High prevalence of potential molecular therapeutic targets in poorly differentiated thyroid carcinoma

High prevalence of potential molecular therapeutic targets in poorly differentiated thyroid carcinoma | 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 High prevalence of potential molecular therapeutic targets in poorly differentiated thyroid carcinoma Vanessa Zambelli, Giulia Orlando, Marta Fornaro, Giulia Vocino Trucco, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7112785/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 22 Oct, 2025 Read the published version in Endocrine Pathology → Version 1 posted 11 You are reading this latest preprint version Abstract Poorly differentiated thyroid carcinoma (PDTC) is a rare thyroid cancer with aggressive clinical course and peculiar clinical/pathological characteristics but lacking effective therapeutic options, when surgery is not curative. We aimed at the molecular characterization of PDTC with a specific focus on the identification of potential therapeutic targets. A series of PDTC cases was selected from a multi-institutional network. Fifty-nine samples underwent wide targeted DNA and RNA next generation sequencing (NGS) testing and immunohistochemical analysis for mismatch repair (MMR) proteins. Gene fusion analysis was enriched by 25 additional samples. Prevalence of MMR protein loss was 11.9%. The most prevalent mutations were in NRAS (25%) and TP53 (25%), mutually exclusive each other. TERT promoter ( TERTp ) mutations were detected in 21.6% of cases. NRAS -mutated cases were enriched for mutations in genes belonging to the same pathway. TP53 -mutated samples lacked TERTp co-mutations, but were associated with mutations in PTEN and in genes related to MMR system and/or loss of MMR proteins. TERTp mutations were enriched (up to 32%) in a third group that lacked NRAS or TP53 mutations. Four cases harbored gene fusions, including two cases harboring the TBL1XR1-PIK3CA fusion that has never been reported in thyroid cancer, so far. In conclusion, PDTC may be genomically segregated in subgroups with specific molecular characteristics. Overall, targetable gene fusions have a prevalence of 7%. Moreover, 38% of cases are potential candidates for individualized target therapies since they harbor mutations/fusions in genes coding for potentially targetable tyrosine kinases and/or have defects in the MMR system. Poorly differentiated thyroid carcinoma molecular biomarkers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Poorly-differentiated thyroid carcinoma (PDTC) represents 2–15% of all thyroid carcinomas ( 1 ) and shows an intermediate prognosis between well-differentiated papillary and follicular carcinomas and anaplastic carcinoma, with a five-year disease-specific survival of 66% ( 2 ). PDTC represents a heterogeneous group of aggressive thyroid neoplasms that has been a matter of discussion since its original description in the early eighties. PDTC was introduced as a distinct thyroid cancer subtype in the 2004 WHO Classification of Tumors, and in 2007 a diagnostic algorithmic approach was proposed in the so-called Turin consensus proposal, that embedded architectural features (solid, insular and/or trabecular growth pattern) together with the presence of high-grade parameters (increased mitotic activity and/or presence of necrosis) ( 3 ). An alternative diagnostic approach, proposed by the Memorial Sloan Kettering Cancer Center (MSKCC), considered PDTC as a group of aggressive thyroid carcinomas defined by the presence of high-grade features, only, in the presence of follicular cell differentiation but irrespective of the tumor architecture ( 4 ). Subsequent studies confirmed that both approaches are able to recognize follicular cell-derived thyroid cancers bearing an intermediate prognosis ( 5 ). All such evidence led to the current WHO classification, that identifies a group of high-grade follicular cell-derived non-anaplastic thyroid carcinomas, further segregated into two distinct histological types, namely PDTC as for the Turin Consensus criteria and high-grade differentiated thyroid carcinomas as for the MSKCC criteria ( 6 ). PDTC may arise de novo or may progress from well-differentiated carcinoma of follicular cell derivation. At the molecular level, consistent with a general model of multi-step progression from well- to poorly- to anaplastic carcinoma, somatic genetic alterations include “Early” and “Late” events ( 7 ). “Early” driver changes are mostly RAS and BRAF p.V600E mutations. Moreover, similarly to what is described for anaplastic thyroid cancer, the most frequent “Late” changes are TP53 and TERT promoter ( TERTp ) mutations or alterations of the PI3K/PTEN/AKT pathway. Gene fusions are expected to be rare, but PDTC histology is enriched in cases harboring such alterations ( 8 ). The heterogeneity of classification criteria has been a major bias in terms of the definition of the main molecular characteristics of PDTC. A seminal study depicted in detail the molecular landscape of PDTC, but at the same time highlighted how the two different classification approaches were interfering with the molecular mapping. In fact, between the two main molecular subgroups identified, the BRAF -like group was dominated by MSKCC-classified cases and the RAS -like group was dominated by Turin Consensus-classified cases ( 9 ). Indeed, subsequent reports were supportive of the molecular diversity of genomic alterations between PDTC and high-grade differentiated thyroid carcinoma as proposed in the new WHO classification ( 10 ). Therefore, most of the available literature on the genomic landscape of PDTC is influenced by non-homogeneous inclusion criteria, by the relatively small sample size of analyzed series and by a pathogenetic rather than clinically-driven approach. All these factors influence the relative prevalence of molecular alterations detected and their integration with pathological and clinical data. In terms of therapeutic strategies, unlike papillary and follicular thyroid carcinomas, PDTC therapy is not standardized due to the rarity of the disease and the heterogeneity of inclusion criteria in the few clinical studies available. Radioiodine responsiveness of PDTC after surgery is variable, possibly as the result of intra-tumor heterogeneity and coexistence of well and less well-differentiated tumor components ( 11 ). Treatments using novel therapeutics have been proposed in thyroid cancer with no response or progression after radioiodine treatment ( 12 ). However, no robust data are available in PDTC, with special reference to the prevalence of alterations in potential targets or to the real clinical benefit of therapeutic targeted approaches. Based on the above, there is a strong need to identify novel strategies that might lead to a better personalized approach and individualization of the therapeutic strategies in PDTC. Therefore, the aim of this study was to characterize a series of PDTC, homogeneously coded following the Turin criteria as proposed for this group in the current WHO classification, by means of a multimodal molecular approach with the objective of identifying the prevalence and potential clinical usefulness of molecular targets for therapy. We decided to restrict the analysis to the PDTC subtype because homogeneous criteria for its definition were claimed to provide a robust and reliable group of tumors and - last but not least- because these particular tumors are more common in alpine/mountain areas including our Country, and their molecular characterization is less established in the literature as compared to high-grade differentiated thyroid carcinoma. Materials and methods Patient and tissue samples. Fifty-nine samples of PDTC were selected from the files of the Pathology Units at “San Luigi” and “Città della Salute e della Scienza” Hospitals and tested for the presence of mismatch repair defects and for DNA and RNA alterations through a wide targeted NGS approach. Due to the high number of failures in RNA analysis (see below), 25 additional PDTC samples from Mauriziano (Turin) and Reggio Emilia Hospitals were added to RNA analysis. All samples were formalin fixed and paraffin embedded surgical materials, retrieved from years 1993 to 2022. For all enrolled cases, histological slides were re-assessed by a pathologist (MV) to confirm the diagnosis following diagnostic criteria for PDTC proposed by the Turin Consensus ( 3 ) and embraced by the current WHO classification ( 6 ). Major clinical and pathological data were collected and included sex, age, presence of predominant oncocytic features (> 75% of the tumor), pTN stage according to AJCC system 8th edition, presence of recurrences/metastases, site of metastases, and patient status. The study was approved by the local Ethical Committee (#610, on December 20, 2017), and conducted in accordance with the principles set out in the Declaration of Helsinki. Considering the retrospective nature of this research protocol and that it had no impact on patients’ care, no specific written informed consent was required. Nucleic acid extraction and sample quality control. Genomic DNA and RNA were extracted from the formalin-fixed paraffin-embedded tumor material. Enrichment of tumor cells was obtained by manual microdissection under light microscopy from one to ten sections for each case as previously reported ( 13 ). The selected material was extracted using Maxwell® RSC DNA FFPE kit (Promega Corporation, Madison, WI, USA, CN: AS1450) and Maxwell® RSC RNA FFPE kit (Promega Corporation, Madison, WI, USA, CN: 14402) according to the manufacturer’s instructions. Nucleic acids were quantified on QuantusTM fluorometer (Promega Corporation, Madison, WI, USA) using Quantifluor® DNA System (Promega Corporation, Madison, WI, USA, CN: E4871) and Quantifluor® RNA System (Promega Corporation, Madison, WI, USA, CN: E3310) following manufacturer’s instructions. DNA quality was evaluated with Real Time PCR of EGFR Exon2 amplification through Rotor-Gene Q (Qiagen, Hilden, Germany) Real Time PCR instrument, the following primers were used for EGFR : EGFRex2b Fw (5’-GAAGATCATTTTCTCAGCCTCCA-3’) and EGFRex2b Rw (5’-AGGAAAATCAAAGTCACCAACCT-3’) (Diatech Pharmacogenetics, Jesi, Ancona, Italy). RNA quality was evaluated with Real Time PCR with beta-actin amplification through Rotor-Gene Q (Qiagen, Hilden, Germany) Real Time PCR instrument, the following primers were used for B-ACT: BACT Fw (5’-CCTTCCTGGGCATGGAGTCTTG-3’) and BACT Rw (5’-GGAGCAATGATCTTGATCTTC-3’). Analysis of mismatch repair status. The expression of mismatch repair (MMR) proteins was tested using immunohistochemistry in an automated system (Dako Omnis, Dako, Agilent) using the following antibodies (all from Dako): MLH1 (clone ES05, CN:GA079), MSH2 (clone FE11,CN:GA085), MSH6 (clone EP49, CN:GA086) and PMS2 (clone EP51, CN:GA087). Loss of nuclear expression for paired proteins (MLH1 and/or PMS2 or MSH2 and/or MSH6) was considered as altered expression pattern. Cases with an altered pattern were also tested for the presence of microsatellite instability (MSI) using genomic DNA extracted as described above. Since thyroid cancer-specific panels are not commercially available, all cases were analyzed using a kit clinically approved for colon and endometrial cancer (EasyPGX ready MSI KIT CE IVD, Diatech Pharmacogenetics, CN:RT033) that includes the following markers: BAT25, BAT26, NR21, NR22, NR24, NR27, CAT25 and MONO27. Bioinformatic analysis was carried out though the software for data exportation Agilent Aria Software v1.4 and data analysis were performed with EasyPGX Analysis Software v3.0. Results are expressed as microsatellite stable (MSS), low microsatellite instability (MSI-low) and high microsatellite instability (MSI-high). Next-generation sequencing. Library preparation was carried out automatically using the DNA and RNA Oncomine™ Comprehensive Assay v3 (Thermo Fisher Scientific, Waltham, MA, USA, CN: A36111) using a total from 10 to 40 ng input DNA and RNA in an Ion Chef System (Thermo Fisher Scientific, Waltham, MA, USA) following manufacturer’s instructions. The Oncomine™ Comprehensive Assay v3 (Thermo Fisher Scientific, Waltham, MA, USA) comprises DNA panel which was designed to interrogate hotspot mutations (#87), full exon coverage (#48) and copy number variations (#43) and RNA panel which was designed to interrogate fusion drivers (#51) (Table 1 ). This panel can identify current actionable genetic variants and potential future targets for personalized therapy. Table 1 Genes covered by the Oncomine™ Comprehensive Assay v3 (Thermo Fisher Scientific, Waltham, MA, USA) panel. Hotspot genes (87) Copy number variants (43) Fusion drivers (51) Full exon coverage (48) AKT1 ESR1 KIT PDGFRB AKT1 FGFR4 AKT2 KRAS RB1 ARID1A NF1 STK11 AKT2 EZH2 KNSTRN PIK3CA AKT2 FLT3 ALK MDM4 RELA ATM NF2 TP53 AKT3 FGFR1 KRAS PIK3CB AKT3 IGF1R AR MET RET ATR NOTCH1 TSC1 ALK FGFR2 MAGOH PPP2R1A ALK KIT AXL MYB ROS1 ATRX NOTCH2 TSC2 AR FGFR3 MAP2K1 PTPN11 AR KRAS BRAF MYBL1 RSPO2 BAP1 NOTCH3 ARAF FGFR4 MAP2K2 RAC1 AXL MDM2 BRCA1 NF1 RSPO3 BRCA1 PALB2 AXL FLT3 MAP2K4 RAF1 BRAF MDM4 BRCA2 NOTCH1 TERT BRCA2 PIK3R1 BRAF FOXL2 MAPK1 RET CCND1 MET CDKN2A NOTCH4 CDK12 PMS2 BTK GATA2 MAX RHEB CCND2 MYC EGFR NRG1 CDKN1B POLE CBL GNA11 MDM4 RHOA CCND3 MYCL ERBB2 NTRK1 CDKN2A PTCH1 CCND1 GNAQ MED12 ROS1 CCNE1 MYCN ERBB4 NTRK2 CDKN2B PTEN CDK4 GNAS MET SF3B1 CDK2 NTRK1 ERG NTRK3 CHEK1 RAD50 CDK6 H3F3A MTOR SMAD4 CDK4 NTRK2 ESR1 NUTM1 CREBBP RAD51 CHEK2 HIST1H3B MYC SMO CDK6 NTRK3 ETV1 PDGFRA FANCA RAD51C CSF1R HNF1A MYCN SPOP EGFR PDGFRA ETV4 PDGFRB FANCD2 RAD51D CTNNB1 HRAS MYD88 SRC ERBB2 PDGFRB ETV5 PIK3CA FANCI RAD51B DDR2 IDH1 NFE2L2 STAT3 ESR1 PIK3CA FGFR1 PPARG FBXW7 RB1 EGFR IDH2 NRAS TERT FGF19 PIK3CB FGFR2 PRKACA MLH1 RNF43 ERBB2 JAK1 NTRK1 TOP1 FGF3 PPARG FGFR3 PRKACB MRE11 SETD2 ERBB3 JAK2 NTRK2 U2AF1 FGFR1 RICTOR FGR PTEN MSH2 SLX4 ERBB4 JAK3 NTRK3 XPO1 FGFR2 TERT FLT3 RAD51B MSH6 SMARCA4 ERCC2 KDR PDGFRA FGFR3 JAK2 RAF1 NBN SMARCB1 The prepared libraries were clonally amplified onto Ion Sphere Particles (ISP) using emulsion PCR in an Ion Chef System (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Enriched ISPs were loaded onto 540 chips accommodating eight DNA samples and eight RNA samples on a single chip and sequencing on the Ion Torrent S5 Prime StudioTM (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions. DNA Data analysis. Analysis was carried out using Ion Torrent Suite™ Browser version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA) and Ion Reporter™ version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA). The Torrent Suite™ Browser was used to perform initial quality control including chip loading density, median read length and number of mapped reads. The Coverage Analysis plugin was applied to all data and used to assess amplicon coverage for regions of interest. The Ion Reporter suite (Thermo Fisher Scientific, Waltham, MA, USA) was used to filter out known polymorphic variants. The variants were annotated by genetic databases: the Single Nucleotide Polymorphism Database (dbSNP) ( http://www.ncbi.nlm.nih.gov/projects/SNP/ ), Catalogue of Somatic Mutations in Cancer (COSMIC) ( http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/ ) and ClinVar database ( http://www.ncbi.nlm.nih.gov/clinvar/ ). Variants with altered allele depth ≤ 100 base coverage and a variant allelic frequency ≤ 5% were eliminated from the analysis. Identified variants were checked for correct nomenclature using Alamut Visual Plus (Interactive Biosoftware, Sophia Genetics). Any discrepancies in variant identification, between Ion Reporter and Alamut, were validated manually using the Integrative Genomics Viewer ( 14 ). Variants were annotated following ACGM guidelines ( 15 ) and the search engine VarSomePremium.com ( 16 ). The prediction of functional effects of the variants that were find as Variants of Uncertain Significance (VUS) was assessed with 13 in silico tools (Align GVGD [ http://agvgd.hci.utah.edu/agvgd_input.php ], Mutation Taster [ https://www.mutationtaster.org ], Provean [ http://provean.jcvi.org ], SIFT [ https://sift.bii.a-star.edu.sg ], Grantham [ https://ionreporter.thermofisher.com ], Polyphen2 [ https://ionreporter.thermofisher.com ], DANN [ https://varsome.com ], FATHMM-MKL [ https://fathmm.biocompute.org.uk ], LRT [ https://sites.google.com/site/jpopgen/dbNSFP ], Meta-RNN [ http://www.liulab.science/metarnn.html ], MutPred [ http://mutpred.mutdb.org ], Mutation Assessor [ http://mutationassessor.org/r3 ] and REVEL [ https://labworm.com/tool/revel ]) ( Supplementary Table 1 ). Each tool had his own threshold, giving for each score a prediction of tolerated or damaging, VUS was qualify as Damaging when the sum of all in silico tools that resulted damaging was higher than 7 ( 17 ). The missense variants called as both benign and tolerated were excluded, as well as variant shaving a frequency higher than 1% in all populations from the 1000 Genomes data. Synonymous mutations were excluded from the analysis. RNA Data analysis was carried out using Ion Torrent Suite™ Browser version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA) and Ion Reporter™ version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA). Sanger sequencing. To validate TERTp mutations that are difficult to detect in NGS analysis as they are intronic, we performed Sanger sequencing analysis on all 59 cases tested for DNA genomic alterations in NGS. TERTp region was sequenced for the detection of the two mutations C228T and C250T. Target region was amplified by conventional PCR with the following primes: TERT Fw (5’AGTGGATTCGCGGGCACAGA-3’) and TERT Rw (5’-CAGCGCTGCCTGAAACTC-3’). A first step with Uracil-DNA Glycosylase (Thermo Fisher Scientific, Waltham, MA, USA) was performed on all samples, following manufacturer’s instructions. Then, the PCR run in 50 µL reactions with 25µL of 2X PlatinumTM SuperfiTM II PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA, CN:12361010), 5µM of each primer and 10µL of gDNA. The amount of gDNA for each PCR varies from 5 to 100 ng, depending on sample’s quality. PCR conditions consist of one cycle of 98°C for 1 min, 3 cycles of (98°C for 30s, 62°C for 30s, 72°C for 45s), followed by 35 cycles of (98°C for 30s, 60°C for 30s, 72°C for 45s), and final extension at 72°C for 5 min. Resulting amplicons were visualized in 2% agarose gels and verified to have the expected size of 193 bp. TERTp sequences were generated by Sanger sequencing and sequencing was performed at Eurofins Genomics (Ebersberg, Germany), all samples were sequenced in both directions. Fluorescence In-Situ Hybridization (FISH). To validate the TBL1XRA-PIK3CA fusion, a FISH approach was applied on four-micron thick formalin-fixed paraffin-embedded section using a TBL1XR1/PIK3CA probe set (Empire Genomics, New York, US, CN: TBL1XR1-PIK3CA-20-GROR) following manufacturer instructions. The two cases positive in RNA NGS analysis and two cases negative, randomly selected from the series, were tested. TBL1XR1/PIK3CA probe set consisted of DNA labeled in Spectrum Green and Spectrum Orange. The DNA probe set hybridizes to chromosome 3q26.32 (Green) and 3q26.32-q26.33 (Orange) in interphase nuclei ( Supplementary Fig. 1 ). The presence of two green and red separated signals were considered as normal pattern, while altered partner was characterized by fused signals (yellow) and/or with multiple red and green signals without fusion signal. The sections were examined with an Olympus BX61 fluorescence microscope (Olympus Corporation, Tokyo, Japan) equipped with a triple-pass filter (DAPI/Green/Orange; Vysis, Downers Grove, IL,USA) with CytoVision® software version 7.6 (Leica Biosystems, Buffalo Grove, IL, United States). Statistical analyses. Pathological features, immunohistochemical and molecular results were correlated to clinical variables, using appropriate statistical tests (chi-square and t Student’s test for qualitative and quantitative parameters correlation, and univariate analyses of both disease-free interval (from the date of diagnosis to first metastasis/recurrence) and disease-specific survival (from the date of diagnosis to death if related to the disease). All statistical analyses were performed using Graph Pad Prism 9.4.1 software. Results Mismatch repair status. All samples were adequate for analysis, with a reliable reactivity of the tested markers in positive control cells within the tissue sections. Seven out of 59 cases (11.9%) had an altered MMR protein pattern (Fig. 1 ). In particular, four cases had MSH2-MSH6 loss, one sample MLH1-PMS2 loss, one sample MSH6 loss and one sample PMS2 loss. MSI molecular analysis on samples that showed an altered pattern of protein expression resulted in microsatellite stability in all cases with the panel of markers employed. Molecular profiling. Fifty-one over 59 PDTC samples (86%) were suitable for DNA NGS analysis. The eight cases with inadequate DNA for NGS analysis had an age of blocks ranging from 2002 to 2016. Mean age in years of blocks in adequate and inadequate samples was 14 and 11, respectively, (p = 0.36). Genomic alterations found in the series are summarized in Fig. 2 . Details in genomic DNA alterations, as well as RNA fusions and CNV detected in the series, are reported in Supplementary Table 2 . Three cases were wild type for all genes included in the NGS panel. The number of overall mutations per case ranged from 1 to 25. The most prevalent mutations were in NRAS (13/51, 25%) and TP53 (13/51, 25%), all mutually exclusive each other. TERTp mutations were detected in 11/51 of overall cases (21.6%; 10/11 C228T [c.-124 C > T] and 1/11 C250T [c.-146 C > T]). All TERTp mutations detected through NGS analysis were confirmed by means of Sanger sequencing. No additional mutations in TERTp were detected by Sanger sequencing analysis in NGS negative cases, with an overall concordance between the two methods of 100%. Mutations in MMR genes were detected in 10 cases (19.6%). Mutational profile in MMR genes was concordant in three samples with protein loss at immunohistochemistry, including two cases with MSH2 mutation (one with and one without associated MSH6 mutations) and one case with MLH1 mutation. One additional case harbored MLH1 mutation but loss of PMS2 protein, only. In the remaining three cases with altered expression of MMR proteins, no mutations in MMR genes were detected. Six additional cases harbored mutations in MMR genes (two MLH1 , two MSH2 , one MSH6 and one PMS2 ) with no loss of MMR proteins expression. Other genes with a prevalence of alterations exceeding 10% were PTEN (15.7%), NF1 (13.7%), ATM (13.7%), NOTCH3 (11.8%) and BAP1 (11.8%). NRAS mutated and TP53 mutated cases showed different molecular characteristics. Mean number of alterations was higher in TP53 -mutated cases (5.8 mutations/case) rather than in NRAS -mutated cases (2.8 mutations/case). PIK3CA and TERTp were the most prevalent co-mutated genes (three cases, each, mutually exclusive) in NRAS -mutated cases. TP53 -mutated samples lacked TERTp co-mutations but were significantly associated with mutations in PTEN (46% of cases, p = 0.024 as compared with the other molecular subgroups) and in genes related to MMR system and/or loss of MMR proteins (53.8% of cases, p = 0.005 as compared with the other molecular subgroups). Overall, most co-mutated alterations in TP53 mutated as compared to NRAS mutated cases were mutually exclusive (Fig. 3 ). A third heterogeneous group (25 cases) lacked NRAS or TP53 mutations, had a low mean number of alterations (2.7 mutations/case) but was enriched for TERTp mutations (32%, not reaching statistical significance as compared to the two other molecular subgroups). One case with HRAS mutation was aggregated within this group because of the co-presence of different other mutations and a low allelic frequency (14%). Copy number variations were not detected. Twenty-eight out of 59 cases were adequate for RNA NGS analysis (47%). Due to this high rate of failure, 25 additional cases were included. Overall, 84 samples were tested, with 43 cases passing quality controls for analysis (52%). Mean age of blocks in adequate and inadequate samples was 11 and 12, respectively (p = 0.38). Chromosomal rearrangements involving genes known to be translocated in thyroid cancer were found in two samples, including one case with RET rearrangement involving the common RET partner CCDC6 and one case with the PAX8-PPARG fusion. Two other cases harbored a TBL1XR1-PIK3CA fusion (Fig. 4 ). In the remaining 39 samples no gene fusions were detected. The presence of the TBL1XR1-PIK3CA fusion was associated with an altered pattern by FISH in both the two positive cases, whereas fusion negative samples showed the expected non-altered pattern (Fig. 5 ). Clinical and pathological correlations. The most prevalent molecular findings in our series were compared with major clinical and pathological characteristics (Table 2 ). Cases showing MMR protein loss and TERTp mutated cases were not associated with significant clinical or pathological characteristics in our series. The three distinct molecular subgroups did not show any significant association with clinical or pathological parameters, except for a higher prevalence of PDTC with predominant oncocytic features in the TP53 -mutated group. Moreover, although not reaching statistical significance, TP53 and TERTp mutated cases had a higher prevalence of adverse events as compared with NRAS -mutated cases. Survival data were available in 47 cases. The two cases with the TBL1XR1-PIK3CA fusion had conventional pathological features with no peculiar findings (Fig. 6 ). Median survival times were calculated in the three major subgroups. Median disease-free survival was 17, 15 and 64 months in NRAS -mutated, TP53 -mutated and TERTp -enriched cases, respectively, with a trend to statistical significance with Log Rank test (p = 0.079). Median disease-specific survival was 145, 111 and 274 months in RAS -mutated, TP53 -mutated and TERTp -enriched cases, respectively, without a statistically significant difference. Table 2 Clinical pathological correlations according to molecular subgroups. Parameter MMRp MMRd p value NRAS mutated group TP53 mutated group TERTp enriched group p value TERTp wt TERTp mutated p value Sex (M/F) 18/26 4/3 0.45 5/8 6/7 11/14 0.92 18/22 4/7 0.61 Age (median, range) 62 67 0.56 68 67 61 0.33 65 61 0.40 Predominant oncocytic features (yes/no) 21/23 6/1 0.10 3/10 11/2 13/12 0.007 19/21 8/3 0.13 pT stage (pT1-2/pT3-4) (3 cases missing) 8/33 1/6 0.99 2/11 2/10 5/18 0.87 8/30 1/9 0.42 pN stage (pN0-NX/pN+)(3 cases missing) 25/16 3/4 0.43 8/5 6/6 14/9 0.79 21/17 7/3 0.40 Recurrences/metastases (Yes/no) (9 cases missing) 28/8 5/1 0.12 9/3 9/2 15/4 0.92 25/8 8/1 0.39 Site of metastases (lung/bone/others) 18/13/21 3/2/4 0.97 3/4/5 6/4/7 12/7/13 0.92 18/12/18 3/3/7 0.52 Status (NED-DOC/AWD-DOD) (2 cases missing) 14/28 1/6 0.41 7/6 2/11 6/17 0.08 12/27 2/8 0.50 Legend. M: male, F: female; NED: no evidence of disease; DOC: died other causes; AWD: alive with disease; DOD: died other causes; MMRp: mismatch repair proficient; MMR: mismatch repair deficient; wt: wild type Discussion In the present study, we aimed at the molecular characterization of a series of high grade follicular derived thyroid carcinomas belonging to the PDTC subtype, diagnosed according to the strict WHO classification criteria and with a specific focus on the detection of alterations that might represent potential therapeutic targets. Part of the study was designed to assess the presence and prevalence of alterations in the MMR system. Data on MMR alterations in thyroid carcinomas are relatively scarce. In a study on 241 thyroid carcinomas with different histologies, 7.5% of cases showed loss of MMR proteins, including two cases of PDTC (with a prevalence of MMR deficiency in 4.7% of PDTC in the Authors’ series) ( 18 ). Interestingly, the presence of MMR-deficiency or germline mutations in MMR genes in thyroid cancer have been significantly correlated with the occurrence of double primary cancers ( 19 , 20 ). In our series, nearly 12% of cases presented a MMR-deficient immunophenotype, thus showing a prevalence higher than what expected in the overall thyroid cancer population. Moreover, other six cases have mutations in MMR genes, with an overall prevalence of 22% of cases with an alteration affecting proteins and/or genes of the pathway. In terms of type of protein alterations, loss of MSH6 protein, alone or in combination with loss of MSH2, represented the most prevalent pattern, in line with the recent literature ( 18 ). Microsatellite instability analysis using a panel clinically approved for colon and endometrial cancer, only, failed to detect profiles of instability in all protein-altered cases. This result strongly suggest that patterns of microsatellite instability are tumor-type specific and targeted panels based on real time PCR developed for other cancer types may be not efficient to determine MMR defects in thyroid cancer ( 21 ). As for the gene-to-protein correlation, half of the cases with MMR deficiency at the protein level had mutations in MMR genes. Six other cases with MMR gene mutations had no altered protein profile, supporting that these mutations were either in heterozygosity or impaired protein functionality but not expression. Moreover, three cases with MMR-altered protein expression had no mutations in MMR genes. This observation supports the hypothesis that epigenetic regulation (i.e. promoter methylation) may be an alternative active mechanism of inactivation, as it has been described for MLH1 in colorectal and endometrial cancer. However, this mechanism is not clearly described in the literature for MSH6, so far. Cases with MMR defects were not associated with any clinical or pathological feature. DNA analysis through NGS testing using a wide targeted panel revealed three major molecular types, namely a NRAS -mutated, a TP53 -mutated and a TERTp mutated-enriched group. NRAS mutations were mutually exclusive with TP53 mutations. Key molecular features of the three subgroups included: a) NRAS -mutated cancers had a low mean number of mutations and were frequently co-mutated with PIK3CA ; b) TP53 -mutated cancers had the highest mean number of mutations, were frequently co-mutated with PTEN but lacked co-mutations in TERTp ; c) TERTp mutation-enriched (double negative for NRAS & TP53 mutations) cases had a mean number of mutations comparable with the NRAS -mutated group and lacked recurrent specific mutations. Interestingly, all but one immunohistochemically MMR-deficient tumors belonged to the TP53 -mutated group. This result supports the hypothesis that defects in the MMR-system are more likely sustaining molecular mechanisms of progression, rather than representing early driver alterations ( 22 ). This overall scenario is in line with some previous literature data. In particular, our data strongly support that the PDTC subtype - as defined by Turin consensus criteria - is separate even molecularly from the other high-grade differentiated thyroid cancers, mainly because of the high prevalence of NRAS mutations and the extremely low prevalence of BRAF mutations ( 9 , 23 ). Moreover, the mutually exclusive presence of NRAS and TP53 mutations was already present in the recent study by Xu et al ( 10 ) although with a different prevalence of mutations. Finally, we observed an overall prevalence of TERTp mutations (all validated by Sanger sequencing) lower than that of previous studies, and with a lower concurrence with NRAS mutations ( 10 ). The three PDTC molecular subgroups were not associated with peculiar clinical or pathological characteristics except for the presence of predominant oncocytic features, that was more prevalent in the TP53 -mutated group, as opposed to NRAS -mutated tumors. In terms of outcome and disease-free and disease-specific survivals, the three groups did not differ significantly. TP53 -mutated and TERTp -enriched groups showed a higher proportion of cases with adverse outcome (alive with disease status or death because of cancer) but survival analyses failed to reach statistical significance. Therefore, we could not confirm the adverse impact on survival of TP53 and TERTp mutations observed by Xu et al ( 10 ). However, this is most probably related to the fact that PDTC cases only, and not other high-grade differentiated carcinomas, were included in our study. In terms of detection of gene fusions by RNA targeted sequencing, the prevalence of fusions already known to be present in thyroid cancer was low (2 cases, 4.6%) but comparable with previous data. More interestingly, two cases harbored the TBL1XR1-PIK3CA fusion, a molecular alteration never described in thyroid cancer, so far. TBL1XR1 (Transducin beta-like 1X related protein 1, also known as TBLR1) encodes for a protein that acts as an integral subunit of the NCoR (nuclear receptor corepressor) and SMRT (silencing mediator of retinoic acid and thyroid hormone receptors) repressor complexes ( 24 ). TBL1XR1 mRNA is highly expressed in many human tissues, including thyroid, prostate and breast tissues, and may function as an oncogene by activating many signal transduction pathways, such as Wnt-β-catenin, NF-κB, and Notch ( 25 ). Rearrangement of TBL1XR1 (3q26.32) have been identified in various cancers involving different genes, including RARA (17q21) ( 26 ), HMGA1 (6p21) ( 27 ), TP63 (3q28) ( 28 ), RET (10q11.2) ( 29 ) and PIK3CA (3q26.32) ( 30 , 31 ). In the case of TBL1XR1-PIK3CA fusion, the first exon of TBL1XR1 is fused with the second exon of PIK3CA by inversion and leads to the complete transcription of the wild-type sequence of PIK3CA in the fusion transcript. TBL1XR1 is thought to regulate the expression of nuclear hormone receptor co-repressor ( 32 ), and tissue types in which the TBL1XR1–PIK3CA fusions were found (invasive breast carcinoma and prostate cancer) are hormonally regulated ( 30 , 33 , 34 ). Furthermore, TBL1XR1-PIK3CA fusions were detected in chordoma and pancreatic cancer ( 31 , 35 ). The recurrence of this alteration in our series supports the potential role of the TBL1XR1-PIK3CA fusion as a novel additional driver event in PDTC. The interest for this recurrent molecular event is also associated with its potential role as a druggable target for therapy, as suggested in other cancer models ( 31 ) Apart from the impact of our results in the understanding of the pathogenesis of PDTC, the translational relevance of our data into the clinics is highlighted by two main aspects. The first is the high prevalence of MMR defects in PDTC that paves the way for clinical studies testing the potential benefit of immunotherapy specifically in these tumors, as recently suggested for anaplastic thyroid cancer ( 36 ). Secondly, a relevant number of cases harbored mutations in potentially druggable genes, mainly coding for tyrosine kinases (i.e. PDGFRA and PDGFRB , MET , EGFR , ERBB3 , FGFR1 and FGFR2 ). Although such mutations were individually rare (from 2 to 7% of cases), 31% of patients had at least one of such targetable alterations, thus supporting a role of tyrosine kinase inhibitors in the future clinical scenario of PDTC patients, especially when poorly responsive or progressive along radio-iodine treatment. Preclinical data on the effective activation of tyrosine kinase pathways in thyroid cancer cells further support this hypothesis ( 37 , 38 ). In conclusion, PDTC in our series homogeneously classified by the Turin consensus were genomically clustered into NRAS -mutated tumors (with low mutational burden and co-mutations affecting genes involved in the same pathway), TP53 -mutated cancers (with high mutational burden, absence of TERTp mutations, strong association with MMR defects and predominant oncocytic features) and a third heterogeneous group enriched for TERTp mutations. Overall, currently or potentially targetable gene fusions have a prevalence of 9%, including the TBL1XR1-PIK3CA fusion that has never been described in the thyroid, so far, thus increasing the number of driver alterations and possible therapeutic targets for this aggressive disease. Finally, 38% of overall cases harbor mutations in genes coding for tyrosine kinases potentially targetable and/or have defects in the MMR pathway, that claim a high prevalence of cases candidates for target therapies including immunotherapy. Declarations All Authors declare the absence of any financial potential conflict of interest. MV and MP are members of the Editorial Board of Endocrine Pathology Compliance with Ethical Standards. The study was approved by the local Ethical Committee (#610, date December 20th, 2017), and conducted in accordance with the principles set out in the Declaration of Helsinki. Funding. This study was supported by a grant from the Italian Association for Cancer Research (Italian Association for Cancer Research, AIRC; IG 20100, year 2017 to MP). Author Contributions: V.Z. and M.V. performed study concept and design and writing of first draft of the manuscript; M.F. and F.N. performed molecular analyses; I.R. performed development of methodology and writing; S.C. and M.P. performed analysis and interpretation of data and revision of the paper; G.V.T. and G.O. provided technical support and statistical analysis; L.D. and S.P. provided material support and revision of the paper. All authors read and approved the final paper. Data Availability Statement. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. References Sanders EM Jr, LiVolsi VA, Brierley J, Shin J, Randolph GW (2007) An evidence-based review of poorly differentiated thyroid cancer. 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Liang J, Jin Z, Kuang J, Feng H, Zhao Q, Yang Z, Zhan L, Shen B, Yan J, Cai W, Cheng X, Qiu W (2021) The role of anlotinib-mediated EGFR blockade in a positive feedback loop of CXCL11-EGF-EGFR signalling in anaplastic thyroid cancer angiogenesis. Br J Cancer 125:390-401. doi: 10.1038/s41416-021-01340-x. Sa R, Liang R, Qiu X, He Z, Liu Z, Chen L (2022) IGF2BP2-dependent activation of ERBB2 signaling contributes to acquired resistance to tyrosine kinase inhibitor in differentiation therapy of radioiodine-refractory papillary thyroid cancer. Cancer Lett 527:10-23. doi: 10.1016/j.canlet.2021.12.005. Additional Declarations Competing interest reported. MV and MP are members of the Editorial Board of Endocrine Pathology Supplementary Files Zambellietalsupplementaryfigure1.tif Supplementary Figure 1. Schematic illustration of the dual DNA probe set employed to detect the presence of the TBL1XR1-PIK3CA fusion. ZambellietalSupplementaryTable1.xlsx Supplementary Table 1. List and characteristics of the different bioinformatic tools used for variant classification. ZambellietalSupplementaryTable2.xlsx Supplementary Table 2. Molecular data obtained in NGS analysis using OCAv3 panel. Cite Share Download PDF Status: Published Journal Publication published 22 Oct, 2025 Read the published version in Endocrine Pathology → Version 1 posted Editorial decision: Revision requested 05 Aug, 2025 Reviews received at journal 03 Aug, 2025 Reviews received at journal 02 Aug, 2025 Reviews received at journal 31 Jul, 2025 Reviewers agreed at journal 25 Jul, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers invited by journal 23 Jul, 2025 Editor assigned by journal 14 Jul, 2025 Submission checks completed at journal 14 Jul, 2025 First submitted to journal 13 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. 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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-7112785","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":489647036,"identity":"57ccd06b-a6a2-41b8-ace8-c2cd1221a84f","order_by":0,"name":"Vanessa Zambelli","email":"","orcid":"","institution":"University of Turin, at San Luigi Hospital","correspondingAuthor":false,"prefix":"","firstName":"Vanessa","middleName":"","lastName":"Zambelli","suffix":""},{"id":489647037,"identity":"fe1a4e3c-b3ef-41f8-8104-182df5de6900","order_by":1,"name":"Giulia Orlando","email":"","orcid":"","institution":"University of Turin, at Città della 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lymphocytes).\u003c/p\u003e","description":"","filename":"Zambellietalfigure1.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/2fa57ebe557ce9926a3e7181.jpg"},{"id":87729428,"identity":"0dceed6a-91f9-4055-aa8d-88608c9bd418","added_by":"auto","created_at":"2025-07-28 11:22:38","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1129833,"visible":true,"origin":"","legend":"\u003cp\u003eHeat map of genomic DNA alterations detected in 51 PDTCs.\u003c/p\u003e","description":"","filename":"Zambellietalfigure2.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/dd049f0bf7171c286a27a6e1.jpg"},{"id":87728013,"identity":"7bfdd82c-b550-4a04-8ca8-cb6b5eec7619","added_by":"auto","created_at":"2025-07-28 11:06:38","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1122770,"visible":true,"origin":"","legend":"\u003cp\u003eCo-mutated genes in \u003cem\u003eRAS\u003c/em\u003e-mutated and \u003cem\u003eTP53\u003c/em\u003e-mutated cases belong to alternative molecular pathways.\u003c/p\u003e","description":"","filename":"Zambellietalfigure3.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/8320d7e51e1a14046c8d160b.jpg"},{"id":87728901,"identity":"f7037ccb-65f2-44e3-b62f-9eca8afdf90d","added_by":"auto","created_at":"2025-07-28 11:14:38","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":793731,"visible":true,"origin":"","legend":"\u003cp\u003eIGV image of genes involved in fusion \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e(the first exon of \u003cem\u003eTBL1XR1\u003c/em\u003e is fused to the second exon of \u003cem\u003ePIK3CA\u003c/em\u003e by inversion) and overlap point between \u003cem\u003eTBL1XR1\u003c/em\u003eand \u003cem\u003ePIK3CA\u003c/em\u003e sequences (3 grey nucleotides, AGG).\u003c/p\u003e","description":"","filename":"Zambellietalfigure4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/ca98691ff195d75c01481be5.jpg"},{"id":87728024,"identity":"01626ef4-dc77-4573-b6e4-aa7ca7912d52","added_by":"auto","created_at":"2025-07-28 11:06:38","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":339940,"visible":true,"origin":"","legend":"\u003cp\u003eDual FISH analysis showing abnormal pattern in two cases with \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003efusion and normal pattern in a wild type case (see Materials and Methods and \u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e for reference).\u003c/p\u003e","description":"","filename":"Zambellietalfigure5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/41321dbac4a38ae1ec2334dd.jpg"},{"id":87728029,"identity":"8e9e40b7-b610-479b-8e63-f10eec3df2c3","added_by":"auto","created_at":"2025-07-28 11:06:38","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2691060,"visible":true,"origin":"","legend":"\u003cp\u003ePathological features of the two cases harboring the \u003cem\u003eTBL1XR1-PIK3CA \u003c/em\u003efusion (all hematoxylin and eosin stainings). PDTC case #O3 displayed an insular growth pattern (left panel) and foci of comedo-necrosis (right panel). PDTC case #S3 had a solid growth (left panel) and extensive areas of necrosis (right panel).\u003c/p\u003e","description":"","filename":"Zambellietalfigure6.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/8028187a3a7015557d0e2f01.jpg"},{"id":94490571,"identity":"0a3b574c-3c0e-4892-8c64-1db63db8f376","added_by":"auto","created_at":"2025-10-27 17:12:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8072191,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/d52d9392-b2da-46a1-9de9-2a2a6683cb19.pdf"},{"id":87728016,"identity":"b14a2e1e-c415-4205-9217-2cb811359716","added_by":"auto","created_at":"2025-07-28 11:06:38","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":114522,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e. Schematic illustration of the dual DNA probe set employed to detect the presence of the \u003cem\u003eTBL1XR1-PIK3CA \u003c/em\u003efusion.\u003c/p\u003e","description":"","filename":"Zambellietalsupplementaryfigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/a02ce84ce75dffb43a5d9dbc.tif"},{"id":87728900,"identity":"fdefbfe7-38f3-414a-b356-9eae7df171d4","added_by":"auto","created_at":"2025-07-28 11:14:38","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16249,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 1.\u003c/strong\u003e List and characteristics of the different bioinformatic tools used for variant classification.\u003c/p\u003e","description":"","filename":"ZambellietalSupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/7caa0cf5604c6027ee9e07be.xlsx"},{"id":87728014,"identity":"fd32e6d7-af98-41ba-9c6a-79d05ab6cc65","added_by":"auto","created_at":"2025-07-28 11:06:38","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":30385,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Table 2. \u003c/strong\u003eMolecular data obtained in NGS analysis using OCAv3 panel.\u003c/p\u003e","description":"","filename":"ZambellietalSupplementaryTable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7112785/v1/dd278dfa25438d3319b10e2a.xlsx"}],"financialInterests":"Competing interest reported. MV and MP are members of the Editorial Board of Endocrine Pathology","formattedTitle":"High prevalence of potential molecular therapeutic targets in poorly differentiated thyroid carcinoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePoorly-differentiated thyroid carcinoma (PDTC) represents 2\u0026ndash;15% of all thyroid carcinomas (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) and shows an intermediate prognosis between well-differentiated papillary and follicular carcinomas and anaplastic carcinoma, with a five-year disease-specific survival of 66% (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePDTC represents a heterogeneous group of aggressive thyroid neoplasms that has been a matter of discussion since its original description in the early eighties. PDTC was introduced as a distinct thyroid cancer subtype in the 2004 WHO Classification of Tumors, and in 2007 a diagnostic algorithmic approach was proposed in the so-called Turin consensus proposal, that embedded architectural features (solid, insular and/or trabecular growth pattern) together with the presence of high-grade parameters (increased mitotic activity and/or presence of necrosis) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). An alternative diagnostic approach, proposed by the Memorial Sloan Kettering Cancer Center (MSKCC), considered PDTC as a group of aggressive thyroid carcinomas defined by the presence of high-grade features, only, in the presence of follicular cell differentiation but irrespective of the tumor architecture (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Subsequent studies confirmed that both approaches are able to recognize follicular cell-derived thyroid cancers bearing an intermediate prognosis (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). All such evidence led to the current WHO classification, that identifies a group of high-grade follicular cell-derived non-anaplastic thyroid carcinomas, further segregated into two distinct histological types, namely PDTC as for the Turin Consensus criteria and high-grade differentiated thyroid carcinomas as for the MSKCC criteria (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePDTC may arise \u003cem\u003ede novo\u003c/em\u003e or may progress from well-differentiated carcinoma of follicular cell derivation. At the molecular level, consistent with a general model of multi-step progression from well- to poorly- to anaplastic carcinoma, somatic genetic alterations include \u0026ldquo;Early\u0026rdquo; and \u0026ldquo;Late\u0026rdquo; events (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). \u0026ldquo;Early\u0026rdquo; driver changes are mostly \u003cem\u003eRAS\u003c/em\u003e and \u003cem\u003eBRAF\u003c/em\u003e p.V600E mutations. Moreover, similarly to what is described for anaplastic thyroid cancer, the most frequent \u0026ldquo;Late\u0026rdquo; changes are \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eTERT\u003c/em\u003e promoter (\u003cem\u003eTERTp\u003c/em\u003e) mutations or alterations of the PI3K/PTEN/AKT pathway. Gene fusions are expected to be rare, but PDTC histology is enriched in cases harboring such alterations (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe heterogeneity of classification criteria has been a major bias in terms of the definition of the main molecular characteristics of PDTC. A seminal study depicted in detail the molecular landscape of PDTC, but at the same time highlighted how the two different classification approaches were interfering with the molecular mapping. In fact, between the two main molecular subgroups identified, the \u003cem\u003eBRAF\u003c/em\u003e-like group was dominated by MSKCC-classified cases and the \u003cem\u003eRAS\u003c/em\u003e-like group was dominated by Turin Consensus-classified cases (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Indeed, subsequent reports were supportive of the molecular diversity of genomic alterations between PDTC and high-grade differentiated thyroid carcinoma as proposed in the new WHO classification (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Therefore, most of the available literature on the genomic landscape of PDTC is influenced by non-homogeneous inclusion criteria, by the relatively small sample size of analyzed series and by a pathogenetic rather than clinically-driven approach. All these factors influence the relative prevalence of molecular alterations detected and their integration with pathological and clinical data.\u003c/p\u003e\u003cp\u003eIn terms of therapeutic strategies, unlike papillary and follicular thyroid carcinomas, PDTC therapy is not standardized due to the rarity of the disease and the heterogeneity of inclusion criteria in the few clinical studies available. Radioiodine responsiveness of PDTC after surgery is variable, possibly as the result of intra-tumor heterogeneity and coexistence of well and less well-differentiated tumor components (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Treatments using novel therapeutics have been proposed in thyroid cancer with no response or progression after radioiodine treatment (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). However, no robust data are available in PDTC, with special reference to the prevalence of alterations in potential targets or to the real clinical benefit of therapeutic targeted approaches.\u003c/p\u003e\u003cp\u003eBased on the above, there is a strong need to identify novel strategies that might lead to a better personalized approach and individualization of the therapeutic strategies in PDTC. Therefore, the aim of this study was to characterize a series of PDTC, homogeneously coded following the Turin criteria as proposed for this group in the current WHO classification, by means of a multimodal molecular approach with the objective of identifying the prevalence and potential clinical usefulness of molecular targets for therapy. We decided to restrict the analysis to the PDTC subtype because homogeneous criteria for its definition were claimed to provide a robust and reliable group of tumors and - last but not least- because these particular tumors are more common in alpine/mountain areas including our Country, and their molecular characterization is less established in the literature as compared to high-grade differentiated thyroid carcinoma.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cb\u003ePatient and tissue samples.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFifty-nine samples of PDTC were selected from the files of the Pathology Units at \u0026ldquo;San Luigi\u0026rdquo; and \u0026ldquo;Citt\u0026agrave; della Salute e della Scienza\u0026rdquo; Hospitals and tested for the presence of mismatch repair defects and for DNA and RNA alterations through a wide targeted NGS approach. Due to the high number of failures in RNA analysis (see below), 25 additional PDTC samples from Mauriziano (Turin) and Reggio Emilia Hospitals were added to RNA analysis. All samples were formalin fixed and paraffin embedded surgical materials, retrieved from years 1993 to 2022. For all enrolled cases, histological slides were re-assessed by a pathologist (MV) to confirm the diagnosis following diagnostic criteria for PDTC proposed by the Turin Consensus (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) and embraced by the current WHO classification (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Major clinical and pathological data were collected and included sex, age, presence of predominant oncocytic features (\u0026gt;\u0026thinsp;75% of the tumor), pTN stage according to AJCC system 8th edition, presence of recurrences/metastases, site of metastases, and patient status. The study was approved by the local Ethical Committee (#610, on December 20, 2017), and conducted in accordance with the principles set out in the Declaration of Helsinki. Considering the retrospective nature of this research protocol and that it had no impact on patients\u0026rsquo; care, no specific written informed consent was required.\u003c/p\u003e\u003cp\u003e\u003cb\u003eNucleic acid extraction and sample quality control.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eGenomic DNA and RNA were extracted from the formalin-fixed paraffin-embedded tumor material. Enrichment of tumor cells was obtained by manual microdissection under light microscopy from one to ten sections for each case as previously reported (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe selected material was extracted using Maxwell\u0026reg; RSC DNA FFPE kit (Promega Corporation, Madison, WI, USA, CN: AS1450) and Maxwell\u0026reg; RSC RNA FFPE kit (Promega Corporation, Madison, WI, USA, CN: 14402) according to the manufacturer\u0026rsquo;s instructions. Nucleic acids were quantified on QuantusTM fluorometer (Promega Corporation, Madison, WI, USA) using Quantifluor\u0026reg; DNA System (Promega Corporation, Madison, WI, USA, CN: E4871) and Quantifluor\u0026reg; RNA System (Promega Corporation, Madison, WI, USA, CN: E3310) following manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cp\u003eDNA quality was evaluated with Real Time PCR of \u003cem\u003eEGFR\u003c/em\u003e Exon2 amplification through Rotor-Gene Q (Qiagen, Hilden, Germany) Real Time PCR instrument, the following primers were used for \u003cem\u003eEGFR\u003c/em\u003e: EGFRex2b Fw (5\u0026rsquo;-GAAGATCATTTTCTCAGCCTCCA-3\u0026rsquo;) and EGFRex2b Rw (5\u0026rsquo;-AGGAAAATCAAAGTCACCAACCT-3\u0026rsquo;) (Diatech Pharmacogenetics, Jesi, Ancona, Italy). RNA quality was evaluated with Real Time PCR with beta-actin amplification through Rotor-Gene Q (Qiagen, Hilden, Germany) Real Time PCR instrument, the following primers were used for B-ACT: BACT Fw (5\u0026rsquo;-CCTTCCTGGGCATGGAGTCTTG-3\u0026rsquo;) and BACT Rw (5\u0026rsquo;-GGAGCAATGATCTTGATCTTC-3\u0026rsquo;).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAnalysis of mismatch repair status.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe expression of mismatch repair (MMR) proteins was tested using immunohistochemistry in an automated system (Dako Omnis, Dako, Agilent) using the following antibodies (all from Dako): MLH1 (clone ES05, CN:GA079), MSH2 (clone FE11,CN:GA085), MSH6 (clone EP49, CN:GA086) and PMS2 (clone EP51, CN:GA087). Loss of nuclear expression for paired proteins (MLH1 and/or PMS2 or MSH2 and/or MSH6) was considered as altered expression pattern. Cases with an altered pattern were also tested for the presence of microsatellite instability (MSI) using genomic DNA extracted as described above. Since thyroid cancer-specific panels are not commercially available, all cases were analyzed using a kit clinically approved for colon and endometrial cancer (EasyPGX ready MSI KIT CE IVD, Diatech Pharmacogenetics, CN:RT033) that includes the following markers: BAT25, BAT26, NR21, NR22, NR24, NR27, CAT25 and MONO27. Bioinformatic analysis was carried out though the software for data exportation Agilent Aria Software v1.4 and data analysis were performed with EasyPGX Analysis Software v3.0. Results are expressed as microsatellite stable (MSS), low microsatellite instability (MSI-low) and high microsatellite instability (MSI-high).\u003c/p\u003e\u003cp\u003e\u003cb\u003eNext-generation sequencing.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eLibrary preparation was carried out automatically using the DNA and RNA Oncomine\u0026trade; Comprehensive Assay v3 (Thermo Fisher Scientific, Waltham, MA, USA, CN: A36111) using a total from 10 to 40 ng input DNA and RNA in an Ion Chef System (Thermo Fisher Scientific, Waltham, MA, USA) following manufacturer\u0026rsquo;s instructions. The Oncomine\u0026trade; Comprehensive Assay v3 (Thermo Fisher Scientific, Waltham, MA, USA) comprises DNA panel which was designed to interrogate hotspot mutations (#87), full exon coverage (#48) and copy number variations (#43) and RNA panel which was designed to interrogate fusion drivers (#51) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This panel can identify current actionable genetic variants and potential future targets for personalized therapy.\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\u003eGenes covered by the Oncomine\u0026trade; Comprehensive Assay v3 (Thermo Fisher Scientific, Waltham, MA, USA) panel.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"12\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eHotspot genes (87)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eCopy number variants (43)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e\u003cp\u003eFusion drivers (51)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e\u003cp\u003eFull exon coverage (48)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eESR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKIT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePDGFRB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAKT1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFGFR4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAKT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eKRAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eARID1A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eNF1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eSTK11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEZH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKNSTRN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePIK3CA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAKT2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFLT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eALK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMDM4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRELA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eATM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eNF2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTP53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAKT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFGFR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKRAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePIK3CB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAKT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIGF1R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMET\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRET\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eATR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eNOTCH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u003cp\u003eTSC1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" 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colname=\"c10\"\u003e\u003cp\u003eBAP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eNOTCH3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eARAF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFGFR4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMAP2K2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRAC1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAXL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMDM2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eBRCA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNF1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eRSPO3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eBRCA1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePALB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAXL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFLT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMAP2K4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRAF1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBRAF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMDM4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNOTCH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eTERT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eBRCA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePIK3R1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBRAF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFOXL2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMAPK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRET\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCCND1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMET\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eCDKN2A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNOTCH4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCDK12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePMS2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBTK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGATA2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMAX\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRHEB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCCND2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMYC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEGFR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNRG1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCDKN1B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePOLE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCBL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGNA11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMDM4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRHOA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCCND3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMYCL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eERBB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNTRK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCDKN2A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePTCH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCCND1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGNAQ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMED12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eROS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCCNE1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMYCN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eERBB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNTRK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCDKN2B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003ePTEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCDK4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" 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colname=\"c1\"\u003e\u003cp\u003eCDK6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eH3F3A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMTOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSMAD4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCDK4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNTRK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eESR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNUTM1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eCREBBP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRAD51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCHEK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHIST1H3B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMYC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSMO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCDK6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNTRK3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eETV1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePDGFRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eFANCA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRAD51C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCSF1R\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHNF1A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMYCN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSPOP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEGFR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePDGFRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eETV4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePDGFRB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eFANCD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRAD51D\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCTNNB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHRAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMYD88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSRC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eERBB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePDGFRB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eETV5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePIK3CA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eFANCI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRAD51B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDDR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIDH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNFE2L2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSTAT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eESR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePIK3CA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFGFR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePPARG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eFBXW7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEGFR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIDH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNRAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTERT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFGF19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePIK3CB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFGFR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePRKACA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMLH1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eRNF43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERBB2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJAK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNTRK1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTOP1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFGF3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePPARG\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFGFR3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePRKACB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMRE11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSETD2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERBB3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJAK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNTRK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eU2AF1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFGFR1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eRICTOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFGR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ePTEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMSH2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSLX4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERBB4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJAK3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNTRK3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eXPO1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFGFR2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTERT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFLT3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRAD51B\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMSH6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSMARCA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eERCC2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eKDR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePDGFRA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFGFR3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eJAK2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eRAF1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eNBN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003eSMARCB1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe prepared libraries were clonally amplified onto Ion Sphere Particles (ISP) using emulsion PCR in an Ion Chef System (Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer\u0026rsquo;s instructions. Enriched ISPs were loaded onto 540 chips accommodating eight DNA samples and eight RNA samples on a single chip and sequencing on the Ion Torrent S5 Prime StudioTM (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eDNA Data analysis.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnalysis was carried out using Ion Torrent Suite\u0026trade; Browser version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA) and Ion Reporter\u0026trade; version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA). The Torrent Suite\u0026trade; Browser was used to perform initial quality control including chip loading density, median read length and number of mapped reads. The Coverage Analysis plugin was applied to all data and used to assess amplicon coverage for regions of interest.\u003c/p\u003e\u003cp\u003eThe Ion Reporter suite (Thermo Fisher Scientific, Waltham, MA, USA) was used to filter out known polymorphic variants. The variants were annotated by genetic databases: the Single Nucleotide Polymorphism Database (dbSNP) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/projects/SNP/\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/projects/SNP/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), Catalogue of Somatic Mutations in Cancer (COSMIC) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cancer.sanger.ac.uk/cancergenome/projects/cosmic/\u003c/span\u003e\u003cspan address=\"http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and ClinVar database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov/clinvar/\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov/clinvar/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVariants with altered allele depth\u0026thinsp;\u0026le;\u0026thinsp;100 base coverage and a variant allelic frequency\u0026thinsp;\u0026le;\u0026thinsp;5% were eliminated from the analysis. Identified variants were checked for correct nomenclature using Alamut Visual Plus (Interactive Biosoftware, Sophia Genetics). Any discrepancies in variant identification, between Ion Reporter and Alamut, were validated manually using the Integrative Genomics Viewer (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eVariants were annotated following ACGM guidelines (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and the search engine VarSomePremium.com (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe prediction of functional effects of the variants that were find as Variants of Uncertain Significance (VUS) was assessed with 13 \u003cem\u003ein silico\u003c/em\u003e tools (Align GVGD [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://agvgd.hci.utah.edu/agvgd_input.php\u003c/span\u003e\u003cspan address=\"http://agvgd.hci.utah.edu/agvgd_input.php\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], Mutation Taster [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.mutationtaster.org\u003c/span\u003e\u003cspan address=\"https://www.mutationtaster.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], Provean [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://provean.jcvi.org\u003c/span\u003e\u003cspan address=\"http://provean.jcvi.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], SIFT [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sift.bii.a-star.edu.sg\u003c/span\u003e\u003cspan address=\"https://sift.bii.a-star.edu.sg\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], Grantham [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ionreporter.thermofisher.com\u003c/span\u003e\u003cspan address=\"https://ionreporter.thermofisher.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], Polyphen2 [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ionreporter.thermofisher.com\u003c/span\u003e\u003cspan address=\"https://ionreporter.thermofisher.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], DANN [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://varsome.com\u003c/span\u003e\u003cspan address=\"https://varsome.com\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], FATHMM-MKL [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://fathmm.biocompute.org.uk\u003c/span\u003e\u003cspan address=\"https://fathmm.biocompute.org.uk\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], LRT [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sites.google.com/site/jpopgen/dbNSFP\u003c/span\u003e\u003cspan address=\"https://sites.google.com/site/jpopgen/dbNSFP\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], Meta-RNN [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.liulab.science/metarnn.html\u003c/span\u003e\u003cspan address=\"http://www.liulab.science/metarnn.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], MutPred [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mutpred.mutdb.org\u003c/span\u003e\u003cspan address=\"http://mutpred.mutdb.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e], Mutation Assessor [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mutationassessor.org/r3\u003c/span\u003e\u003cspan address=\"http://mutationassessor.org/r3\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e] and REVEL [\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://labworm.com/tool/revel\u003c/span\u003e\u003cspan address=\"https://labworm.com/tool/revel\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e]) (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). Each tool had his own threshold, giving for each score a prediction of tolerated or damaging, VUS was qualify as Damaging when the sum of all \u003cem\u003ein silico\u003c/em\u003e tools that resulted damaging was higher than 7 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The missense variants called as both benign and tolerated were excluded, as well as variant shaving a frequency higher than 1% in all populations from the 1000 Genomes data. Synonymous mutations were excluded from the analysis. RNA Data analysis was carried out using Ion Torrent Suite\u0026trade; Browser version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA) and Ion Reporter\u0026trade; version 5.16 (Thermo Fisher Scientific, Waltham, MA, USA).\u003c/p\u003e\u003cp\u003e\u003cb\u003eSanger sequencing.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo validate \u003cem\u003eTERTp\u003c/em\u003e mutations that are difficult to detect in NGS analysis as they are intronic, we performed Sanger sequencing analysis on all 59 cases tested for DNA genomic alterations in NGS. \u003cem\u003eTERTp\u003c/em\u003e region was sequenced for the detection of the two mutations C228T and C250T. Target region was amplified by conventional PCR with the following primes: \u003cem\u003eTERT\u003c/em\u003e Fw (5\u0026rsquo;AGTGGATTCGCGGGCACAGA-3\u0026rsquo;) and \u003cem\u003eTERT\u003c/em\u003e Rw (5\u0026rsquo;-CAGCGCTGCCTGAAACTC-3\u0026rsquo;). A first step with Uracil-DNA Glycosylase (Thermo Fisher Scientific, Waltham, MA, USA) was performed on all samples, following manufacturer\u0026rsquo;s instructions. Then, the PCR run in 50 \u0026micro;L reactions with 25\u0026micro;L of 2X PlatinumTM SuperfiTM II PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, USA, CN:12361010), 5\u0026micro;M of each primer and 10\u0026micro;L of gDNA. The amount of gDNA for each PCR varies from 5 to 100 ng, depending on sample\u0026rsquo;s quality. PCR conditions consist of one cycle of 98\u0026deg;C for 1 min, 3 cycles of (98\u0026deg;C for 30s, 62\u0026deg;C for 30s, 72\u0026deg;C for 45s), followed by 35 cycles of (98\u0026deg;C for 30s, 60\u0026deg;C for 30s, 72\u0026deg;C for 45s), and final extension at 72\u0026deg;C for 5 min. Resulting amplicons were visualized in 2% agarose gels and verified to have the expected size of 193 bp. \u003cem\u003eTERTp\u003c/em\u003e sequences were generated by Sanger sequencing and sequencing was performed at Eurofins Genomics (Ebersberg, Germany), all samples were sequenced in both directions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFluorescence In-Situ Hybridization (FISH).\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo validate the \u003cem\u003eTBL1XRA-PIK3CA\u003c/em\u003e fusion, a FISH approach was applied on four-micron thick formalin-fixed paraffin-embedded section using a \u003cem\u003eTBL1XR1/PIK3CA\u003c/em\u003e probe set (Empire Genomics, New York, US, CN: TBL1XR1-PIK3CA-20-GROR) following manufacturer instructions. The two cases positive in RNA NGS analysis and two cases negative, randomly selected from the series, were tested. \u003cem\u003eTBL1XR1/PIK3CA\u003c/em\u003e probe set consisted of DNA labeled in Spectrum Green and Spectrum Orange. The DNA probe set hybridizes to chromosome 3q26.32 (Green) and 3q26.32-q26.33 (Orange) in interphase nuclei (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). The presence of two green and red separated signals were considered as normal pattern, while altered partner was characterized by fused signals (yellow) and/or with multiple red and green signals without fusion signal. The sections were examined with an Olympus BX61 fluorescence microscope (Olympus Corporation, Tokyo, Japan) equipped with a triple-pass filter (DAPI/Green/Orange; Vysis, Downers Grove, IL,USA) with CytoVision\u0026reg; software version 7.6 (Leica Biosystems, Buffalo Grove, IL, United States).\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical analyses.\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePathological features, immunohistochemical and molecular results were correlated to clinical variables, using appropriate statistical tests (chi-square and t Student\u0026rsquo;s test for qualitative and quantitative parameters correlation, and univariate analyses of both disease-free interval (from the date of diagnosis to first metastasis/recurrence) and disease-specific survival (from the date of diagnosis to death if related to the disease). All statistical analyses were performed using Graph Pad Prism 9.4.1 software.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eMismatch repair status.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAll samples were adequate for analysis, with a reliable reactivity of the tested markers in positive control cells within the tissue sections. Seven out of 59 cases (11.9%) had an altered MMR protein pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In particular, four cases had MSH2-MSH6 loss, one sample MLH1-PMS2 loss, one sample MSH6 loss and one sample PMS2 loss. MSI molecular analysis on samples that showed an altered pattern of protein expression resulted in microsatellite stability in all cases with the panel of markers employed.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eMolecular profiling.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFifty-one over 59 PDTC samples (86%) were suitable for DNA NGS analysis. The eight cases with inadequate DNA for NGS analysis had an age of blocks ranging from 2002 to 2016. Mean age in years of blocks in adequate and inadequate samples was 14 and 11, respectively, (p\u0026thinsp;=\u0026thinsp;0.36).\u003c/p\u003e\u003cp\u003eGenomic alterations found in the series are summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Details in genomic DNA alterations, as well as RNA fusions and CNV detected in the series, are reported in \u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThree cases were wild type for all genes included in the NGS panel. The number of overall mutations per case ranged from 1 to 25. The most prevalent mutations were in \u003cem\u003eNRAS\u003c/em\u003e (13/51, 25%) and \u003cem\u003eTP53\u003c/em\u003e (13/51, 25%), all mutually exclusive each other. \u003cem\u003eTERTp\u003c/em\u003e mutations were detected in 11/51 of overall cases (21.6%; 10/11 C228T [c.-124 C\u0026thinsp;\u0026gt;\u0026thinsp;T] and 1/11 C250T [c.-146 C\u0026thinsp;\u0026gt;\u0026thinsp;T]). All \u003cem\u003eTERTp\u003c/em\u003e mutations detected through NGS analysis were confirmed by means of Sanger sequencing. No additional mutations in \u003cem\u003eTERTp\u003c/em\u003e were detected by Sanger sequencing analysis in NGS negative cases, with an overall concordance between the two methods of 100%.\u003c/p\u003e\u003cp\u003eMutations in MMR genes were detected in 10 cases (19.6%). Mutational profile in MMR genes was concordant in three samples with protein loss at immunohistochemistry, including two cases with \u003cem\u003eMSH2\u003c/em\u003e mutation (one with and one without associated \u003cem\u003eMSH6\u003c/em\u003e mutations) and one case with \u003cem\u003eMLH1\u003c/em\u003e mutation. One additional case harbored \u003cem\u003eMLH1\u003c/em\u003e mutation but loss of \u003cem\u003ePMS2\u003c/em\u003e protein, only. In the remaining three cases with altered expression of MMR proteins, no mutations in MMR genes were detected. Six additional cases harbored mutations in MMR genes (two \u003cem\u003eMLH1\u003c/em\u003e, two \u003cem\u003eMSH2\u003c/em\u003e, one \u003cem\u003eMSH6\u003c/em\u003e and one \u003cem\u003ePMS2\u003c/em\u003e) with no loss of MMR proteins expression.\u003c/p\u003e\u003cp\u003eOther genes with a prevalence of alterations exceeding 10% were \u003cem\u003ePTEN\u003c/em\u003e (15.7%), \u003cem\u003eNF1\u003c/em\u003e (13.7%), \u003cem\u003eATM\u003c/em\u003e (13.7%), \u003cem\u003eNOTCH3\u003c/em\u003e (11.8%) and \u003cem\u003eBAP1\u003c/em\u003e (11.8%).\u003c/p\u003e\u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e mutated and \u003cem\u003eTP53\u003c/em\u003e mutated cases showed different molecular characteristics. Mean number of alterations was higher in \u003cem\u003eTP53\u003c/em\u003e-mutated cases (5.8 mutations/case) rather than in \u003cem\u003eNRAS\u003c/em\u003e-mutated cases (2.8 mutations/case). \u003cem\u003ePIK3CA\u003c/em\u003e and \u003cem\u003eTERTp\u003c/em\u003e were the most prevalent co-mutated genes (three cases, each, mutually exclusive) in \u003cem\u003eNRAS\u003c/em\u003e-mutated cases. \u003cem\u003eTP53\u003c/em\u003e-mutated samples lacked \u003cem\u003eTERTp\u003c/em\u003e co-mutations but were significantly associated with mutations in \u003cem\u003ePTEN\u003c/em\u003e (46% of cases, p\u0026thinsp;=\u0026thinsp;0.024 as compared with the other molecular subgroups) and in genes related to MMR system and/or loss of MMR proteins (53.8% of cases, p\u0026thinsp;=\u0026thinsp;0.005 as compared with the other molecular subgroups). Overall, most co-mutated alterations in \u003cem\u003eTP53\u003c/em\u003e mutated as compared to \u003cem\u003eNRAS\u003c/em\u003e mutated cases were mutually exclusive (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A third heterogeneous group (25 cases) lacked \u003cem\u003eNRAS\u003c/em\u003e or \u003cem\u003eTP53\u003c/em\u003e mutations, had a low mean number of alterations (2.7 mutations/case) but was enriched for \u003cem\u003eTERTp\u003c/em\u003e mutations (32%, not reaching statistical significance as compared to the two other molecular subgroups). One case with \u003cem\u003eHRAS\u003c/em\u003e mutation was aggregated within this group because of the co-presence of different other mutations and a low allelic frequency (14%). Copy number variations were not detected.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTwenty-eight out of 59 cases were adequate for RNA NGS analysis (47%). Due to this high rate of failure, 25 additional cases were included. Overall, 84 samples were tested, with 43 cases passing quality controls for analysis (52%). Mean age of blocks in adequate and inadequate samples was 11 and 12, respectively (p\u0026thinsp;=\u0026thinsp;0.38).\u003c/p\u003e\u003cp\u003eChromosomal rearrangements involving genes known to be translocated in thyroid cancer were found in two samples, including one case with \u003cem\u003eRET\u003c/em\u003e rearrangement involving the common \u003cem\u003eRET\u003c/em\u003e partner \u003cem\u003eCCDC6\u003c/em\u003e and one case with the \u003cem\u003ePAX8-PPARG\u003c/em\u003e fusion. Two other cases harbored a \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). In the remaining 39 samples no gene fusions were detected. The presence of the \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion was associated with an altered pattern by FISH in both the two positive cases, whereas fusion negative samples showed the expected non-altered pattern (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical and pathological correlations.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe most prevalent molecular findings in our series were compared with major clinical and pathological characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Cases showing MMR protein loss and \u003cem\u003eTERTp\u003c/em\u003e mutated cases were not associated with significant clinical or pathological characteristics in our series. The three distinct molecular subgroups did not show any significant association with clinical or pathological parameters, except for a higher prevalence of PDTC with predominant oncocytic features in the \u003cem\u003eTP53\u003c/em\u003e-mutated group. Moreover, although not reaching statistical significance, \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eTERTp\u003c/em\u003e mutated cases had a higher prevalence of adverse events as compared with \u003cem\u003eNRAS\u003c/em\u003e-mutated cases. Survival data were available in 47 cases. The two cases with the \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion had conventional pathological features with no peculiar findings (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Median survival times were calculated in the three major subgroups. Median disease-free survival was 17, 15 and 64 months in \u003cem\u003eNRAS\u003c/em\u003e-mutated, \u003cem\u003eTP53\u003c/em\u003e-mutated and \u003cem\u003eTERTp\u003c/em\u003e-enriched cases, respectively, with a trend to statistical significance with Log Rank test (p\u0026thinsp;=\u0026thinsp;0.079). Median disease-specific survival was 145, 111 and 274 months in \u003cem\u003eRAS\u003c/em\u003e-mutated, \u003cem\u003eTP53\u003c/em\u003e-mutated and \u003cem\u003eTERTp\u003c/em\u003e-enriched cases, respectively, without a statistically significant difference.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical pathological correlations according to molecular subgroups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\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\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eParameter\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMMRp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMMRd\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eNRAS\u003c/em\u003e mutated group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eTP53\u003c/em\u003e mutated\u003c/p\u003e\u003cp\u003egroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eTERTp\u003c/em\u003e enriched\u003c/p\u003e\u003cp\u003egroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e\u003cem\u003eTERTp\u003c/em\u003e wt\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003e\u003cem\u003eTERTp\u003c/em\u003e mutated\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003ep value\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex (M/F)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18/26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.45\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11/14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.92\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e18/22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e4/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.61\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (median, range)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.56\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.33\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.40\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePredominant oncocytic features (yes/no)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e21/23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6/1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.10\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3/10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e11/2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13/12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.007\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e19/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e8/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.13\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003epT stage (pT1-2/pT3-4) (3 cases missing)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8/33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.99\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2/11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2/10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e5/18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.87\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e8/30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1/9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.42\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003epN stage (pN0-NX/pN+)(3 cases missing)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25/16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3/4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.43\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8/5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e14/9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.79\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e21/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e7/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.40\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRecurrences/metastases (Yes/no) (9 cases missing)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5/1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.12\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9/3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9/2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15/4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.92\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e25/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e8/1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.39\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSite of metastases (lung/bone/others)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18/13/21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3/2/4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.97\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3/4/5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6/4/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12/7/13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.92\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e18/12/18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3/3/7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.52\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStatus (NED-DOC/AWD-DOD) (2 cases missing)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14/28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e0.41\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7/6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2/11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6/17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.08\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e12/27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2/8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e\u003cem\u003e0.50\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003eLegend. M: male, F: female; NED: no evidence of disease; DOC: died other causes; AWD: alive with disease; DOD: died other causes; MMRp: mismatch repair proficient; MMR: mismatch repair deficient; wt: wild type\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we aimed at the molecular characterization of a series of high grade follicular derived thyroid carcinomas belonging to the PDTC subtype, diagnosed according to the strict WHO classification criteria and with a specific focus on the detection of alterations that might represent potential therapeutic targets.\u003c/p\u003e\u003cp\u003ePart of the study was designed to assess the presence and prevalence of alterations in the MMR system. Data on MMR alterations in thyroid carcinomas are relatively scarce. In a study on 241 thyroid carcinomas with different histologies, 7.5% of cases showed loss of MMR proteins, including two cases of PDTC (with a prevalence of MMR deficiency in 4.7% of PDTC in the Authors\u0026rsquo; series) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Interestingly, the presence of MMR-deficiency or germline mutations in MMR genes in thyroid cancer have been significantly correlated with the occurrence of double primary cancers (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In our series, nearly 12% of cases presented a MMR-deficient immunophenotype, thus showing a prevalence higher than what expected in the overall thyroid cancer population. Moreover, other six cases have mutations in MMR genes, with an overall prevalence of 22% of cases with an alteration affecting proteins and/or genes of the pathway. In terms of type of protein alterations, loss of MSH6 protein, alone or in combination with loss of MSH2, represented the most prevalent pattern, in line with the recent literature (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Microsatellite instability analysis using a panel clinically approved for colon and endometrial cancer, only, failed to detect profiles of instability in all protein-altered cases. This result strongly suggest that patterns of microsatellite instability are tumor-type specific and targeted panels based on real time PCR developed for other cancer types may be not efficient to determine MMR defects in thyroid cancer (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). As for the gene-to-protein correlation, half of the cases with MMR deficiency at the protein level had mutations in MMR genes. Six other cases with MMR gene mutations had no altered protein profile, supporting that these mutations were either in heterozygosity or impaired protein functionality but not expression. Moreover, three cases with MMR-altered protein expression had no mutations in MMR genes. This observation supports the hypothesis that epigenetic regulation (i.e. promoter methylation) may be an alternative active mechanism of inactivation, as it has been described for MLH1 in colorectal and endometrial cancer. However, this mechanism is not clearly described in the literature for MSH6, so far. Cases with MMR defects were not associated with any clinical or pathological feature.\u003c/p\u003e\u003cp\u003eDNA analysis through NGS testing using a wide targeted panel revealed three major molecular types, namely a \u003cem\u003eNRAS\u003c/em\u003e-mutated, a \u003cem\u003eTP53\u003c/em\u003e-mutated and a \u003cem\u003eTERTp\u003c/em\u003e mutated-enriched group. \u003cem\u003eNRAS\u003c/em\u003e mutations were mutually exclusive with \u003cem\u003eTP53\u003c/em\u003e mutations. Key molecular features of the three subgroups included:\u003c/p\u003e\u003cp\u003ea) \u003cem\u003eNRAS\u003c/em\u003e-mutated cancers had a low mean number of mutations and were frequently co-mutated with \u003cem\u003ePIK3CA\u003c/em\u003e;\u003c/p\u003e\u003cp\u003eb) \u003cem\u003eTP53\u003c/em\u003e-mutated cancers had the highest mean number of mutations, were frequently co-mutated with \u003cem\u003ePTEN\u003c/em\u003e but lacked co-mutations in \u003cem\u003eTERTp\u003c/em\u003e;\u003c/p\u003e\u003cp\u003ec) \u003cem\u003eTERTp\u003c/em\u003e mutation-enriched (double negative for \u003cem\u003eNRAS\u003c/em\u003e \u0026amp; \u003cem\u003eTP53\u003c/em\u003e mutations) cases had a mean number of mutations comparable with the \u003cem\u003eNRAS\u003c/em\u003e-mutated group and lacked recurrent specific mutations.\u003c/p\u003e\u003cp\u003eInterestingly, all but one immunohistochemically MMR-deficient tumors belonged to the \u003cem\u003eTP53\u003c/em\u003e-mutated group. This result supports the hypothesis that defects in the MMR-system are more likely sustaining molecular mechanisms of progression, rather than representing early driver alterations (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis overall scenario is in line with some previous literature data. In particular, our data strongly support that the PDTC subtype - as defined by Turin consensus criteria - is separate even molecularly from the other high-grade differentiated thyroid cancers, mainly because of the high prevalence of \u003cem\u003eNRAS\u003c/em\u003e mutations and the extremely low prevalence of \u003cem\u003eBRAF\u003c/em\u003e mutations (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Moreover, the mutually exclusive presence of \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eTP53\u003c/em\u003e mutations was already present in the recent study by Xu et al (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) although with a different prevalence of mutations. Finally, we observed an overall prevalence of \u003cem\u003eTERTp\u003c/em\u003e mutations (all validated by Sanger sequencing) lower than that of previous studies, and with a lower concurrence with \u003cem\u003eNRAS\u003c/em\u003e mutations (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe three PDTC molecular subgroups were not associated with peculiar clinical or pathological characteristics except for the presence of predominant oncocytic features, that was more prevalent in the \u003cem\u003eTP53\u003c/em\u003e-mutated group, as opposed to \u003cem\u003eNRAS\u003c/em\u003e-mutated tumors. In terms of outcome and disease-free and disease-specific survivals, the three groups did not differ significantly. \u003cem\u003eTP53\u003c/em\u003e-mutated and \u003cem\u003eTERTp\u003c/em\u003e-enriched groups showed a higher proportion of cases with adverse outcome (alive with disease status or death because of cancer) but survival analyses failed to reach statistical significance. Therefore, we could not confirm the adverse impact on survival of \u003cem\u003eTP53\u003c/em\u003e and \u003cem\u003eTERTp\u003c/em\u003e mutations observed by Xu et al (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). However, this is most probably related to the fact that PDTC cases only, and not other high-grade differentiated carcinomas, were included in our study.\u003c/p\u003e\u003cp\u003eIn terms of detection of gene fusions by RNA targeted sequencing, the prevalence of fusions already known to be present in thyroid cancer was low (2 cases, 4.6%) but comparable with previous data. More interestingly, two cases harbored the \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion, a molecular alteration never described in thyroid cancer, so far. \u003cem\u003eTBL1XR1\u003c/em\u003e (Transducin beta-like 1X related protein 1, also known as TBLR1) encodes for a protein that acts as an integral subunit of the NCoR (nuclear receptor corepressor) and SMRT (silencing mediator of retinoic acid and thyroid hormone receptors) repressor complexes (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). \u003cem\u003eTBL1XR1\u003c/em\u003e mRNA is highly expressed in many human tissues, including thyroid, prostate and breast tissues, and may function as an oncogene by activating many signal transduction pathways, such as Wnt-β-catenin, NF-κB, and Notch (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Rearrangement of \u003cem\u003eTBL1XR1\u003c/em\u003e (3q26.32) have been identified in various cancers involving different genes, including \u003cem\u003eRARA\u003c/em\u003e (17q21) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e), \u003cem\u003eHMGA1\u003c/em\u003e (6p21) (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e), \u003cem\u003eTP63\u003c/em\u003e (3q28) (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), \u003cem\u003eRET\u003c/em\u003e (10q11.2) (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e) and \u003cem\u003ePIK3CA\u003c/em\u003e (3q26.32) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In the case of \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion, the first exon of \u003cem\u003eTBL1XR1\u003c/em\u003e is fused with the second exon of \u003cem\u003ePIK3CA\u003c/em\u003e by inversion and leads to the complete transcription of the wild-type sequence of \u003cem\u003ePIK3CA\u003c/em\u003e in the fusion transcript. \u003cem\u003eTBL1XR1\u003c/em\u003e is thought to regulate the expression of nuclear hormone receptor co-repressor (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), and tissue types in which the \u003cem\u003eTBL1XR1\u0026ndash;PIK3CA\u003c/em\u003e fusions were found (invasive breast carcinoma and prostate cancer) are hormonally regulated (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Furthermore, \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusions were detected in chordoma and pancreatic cancer (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The recurrence of this alteration in our series supports the potential role of the \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion as a novel additional driver event in PDTC. The interest for this recurrent molecular event is also associated with its potential role as a druggable target for therapy, as suggested in other cancer models (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eApart from the impact of our results in the understanding of the pathogenesis of PDTC, the translational relevance of our data into the clinics is highlighted by two main aspects. The first is the high prevalence of MMR defects in PDTC that paves the way for clinical studies testing the potential benefit of immunotherapy specifically in these tumors, as recently suggested for anaplastic thyroid cancer (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Secondly, a relevant number of cases harbored mutations in potentially druggable genes, mainly coding for tyrosine kinases (i.e. \u003cem\u003ePDGFRA\u003c/em\u003e and \u003cem\u003ePDGFRB\u003c/em\u003e, \u003cem\u003eMET\u003c/em\u003e, \u003cem\u003eEGFR\u003c/em\u003e, \u003cem\u003eERBB3\u003c/em\u003e, \u003cem\u003eFGFR1\u003c/em\u003e and \u003cem\u003eFGFR2\u003c/em\u003e). Although such mutations were individually rare (from 2 to 7% of cases), 31% of patients had at least one of such targetable alterations, thus supporting a role of tyrosine kinase inhibitors in the future clinical scenario of PDTC patients, especially when poorly responsive or progressive along radio-iodine treatment. Preclinical data on the effective activation of tyrosine kinase pathways in thyroid cancer cells further support this hypothesis (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn conclusion, PDTC in our series homogeneously classified by the Turin consensus were genomically clustered into \u003cem\u003eNRAS\u003c/em\u003e-mutated tumors (with low mutational burden and co-mutations affecting genes involved in the same pathway), \u003cem\u003eTP53\u003c/em\u003e-mutated cancers (with high mutational burden, absence of \u003cem\u003eTERTp\u003c/em\u003e mutations, strong association with MMR defects and predominant oncocytic features) and a third heterogeneous group enriched for \u003cem\u003eTERTp\u003c/em\u003e mutations. Overall, currently or potentially targetable gene fusions have a prevalence of 9%, including the \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion that has never been described in the thyroid, so far, thus increasing the number of driver alterations and possible therapeutic targets for this aggressive disease. Finally, 38% of overall cases harbor mutations in genes coding for tyrosine kinases potentially targetable and/or have defects in the MMR pathway, that claim a high prevalence of cases candidates for target therapies including immunotherapy.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll Authors declare the absence of any financial potential conflict of interest. MV and MP are members of the Editorial Board of Endocrine Pathology\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompliance with Ethical Standards.\u0026nbsp;\u003c/strong\u003eThe study was approved by the local Ethical Committee (#610, date December 20th, 2017), and conducted in accordance with the principles set out in the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding.\u003c/strong\u003e This study was supported by a grant from the Italian Association for Cancer Research (Italian Association for Cancer Research, AIRC; IG 20100, year 2017 to MP).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eV.Z. and M.V. performed study concept and design and writing of first draft of the manuscript; M.F. and F.N. performed molecular analyses; I.R. performed development of methodology and writing; S.C. and M.P. performed analysis and interpretation of data and revision of the paper; G.V.T. and G.O. provided technical support and statistical analysis; L.D. and S.P. provided material support and revision of the paper. All authors read and approved the final paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement.\u003c/strong\u003e The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSanders EM Jr, LiVolsi VA, Brierley J, Shin J, Randolph GW (2007) An evidence-based review of poorly differentiated thyroid cancer. World J Surg 31:934-945. doi: 10.1007/s00268-007-9033-3.\u003c/li\u003e\n\u003cli\u003eIbrahimpasic T, Ghossein R, Carlson DL, Nixon I, Palmer FL, Shaha AR, Patel SG, Tuttle RM, Shah JP, Ganly I (2014) Outcomes in patients with poorly differentiated thyroid carcinoma. 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Cancer Lett 527:10-23. doi: 10.1016/j.canlet.2021.12.005.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"endocrine-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enpa","sideBox":"Learn more about [Endocrine Pathology](http://link.springer.com/journal/12022)","snPcode":"12022","submissionUrl":"https://submission.nature.com/new-submission/12022/3","title":"Endocrine Pathology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Poorly differentiated, thyroid, carcinoma, molecular, biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7112785/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7112785/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePoorly differentiated thyroid carcinoma (PDTC) is a rare thyroid cancer with aggressive clinical course and peculiar clinical/pathological characteristics but lacking effective therapeutic options, when surgery is not curative.\u003c/p\u003e\u003cp\u003eWe aimed at the molecular characterization of PDTC with a specific focus on the identification of potential therapeutic targets. A series of PDTC cases was selected from a multi-institutional network. Fifty-nine samples underwent wide targeted DNA and RNA next generation sequencing (NGS) testing and immunohistochemical analysis for mismatch repair (MMR) proteins. Gene fusion analysis was enriched by 25 additional samples.\u003c/p\u003e\u003cp\u003ePrevalence of MMR protein loss was 11.9%. The most prevalent mutations were in \u003cem\u003eNRAS\u003c/em\u003e (25%) and \u003cem\u003eTP53\u003c/em\u003e (25%), mutually exclusive each other. \u003cem\u003eTERT\u003c/em\u003e promoter (\u003cem\u003eTERTp\u003c/em\u003e) mutations were detected in 21.6% of cases. \u003cem\u003eNRAS\u003c/em\u003e-mutated cases were enriched for mutations in genes belonging to the same pathway. \u003cem\u003eTP53\u003c/em\u003e-mutated samples lacked \u003cem\u003eTERTp\u003c/em\u003e co-mutations, but were associated with mutations in \u003cem\u003ePTEN\u003c/em\u003e and in genes related to MMR system and/or loss of MMR proteins. \u003cem\u003eTERTp\u003c/em\u003e mutations were enriched (up to 32%) in a third group that lacked \u003cem\u003eNRAS\u003c/em\u003e or \u003cem\u003eTP53\u003c/em\u003e mutations. Four cases harbored gene fusions, including two cases harboring the \u003cem\u003eTBL1XR1-PIK3CA\u003c/em\u003e fusion that has never been reported in thyroid cancer, so far.\u003c/p\u003e\u003cp\u003eIn conclusion, PDTC may be genomically segregated in subgroups with specific molecular characteristics. Overall, targetable gene fusions have a prevalence of 7%. Moreover, 38% of cases are potential candidates for individualized target therapies since they harbor mutations/fusions in genes coding for potentially targetable tyrosine kinases and/or have defects in the MMR system.\u003c/p\u003e","manuscriptTitle":"High prevalence of potential molecular therapeutic targets in poorly differentiated thyroid carcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-28 11:06:33","doi":"10.21203/rs.3.rs-7112785/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-06T00:57:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-03T13:46:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-02T13:21:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-31T14:34:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"58790288504537758092674108524790792496","date":"2025-07-25T08:37:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84240964613717258585970981897799106734","date":"2025-07-23T09:17:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299582205092649064416643605483425939269","date":"2025-07-23T08:48:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-23T08:31:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-15T01:18:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-15T01:17:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Endocrine Pathology","date":"2025-07-13T10:43:37+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"endocrine-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"enpa","sideBox":"Learn more about [Endocrine Pathology](http://link.springer.com/journal/12022)","snPcode":"12022","submissionUrl":"https://submission.nature.com/new-submission/12022/3","title":"Endocrine Pathology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a120d758-f779-4e01-985e-a28de1f638b8","owner":[],"postedDate":"July 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-27T16:31:15+00:00","versionOfRecord":{"articleIdentity":"rs-7112785","link":"https://doi.org/10.1007/s12022-025-09883-y","journal":{"identity":"endocrine-pathology","isVorOnly":false,"title":"Endocrine Pathology"},"publishedOn":"2025-10-22 16:16:54","publishedOnDateReadable":"October 22nd, 2025"},"versionCreatedAt":"2025-07-28 11:06:33","video":"","vorDoi":"10.1007/s12022-025-09883-y","vorDoiUrl":"https://doi.org/10.1007/s12022-025-09883-y","workflowStages":[]},"version":"v1","identity":"rs-7112785","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7112785","identity":"rs-7112785","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}