS). We analyzed the infectious agents and symbiotic microbiological, tumor and clinical data of both groups. Results Infection-related pathogenic detection efficiency rose from 15.15% (control group) to 48.48% (experimental group). Seven patients with chromosome copy number changes had later been confirmed tumors, indicating a 100% of clinical concordance rate of Onco-mNGS. In addition, the time frame for diagnosing or ruling out infection/tumor with Onco-mNGS had greatly reduced to approximately 2 days, which was 7.34 days earlier than that in the control group. Conclusions Onco-mNGS is an ideal rapid diagnostic aid to assist improving the early diagnostic efficiency of FUO-associated diseases. Fever of unknown origin Onco-mNGS Etiology Diagnostic criteria Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Fever of Unknown Origin (FUO) is a clinical manifestation characterized by fever lasting over 3 weeks, oral temperature exceeding 38.3℃ on 3 occasions, or temperature fluctuating by over 1.2℃ within 1 day without confirmed diagnostic results after a week of thorough examinations in an outpatient or inpatient setting [ 1 ]. It is commonly observed in infectious diseases, neoplasm, immune and inflammatory processes [ 2 ]. Because of the etiological complexity, clinical diagnosis of FUO has long been a challenge for physicians. Although standardized diagnostic approach that being proposed by Ghady Haidar and Nina Singh [ 2 ] had improved the diagnostic efficiency of FUO to some extent, there were still 8.35% − 32% of FUO patients ended up with undiagnosed illness [ 3 – 7 ]. Among the documented etiologies that cause FUO, infections and neoplasms were the two leading causation [ 8 , 9 ]. Although numerous methods had been routinely used for infection- and neoplasm- diagnoses, disadvantages of these conventional approaches in FUO diagnoses irreversible started to emerge over time in clinical practices, especially for those caused by infections and neoplasms. For example, the diagnosis of infection commonly relied on sample cultivation, supplemented by PCR and immunological methods. However, apart from problems such as low pathogen detection rate and long diagnostic time that frequently occurred for these methods, they were unable to identify rare or unknown pathogens which might result in infection-mediated FUO. Moreover, clinical screening of malignancies generally involved abdominal ultrasound, posterior chest radiography, chest/abdomen/pelvis computed tomography (CT) scans, or puncture pathology biopsy [ 2 ], which were not only time-consuming but also with low-positive rates. With advances in technology, metagenomic next-generation sequencing (mNGS) that allows for unbiased identification of pathogenic microorganisms had been increasingly used for early diagnoses of infection-induced FUO [ 10 – 12 ]. However, conventional mNGS methods were applicable only for infection-associated diseases, but not for those caused by tumors. To fill in this technical gap, Onco-mNGS technology recently emerged which allowed precise identifications of both pathogens and human chromosome copy number variations (CNVs) in clinical samples with a one-step approach[ 13 – 15 ]. In our prior studies, Onco-mNGS had a sensitivity of 93.04% and a specificity of 60.00% for pathogenic identification [ 16 ], and a clinical compliance rate of 100% and a positive detection rate of 83.7% for aberrant tumour-associated CNV signals in body fluid samples[ 14 ]. In this study, we compared the diagnostic efficiency of between Onco-mNGS and conventional diagnostic methods in 65 classic FUO patients. Depending on the outstanding diagnostic efficacy of FUO in terms of detection sensitivity, accuracy, and time frame, we confirmed the avdantages of Onco-mNGS in complementing clinical diagnosis of FUO. Materials and methods Patients and study design This is a single-center prospective study which involves 65 patients with classic FUO at the First Affiliated Hospital of China Medical University between the 1st of May and 30th of September in 2021. The patients or their families provided consent for the samples before enrollment and signed the informed consent form for blood collection and study. The enrolled patients were randomly divided into experimental and control groups. They underwent routine biochemical tests, while samples were collected according to the clinical needs and synchronised for Onco- mNGS analysis and conventional microbiological cultures. The microbiological detection method was a combination of Onco-mNGS and culture in the experimental group and culture only in the control group. DNA extraction and mNGS Based on the mNGS Automatic Library Preparation System (Cat. MAR002, MatriDx Biotechnology Co., Ltd. Hangzhou, China), all clinical samples were subjected to DNA extraction, library preparation and mNGS (50-bp single-end reads; Illumina). The abbreviated steps were as follows: 1) DNA extraction and library preparation were performed on an NGS automated library preparation system. Relevant reagents include: Nucleic Acid Extraction Kit (Cat. MD013, MatriDx Biotechnology Co., Ltd. Hangzhou, China), Cell-free DNA Library Preparation Kit (blood samples) (Cat. MD007, MatriDx Biotechnology Co., Ltd., Hangzhou, China) and Total DNA Library Preparation Kit (other sample types) (Cat. MD001T, MatriDx Biotechnology Co., Ltd., China); 2) Libraries were pooled and then sequenced on an Illumina NextSeq500 system using a 75-cycle sequencing kit. CNV and Pathogen Detection With mNGS Data Simultaneously We used Onco-mNGs to look for both pathogen and tumor clues through mNGS data simultaneously. The method is as follows. Sequenced reads were first compared to the human reference genome (hg19) from the NCBI database, and only uniquely positioned reads were selected for subsequent analysis. The reference genome was partitioned into contiguous windows of fixed length, and read depths were calculated for each window and then normalised to the total number of reads per sample. The copy number ratio for each window was obtained by dividing the normalised read depth by the average read depth in the reference dataset. The copy number is then transformed to log2 and adjacent open frames with similar ratios are combined into segments annotated with chromosome position and average ratio. The copy number of each segment was calculated based on the mean ratio and normal copy number of the corresponding chromosome and then compared to a preset threshold to validate CNV. Clean reads obtained after raw data demultiplexing, adapter trimming and human reads removing were subjected to microbial identification based on a reference database containing over 20000 microorganisms. All species detected in clinical samples using mNGS are first filtered with all microorganisms detected in the parallel no template control (NTC) (background microorganisms) with a ratio of unique reads per million (RPM) above 10, and the RPM ratio = RPM sample /RPM NTC or RPM ratio = RPM sample if the organism was not detected in the parallel NTC. All the species authentically present in clinical samples are defined as microbiota. Substantially, all species of microbiota were looked up in PubMed ( https://pubmed.ncbi.nlm.nih.gov/ ) to determine whether the organisms cause infection and the positive pathogenic microorganisms were defined as pathogens. Finally, potential pathogens were selected from the results of previous analyses according to the clinical phenotype; these data were reviewed by senior clinicians. Diagnosis of Infection and Tumor The results of the etiological screening of the patients were evaluated by a panel of clinical experts, including three experienced physicians and a clinical microbiologists. MNGS results were interpreted according to the standard data processing workflow of MatriDx Biotechnology Co., Ltd.. Infections are diagnosed on the basis of microbiological tests, mNGS results and clinical review results. Tumors are judged on the basis of Onco-mNGS results in addition to histopathology, cytological examination, microscopic examination and other validation tests. Clinical impact was arbitrated by all authors according to the project's pre-defined clinical impact rubric after review and discussion of each case by the treatment team. Statistical Analysis Statistical analysis was performed by SPSS 26.0. Alpha diversity was estimated on the basis of the expression profile of each sample according to the Shanon, Simpson, simpson, Chao 1 index. Beta diversity was estimated by the Bray-Curtis dissimilarity between samples. A p -value < 0.05 was considered as statistically significant. Results Basic information of the enrolled patients Two of the 67 patients initially enrolled in this study were eliminated due to low validated mNGS data, and 65 were eventually enrolled, including 32 (49.23%) males and 33 (50.77%) females. These patients were randomly assigned to experimental (n = 33) and control (n = 32) groups, then undergoing the corresponding treatment protocols (Fig. 1 A). Table 1 and Supplementary Material Table S-1 listed the baseline and initial lab results. A total of 3 alveolar lavage, 3 pleural fluid, 2 cerebrospinal fluid, 1 sputum, 1 pericardial fluid, 1 bone marrow, 1 tissue, and 53 blood samples were included in this study (Fig. 1 B, 1 C and Supplementary Material Fig. S-1). Of the enrolled 65 patients, 59 (90.77%) were diagnosed after routine pathogenesis, imaging, Onco-mNGS testing or clinical experience of physicians, while 6 (9.23%) still had an unknown cause of fever after repeated testings. The confirmed cases included 28 cases (43.07%) of infections, 13 (20%) of tumors and 18 (27.69%) of other diseases(Fig. 1 D). mNGS improves pathogen detection rate Based on the Onco-mNGS results, 20 pathogens were found to be causative in the experimental group (48.48%, 16/33), while 6 were found in the control group (25%, 8/32). The predominant pathogens detected in both groups were bacteria and viruses, with the frequencies of detection being 13 and 10 for bacteria, and 7 and 1 for viruses, respectively. Of the 20 responsible pathogens detected in the experimental group, four were solely obtained by sample cultivation and 15 were detected by Onco-mNGS, while Enterococcus faecalis had been detected by both methods (Fig. 2 A). These pathogens were originated from 16 cases, 14 of which were detected by Onco-mNGS alone. These cases contained13 single bacterial or viral infections, and one mixed infection (Fig. 2 B). We also analysed the pathogen detection rates for cases of different etiology in experimental group: the pathogen detection rate for infectious FUO was 100% (13/13), which was significantly higher than those caused by tumour (50%, 4/8) and other causes like non-infectious non-tumour inflammation (55.56%, 5/9) (Fig. 2 C, 2 D). In addition to the responsible pathogens, microecology in blood samples from the experimental group has also been analysed. In the 25 blood samples, 49 genera and 84 species of bacteria were identified (Fig. 2 E). These microorganisms were analysed for alpha (Fig. 2 F) and beta (Supplementary Material Fig. S-2) diversity. With the significant indices of Shanon, Simpson, Invers. simpson and Chao 1 showing a substantial change in microecological richness and variety between infection and tumor group. The PCoA value of beta diversity analysis between infection and tumour groups showed a trend of evolutionary distance difference but no significant difference. The empirical use of antibiotics had less effect on the pathogen detection results of Onco-mNGS than culture To explore the impact of empirical antibiotic use on the test effectiveness of both methods, a statistical analysis about the empirical use of antibiotics and pathogen detection has been performed. There were 53 patients had empirical antibiotic history before microbiological detection. Of these patients, 36 used single antibiotic and 17 used combined antibiotics (Fig. 3 A and Supplementary Material Table S-2). Among the 29 patients in the experimental group who used antibiotics empirically, pathogens were detected in 13 cases (44.83%) by Onco-mNGS but only 4 (13.79%) by culture; among the 4 patients who did not use antibiotics, two methods both has detected 1 positive case (25%) (Fig. 3 B). This result showed that the use of antibiotics significantly reduced the culture detected efficiency, but has little effect on the Onco-mNGS results. After analyzing the clinical concordance between these two methods, the clinical committee found that Onco-mNGS had a clinical concordance rate of 72.4% (21/29) in empirical antibiotic used cases of the experimental group, compared to 65.5% (19/29) for culture. Both methods had 100% clinical concordance (4/4, 4/4) for patients not on antibiotics (Fig. 3 C). Onco-mNGS improves the efficiency of tumour diagnosis CNV analysis was performed on 33 samples from the experimental group to test the tumor screening capacity of Onco-mNGS. On average, about 21 million homo reads (ranging from 8.8 to 89 million) were obtained from each sample after excluding microbial sequences. These sequenced fragments were spliced and analysed against the normal human genome sequence (hg19), and the CNV abnormalities were determined by the correspondence of chromosomal and CNV wave maps (Fig. 4 A). The experimental group has seven aberrant CNV patients. Two of the patients (T-4, T-7) had previously been diagnosed as tumor patients, and one (T-5) had multiple lymph nodes in the abdominal cavity with abnormal CNV results, was considered a neoplasm. The rest of 4 patients (T-2, T-3, T-6, T-8) confirmed tumors through immunohistochemical (Supplementary Material Table S-3) or pathological staining (Fig. 4 A and supplementary material Fig. S-3) results. Further analysis of CNV variant sites showed that bladder cancer patients had 79.17% (19/24) variant sites, lymphoma patients had 36.46% (8.75/24) chromosomal mutations on average(Fig. 4 B, 4 C). The results above showed that Onco-mNGS has 100% of specificity and 87.5% of sensitivity for cancer screening (Supplementary Material Fig. S-4). Notably, lymphoma was diagnosed in four of these seven patients (57.14%). One patient who was negative for CNV by Onco-mNGS but had a clinically confirmed tumour was confirmed as pleural mesothelioma by CT and pleural fluid cytology. Onco-mNGS significantly reduces the diagnostic time We compared the time needed for diagnosing or ruling out infection/tumor of the two groups. The average time period for experimental group (n = 30) clarify or ruling out infection/tumor was 7.3 days shorter than that of the control group (n = 29) (Supplementary Material Fig. S-5A). In addition, We investigated the implications of Onco-mNGS for the clinical management of FUO patients. 17 of 33 experimental group patients stopped application of antibiotics after the causative agents being identified or excluded and 9 patients were transferred to other departments for further treatment. The clinical committee concluded that the Onco-mNGS results had positive implications for the diagnosis and clinical management of these 26 patients (Supplementary Material Fig. S-5B). The remaining 7 patients had a final diagnosis of inflammatory diseases or early neoplastic stage confirmed by clinical combination of antigen/antibody testing, pathology, ultrasound or CT. Discussion More than 200 etiologies have been documented to contribute to FUO [ 5 , 6 , 17 ]. The standardized diagnostic procedure proposed by Ghady Haidar et al. [ 2 ]combined understanding the natural history, routine biochemical tests, and other imaging techniques to diagnose FUO. Unfortunately, this strategy is basically inaccurate, low-efficient and largely dependent on the external environment, experiences of clinicians, and characteristics of patients. Therefore, increasing clinical research has focused on improving the efficiency and accuracy of FUO etiological diagnosis. Infection and tumor are the main causes of FUO, and William F. Wright et al. [ 9 ] observed in a large literature research that 37% of FUO patients had infectious illnesses. Current clinical diagnosis of infection is mostly based on microbiology laboratory culture results, which relies heavily on the physician's clinical experience, the standardization of the laboratory testing process, and the patient's epidemiological information. This method has low controllability and is unfavorable for detecting rare and emerging pathogens. In recent years, the methods of testing for FUO pathology have been continuously optimized. For example, Wanru Guo et al. [ 18 ] attempted to use complete exome sequencing technology to address the problem of FUO tumour screening. Kim-Heang Ly [ 19 ], Friedrich Weitzer [ 20 ], applied F-18 FDG PET/CT to the etiological screening of inflammatory FUO patients and compared PET/CT with thoracoabdominal-pelvic CT (CAP-CT) in terms of diagnostic direction, contribution and time. They showed that PET/CT screened FUO patients faster and more efficiently than CAP-CT and proposed using F-18 FDG PET/CT to help diagnose early. However, these approaches only screen for one etiology of FUO. Thus, a non-invasive test that can detect both pathogens and tumors would greatly improve the efficiency of FUO aetiology screen. As an emerging molecular diagnostic technique, mNGS is increasingly used to screen pathogens in patients with suspected infections. This approach detects pathogenic gene sequences, hence it is not useful for diagnosing non-infectious disorders yet. To fill this technical gap, the new technology Onco-mNGS is being employed in clinic from 2022. This technique superimposes chromosomal CNV analysis on top of the mNGS technology, allowing simultaneous screening for infections and tumours [ 15 ]. Our study examined the use of Onco-mNGS in FUO etiological screening and found the following. Firstly, Onco-mNGS is useful for clinical aetiological screening. In this study, we found that the experimental group had significantly higher detection efficiency than the control group in terms of pathogen type (20 vs. 6), number (23 vs. 8) and detection rate (48.48% vs. 25%). Moreover, Onco-mNGS is useful in detecting clinically emerging, rare and uncommon pathogens. This study found 16 responsible pathogens via Onco-mNGS, including Coxiella burneti , Mycobacterium intracellulare , Mycobacterium torulare , and viruses, which are harder to culture. C. burneti is an internal parasitic bacterium that eludes clinical microbiological culture procedures like Petri dishes [ 21 ], while microorganisms of the genus Mycobacterium and viruses are often more difficult to achieve in clinical culture due to the harsh culture conditions or long culture cycles. In addition to identify the responsible pathogens, Onco-mNGS is also able to output human microecological data simultaneously. In this study, we analyzed 25 blood samples from the experimental group and found that patients with infection-associated FUO had higher abundance of blood microecology than those with other etiologies and that the diversity of microecological populations were significantly different from the tumor group. High abundance of human microecology has been progressively shown to be strongly associated with the development of infections, tumors and other diseases. Kypros Dereschuk et al. found [ 22 ] the abundance of six microorganisms was associated with the severity of COVID-19, while the abundance of Bacillus subtilis had a positive correlation with the improvement of COVID-19. Thus, Onco-mNGS microbiome data can be used by clinicians to anticipate disease progression where the microbiota-disease association is extensively characterized. Onco-mNGS could also screen abnormal CNV signals in human genome, which allows for effective early warning of tumors. The current gold standard for tumor diagnosis is pathological biopsy, however, this invasive technique required clinical confirmation of the tumor site, resulting its limited application in clinical practices. Onco-mNGS, on the other hand, is a simple and highly accurate method of screening for abnormal CNV signals using only a blood test, and can be used as a broad-spectrum early screening aid for tumors. The seven patients described in this study underwent abnormal blood CNV tests, all but two of whom had previously diagnosed tumors, and five were first diagnosed by clinical tumor screening after Onco-mNGS early warning. It was also noticeable that, a patient with a normal CNV signal but a clinically confirmed malignant pleural mesothelioma. The missed detection by Onco-mNGS in this patient might be associated with the lower mutant gene load in the blood as seen in other researches. For instance, Raphael Bueno et al. [ 23 ] sequenced 216 malignant pleural mesothelioma patients and found that the somatic point mutation rate of protein changes was lower than in other solid malignancies. In another cohort of 74 malignant pleural mesotheliomas, whole-exome sequencing confirmed an overall incidence of < 2 bases/M for non-synonymous mutations in all samples except for one sample with a mutation of < 8 bases/M [ 24 ]. It indicated that Onco-mNGS for CNV signalling screening is best for samples with high abnormal cell content, such as haematological tumors and tumor systemic metastases, but its sensitivity is low for early tumor or tumor with low somatic point mutation rates. Meanwhile, multipoint detection should improve the detection sensitivity. Sencondly, Onco-mNGS offers advantages in adapting clinical antibiotic regimens for FUO. In our study, up to 81.5% of febrile patients were empirically treated with antibiotics before diagnosis, some even with carbapenem or a combination of broad-spectrum antibiotics, but generally with poor outcomes. Although empirical antibiotic therapy is indicated in critical FUO patients with no definite cause but a strong suspicion of infection, many doctors are urging caution. William F. Wright [ 1 ] et al. suggested that the empirical use of antibiotics should be avoided except in cases where the patient's condition is urgent and severe, as this may complicate the final diagnosis, and S. Vanderschueren [ 25 ] et al. found in a study on the prognosis of FUO patients that empirical antibiotics were not needed for stable patients. Overuse of antibiotics often poses a threat of resistance to clinical anti-infective therapy [ 26 ], so early diagnosis and rational adjustment of antibiotics are important in the management of FUO. In this project, 24 patients (72.7%) in the experimental group adjusted or discontinued antibiotics after applying Onco-mNGS to identify the cause of the disease, and they had a good prognosis. Thirdly, Onco-mNGS significantly shortens the time for the FUO etiological screening. The time for Onco-mNGS is 13–15 hours, compared to 2–5 days[ 27 , 28 ] for cultures and even longer for tumor screening. In this study, 59 patients have been confirmed the etiology. The mean time period to clarify or exclude infection/tumor in the experimental group was approximately 7.3 days shorter than that of the control group, which greatly improved the efficiency of aetiological screening for FUO. In summary, Onco-mNGS has significantly contributed to the improvement of the aetiological diagnosis of FUO in terms of sensitivity, specificity, accuracy and timeliness. We suggest patients admitted to the hospital after a Minimal FUO test fail to confirm the diagnosis immediately undergo Onco-mNGS testing to improve early diagnosis. Declarations Author contributions LB is the primary physician who provides diagnosis and treatment of the patients. LB, YT and RR collected and analyzed clinical and sequencing data. WN, XN, WJ and LB are the principle members of the panel of clinical experts. LB, YT, RR, CX, WW and ZJ wrote the manuscript. All authors have read and approved the final version of the manuscript. Funding This work was supported by grants from the Liaoning Provincial Key Research and Development Program of Development of Science and Technology (Grant No. 2020JH2/10300040), the Science Foundation for the State Key Laboratory for Infectious Disease Prevention and Control of China (Grant No. 2022SKLID308) and Project for Basic Research by the Education Department of Liaoning Province (Grant No. JYTMS20230072). Data Availability The datasets presented in this study can be found in NCBI with the SRA accession no. PRJNA865023. The raw data of the chromosome copy variation and the picture of each patient were deposited in, or linked to, Zenodo (https://zenodo.org/record/7982217). Ethics Statement The studies involving human participants were reviewed and approved by the board of Ethics at The First Hospital of China Medical University. The patients provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article. The study was conducted in accordance with the International Conference on Harmonization, Good Clinical Practice Guidelines, and the Declaration of Helsinki. Conflicts of Interest Authors YT, RR, CX and WW are employed by MatriDx Biotechnology Co., Ltd. Author RR is also employed by Micro-Health Biotechnology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Acknowledgments Authors are thankful to Department of Infectious Diseases of The First Hospital of China Medical University medical staff for helping in sample collection. References Wright WF, Mulders-Manders CM, Auwaerter PG, Bleeker-Rovers CP. 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Hmeljak J, Sanchez-Vega F, Hoadley KA, Shih J, Stewart C, Heiman D, Tarpey P, Danilova L, Drill E, Gibb EA, Bowlby R, Kanchi R, Osmanbeyoglu HU, Sekido Y, Takeshita J, Newton Y, Graim K, Gupta M, Gay CM, Diao L, Gibbs DL, Thorsson V, Iype L, Kantheti H, Severson DT, Ravegnini G, Desmeules P, Jungbluth AA, Travis WD, Dacic S, Chirieac LR, Galateau-Sallé F, Fujimoto J, Husain AN, Silveira HC, Rusch VW, Rintoul RC, Pass H, Kindler H, Zauderer MG, Kwiatkowski DJ, Bueno R, Tsao AS, Creaney J, Lichtenberg T, Leraas K, Bowen J, Felau I, Zenklusen JC, Akbani R, Cherniack AD, Byers LA, Noble MS, Fletcher JA, Robertson AG, Shen R, Aburatani H, Robinson BW, Campbell P. M. Ladanyi, Integrative Molecular Characterization of Malignant Pleural Mesothelioma, Cancer Discov., 8 (2018) 1548–65. Vanderschueren S, Eyckmans T, De Munter P, Knockaert D. Mortality in patients presenting with fever of unknown origin. Acta Clin Belg. 2014;69:12–6. Septimus EJ. Antimicrobial Resistance: An Antimicrobial/Diagnostic Stewardship and Infection Prevention Approach, Med. Clin North Am. 2018;102:819–29. Maurer FP, Christner M, Hentschke M, Rohde H. Advances in Rapid Identification and Susceptibility Testing of Bacteria in the Clinical Microbiology Laboratory: Implications for Patient Care and Antimicrobial Stewardship Programs, Infect. Dis Rep. 2017;9:6839. Mendonça A, Santos H, Franco-Duarte R, Sampaio P. Fungal infections diagnosis - Past, present and future. Res Microbiol. 2022;173:103915. Table Table 1 is available in the Supplementary Files section. Supplementary Figure Supplementary Figure 2 are not available with this version Additional Declarations No competing interests reported. Supplementary Files Table1.pdf SupplementaryFig.1.tif Supplementary Figure 1 Samples composition of enrolled patients. SupplementaryFig.3.tif Supplementary Figure 3 CNV signal pattern of patients with tumor etiology of FUO. These images show abnormal CNVs of patients (T-2, T-4, T-5, T-6, T-7). SupplementaryFig.4.tif Supplementary Figure 4 CNV contingency table. The clinical gold standard is histopathological examination, cytological examination or microscopic examination. SupplementaryFig.5.tif Supplementary Figure 5 The significance of Onco-mNGS detection in clinical diagnosis and treatment. A) The time to clinical identification or exclusion of infection/tumor was significantly shortened in the experimental and control groups, B) The treatment group combined with the clinical situation to analyze the clinical diagnosis or therapeutic significance of the results of Onco-mNGS, Significance (n=26), Insignificance (n=7), p＜0.01. SupplementaryTableS1.pdf SupplementaryTableS2.pdf SupplementaryTableS3.pdf Cite Share Download PDF Status: Published Journal Publication published 28 Dec, 2024 Read the published version in BMC Infectious Diseases → Version 1 posted Editorial decision: Revision requested 20 Aug, 2024 Reviews received at journal 19 Aug, 2024 Reviewers agreed at journal 29 Jul, 2024 Reviews received at journal 09 Jul, 2024 Reviewers agreed at journal 29 Jun, 2024 Reviewers invited by journal 31 May, 2024 Editor invited by journal 27 May, 2024 Editor assigned by journal 24 May, 2024 Submission checks completed at journal 24 May, 2024 First submitted to journal 22 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4463841","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":310357716,"identity":"a3aaa2be-8fc0-4216-88b6-32a1736800a9","order_by":0,"name":"Bingbing LIU","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Bingbing","middleName":"","lastName":"LIU","suffix":""},{"id":310357722,"identity":"1750182d-0e22-4b9d-b339-8b64220c5c0e","order_by":1,"name":"Tengfei Yu","email":"","orcid":"","institution":"Institute of Innovative Applications, MatriDx Biotechnology Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Tengfei","middleName":"","lastName":"Yu","suffix":""},{"id":310357723,"identity":"75a96fe8-6c79-463c-9398-52f375fc7e81","order_by":2,"name":"Ruotong Ren","email":"","orcid":"","institution":"Micro-Health Biotechnology Co., Ltd.","correspondingAuthor":false,"prefix":"","firstName":"Ruotong","middleName":"","lastName":"Ren","suffix":""},{"id":310357724,"identity":"4a0f2d7e-2691-4a73-9fa6-cc1f068c2614","order_by":3,"name":"Na wu","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"wu","suffix":""},{"id":310357728,"identity":"1a06cd5f-75f0-4c6a-8a0e-6a4acf626eed","order_by":4,"name":"Nanshu xing","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Nanshu","middleName":"","lastName":"xing","suffix":""},{"id":310357729,"identity":"14cbdd34-acf8-4984-96a3-9091e148998e","order_by":5,"name":"Jingya wang","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jingya","middleName":"","lastName":"wang","suffix":""},{"id":310357735,"identity":"eeb99f54-6ede-4e4e-948c-02a7e492b679","order_by":6,"name":"Wenjie wu","email":"","orcid":"","institution":"Institute of Innovative Applications, MatriDx Biotechnology Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Wenjie","middleName":"","lastName":"wu","suffix":""},{"id":310357743,"identity":"6bc1d445-6b99-432d-92a4-a3792bf4140a","order_by":7,"name":"Xuefang cao","email":"","orcid":"","institution":"Institute of Innovative Applications, MatriDx Biotechnology Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Xuefang","middleName":"","lastName":"cao","suffix":""},{"id":310357744,"identity":"687c4552-dbb3-42a3-ac20-feeb636b6716","order_by":8,"name":"Jingping Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYFCCA4wPEipqePjZGxsffiBSC7PBhzPH5CR7DjcbSxBpDZvkzDZmY4Mb6W0CPMSol288e9iYt40tseHmwzYGCQY7Od0GAloYG84lPuY5J5PYODux7UEBQ7Kx2QECWpgZzhgb85SxJTZLJ7YbSDAcSNxGSAsbwxkzaR425sQ2yYNtEjzEaOEBapGcAfQ+jwQjkVokGM4lgwNZgicRGMgGRPhFfsbZg+CotD9+/OHDDxV2cgS1MEicQeYZEFIOAvw9xKgaBaNgFIyCEQ0AIoNFg0N4V8QAAAAASUVORK5CYII=","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":true,"prefix":"","firstName":"Jingping","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-05-23 03:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4463841/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4463841/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12879-024-10383-3","type":"published","date":"2024-12-28T15:57:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58148005,"identity":"3af3b614-4de2-4a8a-a7b9-301a0dfe72ac","added_by":"auto","created_at":"2024-06-11 18:49:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":416191,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of Research, Clinical grouping and patient distribution.\u003c/strong\u003e A) Flowchart of this research, B) Sample types in Control group, C) Sample types in Experimental group, D) Patient distribution with four different etiologies in two groups.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/68eda20530fc50d679f18c12.jpg"},{"id":58147360,"identity":"cfa39760-1c8e-49b5-9d53-d7caae5b260e","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":565507,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of the efficacy of Onco-mNGS and conventional culture methods for pathogenicity detection in the experimental group. \u003c/strong\u003eA) Analysis of responsible pathogens detected by Onco-mNGS and conventional culture methods, B) Types of pathogens in infected cases, C) The distribution pattern of bacteria, fungi and virus identified by Onco-mNGS in patients with different etiology, D) Difference analysis of the abundance and frequency in three different types of responsible pathogens (bacteria, fungi, and viruses) identified by Onco-mNGS, E) The microecological heatmap of blood samples showed that the infected patients had higher level of microecology diversity than the other groups, F) Alpha diversity analysis of microecology of patients with different etiology in the experimental group. Infection, n=8; Tumor, n=9; Other, n=4; ND, n=3. p＜0.05, *, p＜0.01, **.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/3d2e5af75f84f00a43a0d792.jpg"},{"id":58147363,"identity":"8635f7e3-fa50-41e2-bb74-86f9db41b2f0","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":214645,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnalysis of empirical antibiotic use in experimental group.\u003c/strong\u003e A) Most patients in both experimental group and control group used antibiotics empirically, B) Among the empirical anti-infective cases, 4 cases were positive from traditional culture, and 13 cases were positive from Onco-mNGS, C) Analysis of consistency between culture and Onco-mNGS detection results and clinical diagnosis in empirical anti-infective cases.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/f6c1d0d08131f13cd8939dc4.jpg"},{"id":58147368,"identity":"1de335ec-1a87-454f-b4fa-91f934267b99","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":380186,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCNV analysis in patients with tumor etiology of FUO.\u003c/strong\u003e A) Abnormal CNV signals in tumor patients and their pathological findings: T-3 was bone biopsy, T-8 was bone marrow biopsy, B) Chromosome variation types of 7 CNV positive patients, C) The chromosomal variation types of different cancer species showed the solid tumor has more variation sites.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/616d1865c04e7dfc5fb91c8f.jpg"},{"id":72640739,"identity":"32d6b660-7f33-4352-9808-d56a05b7aaee","added_by":"auto","created_at":"2024-12-30 16:09:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2132056,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/c18379bb-a8d0-4f1f-8a78-718828fb8691.pdf"},{"id":58148006,"identity":"e6e4037d-8fae-47ae-a40c-d6a1fb1b4c3e","added_by":"auto","created_at":"2024-06-11 18:49:57","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":67886,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/97aa5a48497c3c83417e4f46.pdf"},{"id":58147366,"identity":"030ea0eb-b919-413b-8a1c-5451d74df112","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2380140,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1 Samples composition of enrolled patients.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"SupplementaryFig.1.tif","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/bf149241210188bd1cc906a0.tif"},{"id":58147371,"identity":"e0bba9a3-d659-4b9e-9453-cb465d2cf4b9","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13539740,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 3 CNV signal pattern of patients with tumor etiology of FUO. \u003c/strong\u003eThese images show abnormal CNVs of patients (T-2, T-4, T-5, T-6, T-7).\u003c/p\u003e","description":"","filename":"SupplementaryFig.3.tif","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/f25b74feb1d13cca214f9c26.tif"},{"id":58147370,"identity":"fdb7a1d0-070b-4256-9358-66661c900358","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"tif","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":9107464,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 4 CNV contingency table. \u003c/strong\u003eThe clinical gold standard is histopathological examination, cytological examination or microscopic examination.\u003c/p\u003e","description":"","filename":"SupplementaryFig.4.tif","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/37ecca35614c1caa9f56dc84.tif"},{"id":58147367,"identity":"fef9b5ab-f795-4852-aacd-e126303dc144","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"tif","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":7501956,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 5 The significance of Onco-mNGS detection in clinical diagnosis and treatment. \u003c/strong\u003eA) The time to clinical identification or exclusion of infection/tumor was significantly shortened in the experimental and control groups, B) The treatment group combined with the clinical situation to analyze the clinical diagnosis or therapeutic significance of the results of Onco-mNGS, Significance (n=26), Insignificance (n=7), p＜0.01.\u003c/p\u003e","description":"","filename":"SupplementaryFig.5.tif","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/e1f241fb4685cc71cccfbe3b.tif"},{"id":58148009,"identity":"aef1a04f-51ad-4ed7-beac-251be865cc4c","added_by":"auto","created_at":"2024-06-11 18:49:57","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":71174,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/3757f9ce15597e65326e2600.pdf"},{"id":58147364,"identity":"86898bb2-926c-4f58-94ed-c58abee8f80e","added_by":"auto","created_at":"2024-06-11 18:41:57","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":35974,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/37448fa8c28e76a095f92c1b.pdf"},{"id":58148008,"identity":"9dcc8397-3617-44e3-b665-ee985537a125","added_by":"auto","created_at":"2024-06-11 18:49:57","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":126458,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4463841/v1/3f651f75069a5c322afce3cf.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Onco-mNGS Facilitates Rapid and Precise Identification of The Etiology of Fever of Unknown Origin: A Single-centre Prospective Study in North China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eFever of Unknown Origin (FUO) is a clinical manifestation characterized by fever lasting over 3 weeks, oral temperature exceeding 38.3℃ on 3 occasions, or temperature fluctuating by over 1.2℃ within 1 day without confirmed diagnostic results after a week of thorough examinations in an outpatient or inpatient setting [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is commonly observed in infectious diseases, neoplasm, immune and inflammatory processes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Because of the etiological complexity, clinical diagnosis of FUO has long been a challenge for physicians. Although standardized diagnostic approach that being proposed by Ghady Haidar and Nina Singh [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] had improved the diagnostic efficiency of FUO to some extent, there were still 8.35% \u0026minus;\u0026thinsp;32% of FUO patients ended up with undiagnosed illness [\u003cspan additionalcitationids=\"CR4 CR5 CR6\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong the documented etiologies that cause FUO, infections and neoplasms were the two leading causation [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although numerous methods had been routinely used for infection- and neoplasm- diagnoses, disadvantages of these conventional approaches in FUO diagnoses irreversible started to emerge over time in clinical practices, especially for those caused by infections and neoplasms. For example, the diagnosis of infection commonly relied on sample cultivation, supplemented by PCR and immunological methods. However, apart from problems such as low pathogen detection rate and long diagnostic time that frequently occurred for these methods, they were unable to identify rare or unknown pathogens which might result in infection-mediated FUO. Moreover, clinical screening of malignancies generally involved abdominal ultrasound, posterior chest radiography, chest/abdomen/pelvis computed tomography (CT) scans, or puncture pathology biopsy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], which were not only time-consuming but also with low-positive rates.\u003c/p\u003e \u003cp\u003eWith advances in technology, metagenomic next-generation sequencing (mNGS) that allows for unbiased identification of pathogenic microorganisms had been increasingly used for early diagnoses of infection-induced FUO [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, conventional mNGS methods were applicable only for infection-associated diseases, but not for those caused by tumors. To fill in this technical gap, Onco-mNGS technology recently emerged which allowed precise identifications of both pathogens and human chromosome copy number variations (CNVs) in clinical samples with a one-step approach[\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In our prior studies, Onco-mNGS had a sensitivity of 93.04% and a specificity of 60.00% for pathogenic identification [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and a clinical compliance rate of 100% and a positive detection rate of 83.7% for aberrant tumour-associated CNV signals in body fluid samples[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we compared the diagnostic efficiency of between Onco-mNGS and conventional diagnostic methods in 65 classic FUO patients. Depending on the outstanding diagnostic efficacy of FUO in terms of detection sensitivity, accuracy, and time frame, we confirmed the avdantages of Onco-mNGS in complementing clinical diagnosis of FUO.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and study design\u003c/h2\u003e \u003cp\u003eThis is a single-center prospective study which involves 65 patients with classic FUO at the First Affiliated Hospital of China Medical University between the 1st of May and 30th of September in 2021. The patients or their families provided consent for the samples before enrollment and signed the informed consent form for blood collection and study.\u003c/p\u003e \u003cp\u003eThe enrolled patients were randomly divided into experimental and control groups. They underwent routine biochemical tests, while samples were collected according to the clinical needs and synchronised for Onco- mNGS analysis and conventional microbiological cultures. The microbiological detection method was a combination of Onco-mNGS and culture in the experimental group and culture only in the control group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction and mNGS\u003c/h2\u003e \u003cp\u003eBased on the mNGS Automatic Library Preparation System (Cat. MAR002, MatriDx Biotechnology Co., Ltd. Hangzhou, China), all clinical samples were subjected to DNA extraction, library preparation and mNGS (50-bp single-end reads; Illumina). The abbreviated steps were as follows: 1) DNA extraction and library preparation were performed on an NGS automated library preparation system. Relevant reagents include: Nucleic Acid Extraction Kit (Cat. MD013, MatriDx Biotechnology Co., Ltd. Hangzhou, China), Cell-free DNA Library Preparation Kit (blood samples) (Cat. MD007, MatriDx Biotechnology Co., Ltd., Hangzhou, China) and Total DNA Library Preparation Kit (other sample types) (Cat. MD001T, MatriDx Biotechnology Co., Ltd., China); 2) Libraries were pooled and then sequenced on an Illumina NextSeq500 system using a 75-cycle sequencing kit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCNV and Pathogen Detection With mNGS Data Simultaneously\u003c/h2\u003e \u003cp\u003eWe used Onco-mNGs to look for both pathogen and tumor clues through mNGS data simultaneously. The method is as follows. Sequenced reads were first compared to the human reference genome (hg19) from the NCBI database, and only uniquely positioned reads were selected for subsequent analysis. The reference genome was partitioned into contiguous windows of fixed length, and read depths were calculated for each window and then normalised to the total number of reads per sample. The copy number ratio for each window was obtained by dividing the normalised read depth by the average read depth in the reference dataset. The copy number is then transformed to log2 and adjacent open frames with similar ratios are combined into segments annotated with chromosome position and average ratio. The copy number of each segment was calculated based on the mean ratio and normal copy number of the corresponding chromosome and then compared to a preset threshold to validate CNV.\u003c/p\u003e \u003cp\u003eClean reads obtained after raw data demultiplexing, adapter trimming and human reads removing were subjected to microbial identification based on a reference database containing over 20000 microorganisms. All species detected in clinical samples using mNGS are first filtered with all microorganisms detected in the parallel no template control (NTC) (background microorganisms) with a ratio of unique reads per million (RPM) above 10, and the RPM ratio\u0026thinsp;=\u0026thinsp;RPM\u003csub\u003esample\u003c/sub\u003e/RPM\u003csub\u003eNTC\u003c/sub\u003e or RPM ratio\u0026thinsp;=\u0026thinsp;RPM\u003csub\u003esample\u003c/sub\u003e if the organism was not detected in the parallel NTC. All the species authentically present in clinical samples are defined as microbiota. Substantially, all species of microbiota were looked up in PubMed (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to determine whether the organisms cause infection and the positive pathogenic microorganisms were defined as pathogens. Finally, potential pathogens were selected from the results of previous analyses according to the clinical phenotype; these data were reviewed by senior clinicians.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDiagnosis of Infection and Tumor\u003c/h2\u003e \u003cp\u003eThe results of the etiological screening of the patients were evaluated by a panel of clinical experts, including three experienced physicians and a clinical microbiologists. MNGS results were interpreted according to the standard data processing workflow of MatriDx Biotechnology Co., Ltd.. Infections are diagnosed on the basis of microbiological tests, mNGS results and clinical review results. Tumors are judged on the basis of Onco-mNGS results in addition to histopathology, cytological examination, microscopic examination and other validation tests. Clinical impact was arbitrated by all authors according to the project's pre-defined clinical impact rubric after review and discussion of each case by the treatment team.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed by SPSS 26.0. Alpha diversity was estimated on the basis of the expression profile of each sample according to the Shanon, Simpson, simpson, Chao 1 index. Beta diversity was estimated by the Bray-Curtis dissimilarity between samples. A \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBasic information of the enrolled patients\u003c/h2\u003e \u003cp\u003eTwo of the 67 patients initially enrolled in this study were eliminated due to low validated mNGS data, and 65 were eventually enrolled, including 32 (49.23%) males and 33 (50.77%) females. These patients were randomly assigned to experimental (n\u0026thinsp;=\u0026thinsp;33) and control (n\u0026thinsp;=\u0026thinsp;32) groups, then undergoing the corresponding treatment protocols (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Table\u0026nbsp;1 and Supplementary Material Table S-1 listed the baseline and initial lab results. A total of 3 alveolar lavage, 3 pleural fluid, 2 cerebrospinal fluid, 1 sputum, 1 pericardial fluid, 1 bone marrow, 1 tissue, and 53 blood samples were included in this study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC and Supplementary Material Fig. S-1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOf the enrolled 65 patients, 59 (90.77%) were diagnosed after routine pathogenesis, imaging, Onco-mNGS testing or clinical experience of physicians, while 6 (9.23%) still had an unknown cause of fever after repeated testings. The confirmed cases included 28 cases (43.07%) of infections, 13 (20%) of tumors and 18 (27.69%) of other diseases(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003emNGS improves pathogen detection rate\u003c/h2\u003e \u003cp\u003eBased on the Onco-mNGS results, 20 pathogens were found to be causative in the experimental group (48.48%, 16/33), while 6 were found in the control group (25%, 8/32). The predominant pathogens detected in both groups were bacteria and viruses, with the frequencies of detection being 13 and 10 for bacteria, and 7 and 1 for viruses, respectively. Of the 20 responsible pathogens detected in the experimental group, four were solely obtained by sample cultivation and 15 were detected by Onco-mNGS, while \u003cem\u003eEnterococcus faecalis\u003c/em\u003e had been detected by both methods (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). These pathogens were originated from 16 cases, 14 of which were detected by Onco-mNGS alone. These cases contained13 single bacterial or viral infections, and one mixed infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). We also analysed the pathogen detection rates for cases of different etiology in experimental group: the pathogen detection rate for infectious FUO was 100% (13/13), which was significantly higher than those caused by tumour (50%, 4/8) and other causes like non-infectious non-tumour inflammation (55.56%, 5/9) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn addition to the responsible pathogens, microecology in blood samples from the experimental group has also been analysed. In the 25 blood samples, 49 genera and 84 species of bacteria were identified (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). These microorganisms were analysed for alpha (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF) and beta (Supplementary Material Fig. S-2) diversity. With the significant indices of Shanon, Simpson, Invers. simpson and Chao 1 showing a substantial change in microecological richness and variety between infection and tumor group. The PCoA value of beta diversity analysis between infection and tumour groups showed a trend of evolutionary distance difference but no significant difference.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe empirical use of antibiotics had less effect on the pathogen detection results of Onco-mNGS than culture\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo explore the impact of empirical antibiotic use on the test effectiveness of both methods, a statistical analysis about the empirical use of antibiotics and pathogen detection has been performed. There were 53 patients had empirical antibiotic history before microbiological detection. Of these patients, 36 used single antibiotic and 17 used combined antibiotics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and Supplementary Material Table S-2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong the 29 patients in the experimental group who used antibiotics empirically, pathogens were detected in 13 cases (44.83%) by Onco-mNGS but only 4 (13.79%) by culture; among the 4 patients who did not use antibiotics, two methods both has detected 1 positive case (25%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). This result showed that the use of antibiotics significantly reduced the culture detected efficiency, but has little effect on the Onco-mNGS results.\u003c/p\u003e \u003cp\u003eAfter analyzing the clinical concordance between these two methods, the clinical committee found that Onco-mNGS had a clinical concordance rate of 72.4% (21/29) in empirical antibiotic used cases of the experimental group, compared to 65.5% (19/29) for culture. Both methods had 100% clinical concordance (4/4, 4/4) for patients not on antibiotics (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOnco-mNGS improves the efficiency of tumour diagnosis\u003c/h2\u003e \u003cp\u003eCNV analysis was performed on 33 samples from the experimental group to test the tumor screening capacity of Onco-mNGS. On average, about 21\u0026nbsp;million homo reads (ranging from 8.8 to 89\u0026nbsp;million) were obtained from each sample after excluding microbial sequences. These sequenced fragments were spliced and analysed against the normal human genome sequence (hg19), and the CNV abnormalities were determined by the correspondence of chromosomal and CNV wave maps (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The experimental group has seven aberrant CNV patients. Two of the patients (T-4, T-7) had previously been diagnosed as tumor patients, and one (T-5) had multiple lymph nodes in the abdominal cavity with abnormal CNV results, was considered a neoplasm. The rest of 4 patients (T-2, T-3, T-6, T-8) confirmed tumors through immunohistochemical (Supplementary Material Table S-3) or pathological staining (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA and supplementary material Fig. S-3) results. Further analysis of CNV variant sites showed that bladder cancer patients had 79.17% (19/24) variant sites, lymphoma patients had 36.46% (8.75/24) chromosomal mutations on average(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results above showed that Onco-mNGS has 100% of specificity and 87.5% of sensitivity for cancer screening (Supplementary Material Fig. S-4). Notably, lymphoma was diagnosed in four of these seven patients (57.14%). One patient who was negative for CNV by Onco-mNGS but had a clinically confirmed tumour was confirmed as pleural mesothelioma by CT and pleural fluid cytology.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOnco-mNGS significantly reduces the diagnostic time\u003c/h2\u003e \u003cp\u003eWe compared the time needed for diagnosing or ruling out infection/tumor of the two groups. The average time period for experimental group (n\u0026thinsp;=\u0026thinsp;30) clarify or ruling out infection/tumor was 7.3 days shorter than that of the control group (n\u0026thinsp;=\u0026thinsp;29) (Supplementary Material Fig. S-5A).\u003c/p\u003e \u003cp\u003eIn addition, We investigated the implications of Onco-mNGS for the clinical management of FUO patients. 17 of 33 experimental group patients stopped application of antibiotics after the causative agents being identified or excluded and 9 patients were transferred to other departments for further treatment. The clinical committee concluded that the Onco-mNGS results had positive implications for the diagnosis and clinical management of these 26 patients (Supplementary Material Fig. S-5B). The remaining 7 patients had a final diagnosis of inflammatory diseases or early neoplastic stage confirmed by clinical combination of antigen/antibody testing, pathology, ultrasound or CT.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eMore than 200 etiologies have been documented to contribute to FUO [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The standardized diagnostic procedure proposed by Ghady Haidar \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]combined understanding the natural history, routine biochemical tests, and other imaging techniques to diagnose FUO. Unfortunately, this strategy is basically inaccurate, low-efficient and largely dependent on the external environment, experiences of clinicians, and characteristics of patients. Therefore, increasing clinical research has focused on improving the efficiency and accuracy of FUO etiological diagnosis.\u003c/p\u003e \u003cp\u003eInfection and tumor are the main causes of FUO, and William F. Wright \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] observed in a large literature research that 37% of FUO patients had infectious illnesses. Current clinical diagnosis of infection is mostly based on microbiology laboratory culture results, which relies heavily on the physician's clinical experience, the standardization of the laboratory testing process, and the patient's epidemiological information. This method has low controllability and is unfavorable for detecting rare and emerging pathogens. In recent years, the methods of testing for FUO pathology have been continuously optimized. For example, Wanru Guo et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] attempted to use complete exome sequencing technology to address the problem of FUO tumour screening. Kim-Heang Ly [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], Friedrich Weitzer [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], applied F-18 FDG PET/CT to the etiological screening of inflammatory FUO patients and compared PET/CT with thoracoabdominal-pelvic CT (CAP-CT) in terms of diagnostic direction, contribution and time. They showed that PET/CT screened FUO patients faster and more efficiently than CAP-CT and proposed using F-18 FDG PET/CT to help diagnose early. However, these approaches only screen for one etiology of FUO. Thus, a non-invasive test that can detect both pathogens and tumors would greatly improve the efficiency of FUO aetiology screen.\u003c/p\u003e \u003cp\u003eAs an emerging molecular diagnostic technique, mNGS is increasingly used to screen pathogens in patients with suspected infections. This approach detects pathogenic gene sequences, hence it is not useful for diagnosing non-infectious disorders yet. To fill this technical gap, the new technology Onco-mNGS is being employed in clinic from 2022. This technique superimposes chromosomal CNV analysis on top of the mNGS technology, allowing simultaneous screening for infections and tumours [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Our study examined the use of Onco-mNGS in FUO etiological screening and found the following.\u003c/p\u003e \u003cp\u003eFirstly, Onco-mNGS is useful for clinical aetiological screening. In this study, we found that the experimental group had significantly higher detection efficiency than the control group in terms of pathogen type (20 vs. 6), number (23 vs. 8) and detection rate (48.48% vs. 25%). Moreover, Onco-mNGS is useful in detecting clinically emerging, rare and uncommon pathogens. This study found 16 responsible pathogens via Onco-mNGS, including \u003cem\u003eCoxiella burneti\u003c/em\u003e, \u003cem\u003eMycobacterium intracellulare\u003c/em\u003e, \u003cem\u003eMycobacterium torulare\u003c/em\u003e, and viruses, which are harder to culture. \u003cem\u003eC. burneti\u003c/em\u003e is an internal parasitic bacterium that eludes clinical microbiological culture procedures like Petri dishes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], while microorganisms of the genus \u003cem\u003eMycobacterium\u003c/em\u003e and viruses are often more difficult to achieve in clinical culture due to the harsh culture conditions or long culture cycles.\u003c/p\u003e \u003cp\u003eIn addition to identify the responsible pathogens, Onco-mNGS is also able to output human microecological data simultaneously. In this study, we analyzed 25 blood samples from the experimental group and found that patients with infection-associated FUO had higher abundance of blood microecology than those with other etiologies and that the diversity of microecological populations were significantly different from the tumor group. High abundance of human microecology has been progressively shown to be strongly associated with the development of infections, tumors and other diseases. Kypros Dereschuk \u003cem\u003eet al.\u003c/em\u003e found [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] the abundance of six microorganisms was associated with the severity of COVID-19, while the abundance of \u003cem\u003eBacillus subtilis\u003c/em\u003e had a positive correlation with the improvement of COVID-19. Thus, Onco-mNGS microbiome data can be used by clinicians to anticipate disease progression where the microbiota-disease association is extensively characterized.\u003c/p\u003e \u003cp\u003eOnco-mNGS could also screen abnormal CNV signals in human genome, which allows for effective early warning of tumors. The current gold standard for tumor diagnosis is pathological biopsy, however, this invasive technique required clinical confirmation of the tumor site, resulting its limited application in clinical practices. Onco-mNGS, on the other hand, is a simple and highly accurate method of screening for abnormal CNV signals using only a blood test, and can be used as a broad-spectrum early screening aid for tumors. The seven patients described in this study underwent abnormal blood CNV tests, all but two of whom had previously diagnosed tumors, and five were first diagnosed by clinical tumor screening after Onco-mNGS early warning. It was also noticeable that, a patient with a normal CNV signal but a clinically confirmed malignant pleural mesothelioma. The missed detection by Onco-mNGS in this patient might be associated with the lower mutant gene load in the blood as seen in other researches. For instance, Raphael Bueno \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] sequenced 216 malignant pleural mesothelioma patients and found that the somatic point mutation rate of protein changes was lower than in other solid malignancies. In another cohort of 74 malignant pleural mesotheliomas, whole-exome sequencing confirmed an overall incidence of \u0026lt;\u0026thinsp;2 bases/M for non-synonymous mutations in all samples except for one sample with a mutation of \u0026lt;\u0026thinsp;8 bases/M [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. It indicated that Onco-mNGS for CNV signalling screening is best for samples with high abnormal cell content, such as haematological tumors and tumor systemic metastases, but its sensitivity is low for early tumor or tumor with low somatic point mutation rates. Meanwhile, multipoint detection should improve the detection sensitivity.\u003c/p\u003e \u003cp\u003eSencondly, Onco-mNGS offers advantages in adapting clinical antibiotic regimens for FUO. In our study, up to 81.5% of febrile patients were empirically treated with antibiotics before diagnosis, some even with carbapenem or a combination of broad-spectrum antibiotics, but generally with poor outcomes. Although empirical antibiotic therapy is indicated in critical FUO patients with no definite cause but a strong suspicion of infection, many doctors are urging caution. William F. Wright [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] et al. suggested that the empirical use of antibiotics should be avoided except in cases where the patient's condition is urgent and severe, as this may complicate the final diagnosis, and S. Vanderschueren [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] et al. found in a study on the prognosis of FUO patients that empirical antibiotics were not needed for stable patients. Overuse of antibiotics often poses a threat of resistance to clinical anti-infective therapy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], so early diagnosis and rational adjustment of antibiotics are important in the management of FUO. In this project, 24 patients (72.7%) in the experimental group adjusted or discontinued antibiotics after applying Onco-mNGS to identify the cause of the disease, and they had a good prognosis.\u003c/p\u003e \u003cp\u003eThirdly, Onco-mNGS significantly shortens the time for the FUO etiological screening. The time for Onco-mNGS is 13\u0026ndash;15 hours, compared to 2\u0026ndash;5 days[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] for cultures and even longer for tumor screening. In this study, 59 patients have been confirmed the etiology. The mean time period to clarify or exclude infection/tumor in the experimental group was approximately 7.3 days shorter than that of the control group, which greatly improved the efficiency of aetiological screening for FUO.\u003c/p\u003e \u003cp\u003eIn summary, Onco-mNGS has significantly contributed to the improvement of the aetiological diagnosis of FUO in terms of sensitivity, specificity, accuracy and timeliness. We suggest patients admitted to the hospital after a Minimal FUO test fail to confirm the diagnosis immediately undergo Onco-mNGS testing to improve early diagnosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLB is the primary physician who provides diagnosis and treatment of the patients. LB, YT and RR collected and analyzed clinical and sequencing data. WN, XN, WJ and LB are the principle members of the panel of clinical experts. LB, YT, RR, CX, WW and ZJ wrote the manuscript. All authors have read and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from the\u0026nbsp;Liaoning Provincial Key Research and Development Program of Development of Science and Technology (Grant No.\u0026nbsp;2020JH2/10300040), the Science Foundation for the State Key Laboratory for Infectious Disease Prevention and Control of China (Grant No. 2022SKLID308) and Project for Basic Research by the Education Department of Liaoning Province (Grant No. JYTMS20230072).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets presented in this study can be found in NCBI with the SRA accession no. PRJNA865023.\u003c/p\u003e\n\u003cp\u003eThe raw data of the chromosome copy variation and the picture of each patient were deposited in, or linked to, Zenodo (https://zenodo.org/record/7982217).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving human participants were reviewed and approved by the board of Ethics at\u0026nbsp;The First Hospital of China Medical University. The patients provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article. The study was conducted in accordance with the International Conference on Harmonization, Good Clinical Practice Guidelines, and the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors YT, RR, CX and WW are employed by MatriDx Biotechnology Co., Ltd. Author RR is also employed by Micro-Health Biotechnology Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors are thankful to Department of Infectious Diseases of The First Hospital of China Medical University medical staff for helping in sample collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWright WF, Mulders-Manders CM, Auwaerter PG, Bleeker-Rovers CP. Fever of Unknown Origin (FUO) - A Call for New Research Standards and Updated Clinical Management. Am J Med. 2022;135:173\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHaidar G, Singh N. Fever of Unknown Origin. 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Open Forum Infect Dis. 2022;9:ofac151.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFu ZF, Zhang HC, Zhang Y, Cui P, Zhou Y, Wang HY, Lin K, Zhou X, Wu J, Wu HL, Zhang WH, Ai JW. Evaluations of Clinical Utilization of Metagenomic Next-Generation Sequencing in Adults With Fever of Unknown Origin. Front Cell Infect Microbiol. 2021;11:745156.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong Y, Gao Y, Chai Y, Shou S. Use of Quantitative Metagenomics Next-Generation Sequencing to Confirm Fever of Unknown Origin and Infectious Disease. Front Microbiol. 2022;13:931058.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWright WF, Simner PJ, Carroll KC, Auwaerter PG. Next-Generation Sequencing, Multiplex Polymerase Chain Reaction, and Broad-Range Molecular Assays as Diagnostic Tools for Fever of Unknown Origin Investigations in Adults. Clin Infect Dis. 2022;74:924\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu W, Rauschecker AM, Hsu E, Zorn KC, Sucu Y, Federman S, Gopez A, Arevalo S, Sample HA, Talevich E, Nguyen ED, Gottschall M, Nourbakhsh B, Gold CA, Cree BAC, Douglas VC, Richie MB, Shah MP, Josephson SA, Gelfand JM, Miller S, Wang L, Tihan T, DeRisi JL, Chiu CY, Wilson MR. Detection of Neoplasms by Metagenomic Next-Generation Sequencing of Cerebrospinal Fluid. JAMA Neurol. 2021;78:1355\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo Y, Li H, Chen H, Li Z, Ding W, Wang J, Yin Y, Jin L, Sun S, Jing C, Wang H. Metagenomic next-generation sequencing to identify pathogens and cancer in lung biopsy tissue, EBioMedicine, 73 (2021) 103639.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu J, Han X, Xu X, Ding W, Li M, Wang W, Tian M, Chen X, Xu B, Chen Z, Yuan J, Qin X, Lin D, Wang R, Gong Y, Pan L, Wang J, Wang M. Simultaneous Detection of Pathogens and Tumors in Patients With Suspected Infections by Next-Generation Sequencing. Front Cell Infect Microbiol. 2022;12:892087.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou H, Ouyang C, Han X, Shen L, Ye J, Fang Z, Chen W, Chen A, Ma Q, Hua M, Zhu J, Wu X, Lin X, Shui Y, Zhou C, Fang K, Du J, Huang Z, Wang G, Lv Q, Huang W, Wang J, Hua X, Zhou J, Liu C, Yu Y. Metagenomic sequencing with spiked-in internal control to monitor cellularity and diagnosis of pneumonia. J Infect. 2022;84:e13\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMourad O, Palda V, Detsky AS. A comprehensive evidence-based approach to fever of unknown origin. Arch Intern Med. 2003;163:545\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo W, Feng X, Hu M, Shangguan Y, Xia J, Hu W, Li X, Zhang Z, Shi Y, Xu K. The Application of Whole-Exome Sequencing in Patients With FUO. Front Cell Infect Microbiol. 2021;11:783568.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLy KH, Costedoat-Chalumeau N, Liozon E, Dumonteil S, Ducroix JP, Sailler L, Lidove O, Bienvenu B, Decaux O, Hatron PY, Smail A, Astudillo L, Morel N, Boutemy J, Perlat A, Denes E, Lambert M, Papo T, Cypierre A, Vidal E, Preux PM, Monteil J, Fauchais AL. Diagnostic Value of 18F-FDG PET/CT vs. Chest-Abdomen-Pelvis CT Scan in Management of Patients with Fever of Unknown Origin, Inflammation of Unknown Origin or Episodic Fever of Unknown Origin: A Comparative Multicentre Prospective Study. J Clin Med, 11 (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeitzer F, Nazerani Hooshmand T, Pernthaler B, Sorantin E, Aigner RM. Diagnostic value of F-18 FDG PET/CT in fever or inflammation of unknown origin in a large single-center retrospective study. 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Ladanyi, Integrative Molecular Characterization of Malignant Pleural Mesothelioma, Cancer Discov., 8 (2018) 1548\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVanderschueren S, Eyckmans T, De Munter P, Knockaert D. Mortality in patients presenting with fever of unknown origin. Acta Clin Belg. 2014;69:12\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeptimus EJ. Antimicrobial Resistance: An Antimicrobial/Diagnostic Stewardship and Infection Prevention Approach, Med. Clin North Am. 2018;102:819\u0026ndash;29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaurer FP, Christner M, Hentschke M, Rohde H. Advances in Rapid Identification and Susceptibility Testing of Bacteria in the Clinical Microbiology Laboratory: Implications for Patient Care and Antimicrobial Stewardship Programs, Infect. Dis Rep. 2017;9:6839.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMendon\u0026ccedil;a A, Santos H, Franco-Duarte R, Sampaio P. Fungal infections diagnosis - Past, present and future. Res Microbiol. 2022;173:103915.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"},{"header":"Supplementary Figure","content":"\u003cp\u003eSupplementary Figure 2 are not available with this version\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Fever of unknown origin, Onco-mNGS, Etiology, Diagnostic criteria","lastPublishedDoi":"10.21203/rs.3.rs-4463841/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4463841/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e \u003cp\u003eDelayed diagnosis of patients with Fever of Unknown Origin has long been a daunting clinical challenge. Onco-mNGS, which can accurately diagnose infectious agents and identify suspected tumor signatures by analyzing host chromosome copy number changes, has been widely used to assist identifying complex etiologies. However, the application of Onco-mNGS to improve FUO etiological screening has never been studied before.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this single-centre prospective study, we included 65 patients with classic FUO, who were randomly divided into control group (sample cultivation) and mNGS group (cultivation\u0026thinsp;+\u0026thinsp;Onco-mNGS). We analyzed the infectious agents and symbiotic microbiological, tumor and clinical data of both groups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eInfection-related pathogenic detection efficiency rose from 15.15% (control group) to 48.48% (experimental group). Seven patients with chromosome copy number changes had later been confirmed tumors, indicating a 100% of clinical concordance rate of Onco-mNGS. In addition, the time frame for diagnosing or ruling out infection/tumor with Onco-mNGS had greatly reduced to approximately 2 days, which was 7.34 days earlier than that in the control group.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOnco-mNGS is an ideal rapid diagnostic aid to assist improving the early diagnostic efficiency of FUO-associated diseases.\u003c/p\u003e","manuscriptTitle":"Onco-mNGS Facilitates Rapid and Precise Identification of The Etiology of Fever of Unknown Origin: A Single-centre Prospective Study in North China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-11 18:41:52","doi":"10.21203/rs.3.rs-4463841/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-20T11:29:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T16:08:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"247799548909600281272911757815960387794","date":"2024-07-29T16:36:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-09T13:09:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105411420090539777848452894252113215196","date":"2024-06-29T16:18:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-31T10:16:40+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-27T07:31:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-24T12:03:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-24T12:03:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2024-05-23T03:03:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"aa2166bb-1dd0-40be-b592-5aa12060e7f6","owner":[],"postedDate":"June 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-30T16:03:56+00:00","versionOfRecord":{"articleIdentity":"rs-4463841","link":"https://doi.org/10.1186/s12879-024-10383-3","journal":{"identity":"bmc-infectious-diseases","isVorOnly":false,"title":"BMC Infectious Diseases"},"publishedOn":"2024-12-28 15:57:08","publishedOnDateReadable":"December 28th, 2024"},"versionCreatedAt":"2024-06-11 18:41:52","video":"","vorDoi":"10.1186/s12879-024-10383-3","vorDoiUrl":"https://doi.org/10.1186/s12879-024-10383-3","workflowStages":[]},"version":"v1","identity":"rs-4463841","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4463841","identity":"rs-4463841","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}