Whole-Exome Sequencing Reveals Hippo Pathway Mutations as a Hallmark of Aggressive PTMC in Young Males

Whole-Exome Sequencing Reveals Hippo Pathway Mutations as a Hallmark of Aggressive PTMC in Young Males | 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 Whole-Exome Sequencing Reveals Hippo Pathway Mutations as a Hallmark of Aggressive PTMC in Young Males Seongdo Jeong, Junho Kang, Jieon Lee, Sun Min Lee, Seung Hwan Oh, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7153805/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Papillary thyroid microcarcinoma (PTMC) is typically associated with an excellent prognosis, and active surveillance is often appropriate for tumors smaller than 0.5 cm. However, surgical intervention is warranted when there is evidence of tumor progression or suspicion of lymph node metastasis. This study aims to characterize the genetic alterations associated with lymph node metastasis in PTMC to inform risk-adapted surgical management. Methods DNA was extracted from primary tumor tissues of 42 PTMC patients with central lymph node metastasis and 30 patients without metastasis. Whole-exome sequencing (WES) was performed for both groups, and somatic variants were analyzed using the maftools package in R. Mutational signatures were compared against reference profiles from the COSMIC database. Statistical analyses were conducted to evaluate the prognostic significance of the identified variants. Results Patients with lymph node metastasis were significantly younger and more frequently male compared to those without metastasis. Whole-exome sequencing revealed a higher somatic mutational burden in the metastatic group, along with distinct mutational signatures, including an enrichment of COSMIC Signature SBS89. Recurrently mutated genes such as BRAF , FGFR1 , and CREBBP were identified across the cohort, while comparative analysis between primary tumors and lymph node metastases demonstrated divergent mutation profiles. Notably, male patients with lymph node metastasis exhibited frequent missense mutations in FAM98A , CYP26B1 , and EPS8L3 , as well as exclusive alterations in key components of the hippo signaling pathway, including YAP1 , TEAD1 , and WNT16 . Pathway-level analysis confirmed significant enrichment of hippo pathway mutations in this subgroup, suggesting a potential sex-specific molecular mechanism underlying metastatic progression in PTMC. Conclusions This study highlights that PTMC with lymph node metastasis, particularly in male patients, exhibits distinct genomic characteristics, including enrichment of COSMIC Signature SBS89 and recurrent mutations in components of the hippo signaling pathway. These findings underscore the potential value of molecular profiling in identifying high-risk subgroups and optimizing individualized management strategies in PTMC. Papillary thyroid microcarcinoma Whole exome sequencing Hippo pathway lymph node metastasis Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Papillary thyroid carcinoma (PTC) represents the most prevalent subtype of thyroid malignancy, accounting for approximately 80% of all thyroid cancer cases[ 1 ] [ 2 ] [ 3 ]. The disease is generally indolent and associated with a favorable clinical outcome, with a 5-year disease-specific survival rate exceeding 90%, particularly in younger patients [ 4 ]. Papillary thyroid microcarcinoma (PTMC), which is smaller than 1 cm, has an excellent long-term prognosis, with a disease-specific mortality rate of less than 0.1% and a recurrence rate of approximately 3% [ 5 ]. Although 9–42% of patients present with clinically evident lymph node metastases at diagnosis, the majority of cases do not show distant metastasis, and these patients tend to have an especially favorable prognosis [ 6 ] [ 7 ] [ 8 ] [ 9 ]. Given the indolent nature of PTMC, ongoing societal concerns persist regarding the issues of over-diagnosis and over-treatment in the management of cancer [ 10 ] [ 11 ]. Therefore, when PTMC is diagnosed, it is important to evaluate for the presence of lymph node or distant metastasis or extrathyroidal extension. In the absence of such clinical findings, active surveillance with delayed surgery only upon evidence of disease progression may be considered an optimal approach [ 12 ] [ 13 ] [ 14 ]. Based on this concept, active surveillance has been proposed as a feasible alternative to immediate surgery for managing low-risk PTMC. Nevertheless, in cases of PTMC, if there is suspicion of lymph node metastases during follow-up or if the tumor size increases, surgical intervention is recommended. However, it is difficult to identify central neck lymph node metastases with ultrasonography [ 15 ] [ 16 ] [ 17 ] [ 18 ]. Given that PTMC generally has a favorable prognosis, it is crucial to identify cases that necessitate surgical treatment in order to improve patients’ quality of life. Hence, the objective of this study is to ascertain the presence of distinct DNA mutations associated with lymph node metastasis in PTMC by conducting whole exome sequencing (WES) on both the group with lymph node metastasis and the group without. Methods Patients and Samples Fresh frozen primary tumor tissues (n = 72 samples) were collected from 72 patients who were diagnosed with PTMC at Pusan National University Yangsan Hospital, Korea, throughout the period from 2015 to 2022. The patients had surgery and received thyroid hormone replacement treatment. Among the 72 samples, 30 were primary tumor tissues without lymph node metastasis, and 42 were primary tumor tissues with lymph nodes metastases. We evaluated the histology, tumor size, lymph node status, presence of thyroid capsule invasion, presence of multiple tumor foci, and type of surgery. The Institutional Review Board of Pusan National University Yangsan Hospital (55-2023-041) granted this study. The bio-specimens and clinical data were acquired from the Institutional Biobank Project (OF-2023-14) following the approved study protocol. The research conducted in this study adhered to the principles outlined in the Declaration of Helsinki. Whole exome sequencing Genomic DNA (gDNA) library was constructed from 50 ng of input gDNA utilizing the Twist Library Preparation EF Kit 2.0 (96 samples, PN 104207). Full-length combinatorial dual index TruSeq-compatible Y-adapters (Illumina) were employed in accordance with the Twist Bioscience Library Protocol. DNA quantity was quantified using PicoGreen (Invitrogen), while DNA quality was assessed through TapeStation gDNA Screentape (Agilent). 50ng of gDNA, diluted with EB Buffer, were sheared to a target peak size of 200bp with the fragmentation enzyme. DNA fragmentation is followed by end-repair and A-tailing, which involves the enzymatic addition of an ‘A’ tail to the 3’ ends. Twist UDI index adapters are subsequently ligated to the fragments. After evaluating ligation efficiency, the adapter-ligated DNA fragments are amplified via PCR. Quantification of the final purified product was performed using the TapeStation DNA Screentape D1000 (Agilent) and the fluorescence -based PicoGreen assay. For exome capture, each hybridization reaction requires 1500 ng of indexed libraries, prepared by pooling equimolar amounts from eight individual libraries. The mixture was combined with Hybridization mix, Twist exome 2.0 probe, Blocker solution, Universal Blocker, and Hybridization Enhancer according to the Twist library preparation protocol. The captured DNA is thoroughly washed and subsequently amplified. The final purified product is quantified by qPCR, following the qPCR Quantification Protocol Guide (KAPA Library Quantification kits for Illumina Sequencing platforms), and qualified using the TapeStation DNA Screentape D1000 (Agilent). Sequencing was performed using the NovaSeq6000 platform (Illumina, San Diego, USA), achieving an average coverage depth of 100x. Somatic Variant Calling Somatic variants were identified using the Genome Analysis Toolkit (GATK, version 4; https://gatk.broadinstitute.org/ ) DNA analysis pipeline. The pipeline integrates sequence alignment, preprocessing, and haplotype-based variant calling into a unified workflow. Raw sequencing reads were aligned to the human reference genome (hg38) using BWA-MEM, followed by duplicate marking with Picard and base quality score recalibration using GATK. Somatic variant calling was performed using Mutect2, with a Panel of Normals (PoN) generated from the 1000 Genomes Project and the gnomAD database used as a germline resource. To enhance the accuracy of the detected variants, we applied FilterMutectCalls to remove sequencing artifacts and false positives. Annotated variants were obtained using Funcotator. Variants were filtered based on the following criteria: (1) population allele frequency < 1% in gnomAD, (2) exclusion of recurrent artefactual variants observed across multiple samples or known false-positive sites. Analysis of Somatic Variants Somatic variant analysis was performed using the maftools package (v2.14.0) in R. Annotated MAF files were imported and visualized to summarize the mutation landscape across all samples. The overall distribution of base substitution types was assessed using the titv() function, and variant classification was visualized with plotVariantClassification(). The most frequently mutated genes were identified, and mutation patterns were illustrated using oncoplot(). To compare mutation burden between clinical subgroups (e.g., primary vs. lymph node metastasis), total mutation counts were extracted and statistically tested using Wilcoxon rank-sum tests. Clinical metadata including sex, age, and group classification were incorporated into the oncoplot for integrated visualization of clinical and genetic features. Mutational signature analysis was conducted by constructing a trinucleotide mutation matrix using the BSgenome.Hsapiens.NCBI.GRCh38 reference genome. The Non-negative Matrix Factorization (NMF) algorithm was applied to extract de novo mutational signatures using the extractSignatures() function, and the optimal number of signatures was selected based on cophenetic correlation coefficient curves. Extracted signatures were then compared to the COSMIC v3.3 reference using cosine similarity to identify biologically relevant matches. Logistic regression analysis was conducted using the glm() function to assess the association between clinical variables (e.g., sex, lymph node metastasis) and mutational features. Mosaic plots were generated to visualize the distribution of categorical variables across groups. Pathway-level mutation analysis was performed by grouping mutated genes into KEGG pathways, and enrichment was assessed using hypergeometric tests. Notably, mutation burden in the hippo signaling pathway was compared between subgroups using boxplots and statistical testing. Statistical analysis All statistical analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria). Clinical and pathological characteristics between patients with and without lymph node metastasis were assessed using the independent two-sample t-test or Mann-Whitney U test for continuous variables, depending on data normality. For categorical variables, comparisons were made using the chi-square test or Fisher's exact test. Group-wise comparisons of tumor mutational burden (TMB) and pathway-specific mutation counts were also conducted using the Mann-Whitney U test. Associations between clinical variables and metastasis were evaluated using logistic regression models, and results were visualized as odds ratios with 95% confidence intervals. All visualizations and statistical plots were generated using the `ggpubr` and `ggplot2` packages in R. Results Patient characteristics Table 1 shows the clinicopathologic characteristics of patients with and without lymph node metastasis. Patients with lymph node metastasis were significantly younger than those without lymph node metastasis. In terms of gender distribution, the lymph node metastasis group had a higher proportion of male patients (16/42, 38.1%) compared to the non-metastasis group (2/30, 6.7%). In the group with lymph node metastasis, the tumor size was found to be 0.8 cm, which was larger than the 0.7 cm observed in the group without lymph node metastasis. The presence of extension was observed in 73.8% of patients with lymph node metastasis and 76.7% of those without, showing no notable difference. Among the 42 patients with lymph node metastasis, 5 patients had lateral neck lymph node metastasis and underwent lateral neck lymph node dissection. Table 1 Clinicopathologic characteristics of patients Characteristics Patients with LN metastasis (n = 42) Patients without LN metastasis (n = 30) p -value Age (yr) 42.0 ± 11.8 52.0 ± 9.5 0.018 Gender 0.002 Male 16 2 Female 26 28 Tumor size (cm) 0.8 ± 0.1 0.7 ± 0.1 0.042 Extension 0.783 Yes 31 23 No 11 7 Multifocality 0.770 Solitary 28 19 Multifocal 14 11 Number of dissected Central LNs 4.5 ± 4.5(2 ~ 22) 5.0 ± 5.1(2 ~ 20) 0.881 Number of dissected lateral LNs 27.0 ± 17.5(10 ~ 57) 0 < 0.001 Surgery 0.105 Lobectomy with CLND 28 20 Total thyroidectomy with CLND 9 10 Total thyroidectomy with CLND with LND 5 0 LN; Lymph node, CLND; Central neck lymph node dissection, LND; Lateral neck lymph node dissection Somatic mutation landscape in PTMC patients Whole-exome sequencing (WES) was performed on 72 PTMC samples, including 42 primary tumors and 30 matched lymph node metastases. Analysis of the base substitution spectrum revealed a predominance of C > T and T > G transitions across the cohort (Fig. 1 A), a pattern commonly associated with age-related mutational processes in thyroid and other epithelial malignancies. Regarding variant classification, missense mutations were the most frequently observed, followed by frameshift deletions and nonsense mutations (Fig. 1 B). An oncoplot analysis of the top 20 recurrently mutated genes identified BRAF as the most frequently altered gene, consistent with its established role as a key driver in PTC. In addition to BRAF , mutations in genes such as FGFR1 , EIF4EBP1 , and CREBBP , which have been implicated in oncogenic signaling in various cancer types, were also recurrently detected (Fig. 1 C). Clinical variables including age, sex, and tumor group were integrated into the oncoplot to visualize potential associations with mutational profiles. Comparative mutation analysis between primary tumors and lymph node metastases To investigate genetic differences associated with metastatic progression, we compared the somatic mutation profiles between primary tumors and matched lymph node metastases. The lymph node metastasis group exhibited a significantly higher number of somatic mutations compared to the primary tumor group (p = 0.027; Fig. 2 A), suggesting a possible association between increased mutational burden and metastatic potential in PTMC. Mutational signature analysis revealed distinct patterns between the two groups. The primary tumors displayed a mutational profile resembling COSMIC Signature SBS37, characterized by moderate levels of C > T and T > C substitutions. In contrast, lymph node metastases were dominated by SBS89, which is enriched in T > C and T > G substitutions and has been linked to age-related mutagenesis and potential mismatch repair (MMR) deficiency (Fig. 2 B). Group-specific oncoplot analysis identified several genes preferentially mutated in each group (Fig. 2 C). Mutations in UVRAG , USP19 , PLPP1 , FOXD4L3 , and CTSB were observed predominantly in primary tumors, suggesting their involvement in early tumorigenic events. In contrast, YBX1 , SPRED3 , SLFN11 , FAT4 , and COP6 mutations were more frequent in lymph node metastases, implying a role in metastatic progression or tumor adaptation. Clinical annotation further revealed that lymph node–associated mutations were more frequently observed in male patients and individuals under 60 years of age, consistent with previously reported risk factors for aggressive disease in PTMC. All mutation information appears in Supplemental data 1. Sex-specific mutation enrichment in metastatic PTMC Patients Given the observed increase in mutation burden and male predominance in the lymph node metastasis group, we performed a subgroup analysis to further investigate the interaction between sex and metastasis in PTMC. Logistic regression analysis revealed that the interaction term "male × lymph node metastasis" was associated with a markedly elevated risk (odds ratio: 7.5), indicating a potential synergistic effect between male sex and metastatic status (Fig. 3 A). To explore sex distribution across groups, a mosaic plot was generated. The analysis revealed a significant overrepresentation of male patients in the lymph node metastasis group compared to the primary tumor group (p = 5.78 × 10⁻³; Fig. 3 B). We next compared the somatic mutation profiles of the “male + lymph node metastasis” group against all other patients. Oncoplot analysis demonstrated that the “male + lymph” group exhibited frequent missense mutations in genes such as FAM98A , CYP26B1 , C2orf78 , PILRA , and EPS8L3 (Fig. 3 C). Notably, several genes involved in the hippo signaling pathway including WNT16 , TEAD1 , and YAP1 were mutated exclusively in this group, suggesting potential biological relevance related to metastatic progression in male patients. Enrichment of hippo pathway mutations in the male + metastatic subgroup To investigate whether this clinically distinct subgroup harbored unique molecular alterations, we performed a pathway-level analysis of somatic mutations. This analysis revealed that the “male + lymph node metastasis” group exhibited a significantly higher number of mutations in genes associated with the hippo signaling pathway (p < 0.01; Fig. 4 A). KEGG pathway enrichment analysis confirmed that the hippo signaling pathway was the most significantly enriched pathway in this group, followed by stem cell–related and EGFR-related signaling pathways (Fig. 4 B). Oncoplot analysis of hippo pathway genes revealed several members including YAP1 , TEAD1 , SAV1 , FAT1 , and LATS2 that were preferentially mutated in lymph node metastases, particularly in male patients (Fig. 4 C) (Supplemental data 2). These findings suggest that hippo pathway dysregulation may play a critical role in the metastatic behavior of PTMC in a sex-specific context. Discussion Active surveillance is increasingly recognized as a safe and effective management strategy for selected patients with PTMC [ 12 ] [ 13 ] [ 14 ]. However, its implementation in routine clinical practice remains limited. Patient-related concerns including anxiety over possible disease progression, psychological discomfort with deferring treatment, and the financial burden of regular follow-up have been identified as major barriers to its broader adoption [ 19 ] [ 20 ] [ 21 ]. To enhance the clinical applicability of active surveillance, it is crucial to identify reliable clinical and molecular predictors of aggressive disease behavior. Current guidelines recommend active surveillance for PTMC patients who lack clinical evidence of lymph node or distant metastasis and show no gross extrathyroidal extension involving critical structures such as the trachea or recurrent laryngeal nerve. However, lymph node metastases are reported in approximately 9–42% of PTMC cases [ 6 ] [ 7 ] [ 8 ] [ 9 ], often necessitating surgical intervention regardless of tumor size. Importantly, preoperative detection of central compartment (level VI) lymph node metastasis remains challenging due to the limited sensitivity and operator dependence of neck ultrasound [ 15 ] [ 16 ] [ 17 ] [ 18 ]. To address this clinical challenge, we performed whole-exome sequencing on surgically resected PTMC samples and stratified patients based on the presence or absence of lymph node metastasis. Our findings revealed that lymph node metastatic tumors displayed a significantly higher somatic mutational burden [ 22 ] and a distinct mutational signature profile, characterized by the enrichment of COSMIC Signature SBS89 [ 23 ]. While PTMC is generally considered a genetically indolent tumor, these results suggest that a subset of metastatic cases may follow a divergent evolutionary trajectory. The presence of higher mutation load and the emergence of a non-canonical mutational signature imply that metastatic PTMC may represent a more genomically unstable and biologically aggressive form of the disease [ 24 ]. This contrasts with the traditionally low-risk profile attributed to most PTMCs [ 25 ] and underscores the importance of identifying patients who may not be suitable candidates for active surveillance. From a molecular standpoint, these data support the view that lymph node metastasis is not merely a spatial extension of disease, but rather a reflection of underlying genomic alterations that may promote invasiveness and poor clinical outcomes [ 26 ]. Recognizing these molecular distinctions may be critical for guiding treatment decisions in early-stage thyroid cancer. Building upon these observations, we further explored whether specific clinical subgroups exhibited distinct molecular characteristics. Subgroup analysis revealed that male patients with lymph node metastases formed a unique cluster, both clinically and genetically. This group exhibited the highest somatic mutation burden in the cohort and harbored recurrent alterations in genes not commonly mutated in indolent PTMC cases, including FAM98A , CYP26B1 , and EPS8L3 . Most notably, this subgroup showed frequent mutations in multiple components of the hippo signaling pathway, including YAP1 , TEAD1 , and WNT16 , which were largely absent in other patient groups [ 27 ]. The hippo pathway is a well-known regulator of tissue growth, cell proliferation, and apoptosis, and its dysregulation has been implicated in metastatic potential across several cancer types [ 28 ]. The convergence of male sex, lymph node metastasis, and hippo pathway mutations suggests a sex-specific, genomically distinct form of PTMC with heightened metastatic behavior. These findings not only support the biological relevance of this subgroup but also raise the possibility of pathway-specific therapeutic vulnerabilities. Taken together, these findings provide molecular evidence supporting the notion that PTMC with lymph node metastasis particularly in male patients represents a clinically and biologically distinct subtype [ 29 ]. The enrichment of somatic mutations and dysregulation of the hippo signaling pathway in this group underscores its potential for aggressive behavior and suggests that a one-size-fits-all approach to PTMC management may be insufficient [ 30 ]. From a clinical perspective, integrating molecular profiling into preoperative assessment may improve risk stratification and help identify patients who are less suitable for active surveillance and more likely to benefit from early surgical intervention [ 31 ] [ 32 ]. In particular, the identification of hippo pathway alterations raises the possibility of using pathway-specific markers to guide future therapeutic decisions [ 33 ]. This study has several limitations, including the relatively small sample size and lack of functional validation of the identified mutations. Additionally, the underrepresentation of male patients in the primary tumor group may introduce selection bias in subgroup analyses. Nevertheless, our data highlight a previously underappreciated link between sex, lymph node metastasis, and specific genomic alterations in PTMC. Further studies with larger, independent cohorts and functional assays are warranted to validate our findings. Ultimately, a better understanding of the genomic landscape of aggressive PTMC may inform more personalized and effective treatment strategies, bridging the gap between molecular oncology and clinical decision-making. Conclusion This study demonstrates that lymph node metastasis in PTMC is associated with distinct genomic features, including a higher somatic mutational burden and enrichment of COSMIC Signature SBS89. Notably, male patients with lymph node metastases exhibited unique mutation profiles, characterized by recurrent alterations in components of the hippo signaling pathway. These findings suggest that a subset of PTMC, particularly in male patients, may follow a more aggressive molecular trajectory and warrant different management strategies. Incorporating molecular profiling into clinical decision-making may enhance the identification of high-risk patients and guide more personalized treatment approaches, helping to refine the balance between active surveillance and surgical intervention in PTMC. Declarations Ethics approval and consent to participate This retrospective study was approved by the Institutional Review Board of Pusan National University Yangsan Hospital (IRB No. 55-2023-041). Bio-specimens and anonymized clinical data were obtained from the Institutional Biobank Project (Approval No. OF-2023-14) in accordance with the approved protocol and the Declaration of Helsinki. The requirement for written informed consent was waived by the IRB due to the retrospective nature of the study and the use of anonymized data. Consent for publication Not applicable. Availability of data and materials The raw whole exome sequencing (WES) data generated in this study have been deposited in the Korea BioData Station (K-BDS, https://kbds.re.kr) under the accession ID KAP241556. De-identified clinical and sample metadata are available to qualified researchers upon request via the K-BDS platform, following the repository’s data access policies and ethical oversight procedures. Competing interests The authors declare no competing interests. Funding This study was supported by the Research Institute for the Convergence of Biomedical Science and Technology (55-2023-041), Pusan National University Yangsan Hospital. Author contributions LS and JS performed all the data analysis and wrote the manuscript. KJ contributed to data analysis. LJ, LSM, OSH, RM, LM, KSK and KHY contributed to sample collection and processing and data collection. LJ and JS designed experiments, interpreted results, guided the data analysis and drafted the manuscript. The project was directed and co-supervised by LS, JS and KJ were responsible for final editing. All authors read and approved final manuscript References Haugen BR: 2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: What is new and what has changed? Cancer 2017, 123 (3):372-381. 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Cunningham R, Hansen CG: The Hippo pathway in cancer: YAP/TAZ and TEAD as therapeutic targets in cancer . Clin Sci (Lond) 2022, 136 (3):197-222. Additional Declarations No competing interests reported. Supplementary Files Supplementaldata1.xlsx Supplemental data 1. SNP gene list Supplementaldata2.docx Supplemental data 2. Specific gene list Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 11 Sep, 2025 Reviews received at journal 04 Sep, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviewers agreed at journal 31 Aug, 2025 Reviews received at journal 31 Aug, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviewers invited by journal 25 Aug, 2025 Editor assigned by journal 20 Aug, 2025 Editor invited by journal 30 Jul, 2025 Submission checks completed at journal 29 Jul, 2025 First submitted to journal 29 Jul, 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7153805","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":508743681,"identity":"50cbf338-b972-480f-ae1f-789b6ae2c0e5","order_by":0,"name":"Seongdo Jeong","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital","correspondingAuthor":false,"prefix":"","firstName":"Seongdo","middleName":"","lastName":"Jeong","suffix":""},{"id":508743682,"identity":"e6e41118-9277-41f2-baf1-c24ab438e7ba","order_by":1,"name":"Junho Kang","email":"","orcid":"","institution":"Keimyung University Dongsan Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Junho","middleName":"","lastName":"Kang","suffix":""},{"id":508743683,"identity":"1116eb91-dfc9-4c98-920c-41f1fa680256","order_by":2,"name":"Jieon Lee","email":"","orcid":"","institution":"Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jieon","middleName":"","lastName":"Lee","suffix":""},{"id":508743684,"identity":"6cca0972-9873-45d3-9dcf-0722073a7ac1","order_by":3,"name":"Sun Min Lee","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sun","middleName":"Min","lastName":"Lee","suffix":""},{"id":508743685,"identity":"925b6331-76ac-49de-8877-5e171f7a9d43","order_by":4,"name":"Seung Hwan Oh","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Seung","middleName":"Hwan","lastName":"Oh","suffix":""},{"id":508743686,"identity":"4fb60d9a-0a9b-4a15-bd68-3a05c79091ea","order_by":5,"name":"Miri Ryu","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Miri","middleName":"","lastName":"Ryu","suffix":""},{"id":508743687,"identity":"c4ba93dc-f5e2-433e-8fc1-cd2db3829271","order_by":6,"name":"Meehyun Lee","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Meehyun","middleName":"","lastName":"Lee","suffix":""},{"id":508743688,"identity":"1221db48-09e3-419e-9a77-9f168c536d0a","order_by":7,"name":"Seok-Kyung Kang","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Seok-Kyung","middleName":"","lastName":"Kang","suffix":""},{"id":508743689,"identity":"a59bbe53-8e67-498a-90d3-a209b02cbf60","order_by":8,"name":"Hyun Yul Kim","email":"","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hyun","middleName":"Yul","lastName":"Kim","suffix":""},{"id":508743690,"identity":"cb7f8166-eba0-4665-95c8-9852594e5999","order_by":9,"name":"Seungju Lee","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYHACgwMMDBYMDMwMjA9I0SIB0sJsQLQWBrAWBgY2CaLU67Y3bzzwo0ZC3ryd+Vh1Qc1hOfMG5oePbuDRYnbmWMHBnmMShnMOs6XdnnHssLHMATZj4xx8Wm7kGBwGOolxBjOP2W0etrTEGQw8bNJ4tdx/A9TyT8J+BjP/t2Kef2n1hLXc4DE4zNgmkQi0hY2Zt80mQYKgljNpBQd7+ySSZzCzGUvz9tkYghj4/XL88OYPP77Z2M7gP/zwM883CXkJ9uaHj/FpwQKYSVM+CkbBKBgFowALAACFXkSAuVpeAgAAAABJRU5ErkJggg==","orcid":"","institution":"Pusan National University Yangsan Hospital, Pusan National University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Seungju","middleName":"","lastName":"Lee","suffix":""}],"badges":[],"createdAt":"2025-07-18 04:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7153805/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7153805/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90464580,"identity":"37d454a4-5b35-4c68-a209-7267bdb43af1","added_by":"auto","created_at":"2025-09-03 05:09:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2593132,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMutational landscape of PTMC samples.\u003c/strong\u003e \u003cbr\u003e\n (A) Stacked bar plot showing the proportion of six types of base substitutions in each sample. The x-axis represents individual samples, and the y-axis indicates the percentage of each substitution type out of the total variants per sample. Color legend for substitution types is shown on the right. (B) Distribution of mutation classifications across samples. The x-axis denotes individual samples, and the y-axis indicates the number of variants per classification.\u003cbr\u003e\n (C) Oncoplot illustrating somatic mutations in the top 20 most frequently mutated genes across all samples. Each row represents a gene, and each column represents a sample. Mutation types are color-coded. Clinical annotations are shown at the bottom, indicating group (e.g., presence of lymph node metastases), sex, and age. Color legends for variant types and clinical categories are shown on the right.\u003c/p\u003e","description":"","filename":"Fig1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/6e54700d6439ef025151d4a9.jpg"},{"id":90464581,"identity":"97a1dcbf-a4ea-4df7-ab8d-683bc34179fa","added_by":"auto","created_at":"2025-09-03 05:09:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2062855,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of mutational profiles between primary and lymph node metastatic PTMC.\u003c/strong\u003e \u003cbr\u003e\n(A) Box plot showing the total number of somatic mutations in primary (blue) and lymph node metastases (red). Independent 2-sample t-test p-values ​​are shown. (B) Mutational signature analysis demonstrating distinct patterns between the two groups. The primary group were enriched in COSMIC signature SBS37, while lymph node group exhibited SBS89, highlighting differences in mutational processes. (C) Oncoplot of group-specific gene mutations. Genes are separated into primary-specific (top), lymph-specific (middle), and shared (bottom) categories. Mutation types are color-coded. Clinical annotations including group, gender, and age are shown at the bottom.\u003c/p\u003e","description":"","filename":"Fig2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/d581585ba03f20a9a90321e6.jpg"},{"id":90464582,"identity":"fefc831a-47ca-47ba-a6bb-f4211270267f","added_by":"auto","created_at":"2025-09-03 05:09:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1346619,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSex-based subgroup analysis in PTMC with lymph node metastasis.\u003c/strong\u003e \u003cbr\u003e\n(A) Forest plot of odds ratios (log10-transformed) with 95% confidence intervals for each covariate from logistic regression. Variables include sex, lymph node status, age, and their interaction. (B) Mosaic plot showing the distribution of sex across primary tumor and lymph node metastasis groups. Male patients were significantly overrepresented in the lymph group. (C) Oncoplot comparing mutation profiles between the “Male + Lymph”group and all other patients. Clinical annotations (age, gender, group) are presented at the bottom.\u003c/p\u003e","description":"","filename":"Fig3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/3b4374d37fee7a935e670ee8.jpg"},{"id":90464586,"identity":"0027d023-d91d-4467-b563-a3c8209f08e9","added_by":"auto","created_at":"2025-09-03 05:09:52","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1617480,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHippo signaling pathway mutation patterns in male PTMC patients with lymph node metastasis.\u003c/strong\u003e \u003cbr\u003e\n(A) Box plot showing the number of somatic mutations in hippo signaling pathway genes. The “male + lymph node metastasis” group demonstrated a significantly higher mutation burden compared to the other group (p \u0026lt; 0.01). (B) KEGG pathway enrichment analysis of differentially mutated genes in the “male + lymph” group. The hippo signaling pathway was the most significantly enriched, followed by pathways related to stem cell pluripotency and EGFR tyrosine kinase inhibitor resistance. (C) Oncoplot of somatic mutations in hippo pathway–associated genes across primary tumors and lymph node metastases. Mutations in key regulators such as \u003cem\u003eYAP1\u003c/em\u003e, \u003cem\u003eTEAD1\u003c/em\u003e, \u003cem\u003eSAV1\u003c/em\u003e, \u003cem\u003eFAT1\u003c/em\u003e, and \u003cem\u003eLATS2\u003c/em\u003e were enriched in lymph node samples, particularly among male patients. Mutation types and clinical variables (age and sex) are annotated.\u003c/p\u003e","description":"","filename":"Fig4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/424c231637daec812c27b572.jpg"},{"id":90466794,"identity":"28bf60f4-4e43-48a1-879a-1fd027a12a41","added_by":"auto","created_at":"2025-09-03 05:38:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9870244,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/b69727a1-7122-40b2-9608-6bcaa9e28158.pdf"},{"id":90464578,"identity":"d02142d8-66ff-48b2-9437-ea971c796b41","added_by":"auto","created_at":"2025-09-03 05:09:52","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16114,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental data 1. \u003c/strong\u003eSNP gene list\u003c/p\u003e","description":"","filename":"Supplementaldata1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/4a3feffe9fb59e6aca231ad2.xlsx"},{"id":90464588,"identity":"67293dd0-3da6-43d3-a908-edfcb8e29f97","added_by":"auto","created_at":"2025-09-03 05:09:52","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":19880,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental data 2. \u003c/strong\u003eSpecific gene list\u003c/p\u003e","description":"","filename":"Supplementaldata2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7153805/v1/06c9a4602d4dfddc941da5a2.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Whole-Exome Sequencing Reveals Hippo Pathway Mutations as a Hallmark of Aggressive PTMC in Young Males","fulltext":[{"header":"Background","content":"\u003cp\u003ePapillary thyroid carcinoma (PTC) represents the most prevalent subtype of thyroid malignancy, accounting for approximately 80% of all thyroid cancer cases[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The disease is generally indolent and associated with a favorable clinical outcome, with a 5-year disease-specific survival rate exceeding 90%, particularly in younger patients [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Papillary thyroid microcarcinoma (PTMC), which is smaller than 1 cm, has an excellent long-term prognosis, with a disease-specific mortality rate of less than 0.1% and a recurrence rate of approximately 3% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although 9–42% of patients present with clinically evident lymph node metastases at diagnosis, the majority of cases do not show distant metastasis, and these patients tend to have an especially favorable prognosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Given the indolent nature of PTMC, ongoing societal concerns persist regarding the issues of over-diagnosis and over-treatment in the management of cancer [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, when PTMC is diagnosed, it is important to evaluate for the presence of lymph node or distant metastasis or extrathyroidal extension. In the absence of such clinical findings, active surveillance with delayed surgery only upon evidence of disease progression may be considered an optimal approach [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Based on this concept, active surveillance has been proposed as a feasible alternative to immediate surgery for managing low-risk PTMC. Nevertheless, in cases of PTMC, if there is suspicion of lymph node metastases during follow-up or if the tumor size increases, surgical intervention is recommended. However, it is difficult to identify central neck lymph node metastases with ultrasonography [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Given that PTMC generally has a favorable prognosis, it is crucial to identify cases that necessitate surgical treatment in order to improve patients’ quality of life. Hence, the objective of this study is to ascertain the presence of distinct DNA mutations associated with lymph node metastasis in PTMC by conducting whole exome sequencing (WES) on both the group with lymph node metastasis and the group without.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003ePatients and Samples\u003c/em\u003e\u003c/p\u003e\u003cp\u003eFresh frozen primary tumor tissues (n = 72 samples) were collected from 72 patients who were diagnosed with PTMC at Pusan National University Yangsan Hospital, Korea, throughout the period from 2015 to 2022. The patients had surgery and received thyroid hormone replacement treatment. Among the 72 samples, 30 were primary tumor tissues without lymph node metastasis, and 42 were primary tumor tissues with lymph nodes metastases. We evaluated the histology, tumor size, lymph node status, presence of thyroid capsule invasion, presence of multiple tumor foci, and type of surgery. The Institutional Review Board of Pusan National University Yangsan Hospital (55-2023-041) granted this study. The bio-specimens and clinical data were acquired from the Institutional Biobank Project (OF-2023-14) following the approved study protocol. The research conducted in this study adhered to the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003e\u003cem\u003eWhole exome sequencing\u003c/em\u003e\u003c/p\u003e\u003cp\u003eGenomic DNA (gDNA) library was constructed from 50 ng of input gDNA utilizing the Twist Library Preparation EF Kit 2.0 (96 samples, PN 104207). Full-length combinatorial dual index TruSeq-compatible Y-adapters (Illumina) were employed in accordance with the Twist Bioscience Library Protocol. DNA quantity was quantified using PicoGreen (Invitrogen), while DNA quality was assessed through TapeStation gDNA Screentape (Agilent). 50ng of gDNA, diluted with EB Buffer, were sheared to a target peak size of 200bp with the fragmentation enzyme. DNA fragmentation is followed by end-repair and A-tailing, which involves the enzymatic addition of an ‘A’ tail to the 3’ ends. Twist UDI index adapters are subsequently ligated to the fragments. After evaluating ligation efficiency, the adapter-ligated DNA fragments are amplified via PCR. Quantification of the final purified product was performed using the TapeStation DNA Screentape D1000 (Agilent) and the fluorescence -based PicoGreen assay. For exome capture, each hybridization reaction requires 1500 ng of indexed libraries, prepared by pooling equimolar amounts from eight individual libraries. The mixture was combined with Hybridization mix, Twist exome 2.0 probe, Blocker solution, Universal Blocker, and Hybridization Enhancer according to the Twist library preparation protocol. The captured DNA is thoroughly washed and subsequently amplified. The final purified product is quantified by qPCR, following the qPCR Quantification Protocol Guide (KAPA Library Quantification kits for Illumina Sequencing platforms), and qualified using the TapeStation DNA Screentape D1000 (Agilent). Sequencing was performed using the NovaSeq6000 platform (Illumina, San Diego, USA), achieving an average coverage depth of 100x.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSomatic Variant Calling\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSomatic variants were identified using the Genome Analysis Toolkit (GATK, version 4; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gatk.broadinstitute.org/\u003c/span\u003e\u003cspan address=\"https://gatk.broadinstitute.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) DNA analysis pipeline. The pipeline integrates sequence alignment, preprocessing, and haplotype-based variant calling into a unified workflow. Raw sequencing reads were aligned to the human reference genome (hg38) using BWA-MEM, followed by duplicate marking with Picard and base quality score recalibration using GATK. Somatic variant calling was performed using Mutect2, with a Panel of Normals (PoN) generated from the 1000 Genomes Project and the gnomAD database used as a germline resource. To enhance the accuracy of the detected variants, we applied FilterMutectCalls to remove sequencing artifacts and false positives. Annotated variants were obtained using Funcotator. Variants were filtered based on the following criteria: (1) population allele frequency \u0026lt; 1% in gnomAD, (2) exclusion of recurrent artefactual variants observed across multiple samples or known false-positive sites.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAnalysis of Somatic Variants\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSomatic variant analysis was performed using the maftools package (v2.14.0) in R. Annotated MAF files were imported and visualized to summarize the mutation landscape across all samples. The overall distribution of base substitution types was assessed using the titv() function, and variant classification was visualized with plotVariantClassification(). The most frequently mutated genes were identified, and mutation patterns were illustrated using oncoplot(). To compare mutation burden between clinical subgroups (e.g., primary vs. lymph node metastasis), total mutation counts were extracted and statistically tested using Wilcoxon rank-sum tests. Clinical metadata including sex, age, and group classification were incorporated into the oncoplot for integrated visualization of clinical and genetic features. Mutational signature analysis was conducted by constructing a trinucleotide mutation matrix using the BSgenome.Hsapiens.NCBI.GRCh38 reference genome. The Non-negative Matrix Factorization (NMF) algorithm was applied to extract de novo mutational signatures using the extractSignatures() function, and the optimal number of signatures was selected based on cophenetic correlation coefficient curves. Extracted signatures were then compared to the COSMIC v3.3 reference using cosine similarity to identify biologically relevant matches. Logistic regression analysis was conducted using the glm() function to assess the association between clinical variables (e.g., sex, lymph node metastasis) and mutational features. Mosaic plots were generated to visualize the distribution of categorical variables across groups. Pathway-level mutation analysis was performed by grouping mutated genes into KEGG pathways, and enrichment was assessed using hypergeometric tests. Notably, mutation burden in the hippo signaling pathway was compared between subgroups using boxplots and statistical testing.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAll statistical analyses were performed using R software (version 4.4.1; R Foundation for Statistical Computing, Vienna, Austria). Clinical and pathological characteristics between patients with and without lymph node metastasis were assessed using the independent two-sample t-test or Mann-Whitney U test for continuous variables, depending on data normality. For categorical variables, comparisons were made using the chi-square test or Fisher's exact test. Group-wise comparisons of tumor mutational burden (TMB) and pathway-specific mutation counts were also conducted using the Mann-Whitney U test. Associations between clinical variables and metastasis were evaluated using logistic regression models, and results were visualized as odds ratios with 95% confidence intervals. All visualizations and statistical plots were generated using the `ggpubr` and `ggplot2` packages in R.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003ePatient characteristics\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the clinicopathologic characteristics of patients with and without lymph node metastasis. Patients with lymph node metastasis were significantly younger than those without lymph node metastasis. In terms of gender distribution, the lymph node metastasis group had a higher proportion of male patients (16/42, 38.1%) compared to the non-metastasis group (2/30, 6.7%). In the group with lymph node metastasis, the tumor size was found to be 0.8 cm, which was larger than the 0.7 cm observed in the group without lymph node metastasis. The presence of extension was observed in 73.8% of patients with lymph node metastasis and 76.7% of those without, showing no notable difference. Among the 42 patients with lymph node metastasis, 5 patients had lateral neck lymph node metastasis and underwent lateral neck lymph node dissection.\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\u003eClinicopathologic characteristics of patients\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=\"left\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePatients with LN metastasis (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePatients without LN metastasis (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep\u003c/em\u003e-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (yr)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42.0\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\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\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\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\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTumor size (cm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtension\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\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.783\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\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\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\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultifocality\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\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.770\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSolitary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultifocal\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\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of dissected Central LNs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5(2\u0026thinsp;~\u0026thinsp;22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1(2\u0026thinsp;~\u0026thinsp;20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.881\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of dissected lateral LNs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27.0\u0026thinsp;\u0026plusmn;\u0026thinsp;17.5(10\u0026thinsp;~\u0026thinsp;57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery\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\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.105\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLobectomy with CLND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal thyroidectomy with CLND\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\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal thyroidectomy with CLND with LND\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5\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\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eLN; Lymph node, CLND; Central neck lymph node dissection, LND; Lateral neck lymph node dissection\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eSomatic mutation landscape in PTMC patients\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWhole-exome sequencing (WES) was performed on 72 PTMC samples, including 42 primary tumors and 30 matched lymph node metastases. Analysis of the base substitution spectrum revealed a predominance of C\u0026thinsp;\u0026gt;\u0026thinsp;T and T\u0026thinsp;\u0026gt;\u0026thinsp;G transitions across the cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), a pattern commonly associated with age-related mutational processes in thyroid and other epithelial malignancies. Regarding variant classification, missense mutations were the most frequently observed, followed by frameshift deletions and nonsense mutations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). An oncoplot analysis of the top 20 recurrently mutated genes identified \u003cem\u003eBRAF\u003c/em\u003e as the most frequently altered gene, consistent with its established role as a key driver in PTC. In addition to \u003cem\u003eBRAF\u003c/em\u003e, mutations in genes such as \u003cem\u003eFGFR1\u003c/em\u003e, \u003cem\u003eEIF4EBP1\u003c/em\u003e, and \u003cem\u003eCREBBP\u003c/em\u003e, which have been implicated in oncogenic signaling in various cancer types, were also recurrently detected (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Clinical variables including age, sex, and tumor group were integrated into the oncoplot to visualize potential associations with mutational profiles.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eComparative mutation analysis between primary tumors and lymph node metastases\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo investigate genetic differences associated with metastatic progression, we compared the somatic mutation profiles between primary tumors and matched lymph node metastases. The lymph node metastasis group exhibited a significantly higher number of somatic mutations compared to the primary tumor group (p\u0026thinsp;=\u0026thinsp;0.027; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA), suggesting a possible association between increased mutational burden and metastatic potential in PTMC. Mutational signature analysis revealed distinct patterns between the two groups. The primary tumors displayed a mutational profile resembling COSMIC Signature SBS37, characterized by moderate levels of C\u0026thinsp;\u0026gt;\u0026thinsp;T and T\u0026thinsp;\u0026gt;\u0026thinsp;C substitutions. In contrast, lymph node metastases were dominated by SBS89, which is enriched in T\u0026thinsp;\u0026gt;\u0026thinsp;C and T\u0026thinsp;\u0026gt;\u0026thinsp;G substitutions and has been linked to age-related mutagenesis and potential mismatch repair (MMR) deficiency (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Group-specific oncoplot analysis identified several genes preferentially mutated in each group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Mutations in \u003cem\u003eUVRAG\u003c/em\u003e, \u003cem\u003eUSP19\u003c/em\u003e, \u003cem\u003ePLPP1\u003c/em\u003e, \u003cem\u003eFOXD4L3\u003c/em\u003e, and \u003cem\u003eCTSB\u003c/em\u003e were observed predominantly in primary tumors, suggesting their involvement in early tumorigenic events. In contrast, \u003cem\u003eYBX1\u003c/em\u003e, \u003cem\u003eSPRED3\u003c/em\u003e, \u003cem\u003eSLFN11\u003c/em\u003e, \u003cem\u003eFAT4\u003c/em\u003e, and \u003cem\u003eCOP6\u003c/em\u003e mutations were more frequent in lymph node metastases, implying a role in metastatic progression or tumor adaptation. Clinical annotation further revealed that lymph node\u0026ndash;associated mutations were more frequently observed in male patients and individuals under 60 years of age, consistent with previously reported risk factors for aggressive disease in PTMC. All mutation information appears in Supplemental data 1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eSex-specific mutation enrichment in metastatic PTMC Patients\u003c/em\u003e\u003c/p\u003e\u003cp\u003eGiven the observed increase in mutation burden and male predominance in the lymph node metastasis group, we performed a subgroup analysis to further investigate the interaction between sex and metastasis in PTMC. Logistic regression analysis revealed that the interaction term \"male \u0026times; lymph node metastasis\" was associated with a markedly elevated risk (odds ratio: 7.5), indicating a potential synergistic effect between male sex and metastatic status (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). To explore sex distribution across groups, a mosaic plot was generated. The analysis revealed a significant overrepresentation of male patients in the lymph node metastasis group compared to the primary tumor group (p\u0026thinsp;=\u0026thinsp;5.78 \u0026times; 10⁻\u0026sup3;; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). We next compared the somatic mutation profiles of the \u0026ldquo;male\u0026thinsp;+\u0026thinsp;lymph node metastasis\u0026rdquo; group against all other patients. Oncoplot analysis demonstrated that the \u0026ldquo;male\u0026thinsp;+\u0026thinsp;lymph\u0026rdquo; group exhibited frequent missense mutations in genes such as \u003cem\u003eFAM98A\u003c/em\u003e, \u003cem\u003eCYP26B1\u003c/em\u003e, \u003cem\u003eC2orf78\u003c/em\u003e, \u003cem\u003ePILRA\u003c/em\u003e, and \u003cem\u003eEPS8L3\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Notably, several genes involved in the hippo signaling pathway including \u003cem\u003eWNT16\u003c/em\u003e, \u003cem\u003eTEAD1\u003c/em\u003e, and \u003cem\u003eYAP1\u003c/em\u003e were mutated exclusively in this group, suggesting potential biological relevance related to metastatic progression in male patients.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEnrichment of hippo pathway mutations in the male\u0026thinsp;+\u0026thinsp;metastatic subgroup\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTo investigate whether this clinically distinct subgroup harbored unique molecular alterations, we performed a pathway-level analysis of somatic mutations. This analysis revealed that the \u0026ldquo;male\u0026thinsp;+\u0026thinsp;lymph node metastasis\u0026rdquo; group exhibited a significantly higher number of mutations in genes associated with the hippo signaling pathway (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). KEGG pathway enrichment analysis confirmed that the hippo signaling pathway was the most significantly enriched pathway in this group, followed by stem cell\u0026ndash;related and EGFR-related signaling pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Oncoplot analysis of hippo pathway genes revealed several members including \u003cem\u003eYAP1\u003c/em\u003e, \u003cem\u003eTEAD1\u003c/em\u003e, \u003cem\u003eSAV1\u003c/em\u003e, \u003cem\u003eFAT1\u003c/em\u003e, and \u003cem\u003eLATS2\u003c/em\u003e that were preferentially mutated in lymph node metastases, particularly in male patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) (Supplemental data 2). These findings suggest that hippo pathway dysregulation may play a critical role in the metastatic behavior of PTMC in a sex-specific context.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eActive surveillance is increasingly recognized as a safe and effective management strategy for selected patients with PTMC [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. However, its implementation in routine clinical practice remains limited. Patient-related concerns including anxiety over possible disease progression, psychological discomfort with deferring treatment, and the financial burden of regular follow-up have been identified as major barriers to its broader adoption [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. To enhance the clinical applicability of active surveillance, it is crucial to identify reliable clinical and molecular predictors of aggressive disease behavior. Current guidelines recommend active surveillance for PTMC patients who lack clinical evidence of lymph node or distant metastasis and show no gross extrathyroidal extension involving critical structures such as the trachea or recurrent laryngeal nerve. However, lymph node metastases are reported in approximately 9\u0026ndash;42% of PTMC cases [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], often necessitating surgical intervention regardless of tumor size. Importantly, preoperative detection of central compartment (level VI) lymph node metastasis remains challenging due to the limited sensitivity and operator dependence of neck ultrasound [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo address this clinical challenge, we performed whole-exome sequencing on surgically resected PTMC samples and stratified patients based on the presence or absence of lymph node metastasis. Our findings revealed that lymph node metastatic tumors displayed a significantly higher somatic mutational burden [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] and a distinct mutational signature profile, characterized by the enrichment of COSMIC Signature SBS89 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. While PTMC is generally considered a genetically indolent tumor, these results suggest that a subset of metastatic cases may follow a divergent evolutionary trajectory. The presence of higher mutation load and the emergence of a non-canonical mutational signature imply that metastatic PTMC may represent a more genomically unstable and biologically aggressive form of the disease [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This contrasts with the traditionally low-risk profile attributed to most PTMCs [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and underscores the importance of identifying patients who may not be suitable candidates for active surveillance. From a molecular standpoint, these data support the view that lymph node metastasis is not merely a spatial extension of disease, but rather a reflection of underlying genomic alterations that may promote invasiveness and poor clinical outcomes [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Recognizing these molecular distinctions may be critical for guiding treatment decisions in early-stage thyroid cancer.\u003c/p\u003e\u003cp\u003eBuilding upon these observations, we further explored whether specific clinical subgroups exhibited distinct molecular characteristics. Subgroup analysis revealed that male patients with lymph node metastases formed a unique cluster, both clinically and genetically. This group exhibited the highest somatic mutation burden in the cohort and harbored recurrent alterations in genes not commonly mutated in indolent PTMC cases, including \u003cem\u003eFAM98A\u003c/em\u003e, \u003cem\u003eCYP26B1\u003c/em\u003e, and \u003cem\u003eEPS8L3\u003c/em\u003e. Most notably, this subgroup showed frequent mutations in multiple components of the hippo signaling pathway, including \u003cem\u003eYAP1\u003c/em\u003e, \u003cem\u003eTEAD1\u003c/em\u003e, and \u003cem\u003eWNT16\u003c/em\u003e, which were largely absent in other patient groups [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The hippo pathway is a well-known regulator of tissue growth, cell proliferation, and apoptosis, and its dysregulation has been implicated in metastatic potential across several cancer types [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The convergence of male sex, lymph node metastasis, and hippo pathway mutations suggests a sex-specific, genomically distinct form of PTMC with heightened metastatic behavior. These findings not only support the biological relevance of this subgroup but also raise the possibility of pathway-specific therapeutic vulnerabilities.\u003c/p\u003e\u003cp\u003eTaken together, these findings provide molecular evidence supporting the notion that PTMC with lymph node metastasis particularly in male patients represents a clinically and biologically distinct subtype [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The enrichment of somatic mutations and dysregulation of the hippo signaling pathway in this group underscores its potential for aggressive behavior and suggests that a one-size-fits-all approach to PTMC management may be insufficient [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. From a clinical perspective, integrating molecular profiling into preoperative assessment may improve risk stratification and help identify patients who are less suitable for active surveillance and more likely to benefit from early surgical intervention [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In particular, the identification of hippo pathway alterations raises the possibility of using pathway-specific markers to guide future therapeutic decisions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study has several limitations, including the relatively small sample size and lack of functional validation of the identified mutations. Additionally, the underrepresentation of male patients in the primary tumor group may introduce selection bias in subgroup analyses. Nevertheless, our data highlight a previously underappreciated link between sex, lymph node metastasis, and specific genomic alterations in PTMC. Further studies with larger, independent cohorts and functional assays are warranted to validate our findings. Ultimately, a better understanding of the genomic landscape of aggressive PTMC may inform more personalized and effective treatment strategies, bridging the gap between molecular oncology and clinical decision-making.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that lymph node metastasis in PTMC is associated with distinct genomic features, including a higher somatic mutational burden and enrichment of COSMIC Signature SBS89. Notably, male patients with lymph node metastases exhibited unique mutation profiles, characterized by recurrent alterations in components of the hippo signaling pathway. These findings suggest that a subset of PTMC, particularly in male patients, may follow a more aggressive molecular trajectory and warrant different management strategies. Incorporating molecular profiling into clinical decision-making may enhance the identification of high-risk patients and guide more personalized treatment approaches, helping to refine the balance between active surveillance and surgical intervention in PTMC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective study was approved by the Institutional Review Board of Pusan National University Yangsan Hospital (IRB No. 55-2023-041). Bio-specimens and anonymized clinical data were obtained from the Institutional Biobank Project (Approval No. OF-2023-14) in accordance with the approved protocol and the Declaration of Helsinki. The requirement for written informed consent was waived by the IRB due to the retrospective nature of the study and the use of anonymized data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw whole exome sequencing (WES) data generated in this study have been deposited in the Korea BioData Station (K-BDS, https://kbds.re.kr) under the accession ID KAP241556. De-identified clinical and sample metadata are available to qualified researchers upon request via the K-BDS platform, following the repository\u0026rsquo;s data access policies and ethical oversight procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Research Institute for the Convergence of Biomedical Science and Technology (55-2023-041), Pusan National University Yangsan Hospital.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLS and JS performed all the data analysis and wrote the manuscript. KJ contributed to data analysis. LJ, LSM, OSH, RM, LM, KSK and KHY contributed to sample collection and processing and data collection. LJ and JS designed experiments, interpreted results, guided the data analysis and drafted the manuscript. The project was directed and co-supervised by LS, JS and KJ were responsible for final editing. All authors read and approved final manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHaugen BR: \u003cstrong\u003e2015 American Thyroid Association Management Guidelines for Adult Patients with Thyroid Nodules and Differentiated Thyroid Cancer: What is new and what has changed?\u003c/strong\u003e \u003cem\u003eCancer \u003c/em\u003e2017, \u003cstrong\u003e123\u003c/strong\u003e(3):372-381.\u003c/li\u003e\n\u003cli\u003eMegwalu UC, Moon PK: \u003cstrong\u003eThyroid Cancer Incidence and Mortality Trends in the United States: 2000-2018\u003c/strong\u003e. \u003cem\u003eThyroid \u003c/em\u003e2022, \u003cstrong\u003e32\u003c/strong\u003e(5):560-570.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eIntegrated genomic characterization of papillary thyroid carcinoma\u003c/strong\u003e. \u003cem\u003eCell \u003c/em\u003e2014, \u003cstrong\u003e159\u003c/strong\u003e(3):676-690.\u003c/li\u003e\n\u003cli\u003eLin JD, Hsieh SH, Chang HY, Huang CC, Chao TC: \u003cstrong\u003eOutcome after treatment for papillary thyroid cancer\u003c/strong\u003e. \u003cem\u003eHead Neck \u003c/em\u003e2001, \u003cstrong\u003e23\u003c/strong\u003e(2):140-146.\u003c/li\u003e\n\u003cli\u003eMehanna H, Al-maqbili T, Carter B, Martin E, Campain N, Watkinson J, McCabe C, Boelaert K, Franklyn JA: \u003cstrong\u003eDifferences in the Recurrence and Mortality Outcomes Rates of Incidental and Nonincidental Papillary Thyroid Microcarcinoma: A Systematic Review and Meta-Analysis of 21 329 Person-Years of Follow-up\u003c/strong\u003e. \u003cem\u003eThe Journal of Clinical Endocrinology \u0026amp; Metabolism \u003c/em\u003e2014, \u003cstrong\u003e99\u003c/strong\u003e(8):2834-2843.\u003c/li\u003e\n\u003cli\u003eWada N, Duh QY, Sugino K, Iwasaki H, Kameyama K, Mimura T, Ito K, Takami H, Takanashi Y: \u003cstrong\u003eLymph node metastasis from 259 papillary thyroid microcarcinomas: frequency, pattern of occurrence and recurrence, and optimal strategy for neck dissection\u003c/strong\u003e. \u003cem\u003eAnn Surg \u003c/em\u003e2003, \u003cstrong\u003e237\u003c/strong\u003e(3):399-407.\u003c/li\u003e\n\u003cli\u003eMercante G, Frasoldati A, Pedroni C, Formisano D, Renna L, Piana S, Gardini G, Valcavi R, Barbieri V: \u003cstrong\u003ePrognostic factors affecting neck lymph node recurrence and distant metastasis in papillary microcarcinoma of the thyroid: results of a study in 445 patients\u003c/strong\u003e. \u003cem\u003eThyroid \u003c/em\u003e2009, \u003cstrong\u003e19\u003c/strong\u003e(7):707-716.\u003c/li\u003e\n\u003cli\u003eBesic N, Zgajnar J, Hocevar M, Petric R: \u003cstrong\u003eExtent of thyroidectomy and lymphadenectomy in 254 patients with papillary thyroid microcarcinoma: a single-institution experience\u003c/strong\u003e. \u003cem\u003eAnn Surg Oncol \u003c/em\u003e2009, \u003cstrong\u003e16\u003c/strong\u003e(4):920-928.\u003c/li\u003e\n\u003cli\u003eZhou YL, Gao EL, Zhang W, Yang H, Guo GL, Zhang XH, Wang OC: \u003cstrong\u003eFactors predictive of papillary thyroid micro-carcinoma with bilateral involvement and central lymph node metastasis: a retrospective study\u003c/strong\u003e. \u003cem\u003eWorld J Surg Oncol \u003c/em\u003e2012, \u003cstrong\u003e10\u003c/strong\u003e:67.\u003c/li\u003e\n\u003cli\u003eAhn HS, Kim HJ, Welch HG: \u003cstrong\u003eKorea\u0026apos;s thyroid-cancer \u0026quot;epidemic\u0026quot;--screening and overdiagnosis\u003c/strong\u003e. \u003cem\u003eN Engl J Med \u003c/em\u003e2014, \u003cstrong\u003e371\u003c/strong\u003e(19):1765-1767.\u003c/li\u003e\n\u003cli\u003eVaccarella S, Franceschi S, Bray F, Wild CP, Plummer M, Dal Maso L: \u003cstrong\u003eWorldwide Thyroid-Cancer Epidemic? 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\u003cstrong\u003e136\u003c/strong\u003e(3):197-222.\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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Papillary thyroid microcarcinoma, Whole exome sequencing, Hippo pathway, lymph node metastasis","lastPublishedDoi":"10.21203/rs.3.rs-7153805/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7153805/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003ePapillary thyroid microcarcinoma (PTMC) is typically associated with an excellent prognosis, and active surveillance is often appropriate for tumors smaller than 0.5 cm. However, surgical intervention is warranted when there is evidence of tumor progression or suspicion of lymph node metastasis. This study aims to characterize the genetic alterations associated with lymph node metastasis in PTMC to inform risk-adapted surgical management.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eDNA was extracted from primary tumor tissues of 42 PTMC patients with central lymph node metastasis and 30 patients without metastasis. Whole-exome sequencing (WES) was performed for both groups, and somatic variants were analyzed using the maftools package in R. Mutational signatures were compared against reference profiles from the COSMIC database. Statistical analyses were conducted to evaluate the prognostic significance of the identified variants.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePatients with lymph node metastasis were significantly younger and more frequently male compared to those without metastasis. Whole-exome sequencing revealed a higher somatic mutational burden in the metastatic group, along with distinct mutational signatures, including an enrichment of COSMIC Signature SBS89. Recurrently mutated genes such as \u003cem\u003eBRAF\u003c/em\u003e, \u003cem\u003eFGFR1\u003c/em\u003e, and \u003cem\u003eCREBBP\u003c/em\u003e were identified across the cohort, while comparative analysis between primary tumors and lymph node metastases demonstrated divergent mutation profiles. Notably, male patients with lymph node metastasis exhibited frequent missense mutations in \u003cem\u003eFAM98A\u003c/em\u003e, \u003cem\u003eCYP26B1\u003c/em\u003e, and \u003cem\u003eEPS8L3\u003c/em\u003e, as well as exclusive alterations in key components of the hippo signaling pathway, including \u003cem\u003eYAP1\u003c/em\u003e, \u003cem\u003eTEAD1\u003c/em\u003e, and \u003cem\u003eWNT16\u003c/em\u003e. Pathway-level analysis confirmed significant enrichment of hippo pathway mutations in this subgroup, suggesting a potential sex-specific molecular mechanism underlying metastatic progression in PTMC.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study highlights that PTMC with lymph node metastasis, particularly in male patients, exhibits distinct genomic characteristics, including enrichment of COSMIC Signature SBS89 and recurrent mutations in components of the hippo signaling pathway. These findings underscore the potential value of molecular profiling in identifying high-risk subgroups and optimizing individualized management strategies in PTMC.\u003c/p\u003e","manuscriptTitle":"Whole-Exome Sequencing Reveals Hippo Pathway Mutations as a Hallmark of Aggressive PTMC in Young Males","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 05:09:47","doi":"10.21203/rs.3.rs-7153805/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-09-11T05:23:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-04T10:46:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338084493906634410182777989886834134352","date":"2025-09-03T14:43:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"240229211901366330938918682820433868613","date":"2025-09-01T02:34:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-01T02:22:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"81085323707212309188598236425952060767","date":"2025-08-27T14:26:06+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-25T07:20:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-20T09:42:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-30T14:54:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-30T02:15:17+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-07-30T02:12:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b0a3d74-e68c-48b7-a9a1-720d2dab11d4","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-09-03T05:09:47+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 05:09:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7153805","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7153805","identity":"rs-7153805","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}