Clinical Utility of Comprehensive Genomic Profiling Tests Using MTB Management System at a Single Center in Japan

Clinical Utility of Comprehensive Genomic Profiling Tests Using MTB Management System at a Single Center in Japan | 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 Article Clinical Utility of Comprehensive Genomic Profiling Tests Using MTB Management System at a Single Center in Japan Chie Sarudate, Miki Dobashi, Maako Kawamura, Hidekazu Shirota, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5501115/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Cancer genomic medicine interprets genetic information for diagnosis and treatment. It requires an organized team of experts from various fields to discuss treatment recommendations at a molecular tumor board (MTB). It is also important to track patient outcomes based on these decisions and seamlessly incorporate them into future discussions at the MTB. We developed a system to manage the MTB efficiently. Using this system, we followed the outcome and prognosis of 1643 patients whose treatment was discussed at the MTB and evaluated the utility of a realistic comprehensive genomic profiling (CGP) test. Treatment recommendations were made for 240 patients (14% of the total cases). Of these, 118 (7% of the total) were treated with the drugs recommended by the MTB. The cancer type with the highest percentage of patients in which treatment recommendations were made and drugs were administered was thyroid cancer, followed by breast cancer, lung cancer, prostate cancer, and cholangiocarcinoma. While cancer-specific overall survival was inconclusive due to few cases, CGP-recommended treatment significantly extended patient survival from the CGP test date. This analysis, utilizing our patient follow-up system, suggests that CGP testing expands treatment options for a subset of patients and may improve treatment efficacy. Biological sciences/Cancer Biological sciences/Cancer/Cancer genomics Biological sciences/Genetics/Cancer genomics Biological sciences/Genetics/Clinical genetics Biological sciences/Genetics/Genetic markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Next-generation sequencing-based comprehensive genomic profiling (CGP) for cancer patients has become widely used in many countries (1,2). In Japan, the CGP test has been available under the national health insurance reimbursement program since 2019 (3,4). The molecular tumor board (MTB), which interprets genetic information for diagnosis and treatment, requires insurance reimbursement and a high level of expertise, ranging from basic knowledge of molecular biology to clinical experience with molecular-targeted drugs (5). The MTB has reported recommending new therapies for approximately 10–20% of the patients (6,7). However, it is anticipated that not all patients receive these therapies. The problem is that since the launch of cancer genomic medicine, its overall effectiveness has yet to be proven. Subsequent treatment and response rates to recommended agents must be further improved. In addition, the criteria for the treatment recommendations of the MTB and access to clinical trials are different at each facility; thus, each facility should provide its results. The Ministry of Health, Labor, and Welfare (MHLW) of Japan established a system to centrally manage CGP tests before the launch of cancer genome medicine (3,4). The purpose of this system is to promote cancer genome medicine that is consistent with the available evidence without regional disparities and to centralize data for use in drug development and research. However, this system substantially burdens many hospitals and frontline medical professionals. Regional core hospitals must organize MTB teams and collaborate with other hospitals to review the CGP data. Effective data sharing will provide quality genomic medicine to patients across clinical specialties. To avoid human error, manual work in time-consuming areas should be reduced and MTB medical teams require systems to support their work. In recent years, we have reported on the rate of treatment recommendations for MTB and on the management of presumed germline pathogenic variants at our facility (5,8). The rate of treatment recommendations is 19%, and the rate of hereditary tumor identification is 4.5%. Here, we report on the MTB system and treatment outcomes at our hospital as a result of five years of genomic medicine. The MTB portal system that we have developed shares patient information with various medical professionals through the Internet to recommend treatment and track patients. The MTB team must collaborate with other facilities, collect patient information with security assurance, and generate reports. The CGP test and treatment outcomes of 1643 cases using the system were summarized to determine the overall usefulness of this test. Based on the results, it is important to identify cancer types likely to be recommended for treatment and the timing of tests leading to treatment in the future. Patients and Methods Study design, Patients, and the CGP test CGP tests were performed at Tohoku University Hospital to identify molecular therapeutic targets. They were retrospectively analyzed for genetic alterations, treatment suggestions, and subsequent treatment. The CGP test was performed on 1643 patients with solid tumors from September 2019 to June 2024. The criteria for this test in Japan for health insurance coverage have been previously reported (5,8). All patients were stage 4 cancer patients receiving chemotherapy. Table 1 lists the characteristics (age, sex ratio, and type of CGP test) of the 1643 patients who underwent CGP testing. The characteristics of each test were reported previously (5,8). The Ethics Committee of Tohoku University Hospital approved this study. Informed consent was obtained from all patients to use their CGP data in clinical practice and for retrospective studies. In addition, patients were provided an opt-out disclosure for the details of specific studies. Approval of the research protocol and ethics by an Institutional Reviewer Board: IRB No. 2021-1-250 and 2023-1-1036. Table 1 Characteristics of patients, CGP test Median (range) age 61 (0–90) Sex Male (%) 844 (51) Female (%) 799 (49) CGP test FoundationOne CDx (%) 1259 (76.6) FoundationOne liquid CDx (%) 336 (20.4) Guardant360 21 (1.2) NCC Oncopanel (%) 18 (1.1) GenMineTOP 9 (0.5) total 1643 MTB management and portal system The Japanese public insurance system mandates discussing cases in the MTB before the attending physician explains the outcome to the patients (3,4). The operation of our MTB has been reported previously (5). The MTB includes at least 10 oncologists, geneticists, genetic counselors, bioinformaticians, and data sequencing experts. During the meeting, the attending physician presents the patient's medical history and condition, and the team discusses potential treatment recommendations and clinical trial participation. Treatment recommendations for genetic alterations are categorized by level of evidence, based on the C-CAT report and other databases: level A, Japan- or FDA-approved drug for the cancer type; level B, expert consensus supported by clinical trials and meta-analyses; level C, Japan- or FDA-approved drug for other cancers; level D, case reports demonstrating efficacy across cancer types; level E, pre-clinical stage; level F, genetic changes involved in cancer. Treatment recommendations were made for genetic alterations at level D or higher. We have developed a web-based system with Hitachi High-Tech Corporation. For the efficient operation and discussion of the MTB teams. The secure system enables patient and genomic information to be shared among facilities. The results from several providers may be compiled into a comprehensive report using the same format. The comprehensive report contains citations from various databases, such as ClinVar, OncoKB (-2023), ToMMo, gnomAD, COSMIC, and CIViC (9–14). Patients are listed and each specialist on the MTB team can leave comments. This allows seamless communication among the clinical staff. Patients are registered in the system and their treatment and prognosis are tracked. The definition of treatment recommendation The definition of a treatment recommendation by the MTB is the therapy the patient receives based on the results of CGP testing and the recommendation of the MTB. The treatment is either covered by health insurance in Japan or a Phase 2 or higher clinical trial expected to have beneficial therapeutic effects. Off-label drugs for personal use are not recommended. It does not include genes identified in companion diagnoses or treatments included in the standard of care. In Japan, treatment guidelines are updated periodically for each type of cancer. We adhere to the standard of care at the time of testing. Pan-cancer indications, such as TMB-H, BRAF, and NTRK fusions, are also considered. For example, immune checkpoint inhibitors are approved for many cancers and are part of standard treatment, allowing their use even without TMB-H. Therefore, TMB-H-based ICI recommendations are not made for cancer types already covered by standard treatment. Also, it will not be recommended if the patient's condition is too poor to undergo treatment. In other words, patients would only receive treatment with a CGP test. Treatments may include investigational drugs in clinical trials. Because of the confidential aspect of the clinical trials, all drug names were redacted and recommended treatments were based on biomarkers or genetic mutations. Patient follow-up after MTB Patient clinical information, previous treatments, and effects must be registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) (15). Treatment after the test was completed and prognostic information was part of the follow-up. We also surveyed whether the patients were treated as recommended, the date of last verified survival, and the date of death with the cooperation of other hospitals. The duration of treatment evaluated the recommended treatment. It was not evaluated by RECIST classification through imaging as in a clinical trial; instead, the duration of treatment was monitored until the attending physician determined that it was beneficial to the patient. Statistical analysis Kaplan–Meier analysis was performed to estimate the distribution of overall survival (OS) and a log-rank test was used to analyze the statistical differences in survival. The Cox proportional hazard model was used to calculate the hazard ratio and 95% confidence interval. Differences were considered statistically significant at p < 0.05. Results Management of patients with the MTB portal system We developed a web-based system to manage the efficient operation of the MTB and its collaboration with other facilities. We designated this system “the MTB portal system.” The objectives of this platform are 1) the preparation and operation of the MTB through multi-center collaboration, 2) patient tracking and management, and 3) research and education in cancer genome medicine (Fig. 1 ). The patient database is securely listed and managed in a separate system from the electronic medical records. All tested cases are registered in this system, which can track the patient's clinical information and prognosis, an essential component of the C-CAT registry. The patient, cancer type, and a variant of the genetic alteration may query the system. The discussion of past MTB meetings can be reviewed. The system can also identify patients who are candidates for clinical trials or approved new drugs based on their genetic variants. We used this system to analyze the data regarding realistic cancer genomic medicine at our hospital. CGP test and treatment recommendations The patient background, gender ratio, type of CGP test, and cancer type are listed in Tables 1 and 2 . For 1643 patients, the most frequent type of cancer was pancreatic cancer (15.1%), followed by colorectal cancer (13.9%), bile duct cancer (10.3%), breast cancer (7.2%), prostate cancer (5.9%), ovarian cancer (4.9%), sarcomas (4.8%), brain cancer (4.7%), and lung cancer (3.6%). The median turnaround time to obtain consent for the test and provide the results to the patient was 35 (range: 23–70) days. In our previous study, 67% of the actionable genes (Level of Evidence D or higher) were identified, and the treatment recommendation rate was 19% in the first 2 years (5). However, the subsequent treatment recommendation rate decreased to 14.6% (Fig. 2 ). Table 2 lists the percentage of treatment recommendations based on each cancer type. These results were similar to those of our previous results. Thirty-seven patients were screened through the MTB portal system for recruitment to newly approved drugs and clinical trials after MTB. This figure accounted for 2.3% of the total patients. Table 2 Type of cancer and number of treatment recommendation and received treatment Type of cancer total No. of treatment recommend (%) No. of treatment received (%) Pancreatic 248 15 (6.0) 7 (2.8) Colorectal 228 22 (9.6) 10 (4.4) Bile duct 170 35 (20.6) 18 (10.6) Breast 119 38 (31.9) 17 (14.3) Prostate 97 20 (20.6) 13 (13.4) Ovarian 81 9 (11.1) 3 (3.7) Sarcoma 79 10 (12.7) 6 (7.6) Brain 78 7 (9.0) 5 (6.4) Non-small cell lung 59 17 (28.8) 10 (16.9) Head and neck 57 4 (7.0) 2 (3.5) Gastric 54 4 (7.4) 1 (1.9) Endometrial 52 8 (15.4) 1 (1.9) Esophageal 42 2 (4.8) 1 (2.4) CUP 41 5 (12.2) 2 (4.9) Small intestine 34 5 (14.7) 1 (2.9) Pediatric 32 4 (12.5) 2 (6.3) Thyroid 26 13 (50) 9 (34.6) Neuroendocrine 24 4 (16.7) 2 (8.3) Melanoma 23 7 (30.4) 1 (4.3) Cervical Ca. 13 2 (15.4) 2 (15.4) Thymic ca. 11 0 0 Kidney, urinary tract 10 0 0 Other 65 9 (13.8) 6 (9.2) 1643 240 (14.6) 118 (7.2) Note: Cancer of unknown primary (CUP) Treatment cases recommended by MTB Of the cases for which treatment was recommended, nearly half (118 patients; 7.2% of the total) were treated with the drug recommended by the MTB (Fig. 2 ). The cancer types with the most frequent cases leading to a recommended treatment were, in order, thyroid cancer (34.6%), non-small cell lung cancer (15.3%), breast cancer (14.3%), prostate cancer (13.4%), and bile duct cancer (10.6%) (Table 2 ). The median time between returning the results to the patient and initiating treatment was 84 (range: 0–798) days. The genetic mutations or biomarkers associated with the treated patients, including both under health insurance and clinical trials, were TMB-H (n = 29), BRCA1/2 (n = 21), ERBB2 (n = 17), BRAF V600E (n = 13), FGFR1/2 (n = 8) and others (n = 18) (Table 3 ). In contrast, it was necessary to describe the reasons for not treating a patient, even though it was recommended in the report to the C-CAT. The reasons were categorized into five groups as shown in Fig. 2 . Group 1 (n = 42), which received different treatments, may receive the recommended treatment in the future. Groups 2–5 in the table consisted of 53 patients, and of those available for follow-up, about half were considered to be in poor condition or did not meet the study criteria. Thus, they were not able to receive the recommended treatment. Table 3 Treatment recommendation according to gene alteration, biomarker Gene alteration or Biomarker Treatment recommended Treatment received No treatment TMB-H 41 29 12 BRCA1/2 37 21 16 ERBB2 39 17 22 BRAF 16 13 3 FGFR1/2 25 8 17 PIK3CA 12 4 8 TP53/MDM2 10 4 6 KIT/PDGFRA 7 4 3 KRAS/MEK 20 3 17 HRD/ PALB2/BRIP1 7 3 4 NTRK1/3 3 2 1 TSC1/2 2 2 0 ALK 3 1 2 RET 2 1 1 ROS1 2 1 1 ESR1 1 1 0 MET 1 1 0 CCND1 1 1 0 CDK4 1 1 0 EGFR 3 1 2 CDK12 4 0 4 IDH1 3 0 3 Total 240 118 122 Outcomes of treatment as recommended by MTB All cases in which treatment was performed were followed except for one case. The median observation period from submitting the test was 416 days. Of the 117 patients that could be traced, 59 died. The actual duration of the recommended treatment and genetic mutations are shown in a swimmer’s plot (Fig. 3 ). A list of recommended and actual treatment drugs has been added as a supplementary table 1 . Clinical trial drugs are listed as investigational drugs. In this case, the clinical trial included 25 patients. The combination of cancer type and genetic mutation is not listed because it could identify the drug in the clinical trial. In clinical practice, there are no clear criteria for the duration of treatment as defined in clinical trials. Treatment may be continued even if tumor growth is observed; however, the attending physician determines if it benefits the patient. The median duration of the recommended treatment was 132 days. The number of cases treated for more than 100 days was 74 (63%). These treatments were generally considered beneficial. The median duration of each treatment for TMB-H, BRCA1/2, ERBB2, BRAF V600E, and FGFR1/2 (biomarkers with at least 5 cases) was more significant than 100 days (data not shown). OS after submitting a CGP test was compared with/without the recommended treatment in Fig. 4 . The median survival time for the patients who received the recommended treatment (n = 118) based on the test was 21.0 months, whereas that for the patients who could not be treated for any reason, despite a treatment recommendation (n = 126), was 12.9 months and 13.5 months for the patients who did not receive a treatment recommendation (n = 1,398) (Fig. 4 ). The group with a recommended treatment showed a significantly improved prognosis. The OS of the group that could not be treated for any reason, despite a treatment recommendation, and those with no recommended treatment were comparable. The average ages of the three groups were nearly identical: 61.3, 61.6, and 61.5 years, respectively. OS from first-line chemotherapy for each cancer type was evaluated (Supplemental Figure). Only the five cancer types with the highest treatment recommendation rates were compared between the treated and untreated groups. Although the number of patients for all cancer types was relatively small, making it difficult to determine statistical differences, the curves for non-small cell lung cancer, thyroid cancer, and cholangiocarcinoma were higher in the treatment group compared with that in the untreated group. No differences were observed for breast or prostate cancer. Discussion This study evaluated real-world data on new treatment recommendations by the MTB based on a CGP test, the efficacy of the treatment, and patient prognosis at a single center in Japan. We also introduced the MTB portal system, which is an academic clinical decision support system developed with Hitachi High-Tech Corporation. It represents a scientific and technological platform to collect and share data from the CGP test. This system may be used for efficient MTB management, patient treatment, and prognosis follow-up. The recommended treatment rate by the MTB at our facility over five years was 14% and half of these patients (7%) were treated with the recommended drugs. Several patients who received treatment as recommended had a favorable response and a significantly better prognosis compared with those who did not receive treatment. There is a growing need for a system that efficiently supports the work of the medical team and the MTB (16). The MTB system mandated by the MHLW is complex because it involves many specialists and includes other facilities in the discussion (3). Therefore, we have developed a platform that integrates into the clinical workflow using a unique format, distributes results, and supports a shared discussion. Using the same format for multiple CGP tests facilitates consistent decision-making and structured data collection across all facilities. Automating the interpretation and reporting of the sequencing results reduces the need for error-prone and time-consuming manual labor. In addition, each specialist who views the data can leave comments, facilitating a collaborative discussion of complex cases over time through virtual molecular oncology meetings. The evidence for treatment is constantly changing, and there is a need to revise and update it for cases in the past constantly. Overall, this streamlined digital system can address the issues that are rapidly changing the precision oncology landscape and mobilize and leverage the expertise of the community. We also used this system to review evidence of drug use, newly approved drugs, and clinical trials for updated information on past cases and to provide up-to-date data for 37 patients. Summarizing treatment recommendations by cancer type is a clinical indicator for selecting cases to be submitted for CGP testing. Treatment recommendations decreased from 19% in the first two years of reporting to 14% in the subsequent three years. The decrease has occurred because of new diagnostics and molecular-targeted drugs that do not require CGP testing, such as immune checkpoint inhibitors, BRAF inhibitors, and HER2 inhibitors, which have been approved in the past few years. In addition, some cases were immature, such as when a realistic treatment proposal was recommended even though access to the drugs in Japan was difficult. Treatment recommendations were made in 240 cases and the cancer type with the highest rate of recommendations was thyroid cancer, followed by non-small cell lung, prostate cancers, breast, and bile duct cancer, all of which resulted in a high percentage of treated patients. In particular, for lung cancer, new treatment recommendations have been identified despite multiple companion diagnoses. In contrast, pancreatic, colorectal, head and neck, stomach, and esophageal cancers had a low rate of treatment recommendations. In this report, 7% of all patients were treated with the recommended drugs, primarily molecular-targeted by the MTB. One of the major limitations of this report is that the names of the drugs used in the clinical trials had to be withheld. The treatment was effective in many cases, with 74 patients (62.7%) being treated for over 100 days. Reports from other facilities in Japan reported that 12.2% were treated based on the gene mutation identified in the CGP test by Ida et al., 13.4% by Sunami et al., 11.1% by Kikuchi et al., 3.6% by Inagaki et al., and 6.5% by Fukuda et al. Thus, our results are comparable (17–20). However, half of the patients failed to undergo treatment despite the recommendations. Patients in group 1 receiving other treatments also left open the possibility of receiving those treatments in the future. Approximately 30% of the patients received treatment immediately (within 30 days) after receiving a recommendation. In addition, many patients could not participate in clinical trials or abandoned treatment because of their poor general condition (groups 2–5 in Fig. 2 ). Although comparing patients with different cancer types, genetic mutations, and treatment regimens makes simple comparisons impossible, the prognosis for the patients who submitted a CGP test was significantly better in the group that received the treatment. At least some patients who underwent CGP testing realized a benefit. The results suggest that the cancer types with the higher recommended treatment rates have improved OS, although the number of cases treated was small and not significantly different. We hope to increase the number of cases and assess the results with consideration of confounding factors in future studies. Now that the CGP test is covered by health insurance in Japan, it is important to verify periodically whether it benefits cancer patients. Evidence of its effectiveness will lead to the widespread use of cancer genome medicine. Of course, the criteria for determining the usefulness of the CGP test are not limited to just treatment recommendations. There are molecular diagnoses that cannot be determined by pathology alone, treatment selection within the standard care, prognostic prediction, and other factors that must be considered. Patient satisfaction surveys are also important (21,22). In addition, it is important to use systems for managing CGP testing, preparing the MTB, and following up on patient care. Here, we presented our unique MTB portal system. To provide equal access to cancer genome medicine, which is becoming increasingly complex with constantly changing evidence, managing patients solely by attending physicians is difficult. Thus, it would be ideal to establish a system in which centralized management is provided. As a result of drug development, patients with genetic mutations and cancer types for which treatment could not be recommended in the past may benefit. In addition, verifying the efficacy of recommended treatments will provide significant evidence for future treatment proposals for patients with similar genetic mutations. For this reason, it is necessary to track patients and provide feedback. The MTB team will need to track patients in a system, such as that described here, to apply the benefits of new evidence-based treatments to past cases. Declarations Acknowledgments The authors would like to thank all the physicians who attended our MTB meeting. Funding This research received no external funding. Ethics declarations Ethical approval All patients obtained Informed consent for research, but more detailed study protocols were approved by the IRB through the disclosure of information. Approval of the research protocol and ethics by an Institutional Reviewer Board: IRB No. 2021-1-250 and 2023-1-1036. Conflict of Interest Conflict of interest: Dr. Ishioka has received scholarship endowments from Takeda, Daiichi-Sankyo, Ono, Asahi-Kasei Pharma, Taiho, and Chugai, as well as research grant from Hitachi Co. Ltd. and Riken Genesis Co. Ltd. M. Takahashi has received research funding from Ono Pharmaceutical, Chugai Pharmaceutical, and MSD, lecturer fees from Daiichi Sankyo, Ono Pharmaceutical, Bristol Meyers Squibb, Taiho Pharmaceutical Company. Drs. Shirota and Komine have received research grant from Hitachi Co. Ltd. All remaining authors have declared no conflict of interest. Data availability statement: The datasets used or analyzed during the current study are available from the corresponding author on reasonable request. Author information Shirota H designed the study. Sarudate C, Dobashi M, Kawamura M, Iwasaki T and Shirota H acquired and analyzed the patient data. Shirota H participated in the interpretation of results. Shirota H drafted the manuscript. All authors have read, reviewed, and approved the final manuscript. References Collins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793–795. Frampton GM, Fichtenholtz A, Otto GA, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 2013;31(11):1023–1031. Ebi H, Bando H. Precision Oncology and the Universal Health Coverage System in Japan. JCO Precis Oncol. 2019 Dec 11;3:PO.19.00291. Mukai Y, Ueno H. Establishment and implementation of Cancer Genomic Medicine in Japan. Cancer Sci. 2021 Mar;112(3):970–977. Shirota H, Komine K, Takahashi M, Takahashi S, Miyauchi E, Niizuma H, Tada H, Shimada M, Niihori T, Aoki Y, Sugiyama I, Kawamura M, Yasuda J, Suzuki S, Iwaya T, Saito M, Saito T, Shibata H, Furukawa T, Ishioka C. Clinical decisions by the molecular tumor board on comprehensive genomic profiling tests in Japan: A retrospective observational study. Cancer Med. 2023 Mar;12(5):6170–6181. Larson KL, Huang B, Weiss HL, et al. Clinical outcomes of molecular tumor boards: a systematic review. JCO Precis Oncol. 2021;5:PO.20.00495. Seet AOL, Tan AC, Tan TJ, et al. Individualized molecular profiling for allocation to clinical trials Singapore study-an Asian tertiary cancer center experience. JCO Precis Oncol. 2021;5:PO.20.00261. Kawamura M, Shirota H, Niihori T, Komine K, Takahashi M, Takahashi S, Miyauchi E, Niizuma H, Kikuchi A, Tada H, Shimada M, Kawamorita N, Kanamori M, Sugiyama I, Tsubata M, Ichikawa H, Yasuda J, Furukawa T, Aoki Y, Ishioka C. Management of patients with presumed germline pathogenic variant from tumor-only genomic sequencing: A retrospective analysis at a single facility. J Hum Genet. 2023 Jun;68(6):399–408. Landrum MJ, Lee JM, Benson M, et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016;44(D1):D862-D868. Chakravarty D, Gao J, Phillips SM, et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol. 2017;2017:PO.17.00011. Tadaka S, Hishinuma E, Komaki S, et al. jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population. Nucleic Acids Res. 2021;49(D1):D536-D544. Koch L. Exploring human genomic diversity with gnomAD. Nat Rev Genet. 2020;21(8):448. Forbes SA, Tang G, Bindal N, et al. COSMIC (the catalogue of somatic mutations in cancer): a resource to investigate acquired mutations in human cancer. Nucleic Acids Res. 2010;38(Database issue):D652-D657. Griffith M, Spies NC, Krysiak K, et al. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet. 2017;49(2):170–174. Kohno T, Kato M, Kohsaka S, Sudo T, Tamai I, Shiraishi Y, Okuma Y, Ogasawara D, Suzuki T, Yoshida T, Mano H. C-CAT: The National Datacenter for Cancer Genomic Medicine in Japan. Cancer Discov. 2022 Nov 2;12(11):2509–2515. Tamborero D, Dienstmann R, Rachid MH, Boekel J, Lopez-Fernandez A, Jonsson M, Razzak A, Braña I, De Petris L, Yachnin J, Baird RD, Loriot Y, Massard C, Martin-Romano P, Opdam F, Schlenk RF, Vernieri C, Masucci M, Villalobos X, Chavarria E; Cancer Core Europe consortium; Balmaña J, Apolone G, Caldas C, Bergh J, Ernberg I, Fröhling S, Garralda E, Karlsson C, Tabernero J, Voest E, Rodon J, Lehtiö J. The Molecular Tumor Board Portal supports clinical decisions and automated reporting for precision oncology. Nat Cancer. 2022 Feb;3(2):251–261. Ida H, Koyama T, Mizuno T, Sunami K, Kubo T, Sudo K, Tao K, Hirata M, Yonemori K, Kato K, Okusaka T, Ohe Y, Matsui Y, Yamazaki N, Ogawa C, Kawai A, Narita Y, Esaki M, Yamamoto N. Clinical utility of comprehensive genomic profiling tests for advanced or metastatic solid tumor in clinical practice. Cancer Sci. 2022 Dec;113(12):4300–4310. Sunami K, Naito Y, Komine K, Amano T, Ennishi D, Imai M, Kage H, Kanai M, Kenmotsu H, Koyama T, Maeda T, Morita S, Sakai D, Kohsaka S, Tsuchihara K, Saigusa Y, Yoshino T. Chronological improvement in precision oncology implementation in Japan. Cancer Sci. 2022 Nov;113(11):3995–4000. Kikuchi J, Ohhara Y, Takada K, Tanabe H, Hatanaka K, Amano T, C Hatanaka K, Hatanaka Y, Mitamura T, Kato M, Shibata Y, Yabe I, Endoh A, Komatsu Y, Matsuno Y, Sugiyama M, Manabe A, Sakurai A, Takahashi M, Naruse H, Torimoto Y, Dosaka- Akita H, Kinoshita I. Clinical significance of comprehensive genomic profiling tests covered by public insurance in patients with advanced solid cancers in Hokkaido, Japan. Jpn J Clin Oncol. 2021 Apr 30;51(5):753–761. Fukada I, Mori S, Hayashi N, Hosonaga M, Xiaofei W, Yamazaki M, Ueki A, Kiyotani K, Tonooka A, Takeuchi K, Ueno T, Takahashi S. Prognostic impact of cancer genomic profile testing for advanced or metastatic solid tumors in clinical practice. Cancer Sci. 2023 Dec;114(12):4632–4642. Kage H, Akiyama N, Chang H, Shinozaki-Ushiku A, Ka M, Kawata J, Muto M, Okuma Y, Okita N, Tsuchihara K, Kikuchi J, Shirota H, Hayashi H, Kokuryo T, Yachida S, Hirasawa A, Kubo M, Kenmotsu H, Tanabe M, Ushiku T, Muto K, Seto Y, Oda K. Patient survey on cancer genomic medicine in Japan under the national health insurance system. Cancer Sci. 2024 Mar;115(3):954–962. Kage H, Oda K, Muto M, Tsuchihara K, Okita N, Okuma Y, Kikuchi J, Shirota H, Hayashi H, Kokuryo T, Sakai D, Hirasawa A, Kubo M, Kenmotsu H, Akiyama N, Shinozaki-Ushiku A, Tanabe M, Ushiku T, Miyagawa K, Seto Y. Human resources for administrative work to carry out a comprehensive genomic profiling test in Japan. Cancer Sci. 2023 Jul;114(7):3041–3049. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFigure.docx SupplementaryTable1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 10 Jul, 2025 Reviews received at journal 16 Apr, 2025 Reviewers agreed at journal 16 Apr, 2025 Reviewers invited by journal 15 Apr, 2025 Submission checks completed at journal 10 Apr, 2025 First submitted to journal 03 Apr, 2025 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5501115","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":443242569,"identity":"5ab3c4da-5ca3-4c8f-8365-0826b087d777","order_by":0,"name":"Chie Sarudate","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chie","middleName":"","lastName":"Sarudate","suffix":""},{"id":443242570,"identity":"aed03650-72d7-4ef9-8880-c1dd73806fc1","order_by":1,"name":"Miki Dobashi","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Miki","middleName":"","lastName":"Dobashi","suffix":""},{"id":443242572,"identity":"e35cf6db-1d75-45a5-9a98-dd6d74647513","order_by":2,"name":"Maako Kawamura","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Maako","middleName":"","lastName":"Kawamura","suffix":""},{"id":443242574,"identity":"e2c18a68-ee3a-40bf-bca6-f16e4febfa2d","order_by":3,"name":"Hidekazu Shirota","email":"data:image/png;base64,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","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hidekazu","middleName":"","lastName":"Shirota","suffix":""},{"id":443242576,"identity":"dbb765ad-fb38-4a71-a898-0b18d0828617","order_by":4,"name":"Tomoyuki Iwasaki","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tomoyuki","middleName":"","lastName":"Iwasaki","suffix":""},{"id":443242579,"identity":"d55da369-5bf9-49be-86ff-c0c496472d0d","order_by":5,"name":"Hiroshi Tada","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hiroshi","middleName":"","lastName":"Tada","suffix":""},{"id":443242580,"identity":"719bf6c2-de26-410d-8425-d396932fef72","order_by":6,"name":"Muneaki Shimada","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Muneaki","middleName":"","lastName":"Shimada","suffix":""},{"id":443242581,"identity":"1189b282-dda5-4820-b7b1-af4108100b85","order_by":7,"name":"Naoki Kawamorita","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Kawamorita","suffix":""},{"id":443242582,"identity":"a6b52cbf-a376-440f-abf2-fd40a1b89619","order_by":8,"name":"Masayuki Kanamori","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masayuki","middleName":"","lastName":"Kanamori","suffix":""},{"id":443242583,"identity":"dbd19540-ca29-44b6-883d-f132715aa40b","order_by":9,"name":"Eisaku Miyauchi","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Eisaku","middleName":"","lastName":"Miyauchi","suffix":""},{"id":443242584,"identity":"c624fe35-c757-48c9-a38a-5cc34952f6ff","order_by":10,"name":"Hidetaka Niizuma","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hidetaka","middleName":"","lastName":"Niizuma","suffix":""},{"id":443242585,"identity":"402dfdb9-d43e-4c94-b989-92f998aa880b","order_by":11,"name":"Yuki Kasahara","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Kasahara","suffix":""},{"id":443242586,"identity":"87adcbe0-5c38-49b1-937d-5eb09f97ece8","order_by":12,"name":"Kota Ouchi","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kota","middleName":"","lastName":"Ouchi","suffix":""},{"id":443242587,"identity":"77e85842-3d30-4081-8405-7a42c47b1020","order_by":13,"name":"Hiroo Imai","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hiroo","middleName":"","lastName":"Imai","suffix":""},{"id":443242588,"identity":"7cb6fe9a-836b-46d1-98e6-da4cea17aeba","order_by":14,"name":"Ken Saijo","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ken","middleName":"","lastName":"Saijo","suffix":""},{"id":443242589,"identity":"3828dc83-4a8b-4c95-8755-acc5b2a7617d","order_by":15,"name":"Keigo Komine","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Keigo","middleName":"","lastName":"Komine","suffix":""},{"id":443242590,"identity":"9084d42e-bffa-4fa8-9eae-7b33d5d3c295","order_by":16,"name":"Masanobu Takahashi","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Masanobu","middleName":"","lastName":"Takahashi","suffix":""},{"id":443242591,"identity":"3b471667-1ff6-4ff1-b03b-dff84b489a8f","order_by":17,"name":"Toru Furukawa","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Toru","middleName":"","lastName":"Furukawa","suffix":""},{"id":443242592,"identity":"7885b105-9384-4e6b-9ed8-93abb6563d11","order_by":18,"name":"Aya Yokota","email":"","orcid":"","institution":"Hitachi High-Tech Corporation","correspondingAuthor":false,"prefix":"","firstName":"Aya","middleName":"","lastName":"Yokota","suffix":""},{"id":443242593,"identity":"6a8c0646-dd65-4df0-836f-4f93e8c33241","order_by":19,"name":"Eiji Kanamori","email":"","orcid":"","institution":"Hitachi High-Tech Corporation","correspondingAuthor":false,"prefix":"","firstName":"Eiji","middleName":"","lastName":"Kanamori","suffix":""},{"id":443242594,"identity":"21cbefbb-9ab2-431a-815c-1e854709ba6e","order_by":20,"name":"Chikashi Ishioka","email":"","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chikashi","middleName":"","lastName":"Ishioka","suffix":""}],"badges":[],"createdAt":"2024-11-22 02:53:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5501115/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5501115/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80782245,"identity":"ba9273f8-530b-41cc-aea3-08ce986093a2","added_by":"auto","created_at":"2025-04-17 04:58:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1763663,"visible":true,"origin":"","legend":"\u003cp\u003eDashboard window of the molecular tumor board portal system and summary of its features\u003c/p\u003e","description":"","filename":"CGPFig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/54ae48bb9a4e47ed953c6c30.png"},{"id":80782248,"identity":"197300bc-fdb0-4a74-8a9d-f2892dd19dea","added_by":"auto","created_at":"2025-04-17 04:58:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":326002,"visible":true,"origin":"","legend":"\u003cp\u003eConsort diagram for the outcome survey from the results of the CGP test to receiving a recommended treatment.\u003c/p\u003e","description":"","filename":"CGPFig2.png","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/b571ef279949e4d100d9c6e1.png"},{"id":80782517,"identity":"c990fa1f-29b5-4907-a028-f50bfead1275","added_by":"auto","created_at":"2025-04-17 05:06:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1008926,"visible":true,"origin":"","legend":"\u003cp\u003eIndividual swimmer plot for each patient depicting treatment duration with the recommended therapy.\u003c/p\u003e\n\u003cp\u003eThe vertical axis shows the genes in which alterations leading to treatment recommendations or biomarkers were observed, and the horizontal axis shows the recommended treatment period.\u003c/p\u003e","description":"","filename":"CGPFig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/4d4ca7f570605fec991de0d2.png"},{"id":80782250,"identity":"c9f319dd-fedf-44f2-bfe1-7da42db741c5","added_by":"auto","created_at":"2025-04-17 04:58:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":449073,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier plots for overall survival from submission of a CGP test in three groups: patients who received recommended therapy (n=118), patients who did not receive recommended therapy (n=126) and patients who did not receive a treatment recommendation (n=1398).\u003c/p\u003e","description":"","filename":"CGPFig4.png","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/2b936673ab7622fc05215fde.png"},{"id":80782522,"identity":"fd397aae-d183-443d-96c6-1be5d2e2eac1","added_by":"auto","created_at":"2025-04-17 05:06:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4449867,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/19da1013-1917-4972-8449-dbdf88622af3.pdf"},{"id":80782249,"identity":"ffa9d684-e03d-438e-acf6-e076e9016adc","added_by":"auto","created_at":"2025-04-17 04:58:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":160849,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/92d0abee5f530f6e497d392b.docx"},{"id":80782247,"identity":"1aa6cb08-2208-430d-abce-4ca94c68718b","added_by":"auto","created_at":"2025-04-17 04:58:08","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":24323,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5501115/v1/2c2fa0b2f6a6353c94c9a9e7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical Utility of Comprehensive Genomic Profiling Tests Using MTB Management System at a Single Center in Japan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eNext-generation sequencing-based comprehensive genomic profiling (CGP) for cancer patients has become widely used in many countries (1,2). In Japan, the CGP test has been available under the national health insurance reimbursement program since 2019 (3,4). The molecular tumor board (MTB), which interprets genetic information for diagnosis and treatment, requires insurance reimbursement and a high level of expertise, ranging from basic knowledge of molecular biology to clinical experience with molecular-targeted drugs (5). The MTB has reported recommending new therapies for approximately 10\u0026ndash;20% of the patients (6,7). However, it is anticipated that not all patients receive these therapies. The problem is that since the launch of cancer genomic medicine, its overall effectiveness has yet to be proven. Subsequent treatment and response rates to recommended agents must be further improved. In addition, the criteria for the treatment recommendations of the MTB and access to clinical trials are different at each facility; thus, each facility should provide its results.\u003c/p\u003e \u003cp\u003eThe Ministry of Health, Labor, and Welfare (MHLW) of Japan established a system to centrally manage CGP tests before the launch of cancer genome medicine (3,4). The purpose of this system is to promote cancer genome medicine that is consistent with the available evidence without regional disparities and to centralize data for use in drug development and research. However, this system substantially burdens many hospitals and frontline medical professionals. Regional core hospitals must organize MTB teams and collaborate with other hospitals to review the CGP data. Effective data sharing will provide quality genomic medicine to patients across clinical specialties. To avoid human error, manual work in time-consuming areas should be reduced and MTB medical teams require systems to support their work.\u003c/p\u003e \u003cp\u003eIn recent years, we have reported on the rate of treatment recommendations for MTB and on the management of presumed germline pathogenic variants at our facility (5,8). The rate of treatment recommendations is 19%, and the rate of hereditary tumor identification is 4.5%. Here, we report on the MTB system and treatment outcomes at our hospital as a result of five years of genomic medicine. The MTB portal system that we have developed shares patient information with various medical professionals through the Internet to recommend treatment and track patients. The MTB team must collaborate with other facilities, collect patient information with security assurance, and generate reports. The CGP test and treatment outcomes of 1643 cases using the system were summarized to determine the overall usefulness of this test. Based on the results, it is important to identify cancer types likely to be recommended for treatment and the timing of tests leading to treatment in the future.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, Patients, and the CGP test\u003c/h2\u003e \u003cp\u003eCGP tests were performed at Tohoku University Hospital to identify molecular therapeutic targets. They were retrospectively analyzed for genetic alterations, treatment suggestions, and subsequent treatment. The CGP test was performed on 1643 patients with solid tumors from September 2019 to June 2024. The criteria for this test in Japan for health insurance coverage have been previously reported (5,8). All patients were stage 4 cancer patients receiving chemotherapy. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e lists the characteristics (age, sex ratio, and type of CGP test) of the 1643 patients who underwent CGP testing. The characteristics of each test were reported previously (5,8). The Ethics Committee of Tohoku University Hospital approved this study. Informed consent was obtained from all patients to use their CGP data in clinical practice and for retrospective studies. In addition, patients were provided an opt-out disclosure for the details of specific studies. Approval of the research protocol and ethics by an Institutional Reviewer Board: IRB No. 2021-1-250 and 2023-1-1036.\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\u003eCharacteristics of patients, CGP test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMedian (range) age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (0\u0026ndash;90)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e844 (51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e799 (49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCGP test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFoundationOne CDx (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1259 (76.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFoundationOne liquid CDx (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e336 (20.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGuardant360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNCC Oncopanel (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (1.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenMineTOP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (0.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMTB management and portal system\u003c/h3\u003e\n\u003cp\u003eThe Japanese public insurance system mandates discussing cases in the MTB before the attending physician explains the outcome to the patients (3,4). The operation of our MTB has been reported previously (5). The MTB includes at least 10 oncologists, geneticists, genetic counselors, bioinformaticians, and data sequencing experts. During the meeting, the attending physician presents the patient's medical history and condition, and the team discusses potential treatment recommendations and clinical trial participation. Treatment recommendations for genetic alterations are categorized by level of evidence, based on the C-CAT report and other databases: level A, Japan- or FDA-approved drug for the cancer type; level B, expert consensus supported by clinical trials and meta-analyses; level C, Japan- or FDA-approved drug for other cancers; level D, case reports demonstrating efficacy across cancer types; level E, pre-clinical stage; level F, genetic changes involved in cancer. Treatment recommendations were made for genetic alterations at level D or higher. We have developed a web-based system with Hitachi High-Tech Corporation. For the efficient operation and discussion of the MTB teams. The secure system enables patient and genomic information to be shared among facilities. The results from several providers may be compiled into a comprehensive report using the same format. The comprehensive report contains citations from various databases, such as ClinVar, OncoKB (-2023), ToMMo, gnomAD, COSMIC, and CIViC (9\u0026ndash;14). Patients are listed and each specialist on the MTB team can leave comments. This allows seamless communication among the clinical staff. Patients are registered in the system and their treatment and prognosis are tracked.\u003c/p\u003e\n\u003ch3\u003eThe definition of treatment recommendation\u003c/h3\u003e\n\u003cp\u003eThe definition of a treatment recommendation by the MTB is the therapy the patient receives based on the results of CGP testing and the recommendation of the MTB. The treatment is either covered by health insurance in Japan or a Phase 2 or higher clinical trial expected to have beneficial therapeutic effects. Off-label drugs for personal use are not recommended. It does not include genes identified in companion diagnoses or treatments included in the standard of care. In Japan, treatment guidelines are updated periodically for each type of cancer. We adhere to the standard of care at the time of testing. Pan-cancer indications, such as TMB-H, BRAF, and NTRK fusions, are also considered. For example, immune checkpoint inhibitors are approved for many cancers and are part of standard treatment, allowing their use even without TMB-H. Therefore, TMB-H-based ICI recommendations are not made for cancer types already covered by standard treatment. Also, it will not be recommended if the patient's condition is too poor to undergo treatment. In other words, patients would only receive treatment with a CGP test. Treatments may include investigational drugs in clinical trials. Because of the confidential aspect of the clinical trials, all drug names were redacted and recommended treatments were based on biomarkers or genetic mutations.\u003c/p\u003e\n\u003ch3\u003ePatient follow-up after MTB\u003c/h3\u003e\n\u003cp\u003ePatient clinical information, previous treatments, and effects must be registered in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) (15). Treatment after the test was completed and prognostic information was part of the follow-up. We also surveyed whether the patients were treated as recommended, the date of last verified survival, and the date of death with the cooperation of other hospitals. The duration of treatment evaluated the recommended treatment. It was not evaluated by RECIST classification through imaging as in a clinical trial; instead, the duration of treatment was monitored until the attending physician determined that it was beneficial to the patient.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eKaplan\u0026ndash;Meier analysis was performed to estimate the distribution of overall survival (OS) and a log-rank test was used to analyze the statistical differences in survival. The Cox proportional hazard model was used to calculate the hazard ratio and 95% confidence interval. Differences were considered statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eManagement of patients with the MTB portal system\u003c/h2\u003e \u003cp\u003eWe developed a web-based system to manage the efficient operation of the MTB and its collaboration with other facilities. We designated this system \u0026ldquo;the MTB portal system.\u0026rdquo; The objectives of this platform are 1) the preparation and operation of the MTB through multi-center collaboration, 2) patient tracking and management, and 3) research and education in cancer genome medicine (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The patient database is securely listed and managed in a separate system from the electronic medical records. All tested cases are registered in this system, which can track the patient's clinical information and prognosis, an essential component of the C-CAT registry. The patient, cancer type, and a variant of the genetic alteration may query the system. The discussion of past MTB meetings can be reviewed. The system can also identify patients who are candidates for clinical trials or approved new drugs based on their genetic variants. We used this system to analyze the data regarding realistic cancer genomic medicine at our hospital.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCGP test and treatment recommendations\u003c/h3\u003e\n\u003cp\u003eThe patient background, gender ratio, type of CGP test, and cancer type are listed in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For 1643 patients, the most frequent type of cancer was pancreatic cancer (15.1%), followed by colorectal cancer (13.9%), bile duct cancer (10.3%), breast cancer (7.2%), prostate cancer (5.9%), ovarian cancer (4.9%), sarcomas (4.8%), brain cancer (4.7%), and lung cancer (3.6%). The median turnaround time to obtain consent for the test and provide the results to the patient was 35 (range: 23\u0026ndash;70) days. In our previous study, 67% of the actionable genes (Level of Evidence D or higher) were identified, and the treatment recommendation rate was 19% in the first 2 years (5). However, the subsequent treatment recommendation rate decreased to 14.6% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e lists the percentage of treatment recommendations based on each cancer type. These results were similar to those of our previous results. Thirty-seven patients were screened through the MTB portal system for recruitment to newly approved drugs and clinical trials after MTB. This figure accounted for 2.3% of the total patients.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eType of cancer and number of treatment recommendation and received treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of cancer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of treatment recommend (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of treatment received (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColorectal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBile duct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBreast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (31.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (14.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProstate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (13.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOvarian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (3.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSarcoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (12.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (7.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBrain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (6.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-small cell lung\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (16.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHead and neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (3.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndometrial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEsophageal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCUP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (12.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (4.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall intestine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (2.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePediatric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (6.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (34.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeuroendocrine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (8.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMelanoma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCervical Ca.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThymic ca.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKidney, urinary tract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (13.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (9.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e240 (14.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118 (7.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: Cancer of unknown primary (CUP)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTreatment cases recommended by MTB\u003c/h2\u003e \u003cp\u003eOf the cases for which treatment was recommended, nearly half (118 patients; 7.2% of the total) were treated with the drug recommended by the MTB (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The cancer types with the most frequent cases leading to a recommended treatment were, in order, thyroid cancer (34.6%), non-small cell lung cancer (15.3%), breast cancer (14.3%), prostate cancer (13.4%), and bile duct cancer (10.6%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The median time between returning the results to the patient and initiating treatment was 84 (range: 0\u0026ndash;798) days. The genetic mutations or biomarkers associated with the treated patients, including both under health insurance and clinical trials, were TMB-H (n\u0026thinsp;=\u0026thinsp;29), BRCA1/2 (n\u0026thinsp;=\u0026thinsp;21), ERBB2 (n\u0026thinsp;=\u0026thinsp;17), BRAF V600E (n\u0026thinsp;=\u0026thinsp;13), FGFR1/2 (n\u0026thinsp;=\u0026thinsp;8) and others (n\u0026thinsp;=\u0026thinsp;18) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). In contrast, it was necessary to describe the reasons for not treating a patient, even though it was recommended in the report to the C-CAT. The reasons were categorized into five groups as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Group 1 (n\u0026thinsp;=\u0026thinsp;42), which received different treatments, may receive the recommended treatment in the future. Groups 2\u0026ndash;5 in the table consisted of 53 patients, and of those available for follow-up, about half were considered to be in poor condition or did not meet the study criteria. Thus, they were not able to receive the recommended treatment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment recommendation according to gene alteration, biomarker\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene alteration\u003c/p\u003e \u003cp\u003eor Biomarker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment recommended\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreatment received\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo treatment\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTMB-H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBRCA1/2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eERBB2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBRAF\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eFGFR1/2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePIK3CA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTP53/MDM2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKIT/PDGFRA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eKRAS/MEK\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHRD/\u003cem\u003ePALB2/BRIP1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNTRK1/3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTSC1/2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eALK\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRET\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eROS1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eESR1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMET\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCCND1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCDK4\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEGFR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCDK12\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIDH1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes of treatment as recommended by MTB\u003c/h2\u003e \u003cp\u003eAll cases in which treatment was performed were followed except for one case. The median observation period from submitting the test was 416 days. Of the 117 patients that could be traced, 59 died. The actual duration of the recommended treatment and genetic mutations are shown in a swimmer\u0026rsquo;s plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A list of recommended and actual treatment drugs has been added as a supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Clinical trial drugs are listed as investigational drugs. In this case, the clinical trial included 25 patients. The combination of cancer type and genetic mutation is not listed because it could identify the drug in the clinical trial. In clinical practice, there are no clear criteria for the duration of treatment as defined in clinical trials. Treatment may be continued even if tumor growth is observed; however, the attending physician determines if it benefits the patient. The median duration of the recommended treatment was 132 days. The number of cases treated for more than 100 days was 74 (63%). These treatments were generally considered beneficial. The median duration of each treatment for TMB-H, BRCA1/2, ERBB2, BRAF V600E, and FGFR1/2 (biomarkers with at least 5 cases) was more significant than 100 days (data not shown). OS after submitting a CGP test was compared with/without the recommended treatment in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The median survival time for the patients who received the recommended treatment (n\u0026thinsp;=\u0026thinsp;118) based on the test was 21.0 months, whereas that for the patients who could not be treated for any reason, despite a treatment recommendation (n\u0026thinsp;=\u0026thinsp;126), was 12.9 months and 13.5 months for the patients who did not receive a treatment recommendation (n\u0026thinsp;=\u0026thinsp;1,398) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The group with a recommended treatment showed a significantly improved prognosis. The OS of the group that could not be treated for any reason, despite a treatment recommendation, and those with no recommended treatment were comparable. The average ages of the three groups were nearly identical: 61.3, 61.6, and 61.5 years, respectively. OS from first-line chemotherapy for each cancer type was evaluated (Supplemental Figure). Only the five cancer types with the highest treatment recommendation rates were compared between the treated and untreated groups. Although the number of patients for all cancer types was relatively small, making it difficult to determine statistical differences, the curves for non-small cell lung cancer, thyroid cancer, and cholangiocarcinoma were higher in the treatment group compared with that in the untreated group. No differences were observed for breast or prostate cancer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated real-world data on new treatment recommendations by the MTB based on a CGP test, the efficacy of the treatment, and patient prognosis at a single center in Japan. We also introduced the MTB portal system, which is an academic clinical decision support system developed with Hitachi High-Tech Corporation. It represents a scientific and technological platform to collect and share data from the CGP test. This system may be used for efficient MTB management, patient treatment, and prognosis follow-up. The recommended treatment rate by the MTB at our facility over five years was 14% and half of these patients (7%) were treated with the recommended drugs. Several patients who received treatment as recommended had a favorable response and a significantly better prognosis compared with those who did not receive treatment.\u003c/p\u003e \u003cp\u003eThere is a growing need for a system that efficiently supports the work of the medical team and the MTB (16). The MTB system mandated by the MHLW is complex because it involves many specialists and includes other facilities in the discussion (3). Therefore, we have developed a platform that integrates into the clinical workflow using a unique format, distributes results, and supports a shared discussion. Using the same format for multiple CGP tests facilitates consistent decision-making and structured data collection across all facilities. Automating the interpretation and reporting of the sequencing results reduces the need for error-prone and time-consuming manual labor. In addition, each specialist who views the data can leave comments, facilitating a collaborative discussion of complex cases over time through virtual molecular oncology meetings. The evidence for treatment is constantly changing, and there is a need to revise and update it for cases in the past constantly. Overall, this streamlined digital system can address the issues that are rapidly changing the precision oncology landscape and mobilize and leverage the expertise of the community. We also used this system to review evidence of drug use, newly approved drugs, and clinical trials for updated information on past cases and to provide up-to-date data for 37 patients.\u003c/p\u003e \u003cp\u003eSummarizing treatment recommendations by cancer type is a clinical indicator for selecting cases to be submitted for CGP testing. Treatment recommendations decreased from 19% in the first two years of reporting to 14% in the subsequent three years. The decrease has occurred because of new diagnostics and molecular-targeted drugs that do not require CGP testing, such as immune checkpoint inhibitors, BRAF inhibitors, and HER2 inhibitors, which have been approved in the past few years. In addition, some cases were immature, such as when a realistic treatment proposal was recommended even though access to the drugs in Japan was difficult. Treatment recommendations were made in 240 cases and the cancer type with the highest rate of recommendations was thyroid cancer, followed by non-small cell lung, prostate cancers, breast, and bile duct cancer, all of which resulted in a high percentage of treated patients. In particular, for lung cancer, new treatment recommendations have been identified despite multiple companion diagnoses. In contrast, pancreatic, colorectal, head and neck, stomach, and esophageal cancers had a low rate of treatment recommendations.\u003c/p\u003e \u003cp\u003eIn this report, 7% of all patients were treated with the recommended drugs, primarily molecular-targeted by the MTB. One of the major limitations of this report is that the names of the drugs used in the clinical trials had to be withheld. The treatment was effective in many cases, with 74 patients (62.7%) being treated for over 100 days. Reports from other facilities in Japan reported that 12.2% were treated based on the gene mutation identified in the CGP test by Ida et al., 13.4% by Sunami et al., 11.1% by Kikuchi et al., 3.6% by Inagaki et al., and 6.5% by Fukuda et al. Thus, our results are comparable (17\u0026ndash;20). However, half of the patients failed to undergo treatment despite the recommendations. Patients in group 1 receiving other treatments also left open the possibility of receiving those treatments in the future. Approximately 30% of the patients received treatment immediately (within 30 days) after receiving a recommendation. In addition, many patients could not participate in clinical trials or abandoned treatment because of their poor general condition (groups 2\u0026ndash;5 in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Although comparing patients with different cancer types, genetic mutations, and treatment regimens makes simple comparisons impossible, the prognosis for the patients who submitted a CGP test was significantly better in the group that received the treatment. At least some patients who underwent CGP testing realized a benefit. The results suggest that the cancer types with the higher recommended treatment rates have improved OS, although the number of cases treated was small and not significantly different. We hope to increase the number of cases and assess the results with consideration of confounding factors in future studies.\u003c/p\u003e \u003cp\u003eNow that the CGP test is covered by health insurance in Japan, it is important to verify periodically whether it benefits cancer patients. Evidence of its effectiveness will lead to the widespread use of cancer genome medicine. Of course, the criteria for determining the usefulness of the CGP test are not limited to just treatment recommendations. There are molecular diagnoses that cannot be determined by pathology alone, treatment selection within the standard care, prognostic prediction, and other factors that must be considered. Patient satisfaction surveys are also important (21,22). In addition, it is important to use systems for managing CGP testing, preparing the MTB, and following up on patient care. Here, we presented our unique MTB portal system. To provide equal access to cancer genome medicine, which is becoming increasingly complex with constantly changing evidence, managing patients solely by attending physicians is difficult. Thus, it would be ideal to establish a system in which centralized management is provided. As a result of drug development, patients with genetic mutations and cancer types for which treatment could not be recommended in the past may benefit. In addition, verifying the efficacy of recommended treatments will provide significant evidence for future treatment proposals for patients with similar genetic mutations. For this reason, it is necessary to track patients and provide feedback. The MTB team will need to track patients in a system, such as that described here, to apply the benefits of new evidence-based treatments to past cases.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all the physicians who attended our MTB meeting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eAll patients obtained Informed consent for research, but more detailed study protocols were approved by the IRB through the disclosure of information. Approval of the research protocol and ethics by an Institutional Reviewer Board: IRB No. 2021-1-250 and 2023-1-1036.\u003c/p\u003e\n\u003cp\u003eConflict of Interest\u003c/p\u003e\n\u003cp\u003eConflict of interest: Dr. Ishioka has received scholarship endowments from Takeda, Daiichi-Sankyo, Ono, Asahi-Kasei Pharma, Taiho, and Chugai, as well as research grant from Hitachi Co. Ltd. and Riken Genesis Co. Ltd. M. Takahashi has received research funding from Ono Pharmaceutical, Chugai Pharmaceutical, and MSD, lecturer fees from Daiichi Sankyo, Ono Pharmaceutical, Bristol Meyers Squibb, Taiho Pharmaceutical Company. Drs. Shirota and Komine have received research grant from Hitachi Co. Ltd. All remaining authors have declared no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShirota H designed the study. Sarudate C, Dobashi M, Kawamura M, Iwasaki T and Shirota H acquired and analyzed the patient data. Shirota H participated in the interpretation of results. Shirota H drafted the manuscript. All authors have read, reviewed, and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCollins FS, Varmus H. A new initiative on precision medicine. N Engl J Med. 2015;372(9):793\u0026ndash;795.\u003c/li\u003e\n\u003cli\u003eFrampton GM, Fichtenholtz A, Otto GA, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nat Biotechnol. 2013;31(11):1023\u0026ndash;1031.\u003c/li\u003e\n\u003cli\u003eEbi H, Bando H. Precision Oncology and the Universal Health Coverage System in Japan. JCO Precis Oncol. 2019 Dec 11;3:PO.19.00291.\u003c/li\u003e\n\u003cli\u003eMukai Y, Ueno H. Establishment and implementation of Cancer Genomic Medicine in Japan. Cancer Sci. 2021 Mar;112(3):970\u0026ndash;977.\u003c/li\u003e\n\u003cli\u003eShirota H, Komine K, Takahashi M, Takahashi S, Miyauchi E, Niizuma H, Tada H, Shimada M, Niihori T, Aoki Y, Sugiyama I, Kawamura M, Yasuda J, Suzuki S, Iwaya T, Saito M, Saito T, Shibata H, Furukawa T, Ishioka C. Clinical decisions by the molecular tumor board on comprehensive genomic profiling tests in Japan: A retrospective observational study. Cancer Med. 2023 Mar;12(5):6170\u0026ndash;6181.\u003c/li\u003e\n\u003cli\u003eLarson KL, Huang B, Weiss HL, et al. Clinical outcomes of molecular tumor boards: a systematic review. JCO Precis Oncol. 2021;5:PO.20.00495.\u003c/li\u003e\n\u003cli\u003eSeet AOL, Tan AC, Tan TJ, et al. Individualized molecular profiling for allocation to clinical trials Singapore study-an Asian tertiary cancer center experience. JCO Precis Oncol. 2021;5:PO.20.00261.\u003c/li\u003e\n\u003cli\u003eKawamura M, Shirota H, Niihori T, Komine K, Takahashi M, Takahashi S, Miyauchi E, Niizuma H, Kikuchi A, Tada H, Shimada M, Kawamorita N, Kanamori M, Sugiyama I, Tsubata M, Ichikawa H, Yasuda J, Furukawa T, Aoki Y, Ishioka C. Management of patients with presumed germline pathogenic variant from tumor-only genomic sequencing: A retrospective analysis at a single facility. J Hum Genet. 2023 Jun;68(6):399\u0026ndash;408.\u003c/li\u003e\n\u003cli\u003eLandrum MJ, Lee JM, Benson M, et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 2016;44(D1):D862-D868.\u003c/li\u003e\n\u003cli\u003eChakravarty D, Gao J, Phillips SM, et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol. 2017;2017:PO.17.00011.\u003c/li\u003e\n\u003cli\u003eTadaka S, Hishinuma E, Komaki S, et al. jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population. Nucleic Acids Res. 2021;49(D1):D536-D544.\u003c/li\u003e\n\u003cli\u003eKoch L. Exploring human genomic diversity with gnomAD. Nat Rev Genet. 2020;21(8):448.\u003c/li\u003e\n\u003cli\u003eForbes SA, Tang G, Bindal N, et al. COSMIC (the catalogue of somatic mutations in cancer): a resource to investigate acquired mutations in human cancer. Nucleic Acids Res. 2010;38(Database issue):D652-D657.\u003c/li\u003e\n\u003cli\u003eGriffith M, Spies NC, Krysiak K, et al. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet. 2017;49(2):170\u0026ndash;174.\u003c/li\u003e\n\u003cli\u003eKohno T, Kato M, Kohsaka S, Sudo T, Tamai I, Shiraishi Y, Okuma Y, Ogasawara D, Suzuki T, Yoshida T, Mano H. C-CAT: The National Datacenter for Cancer Genomic Medicine in Japan. Cancer Discov. 2022 Nov 2;12(11):2509\u0026ndash;2515.\u003c/li\u003e\n\u003cli\u003eTamborero D, Dienstmann R, Rachid MH, Boekel J, Lopez-Fernandez A, Jonsson M, Razzak A, Bra\u0026ntilde;a I, De Petris L, Yachnin J, Baird RD, Loriot Y, Massard C, Martin-Romano P, Opdam F, Schlenk RF, Vernieri C, Masucci M, Villalobos X, Chavarria E; Cancer Core Europe consortium; Balma\u0026ntilde;a J, Apolone G, Caldas C, Bergh J, Ernberg I, Fr\u0026ouml;hling S, Garralda E, Karlsson C, Tabernero J, Voest E, Rodon J, Lehti\u0026ouml; J. The Molecular Tumor Board Portal supports clinical decisions and automated reporting for precision oncology. Nat Cancer. 2022 Feb;3(2):251\u0026ndash;261.\u003c/li\u003e\n\u003cli\u003eIda H, Koyama T, Mizuno T, Sunami K, Kubo T, Sudo K, Tao K, Hirata M, Yonemori K, Kato K, Okusaka T, Ohe Y, Matsui Y, Yamazaki N, Ogawa C, Kawai A, Narita Y, Esaki M, Yamamoto N. Clinical utility of comprehensive genomic profiling tests for advanced or metastatic solid tumor in clinical practice. Cancer Sci. 2022 Dec;113(12):4300\u0026ndash;4310.\u003c/li\u003e\n\u003cli\u003eSunami K, Naito Y, Komine K, Amano T, Ennishi D, Imai M, Kage H, Kanai M, Kenmotsu H, Koyama T, Maeda T, Morita S, Sakai D, Kohsaka S, Tsuchihara K, Saigusa Y, Yoshino T. Chronological improvement in precision oncology implementation in Japan. Cancer Sci. 2022 Nov;113(11):3995\u0026ndash;4000.\u003c/li\u003e\n\u003cli\u003eKikuchi J, Ohhara Y, Takada K, Tanabe H, Hatanaka K, Amano T, C Hatanaka K, Hatanaka Y, Mitamura T, Kato M, Shibata Y, Yabe I, Endoh A, Komatsu Y, Matsuno Y, Sugiyama M, Manabe A, Sakurai A, Takahashi M, Naruse H, Torimoto Y, Dosaka- Akita H, Kinoshita I. Clinical significance of comprehensive genomic profiling tests covered by public insurance in patients with advanced solid cancers in Hokkaido, Japan. Jpn J Clin Oncol. 2021 Apr 30;51(5):753\u0026ndash;761.\u003c/li\u003e\n\u003cli\u003eFukada I, Mori S, Hayashi N, Hosonaga M, Xiaofei W, Yamazaki M, Ueki A, Kiyotani K, Tonooka A, Takeuchi K, Ueno T, Takahashi S. Prognostic impact of cancer genomic profile testing for advanced or metastatic solid tumors in clinical practice. Cancer Sci. 2023 Dec;114(12):4632\u0026ndash;4642.\u003c/li\u003e\n\u003cli\u003eKage H, Akiyama N, Chang H, Shinozaki-Ushiku A, Ka M, Kawata J, Muto M, Okuma Y, Okita N, Tsuchihara K, Kikuchi J, Shirota H, Hayashi H, Kokuryo T, Yachida S, Hirasawa A, Kubo M, Kenmotsu H, Tanabe M, Ushiku T, Muto K, Seto Y, Oda K. Patient survey on cancer genomic medicine in Japan under the national health insurance system. Cancer Sci. 2024 Mar;115(3):954\u0026ndash;962.\u003c/li\u003e\n\u003cli\u003eKage H, Oda K, Muto M, Tsuchihara K, Okita N, Okuma Y, Kikuchi J, Shirota H, Hayashi H, Kokuryo T, Sakai D, Hirasawa A, Kubo M, Kenmotsu H, Akiyama N, Shinozaki-Ushiku A, Tanabe M, Ushiku T, Miyagawa K, Seto Y. Human resources for administrative work to carry out a comprehensive genomic profiling test in Japan. Cancer Sci. 2023 Jul;114(7):3041\u0026ndash;3049.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5501115/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5501115/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCancer genomic medicine interprets genetic information for diagnosis and treatment. It requires an organized team of experts from various fields to discuss treatment recommendations at a molecular tumor board (MTB). It is also important to track patient outcomes based on these decisions and seamlessly incorporate them into future discussions at the MTB. We developed a system to manage the MTB efficiently. Using this system, we followed the outcome and prognosis of 1643 patients whose treatment was discussed at the MTB and evaluated the utility of a realistic comprehensive genomic profiling (CGP) test. Treatment recommendations were made for 240 patients (14% of the total cases). Of these, 118 (7% of the total) were treated with the drugs recommended by the MTB. The cancer type with the highest percentage of patients in which treatment recommendations were made and drugs were administered was thyroid cancer, followed by breast cancer, lung cancer, prostate cancer, and cholangiocarcinoma. While cancer-specific overall survival was inconclusive due to few cases, CGP-recommended treatment significantly extended patient survival from the CGP test date. This analysis, utilizing our patient follow-up system, suggests that CGP testing expands treatment options for a subset of patients and may improve treatment efficacy.\u003c/p\u003e","manuscriptTitle":"Clinical Utility of Comprehensive Genomic Profiling Tests Using MTB Management System at a Single Center in Japan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 04:58:03","doi":"10.21203/rs.3.rs-5501115/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-10T04:32:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-16T07:27:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"49041349131505903439165414929736010076","date":"2025-04-16T07:23:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-15T11:36:48+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-10T13:35:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-03T05:20:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"712e7321-6de1-459d-b662-d72dd3337d96","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":47190198,"name":"Biological sciences/Cancer"},{"id":47190199,"name":"Biological sciences/Cancer/Cancer genomics"},{"id":47190200,"name":"Biological sciences/Genetics/Cancer genomics"},{"id":47190201,"name":"Biological sciences/Genetics/Clinical genetics"},{"id":47190202,"name":"Biological sciences/Genetics/Genetic markers"}],"tags":[],"updatedAt":"2025-07-13T08:53:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-17 04:58:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5501115","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5501115","identity":"rs-5501115","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}