PDGFRA amplification could be a poor prognostic factor of advanced undifferentiated pleomorphic sarcoma in a comprehensive genomic profiling cohort

PDGFRA amplification could be a poor prognostic factor of advanced undifferentiated pleomorphic sarcoma in a comprehensive genomic profiling cohort | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article PDGFRA amplification could be a poor prognostic factor of advanced undifferentiated pleomorphic sarcoma in a comprehensive genomic profiling cohort Hiroshi Kobayashi, Masachika Ikegami, Liuzhe Zhang, Koichi Okajima, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8360517/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Undifferentiated pleomorphic sarcoma (UPS) is the most common pleomorphic sarcoma, and its genomic landscape has been analyzed, albeit in small numbers. This study aimed to clarify the relationship between gene variants and the prognosis of patients with advanced UPS. Methods This retrospective cohort study was conducted to analyze the data of patients with advanced UPS using a registry of the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database up to Oct 2025 in Japan, analyzed using comprehensive genomic profiling assay. Results A total of 233 patients with advanced UPS were identified in the C-CAT database; 151 men (64.8%), median age: 60.2 years. TP53 variant (55%) was the most frequent event, and the rate of PDGFRA and KDR amplification were 9% and 6%, respectively. PDGFRA amplification co-occurred with KDR amplification ( P < 0.001). Survival from the initiation of chemotherapy was analyzed by adjusting for length bias inherent in the database using the Kaplan–Meier estimator, an established method of adjustment. Patients with PDGFRA amplification (11 patients) had a worse prognosis than those without PDGFRA amplification [hazard ratio 2.9, 95% confidence interval 1.2–6.9 ( P = 0.02 )]. TP53 alterations ( P = 0.24 ) were not associated with prognosis. In addition, treatment time with pazopanib with PDGFRA amplification [4 patients, 2.3 months (1.2–11.2 months)] was not different with those without PDGFRA amplification [28 patients, 3.8 months (0.9 months–not reached)] ( P = 0.52). Conclusions For patients with advanced UPS, PDGFRA amplification was a poor prognostic factor, and is not related to the efficacy of pazopanib treatment. undifferentiated pleomorphic sarcoma soft tissue comprehensive genomic profiling PDGFRA amplification Figures Figure 1 Figure 2 Figure 3 Introduction Undifferentiated pleomorphic sarcoma (UPS) is a malignant neoplasm that does not present with a specific differentiation pattern and accounts for approximately 20% of all newly diagnosed soft tissue sarcomas [ 1 ]. UPS mainly arises in soft tissues, particularly in the extremities. The mainstay of treatment for localized UPS is resection of the primary tumor; radiotherapy, chemotherapy, and immunotherapy are sometimes performed perioperatively. However, the prognosis is poor, with 5-year overall survival rates raging 50–60% [ 2 , 3 ]. Prognostic factors for UPS include tumor size, histological grade, and age, which are also known prognostic factors for other sarcomas [ 4 , 5 ]. Recent multiomics analyses have revealed that transcriptomic and immune profiles can be used for prognostic stratification [ 6 – 9 ]. Cancer genomic profiling (CGP) assays are performed worldwide for cancer treatment and have been covered by public health insurance since 2019 in Japan. All clinical and gene variant data analyzed using the CGP test were collected from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database, allowing access to clinical research and drug development [ 10 ]. There have been several reports on the genomic landscape of UPS [ 6 , 9 , 11 ]; however, few reports have analyzed the relationship between gene variants and prognosis in UPS, especially in patients with advanced UPS. Platelet-derived growth factor receptor alpha ( PDGFRA ) is a gene coding a tyrosine kinase receptor that activates tyrosine kinase. Gene mutations and amplification of PDGFRA are associated with tumorigenesis, affecting tumor cell proliferation, migration, invasion, and immune infiltration [ 12 – 14 ]. Amplification of PDGFRA has been frequently detected in several cancers, including low-grade astrocytoma and invasive breast cancer [ 15 , 16 ] and is reportedly a poor prognostic factor. In soft tissue sarcoma, there have been a few reports on the occurrence and prognostic value of amplification of PDGFRA [ 17 – 19 ], and there have been no reports on advanced UPS. In this study, we aimed to identify the mutational landscape and relationship between gene alterations and prognosis in patients with advanced UPS using C-CAT data. In addition, we focused on PDGFRA amplification and the efficacy of survival-prolonging chemotherapy, especially with the multi-tyrosine kinase inhibitor pazopanib. Patients and Methods Data source and extraction In Japan, CGP was approved in 2019, but only for use in patients with advanced solid tumors who have completed standard chemotherapy or for whom no appropriate standard chemotherapy is available [ 20 ]. The CGP results and clinical information of almost all patients receiving the CGP test were collected at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) [ 20 ]; these data can be used for clinical research and drug development. To date, more than 101,000 patients with advanced cancer have undergone CGP since June 2019, and undifferentiated pleomorphic sarcoma of the soft tissue accounted for 233 of these cases between June 2019 and Oct 2025. The clinical and genetic alteration data detected using CGP were provided to the C-CAT by the patients after receiving an explanation from their physicians and providing informed consent. This study was approved by the Research Ethics Committee of the Faculty of Medicine at the University of Tokyo (permission number: 2021341G) and the C-CAT Data Utilization Review Board (permission number: CDU2022-026N). Information on annotated gene alterations was collected using the OncoKB, ClinVar, and Cancer Knowledge databases provided by C-CAT. From this database, we identified likely pathogenic and pathogenic gene alterations. Five gene panels with different numbers of gene sets were used: Foundation One CDx (174 cases), GenMine TOP (43 cases), OncoGuide NCC Oncopanel (11 cases), Foundation One Liquid CDx (4 cases), and Gurdant360 CDx (1 case). Survival and Statistical analysis Survival analyses were performed using the date of the first survival-prolonging chemotherapy because the C-CAT database does not include the disease stage at the time of diagnosis. A survival simulation based on a semi-independent two-hit model using Bayes inference was conducted to adjust for both right-censored and left-truncation biases as previously reported [ 19 , 21 ]. In short, the survival curves from the date of the first survival-prolonging chemotherapy to CGP testing and from CGP testing to death or the last observation were approximated using Weibull and log-logistic distributions, respectively. The OS curve from the date of the first survival-prolonging chemotherapy was estimated by summing the two survival curves. Eight thousand survival curves were obtained from the inference and the median. Survival and 95% equal-tail intervals were calculated. Mutational landscapes of the 20 genes with the highest frequencies of oncogenic mutations were created using the ComplexHeatmap package in R. Mutually exclusive or co-occurring pair analyses were performed for the 20 most frequently altered genes using the ReDiscover package in R. Statistical analysis All statistical analyses were conducted using R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria), and the ‘tranSurv’ package was used to calculate Kendall’s tau statistic as reported previously [ 22 ]. Survival analyses—including Kaplan–Meier analysis, log-rank test, and Cox regression analysis—were performed using the Kaplan–Meier ‘survival’ package [ 23 ]. Hazard ratios (HRs) were calculated using Cox regression analysis. Overall survival after the first survival-prolonging chemotherapy was performed with risk-set (number at risk) adjustment for left-truncation bias. Results Patient characteristics and prognosis The clinical characteristics are shown in Table 1 . A total of 233 patients with advanced UPS were identified in the C-CAT database: 151 men (64.8%), median age − 60.2 years. Performance status (PS) of 210 patients (90.2%) was 0 or 1. Treatment indicated by expert panel was administered to nine patients (3.9%). The median OS was 13.9 months (95% confidence interval (CI) 12.4–26.8) after the first survival-prolonging chemotherapy. With a Kendall’s tau of 0.04 (p = 0.60), the left truncation period between the initiation of chemotherapy and CGP testing was considered quasi-independent of overall survival, and survival analysis was conducted accordingly (Supplementary Fig. 1). Table 1 Demographics and clinical characteristics of patients with advanced undifferentiated pleomorphic sarcoma in the C-CAT database Characteristic N = 233 % Sex Female 82 35.2 Male 151 64.8 Age at CGP (years) Mean (SD) 60.2 (16.7) Performance status 0 132 56.7 1 78 33.5 2 14 6.0 3 2 0.9 Unknown 7 3.0 Treatment recommended by expert panel No 174 74.7 Yes 59 25.3 Indicated treatment administered No 224 96.1 Yes 9 3.9 Any distant metastasis No 42 18.0 Unknown 8 3.4 Yes 183 78.5 CTx lines before CGP 0 104 44.6 1 73 31.3 2 36 15.5 ≧3 20 8.6 Genetic alterations and prognosis Figure 1 A shows overall mutational landscape. The most common gene variant found was the TP53 variant (55%) followed by the CDKN2A loss (27%), CDKN2B loss (21%), and RB1 variant (20%). The rate of PDGFRA and KDR amplification were 9% and 6%, respectively. High tumor mutation burden was observed in 5%. PDGFRA amplification co-occurred with KDR amplification ( P < 0.001) and KIT amplification ( P < 0.001) (Supplementary Fig. 2), reflecting the co-localization of 4q12. Among the top 20 genes with high variant frequencies, CDKN2B , PDGFRA , and KDR were significantly associated with a shorter prognosis by calculating HRs and P -values (Fig. 1 B). In addition, we evaluated the correlations between these variants and prognosis in the length bias-adjusted model; CDKN2B (HR 1.9, 95% CI 1.1–3.5 P = 0.03) and PDGFRA (HR 2.9, 95% CI 1.2–6.9 P = 0.02) (Fig. 2 ) were associated with poorer overall survival after the initiation of first palliative chemotherapy. PDGFRA amplification and treatment time of palliative chemotherapy PDGFRA and KDR may be the targets of pazopanib, a multityrosine kinase inhibitor. We focused on PDGFRA because KDR amplification was observed in only six cases, and evaluated the relationship between the efficacy of pazopanib and PDGFRA amplification. Among the 32 patients treated with pazopanib, four had PDGFRA amplification. Treatment time of pazopanib was not statistically different between those with and without PDGFRA amplification (median treatment time 2.3 (1.2–11.2) and 3.9 (0.9–NA) months, P = 0.521) (Fig. 3 A). We then compared the efficacy of pazopanib and other drugs in patients with PDGFRA amplification and found no difference in treatment time between the two groups (median treatment time 3.8 (0.9–NA) and 1.6 (0.7–2.8) months, P = 0.38) (Fig. 3 B). Although TP53 variants are reportedly associated with the efficacy of pazopanib, we did not find a relationship between the efficacy of pazopanib and TP53 variants in patients with advanced UPS (Supplementary Fig. 3). Discussion This study analyzed the mutational landscape and relationship between prognostic impact and sensitivity to drugs and gene alterations in patients with advanced UPS using national registry data, which included almost all data of cases that received the CGP test in Japan. The results showed a mutational landscape of UPS and that CDKN2B loss, PDGFRA amplification, and KDR amplification were the significant factors for poor prognosis. In addition, PDGFRA amplification was not related to sensitivity to pazopanib. Our main finding was that CDKN2B loss and PDGFRA amplification were common events in advanced UPS and that these genes were significant poor prognostic factors. First, comparing the mutational landscape of our cohort with that of previous reports, the most frequently mutated gene was TP53 (55%), which was compatible with previous reports ranging 59–69% [ 7 , 11 ]. Similarly, CDKN2A and CDKN2B losses were observed in 27% and 21% cases, compatible with previous reports that CDKN2A loss was 20–24% [ 7 , 24 ]. TERT promoter mutation is known to be a less frequent event in UPS compared to other sarcomas, including myxoid liposarcoma; and instead, ATRX alteration is a frequent event in UPS, ranging 29–34% as alternative lengthening of telomere pathway [ 7 , 11 ]. Consistent with these reports, ATRX alterations, not but TERT promoter mutations was observed; however, the frequency was 7%, which was lower than previous reports [ 7 , 11 ]. Although whether ATRX mutation could be a prognostic factor in UPS has not been reported, the data showed that ATRX mutation was less frequent in advanced UPS and could not be related to the aggressiveness of UPS. In addition to the differences in the frequency of gene alterations, our results revealed that PDGFRA amplification was a relatively frequent event in advanced UPS. According to the data on advanced soft tissue sarcomas with all histological subtypes from the C-CAT data base, PDGFRA amplification was observed in 3% [ 19 ]. In the Sarcoma Genome Project data, PDGFRA amplification was observed in 3% [ 25 ]. In our advanced UPS cases, the rate of PDGFRA amplification was 9%, which was relatively high. In addition, PDGFRA amplification was a significantly poor prognostic factor for advanced UPS. In the aforementioned report on advanced soft tissue sarcomas of all histological subtypes, PDGFRA amplification tended to be a poor prognostic factor, although it was not statistically significant [ 19 ]. In other cancers, patients with IDH wild-type glioblastoma multiforme and PDGFRA amplification have a significantly poor prognosis [ 14 ]. In a pan-cancer analysis, not PDGFRA amplification the amplification of PDGFRA pathway was associated with significantly shorter overall survival [ 15 ]. These findings support our finding that PDGFRA amplification is a poor prognostic factor in advanced UPS. As pazopanib is an inhibitor of multi-tyrosine kinases, including VEGFR and PDGFR, we analyzed the correlation between PDGFRA amplification and the efficacy of pazopanib. Our findings suggest that PDGFRA amplification is not associated with the efficacy of pazopanib. A previous case report showed that patients with UPS and PDGFRA, VEGFR2, and KIT amplifications, all located at 4q12 and usually co-amplified, were successfully treated with pazopanib [ 26 ]. We could not analyze the correlation between the co-amplification of these genes and the efficacy of pazopanib because of the limited number of cases. It is unclear whether the efficacy of pazopanib is influenced by VEGFR2, and KIT amplifications other than PDGFRA amplification, or by co-alteration of genes other than PDGFRA amplification. Our results suggest that PDGFRA amplification is not a predictive marker for pazopanib in patients with UPS. Regarding the prediction of the efficacy of pazopanib, a retrospective analysis of 19 cases of advanced soft tissue sarcoma and patients with TP53 mutations showed longer progression free survival (PFS) than those without TP53 mutations (PFS 208 versus 136 days, P = 0.036) [ 27 ]. In our analysis of 32 patients treated with pazopanib, TP53 mutations were not associated with pazopanib efficacy. The possible cause of the discrepancy between the previous report and our results is that the previous report included several types of histology, including leiomyosarcoma and angiosarcoma, and five out of 19 cases were leiomyosarcoma, which is sensitive to pazopanib [ 28 , 29 ]; all leiomyosarcoma cases were positive for TP53 mutation. Another report that analyzed soft tissue sarcoma cases with a high response to pazopanib showed that GLI1 amplification, which upregulates PDGFRB expression, could be a predictive marker of the response to pazopanib [ 30 ]. In our cases, GLI1 amplification was not observed, and further analysis using the C-CAT database, including other histological subtypes, should be performed in the future. In another study of predictive markers of pazopanib in soft tissue sarcoma conducted in Germany, which analyzed 62 patients using transcriptome sequencing, the combination of NTRK3 -high, IGF1R -low, and KDR -high was reportedly associated with longer PFS [ 31 ]. However, we were unable to use transcriptomic data to verify these results. Furthermore, analysis using GenMine TOP data, which have been available since Aug 2023 in Japan and include an RNA panel, could also be a future task. This study has some limitations that should be considered when interpreting the results. First, several cases were excluded because of insufficient prognostic or clinical data, and the short follow-up period, particularly after CGP, may have introduced bias. Second, this was a retrospective analysis of the C-CAT database. Patients without CGP testing or genes not represented in the CGP panel were excluded from the study. Third, the number of cases was relatively small, particularly in the analysis of genetic alterations and drug efficacy, despite the use of a national database, owing to the rarity of the disease. Fourth, survival analysis after the first survival-prolonging chemotherapy was performed under the assumption of quasi-independent left truncation, as Kendall’s tau between the time from chemotherapy initiation to CGP testing and overall survival was 0.04. Although this weak correlation suggests limited dependence, potential bias due to residual dependence between truncation and survival time cannot be completely ruled out. In conclusion, using a comprehensive national registry encompassing nearly all CGP-tested cases in Japan, this study characterized the mutational landscape of advanced UPS and examined the associations between gene alterations, prognosis, and drug response. This survival analysis offers important insights into the relationship between recurrent genetic alterations and the clinical outcomes of patients with advanced UPS. CDKN2B loss and PDGFRA/KDR amplification were identified as unfavorable prognostic markers, whereas PDGFRA amplification was not associated with pazopanib responsiveness. Although this study has certain limitations, its findings provide meaningful contributions to optimize the use of CGP testing and improve the management of advanced UPS. Declarations Conflict of interest statement: The authors declare no conflicts of interest. Authors’ contributions HK wrote the paper and performed the literature review. 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Asterisks denote statistically significant correlations ( P <0.001). Supplementary Fig. 3 Kaplan–Meier curves showing treatment time with pazopanib comparing between patients with and without TP53 alterations. Cite Share Download PDF Status: Posted Version 1 posted 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. 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Byoin","correspondingAuthor":false,"prefix":"","firstName":"Sakae","middleName":"","lastName":"Tanaka","suffix":""}],"badges":[],"createdAt":"2025-12-14 23:31:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8360517/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8360517/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100859370,"identity":"509fb0b1-dbf4-44d3-8439-92e1103fc944","added_by":"auto","created_at":"2026-01-22 07:27:16","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":10417,"visible":true,"origin":"","legend":"","description":"","filename":"ijcoIJCOD2501523.xml","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/5fa6dc4495496860604bdeb4.xml"},{"id":100856506,"identity":"616c7e68-f297-4177-8715-94273c91b323","added_by":"auto","created_at":"2026-01-22 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07:06:20","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78445,"visible":true,"origin":"","legend":"","description":"","filename":"IJCOD25015230structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/c047ba9dee4028e76133c2e1.xml"},{"id":100856505,"identity":"54cc0479-a751-4e5f-b2d9-cbbec2663d63","added_by":"auto","created_at":"2026-01-22 07:06:20","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":89210,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/22cff0de979ed6af70f50416.html"},{"id":100949725,"identity":"8fb23d98-a688-468e-b075-f93780d2f5d3","added_by":"auto","created_at":"2026-01-23 07:05:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":168077,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a)\u003c/strong\u003eMutational landscape of advanced soft-tissue undifferentiated pleomorphic sarcoma (UPS). The 20 genes with the highest alteration frequencies are presented.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e(b)\u003c/strong\u003e Forest plot illustrating the correlations between gene alterations and prognosis in advanced UPS. The same 20 genes shown in (a) were evaluated. Overall survival following the initiation of first-line palliative chemotherapy was compared between patients harboring or lacking variants in each gene. Hazard ratios (HRs) and P-values were estimated using Cox proportional hazards models adjusted for length bias with the Kaplan–Meier estimator. HR \u0026lt;1 denotes longer survival in the variant group than in the wild-type group, whereas HR \u0026gt;1 indicates shorter survival.\u003c/p\u003e\n\u003cp\u003eCI, confidence interval\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/9eb3ac788869491962f83289.png"},{"id":100856495,"identity":"3ab671a1-37ad-4fe8-b65f-1223c1787524","added_by":"auto","created_at":"2026-01-22 07:06:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91290,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves showing survival estimates adjusted for both right-censoring and left-truncation biases, comparing overall survival after the first survival-prolonging chemotherapy between patients with and without \u003cstrong\u003e(a) \u003c/strong\u003e\u003cem\u003eCDKN2B\u003c/em\u003eloss and \u003cstrong\u003e(b)\u003c/strong\u003e \u003cem\u003ePDGFRA\u003c/em\u003e amplification\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/4cc7b06e1788ca159e9d8e49.png"},{"id":100856504,"identity":"6a81099f-6f31-474c-b76e-1089598d75c0","added_by":"auto","created_at":"2026-01-22 07:06:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":75509,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier curves showing (a) treatment time with pazopanib comparing between patients with and without \u003cem\u003ePDGFRA\u003c/em\u003eamplification, and (b) treatment time with pazopanib and other drugs in patients with \u003cem\u003ePDGFRA\u003c/em\u003e amplification\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/45f58dd3c8da38f19c47d119.png"},{"id":105034773,"identity":"a12886bd-76a0-407b-845c-ec6e898921ff","added_by":"auto","created_at":"2026-03-20 07:24:08","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":948502,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/214abf1c-c849-477b-bdcd-f4abe00fb8af.pdf"},{"id":100856497,"identity":"69f56b92-ee50-4577-aff1-47dd17dcd65f","added_by":"auto","created_at":"2026-01-22 07:06:20","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":317710,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 1 \u003c/strong\u003eOverall survival after the first survival-prolonging chemotherapy after adjusting for left-truncation bias\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 2\u003c/strong\u003e Heat map illustrating mutually exclusive or co-occurring relationships among frequently altered genes. Blue indicates mutual exclusivity, and red indicates co-occurrence. Asterisks denote statistically significant correlations (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Fig. 3 \u003c/strong\u003eKaplan–Meier curves showing treatment time with pazopanib comparing between patients with and without \u003cem\u003eTP53\u003c/em\u003ealterations.\u003c/p\u003e","description":"","filename":"CCATUPSfigureIJCOsubmit.pptx","url":"https://assets-eu.researchsquare.com/files/rs-8360517/v1/221708227f97181cf6ccc4b6.pptx"}],"financialInterests":"","formattedTitle":"PDGFRA amplification could be a poor prognostic factor of advanced undifferentiated pleomorphic sarcoma in a comprehensive genomic profiling cohort","fulltext":[{"header":"Introduction","content":"\u003cp\u003eUndifferentiated pleomorphic sarcoma (UPS) is a malignant neoplasm that does not present with a specific differentiation pattern and accounts for approximately 20% of all newly diagnosed soft tissue sarcomas [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. UPS mainly arises in soft tissues, particularly in the extremities. The mainstay of treatment for localized UPS is resection of the primary tumor; radiotherapy, chemotherapy, and immunotherapy are sometimes performed perioperatively. However, the prognosis is poor, with 5-year overall survival rates raging 50\u0026ndash;60% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Prognostic factors for UPS include tumor size, histological grade, and age, which are also known prognostic factors for other sarcomas [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Recent multiomics analyses have revealed that transcriptomic and immune profiles can be used for prognostic stratification [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Cancer genomic profiling (CGP) assays are performed worldwide for cancer treatment and have been covered by public health insurance since 2019 in Japan. All clinical and gene variant data analyzed using the CGP test were collected from the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database, allowing access to clinical research and drug development [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. There have been several reports on the genomic landscape of UPS [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]; however, few reports have analyzed the relationship between gene variants and prognosis in UPS, especially in patients with advanced UPS.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePlatelet-derived growth factor receptor alpha\u003c/em\u003e (\u003cem\u003ePDGFRA\u003c/em\u003e) is a gene coding a tyrosine kinase receptor that activates tyrosine kinase. Gene mutations and amplification of \u003cem\u003ePDGFRA\u003c/em\u003e are associated with tumorigenesis, affecting tumor cell proliferation, migration, invasion, and immune infiltration [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Amplification of \u003cem\u003ePDGFRA\u003c/em\u003e has been frequently detected in several cancers, including low-grade astrocytoma and invasive breast cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and is reportedly a poor prognostic factor. In soft tissue sarcoma, there have been a few reports on the occurrence and prognostic value of amplification of \u003cem\u003ePDGFRA\u003c/em\u003e [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and there have been no reports on advanced UPS.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to identify the mutational landscape and relationship between gene alterations and prognosis in patients with advanced UPS using C-CAT data. In addition, we focused on \u003cem\u003ePDGFRA\u003c/em\u003e amplification and the efficacy of survival-prolonging chemotherapy, especially with the multi-tyrosine kinase inhibitor pazopanib.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source and extraction\u003c/h2\u003e \u003cp\u003eIn Japan, CGP was approved in 2019, but only for use in patients with advanced solid tumors who have completed standard chemotherapy or for whom no appropriate standard chemotherapy is available [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The CGP results and clinical information of almost all patients receiving the CGP test were collected at the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; these data can be used for clinical research and drug development. To date, more than 101,000 patients with advanced cancer have undergone CGP since June 2019, and undifferentiated pleomorphic sarcoma of the soft tissue accounted for 233 of these cases between June 2019 and Oct 2025. The clinical and genetic alteration data detected using CGP were provided to the C-CAT by the patients after receiving an explanation from their physicians and providing informed consent. This study was approved by the Research Ethics Committee of the Faculty of Medicine at the University of Tokyo (permission number: 2021341G) and the C-CAT Data Utilization Review Board (permission number: CDU2022-026N).\u003c/p\u003e \u003cp\u003eInformation on annotated gene alterations was collected using the OncoKB, ClinVar, and Cancer Knowledge databases provided by C-CAT. From this database, we identified likely pathogenic and pathogenic gene alterations. Five gene panels with different numbers of gene sets were used: Foundation One CDx (174 cases), GenMine TOP (43 cases), OncoGuide NCC Oncopanel (11 cases), Foundation One Liquid CDx (4 cases), and Gurdant360 CDx (1 case).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSurvival and Statistical analysis\u003c/h3\u003e\n\u003cp\u003eSurvival analyses were performed using the date of the first survival-prolonging chemotherapy because the C-CAT database does not include the disease stage at the time of diagnosis. A survival simulation based on a semi-independent two-hit model using Bayes inference was conducted to adjust for both right-censored and left-truncation biases as previously reported [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In short, the survival curves from the date of the first survival-prolonging chemotherapy to CGP testing and from CGP testing to death or the last observation were approximated using Weibull and log-logistic distributions, respectively. The OS curve from the date of the first survival-prolonging chemotherapy was estimated by summing the two survival curves. Eight thousand survival curves were obtained from the inference and the median.\u003c/p\u003e \u003cp\u003eSurvival and 95% equal-tail intervals were calculated. Mutational landscapes of the 20 genes with the highest frequencies of oncogenic mutations were created using the ComplexHeatmap package in R. Mutually exclusive or co-occurring pair analyses were performed for the 20 most frequently altered genes using the ReDiscover package in R.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted using R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria), and the \u0026lsquo;tranSurv\u0026rsquo; package was used to calculate Kendall\u0026rsquo;s tau statistic as reported previously [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Survival analyses\u0026mdash;including Kaplan\u0026ndash;Meier analysis, log-rank test, and Cox regression analysis\u0026mdash;were performed using the Kaplan\u0026ndash;Meier \u0026lsquo;survival\u0026rsquo; package [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Hazard ratios (HRs) were calculated using Cox regression analysis. Overall survival after the first survival-prolonging chemotherapy was performed with risk-set (number at risk) adjustment for left-truncation bias.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics and prognosis\u003c/h2\u003e \u003cp\u003eThe clinical characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 233 patients with advanced UPS were identified in the C-CAT database: 151 men (64.8%), median age \u0026minus;\u0026thinsp;60.2 years. Performance status (PS) of 210 patients (90.2%) was 0 or 1. Treatment indicated by expert panel was administered to nine patients (3.9%). The median OS was 13.9 months (95% confidence interval (CI) 12.4\u0026ndash;26.8) after the first survival-prolonging chemotherapy. With a Kendall\u0026rsquo;s tau of 0.04 (p\u0026thinsp;=\u0026thinsp;0.60), the left truncation period between the initiation of chemotherapy and CGP testing was considered quasi-independent of overall survival, and survival analysis was conducted accordingly (Supplementary Fig.\u0026nbsp;1).\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\u003eDemographics and clinical characteristics of patients with advanced undifferentiated pleomorphic sarcoma in the C-CAT database\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\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;233\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at CGP (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60.2 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePerformance status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTreatment recommended by expert panel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndicated treatment administered\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAny distant metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCTx lines before CGP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e≧3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.6\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=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGenetic alterations and prognosis\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA shows overall mutational landscape. The most common gene variant found was the \u003cem\u003eTP53\u003c/em\u003e variant (55%) followed by the \u003cem\u003eCDKN2A\u003c/em\u003e loss (27%), \u003cem\u003eCDKN2B\u003c/em\u003e loss (21%), and \u003cem\u003eRB1\u003c/em\u003e variant (20%). The rate of \u003cem\u003ePDGFRA\u003c/em\u003e and \u003cem\u003eKDR\u003c/em\u003e amplification were 9% and 6%, respectively. High tumor mutation burden was observed in 5%. \u003cem\u003ePDGFRA\u003c/em\u003e amplification co-occurred with \u003cem\u003eKDR\u003c/em\u003e amplification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and \u003cem\u003eKIT\u003c/em\u003e amplification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Supplementary Fig.\u0026nbsp;2), reflecting the co-localization of 4q12. Among the top 20 genes with high variant frequencies, \u003cem\u003eCDKN2B\u003c/em\u003e, \u003cem\u003ePDGFRA\u003c/em\u003e, and \u003cem\u003eKDR\u003c/em\u003e were significantly associated with a shorter prognosis by calculating HRs and \u003cem\u003eP\u003c/em\u003e-values (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). In addition, we evaluated the correlations between these variants and prognosis in the length bias-adjusted model; \u003cem\u003eCDKN2B\u003c/em\u003e (HR 1.9, 95% CI 1.1\u0026ndash;3.5 \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) and \u003cem\u003ePDGFRA\u003c/em\u003e (HR 2.9, 95% CI 1.2\u0026ndash;6.9 \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) were associated with poorer overall survival after the initiation of first palliative chemotherapy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePDGFRA\u003c/b\u003e \u003cb\u003eamplification and treatment time of palliative chemotherapy\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003ePDGFRA\u003c/em\u003e and \u003cem\u003eKDR\u003c/em\u003e may be the targets of pazopanib, a multityrosine kinase inhibitor. We focused on \u003cem\u003ePDGFRA\u003c/em\u003e because \u003cem\u003eKDR\u003c/em\u003e amplification was observed in only six cases, and evaluated the relationship between the efficacy of pazopanib and \u003cem\u003ePDGFRA\u003c/em\u003e amplification. Among the 32 patients treated with pazopanib, four had \u003cem\u003ePDGFRA\u003c/em\u003e amplification. Treatment time of pazopanib was not statistically different between those with and without \u003cem\u003ePDGFRA\u003c/em\u003e amplification (median treatment time 2.3 (1.2\u0026ndash;11.2) and 3.9 (0.9\u0026ndash;NA) months, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.521) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). We then compared the efficacy of pazopanib and other drugs in patients with \u003cem\u003ePDGFRA\u003c/em\u003e amplification and found no difference in treatment time between the two groups (median treatment time 3.8 (0.9\u0026ndash;NA) and 1.6 (0.7\u0026ndash;2.8) months, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.38) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Although \u003cem\u003eTP53\u003c/em\u003e variants are reportedly associated with the efficacy of pazopanib, we did not find a relationship between the efficacy of pazopanib and \u003cem\u003eTP53\u003c/em\u003e variants in patients with advanced UPS (Supplementary Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study analyzed the mutational landscape and relationship between prognostic impact and sensitivity to drugs and gene alterations in patients with advanced UPS using national registry data, which included almost all data of cases that received the CGP test in Japan. The results showed a mutational landscape of UPS and that \u003cem\u003eCDKN2B\u003c/em\u003e loss, \u003cem\u003ePDGFRA\u003c/em\u003e amplification, and \u003cem\u003eKDR\u003c/em\u003e amplification were the significant factors for poor prognosis. In addition, \u003cem\u003ePDGFRA\u003c/em\u003e amplification was not related to sensitivity to pazopanib.\u003c/p\u003e \u003cp\u003eOur main finding was that \u003cem\u003eCDKN2B\u003c/em\u003e loss and \u003cem\u003ePDGFRA\u003c/em\u003e amplification were common events in advanced UPS and that these genes were significant poor prognostic factors. First, comparing the mutational landscape of our cohort with that of previous reports, the most frequently mutated gene was \u003cem\u003eTP53\u003c/em\u003e (55%), which was compatible with previous reports ranging 59\u0026ndash;69% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Similarly, \u003cem\u003eCDKN2A\u003c/em\u003e and \u003cem\u003eCDKN2B\u003c/em\u003e losses were observed in 27% and 21% cases, compatible with previous reports that \u003cem\u003eCDKN2A\u003c/em\u003e loss was 20\u0026ndash;24% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. \u003cem\u003eTERT\u003c/em\u003e promoter mutation is known to be a less frequent event in UPS compared to other sarcomas, including myxoid liposarcoma; and instead, \u003cem\u003eATRX\u003c/em\u003e alteration is a frequent event in UPS, ranging 29\u0026ndash;34% as alternative lengthening of telomere pathway [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Consistent with these reports, \u003cem\u003eATRX\u003c/em\u003e alterations, not but \u003cem\u003eTERT\u003c/em\u003e promoter mutations was observed; however, the frequency was 7%, which was lower than previous reports [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although whether \u003cem\u003eATRX\u003c/em\u003e mutation could be a prognostic factor in UPS has not been reported, the data showed that \u003cem\u003eATRX\u003c/em\u003e mutation was less frequent in advanced UPS and could not be related to the aggressiveness of UPS. In addition to the differences in the frequency of gene alterations, our results revealed that \u003cem\u003ePDGFRA\u003c/em\u003e amplification was a relatively frequent event in advanced UPS. According to the data on advanced soft tissue sarcomas with all histological subtypes from the C-CAT data base, \u003cem\u003ePDGFRA\u003c/em\u003e amplification was observed in 3% [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In the Sarcoma Genome Project data, \u003cem\u003ePDGFRA\u003c/em\u003e amplification was observed in 3% [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In our advanced UPS cases, the rate of \u003cem\u003ePDGFRA\u003c/em\u003e amplification was 9%, which was relatively high. In addition, \u003cem\u003ePDGFRA\u003c/em\u003e amplification was a significantly poor prognostic factor for advanced UPS. In the aforementioned report on advanced soft tissue sarcomas of all histological subtypes, \u003cem\u003ePDGFRA\u003c/em\u003e amplification tended to be a poor prognostic factor, although it was not statistically significant [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In other cancers, patients with \u003cem\u003eIDH\u003c/em\u003e wild-type glioblastoma multiforme and \u003cem\u003ePDGFRA\u003c/em\u003e amplification have a significantly poor prognosis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In a pan-cancer analysis, not \u003cem\u003ePDGFRA\u003c/em\u003e amplification the amplification of \u003cem\u003ePDGFRA\u003c/em\u003e pathway was associated with significantly shorter overall survival [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These findings support our finding that \u003cem\u003ePDGFRA\u003c/em\u003e amplification is a poor prognostic factor in advanced UPS.\u003c/p\u003e \u003cp\u003eAs pazopanib is an inhibitor of multi-tyrosine kinases, including VEGFR and PDGFR, we analyzed the correlation between \u003cem\u003ePDGFRA\u003c/em\u003e amplification and the efficacy of pazopanib. Our findings suggest that \u003cem\u003ePDGFRA\u003c/em\u003e amplification is not associated with the efficacy of pazopanib. A previous case report showed that patients with UPS and \u003cem\u003ePDGFRA, VEGFR2, and KIT\u003c/em\u003e amplifications, all located at 4q12 and usually co-amplified, were successfully treated with pazopanib [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We could not analyze the correlation between the co-amplification of these genes and the efficacy of pazopanib because of the limited number of cases. It is unclear whether the efficacy of pazopanib is influenced by \u003cem\u003eVEGFR2, and KIT\u003c/em\u003e amplifications other than \u003cem\u003ePDGFRA\u003c/em\u003e amplification, or by co-alteration of genes other than \u003cem\u003ePDGFRA\u003c/em\u003e amplification. Our results suggest that \u003cem\u003ePDGFRA\u003c/em\u003e amplification is not a predictive marker for pazopanib in patients with UPS. Regarding the prediction of the efficacy of pazopanib, a retrospective analysis of 19 cases of advanced soft tissue sarcoma and patients with \u003cem\u003eTP53\u003c/em\u003e mutations showed longer progression free survival (PFS) than those without \u003cem\u003eTP53\u003c/em\u003e mutations (PFS 208 versus 136 days, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In our analysis of 32 patients treated with pazopanib, \u003cem\u003eTP53\u003c/em\u003e mutations were not associated with pazopanib efficacy. The possible cause of the discrepancy between the previous report and our results is that the previous report included several types of histology, including leiomyosarcoma and angiosarcoma, and five out of 19 cases were leiomyosarcoma, which is sensitive to pazopanib [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; all leiomyosarcoma cases were positive for \u003cem\u003eTP53\u003c/em\u003e mutation. Another report that analyzed soft tissue sarcoma cases with a high response to pazopanib showed that \u003cem\u003eGLI1\u003c/em\u003e amplification, which upregulates \u003cem\u003ePDGFRB\u003c/em\u003e expression, could be a predictive marker of the response to pazopanib [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our cases, \u003cem\u003eGLI1\u003c/em\u003e amplification was not observed, and further analysis using the C-CAT database, including other histological subtypes, should be performed in the future. In another study of predictive markers of pazopanib in soft tissue sarcoma conducted in Germany, which analyzed 62 patients using transcriptome sequencing, the combination of \u003cem\u003eNTRK3\u003c/em\u003e-high, \u003cem\u003eIGF1R\u003c/em\u003e-low, and \u003cem\u003eKDR\u003c/em\u003e-high was reportedly associated with longer PFS [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, we were unable to use transcriptomic data to verify these results. Furthermore, analysis using GenMine TOP data, which have been available since Aug 2023 in Japan and include an RNA panel, could also be a future task.\u003c/p\u003e \u003cp\u003eThis study has some limitations that should be considered when interpreting the results. First, several cases were excluded because of insufficient prognostic or clinical data, and the short follow-up period, particularly after CGP, may have introduced bias. Second, this was a retrospective analysis of the C-CAT database. Patients without CGP testing or genes not represented in the CGP panel were excluded from the study. Third, the number of cases was relatively small, particularly in the analysis of genetic alterations and drug efficacy, despite the use of a national database, owing to the rarity of the disease. Fourth, survival analysis after the first survival-prolonging chemotherapy was performed under the assumption of quasi-independent left truncation, as Kendall\u0026rsquo;s tau between the time from chemotherapy initiation to CGP testing and overall survival was 0.04. Although this weak correlation suggests limited dependence, potential bias due to residual dependence between truncation and survival time cannot be completely ruled out.\u003c/p\u003e \u003cp\u003eIn conclusion, using a comprehensive national registry encompassing nearly all CGP-tested cases in Japan, this study characterized the mutational landscape of advanced UPS and examined the associations between gene alterations, prognosis, and drug response. This survival analysis offers important insights into the relationship between recurrent genetic alterations and the clinical outcomes of patients with advanced UPS. \u003cem\u003eCDKN2B\u003c/em\u003e loss and \u003cem\u003ePDGFRA/KDR\u003c/em\u003e amplification were identified as unfavorable prognostic markers, whereas \u003cem\u003ePDGFRA\u003c/em\u003e amplification was not associated with pazopanib responsiveness. Although this study has certain limitations, its findings provide meaningful contributions to optimize the use of CGP testing and improve the management of advanced UPS.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of interest statement:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e \u003cp\u003eHK wrote the paper and performed the literature review. MI, LZ, KO, TA, YT, TH, and ST contributed to the conception and design of the manuscript and critically revised it. All the authors have read and approved the final version of this manuscript.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWHO Classification of Tumours Editorial Board (2020) WHO classification of tumors soft tissue and bone tumours, 5th edn. IARC, Lyon, pp 403\u0026ndash;409\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgura K, Morizane C, Satake T et al (2024) Nov 2) Soft-tissue sarcoma in Japan: National Cancer Registry-based analysis from 2016 to 2019. 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Clin Orthop Relat Res 478:2461\u0026ndash;2476. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/CORR.0000000000001322\u003c/span\u003e\u003cspan address=\"10.1097/CORR.0000000000001322\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeilig CE, La\u0026szlig;mann A, Mughal SS et al (2022) Sep) Gene expression-based prediction of pazopanib efficacy in sarcoma. Eur J Cancer 172:107\u0026ndash;118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ejca.2022.05.025\u003c/span\u003e\u003cspan address=\"10.1016/j.ejca.2022.05.025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"undifferentiated pleomorphic sarcoma, soft tissue, comprehensive genomic profiling, PDGFRA amplification","lastPublishedDoi":"10.21203/rs.3.rs-8360517/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8360517/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUndifferentiated pleomorphic sarcoma (UPS) is the most common pleomorphic sarcoma, and its genomic landscape has been analyzed, albeit in small numbers. This study aimed to clarify the relationship between gene variants and the prognosis of patients with advanced UPS.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study was conducted to analyze the data of patients with advanced UPS using a registry of the Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database up to Oct 2025 in Japan, analyzed using comprehensive genomic profiling assay.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 233 patients with advanced UPS were identified in the C-CAT database; 151 men (64.8%), median age: 60.2 years. \u003cem\u003eTP53\u003c/em\u003e variant (55%) was the most frequent event, and the rate of \u003cem\u003ePDGFRA\u003c/em\u003e and \u003cem\u003eKDR\u003c/em\u003e amplification were 9% and 6%, respectively. \u003cem\u003ePDGFRA\u003c/em\u003e amplification co-occurred with \u003cem\u003eKDR\u003c/em\u003e amplification (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Survival from the initiation of chemotherapy was analyzed by adjusting for length bias inherent in the database using the Kaplan\u0026ndash;Meier estimator, an established method of adjustment. Patients with \u003cem\u003ePDGFRA\u003c/em\u003e amplification (11 patients) had a worse prognosis than those without \u003cem\u003ePDGFRA\u003c/em\u003e amplification [hazard ratio 2.9, 95% confidence interval 1.2\u0026ndash;6.9 (\u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.02\u003c/em\u003e)]. \u003cem\u003eTP53\u003c/em\u003e alterations (\u003cem\u003eP\u0026thinsp;=\u0026thinsp;0.24\u003c/em\u003e) were not associated with prognosis. In addition, treatment time with pazopanib with \u003cem\u003ePDGFRA\u003c/em\u003e amplification [4 patients, 2.3 months (1.2\u0026ndash;11.2 months)] was not different with those without \u003cem\u003ePDGFRA\u003c/em\u003e amplification [28 patients, 3.8 months (0.9 months\u0026ndash;not reached)] (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.52).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eFor patients with advanced UPS, \u003cem\u003ePDGFRA\u003c/em\u003e amplification was a poor prognostic factor, and is not related to the efficacy of pazopanib treatment.\u003c/p\u003e","manuscriptTitle":"PDGFRA amplification could be a poor prognostic factor of advanced undifferentiated pleomorphic sarcoma in a comprehensive genomic profiling cohort","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-22 07:06:15","doi":"10.21203/rs.3.rs-8360517/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"10d65374-2c0c-41a4-9ec7-69fda18e11f8","owner":[],"postedDate":"January 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-18T14:52:28+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-22 07:06:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8360517","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8360517","identity":"rs-8360517","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}