Comprehensive genomic profiling of Taiwanese triple negative breast cancers with medium- and large-sized sequencing panels: a comparative study of actionable genes

Comprehensive genomic profiling of Taiwanese triple negative breast cancers with medium- and large-sized sequencing panels: a comparative study of actionable genes | 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 Comprehensive genomic profiling of Taiwanese triple negative breast cancers with medium- and large-sized sequencing panels: a comparative study of actionable genes Chi-Cheng Huang, Yi-Chen Yeh, Yi-Fang Tsai, Yen-Shu Lin, Ta-Chung Chao, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4638838/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Comprehensive genomic profiling (CGP) is a molecular diagnostic tool with increasing use in cancer research and treatment. There are several commercialized CGP assays with variable targeted genes, however, how large a panel should be used for breast cancer remains undetermined. Methods Triple negative breast cancer (TNBC) patients from the VGH-TAYLOR study were initially assayed by a medium-sized CGP panel (Oncomine Comprehensive Panel, OCP, v3), and the remaining nucleic acid specimens were re-sequenced with a large-sized CGP panel (TruSight Oncology 500, TSO500). Molecular profiling between the two sequencing panels was compared and reported. Results A total of 108 breast cancers were successfully assayed using both platforms and 272 variants were reported at least once by OCP or TSO500. Variants reported were among actionable genes ( AKT1 , BRCA1/2 , PALB2 , ERBB2 , PIK3CA , PTEN ) and TP53 . Concordance rate between TSO500 and OCP was 34.6% and was enhanced to 58.9% after excluding polymorphisms, out-of-targeted region variants and those with low variant allele frequency (< 10%). Conclusion Only one-third of actionable mutations could be detected consistently between the medium- and the large-sized CGP panels using the default analytical pipelines, while extensive bioinformatics analyses improved variant calling consistency substantially. TSO500, the larger panel, detected more variants than OCP from the same set of actionable genes. comprehensive genomic profiling targeted sequencing triple negative breast cancer VGH-TAYLOR study Taiwanese breast cancer Figures Figure 1 Figure 2 Introduction Comprehensive genomic profiling (CGP) is a sophisticated molecular diagnostic tool, based on next-generation sequencing (NGS) technology, used in the field of cancer research and treatment. It involves the comprehensive analysis of an individual's cancerous cells to identify various genetic alterations and mutations within the tumor [ 1 ]. Results from CGP guide oncologists to make decisions about treatment options and select targeted therapies tailored to the specific genetic alterations present within the tumor. CGP examines a broad panel of genes, allowing it to detect a wide range of genomic alterations. This includes point mutations, insertions/deletions (indels), copy number variations (CNVs), and gene fusions. CGP provides precise information about the genetic drivers of a patient's cancer, enabling personalized treatment plans. It can detect multiple genetic alterations in a single test, reducing the need for multiple individual tests. CGP is an application of NGS that specifically focuses on a detailed analysis of a cancer patient's genetic profile. It provides a broad overview of the genomic alterations in a tumor. Consequently, precision, efficiency and therapeutic guidance are potential advantages of CGP, which has been advocated for cancers with advanced-stages [ 2 – 5 ]. Triple-negative breast cancer (TNBC) is a specific subtype of breast cancer characterized by the absence of three deterministic receptors commonly found in other breast cancers: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC cells lack the expression of these three receptors and does not rely on them for growth. TNBC accounts for about 10–20% of all breast cancer cases. It is more commonly diagnosed in younger women, African American women, and those with a family history of breast cancer [ 6 ]. TNBC is known for its aggressive behavior and tends to grow and spread quickly. It is associated with a higher risk of recurrence and metastasis [ 7 ]. Treatment options for TNBC often involve chemotherapy, as endocrine therapies and anti-HER2 targeted therapies that work on ER, PR, or HER2 receptors are not effective due to their absence. The prognosis for TNBC varies depending on factors such as the diagnosed stage and response to treatment. Therefore, TNBC is aggressive in nature and is typically treated with chemotherapy due to the lack of targeted therapies based on receptor status. There is an unmet need to identify actionable targets for TNBC patients. Recent and ongoing research focusing on developing targeted therapies specifically for TNBC continues to improve treatment outcomes and broaden therapeutic options [ 8 – 9 ]. Biomarker-driven therapies for are becoming a reality with the advent of immune checkpoint inhibitor, poly-adenosine-diphosphate-ribose polymerase (PARP) inhibitor, selective PIK3CA and AKT inhibitors, and antibody-drug conjugate, which are corresponding to immune-enriched, DNA repair deficiency, PI3K/AKT/mTOR activated, and surface antigen over-expressed TNBC, respectively. Commercialized CGP assays may be beneficial, however which size panel should be employed to deliver the most optimal coverage of actionable genes for TNBC remains to be explored. There were some studies comparing distinct CGP platforms and resulting biomarkers, but seldom were conducted for TNBC [ 52 – 53 ]. In this study, we took advantage of the VGH-TAYLOR study which included a subgroup of TNBC patients [ 10 ]. TNBC patients were initially assayed by a medium-sized CGP panel, and the remaining specimens of nucleic acid were re-sequenced with a large-sized GCP panel. Molecular profiling between medium- and large-sized panels was compared. Both the Oncomine Comprehensive Assay v3 and the TruSight Oncology 500 panel are used worldwide, while there were very few direct comparison studies for breast cancer actionable genes in the literature. Materials and methods VGH-TAYLOR study The VGH-TAYLOR study was designed to understand the genetic profiling of different subtypes of breast cancer in Taiwan and define the molecular risk factors for breast cancer recurrence [10]. The prospective study was made up of diverse clinical scenarios of breast cancer, namely Group 1: planned to receive first-line surgery followed by adjuvant therapy (1A) or early relapse within 3 years (1B), Group 2 planned to receive first-line neoadjuvant therapy followed by surgery, and Group 3-I: de novo stage IV or recurrence beyond 3 years (3-II) [11-13]. In addition, a retrospective cohort with biobank samples from recurrent/metastatic breast cancers or non-pathological complete response (non-pCR) patients following neoadjuvant therapy was also included [14]. Enrolled subjects were treated according to contemporary guidelines with regular follow up. Regarding immunohistochemistry (IHC) testing, ER and PR were scored by percentage of nuclear labeling (0-100%). HER2 expression was scored using a 0 to 3+ membrane staining intensity score. Hormone receptor (HR) positivity was defined by either ER or PR with at least 1% of tumor cells exhibiting nuclear staining. HER2 over-expression was indicated by either IHC 3+ (positive) or 2+ (equivocal) with fluorescence in situ hybridization (FISH)-amplification [15]. Samples and nucleic acid preparation Formalin-fixed paraffin-embedded (FFPE) samples were collected after obtaining participants’ consent. At least 7 unstained tumor sections were retrieved with one for hematoxylin and eosin (H&E) staining and 6 unstained sections were prepared for nucleic acid extraction. H&E-stained slides were reviewed to ascertain the presence of adequate breast cancer cells (more than 70%). Paraffin was removed by xylene extraction and then by ethanol washes. Nucleic acid was extracted from 5 μm sections with the QIAmp DNA FFPE Tissue Kit or AllPrep DNA/RNA FFPE Kit (Qiagen, Valencia, CA, USA), while the quality control and concentration was checked and determined by the Qubit fluorimeter (Invitrogen, part of Thermo Fisher Scientific, Waltham, MA, USA), Qubit dsDNA HS (High Sensitivity) and Qubit dsDNA BR (Broad Range) Assay Kits (Thermo Fisher Scientific). GAPDH polymerase chain reaction (PCR) fragments were used to evaluate nucleic acid integration for downstream amplification and sequencing. In current study, treatment-naïve cancerous tissue was used for NGS. Oncomine Comprehensive Panel The Ion Torrent Oncomine Comprehensive Assay Panel v3 (OCP, Thermo Fisher Scientific) was used as the default CGP for the VGH-TAYLOR study, which enabled the detection of 161 cancer-related genes and the identification of single nucleotide variants (SNVs), CNVs, gene fusions and indels. 10 ng of DNA and RNA sample input was required. Libraries were generated followed the standard protocols and were multiplexed for templating on the Ion OneTouch 2 System and subsequently sequenced on the Ion GeneStudio S5 Prime System (Thermo Fisher Scientific) using the Ion 318 Chip Kit. Sequencing data were analyzed, aligned and annotated through Torrent Suite (Thermo Fisher Scientific, v5.10.0) and Ion Reporter (Thermo Fisher Scientific, v5.10) software with the default Coverage Analysis (v5.10.0.3), SampleID (v5.10.0.1) and VariantCaller (v5.10.0.18) plugin. Variants were further analyzed and interpreted for clinical actionability using the Oncomine Knowledgebase Reporter (Thermo Fisher Scientific) database. The coverage metrics indicated that the number of mapped reads ranged from 4 to 6 million, with a mean depth of approximately 1100 to 1600. TruSight Oncology 500 The TruSight Oncology 500 (TSO500, Illumina Inc., San Diego, CA, USA) was designed to identify known and emerging tumor biomarkers, using both DNA and RNA from tumor samples to identify key somatic variants underlying tumor progression, such as small DNA variants, fusions and splice variants. TSO500 delivered pan-cancer biomarkers aligned with key guidelines and clinical trials, including 523 genes for assessment of all DNA and RNA variant types, plus microsatellite instability (MSI), tumor mutational burden (TMB) and homologous recombination deficiency (HRD, optional). Libraries were prepared according to the manufacturer’s guidance from up to 80 ng DNA and 40 ng of RNA. Adapter ligation with unique molecular identifiers (UMIs) was performed with target fragments amplified and indexed. NGS was performed with a NextSeq 2000 sequencing system operated by the Department of Pathology and Laboratory Medicine of the Taipei Veterans General Hospital using the NextSeq 1000/2000 P2 Reagents (300 Cycles) v3. Data were analyzed with the TSO500 Local App v2.2 (Illumina), with VCF files further processed and annotated with the PierianDx software (Pierian, St. Louis, MO, USA). The read collapsing analysis step executes an algorithm that collapses sets of reads (known as families) with very similar genomic locations into representative sequences using UMI tags. Median exon fragment coverage across all exon bases ≥150. Benchmark comparisons Final reports from the medium-sized (OCP) and large-sized (TSO500) panels and accompanied TSV files were collected. Genes and variants reported as being actionable were the primary endpoints in the current study. Clinical actionability was defined by the joint consensus of AMP/ASCO/CAP published in 2017 [16]. Additional annotations for actionability and OncoPrinter visualization were carried out using the OncoKB database and ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) criteria [17-19]. By this definition, clinical actionability was categorized as Tier I, actionability indicated an alteration-drug match associated with improved outcome in clinical trials; Tier II, antitumor activity associated with the matched alteration-drug but lacks prospective outcome data and Tier III, the matched drug-alteration led to clinical benefit in another tumor type other than the tumor of interest. The limit of detection (LOD) was set to 5% for SNVs/indels and a VAF < 10% was considered a low VAF status. An average copy number ≥4 was interpreted as a gain (amplification) and <1 as a loss (deletion). Results Study population and targeted actionable genes A total of 108 TNBC patients from the VGH-TAYLOR study with adequate remaining nucleic acid (both DNA and RNA) were recalled. After explaining the purpose of this re-sequencing study, all participants signed informed consent form and their specimens were recruited and assayed with the large-sized CGP, TSO500 panel. There were 54 included in Group 1A, 6 included in Group 1B, 25 included in Group 2, 5 included in Group 3-I, 7 included in Group 3-II, and 11 biobank/retrospective cohort breast cancer samples. Early-stage breast cancer (Group IA and Group II) constituted the majority (73.1%, n=79) of the study population. Four patients initially classified as TNBC at the time of enrollment were then re-tested by FISH and found to be HER2-positive. Due to discrepancy in interrogated genes (523 versus 161 genes), only actionable genes listed by the ESCAT criteria for breast cancer were analyzed, namely Tier IA: ERBB2 amplification, BRCA1/2 germline mutation, and PIK3CA mutation, Tier 1C: NTRK translocation, Tier IIA: PTEN loss and ESR1 mutation, Tier IIB: AKT1 mutation, ERBB2 mutation, Tier IIIA: BRCA1/2 somatic mutation, MDM2 amplification and Tier IIIB: ERBB3 mutation [20]. Mutational landscape of actionable genes with TSO500 Figure 1 (top) shows the mutational landscape of ESCAT-defined actionable genes among Taiwanese TNBC patients interrogated with TSO500. Among 108 Taiwanese breast cancer patients (all were TNBC except 4 were HER2-positive breast cancers), PIK3CA was the most common actionable gene (39%, n=42), including fusion, amplification, copy number gain and point mutation, followed by BRCA2 including fusion, copy number gain, heterozygous loss, truncating and point mutation (24%, n=26). BRCA1 variants, including fusions, truncating, and point mutations were detected in 12% (n=13) of samples. ERBB2 amplification, copy number gain, in-frame and point mutations were identified in 13% (n=14) of the study population. It deserves notice that among three breast cancer samples with HER2 amplification reported by TSO500, two out of three coincided in the four clinically HER2-positive (over-expression) cases. PTEN mutations including hetero-/homozygous loss and truncating/in-frame/point mutations were reported in 15% (n=16) of breast cancer samples. Copy number gain and point mutations in ERBB3 were identified in 10% (n=11) of the samples, while ESR1 (2.8%, n=3, copy number gain/heterozygous loss and point mutation) and MDM2 variants (1.9%, n=2, amplification and heterozygous loss) were infrequently mutated in Taiwanese population. There were no NTRK translocations reported. Supplementary Table 1 summarizes actionable mutations among Taiwanese breast cancer patients assayed with TSO500 CGP. Mutational landscape of actionable genes with OCP Figure 1 (bottom) shows the mutational landscape of actionable genes reported by OCP. Compared with TSO500, OCP reported a higher number of ERBB2 variants (19% versus 13%), most of which came from higher proportion of missense mutations with unknown significance. Of the four clinical HER2-positive breast cancer samples, none reported HER2 alteration except another HER2-equivocal case was associated with an ERBB2 I665V missense mutation, which was a variant of uncertain significance (VUS). On the other hand, both the frequency of BRCA1 and BRCA2 variants were lower than those reported from TSO500 ( BRCA1 : 6% versus 12% and BRCA2 : 5% versus 24%). PIK3CA variants and PTEN mutations were also less frequent than with TSO500 (28% versus 39% and 6% versus 15%, respectively). No alterations were identified by OCP for ESR1 , MDM2 and ERBB3 . Supplementary Table 2 details actionable mutations reported with OCP. Comparisons of reported actionable variants between OCP and TSO500 For benchmark comparisons, we excluded the four HER2-positive samples and focused on tumor DNA sequence variants from actionable genes. We used amino acid change (protein coordinate), genomic and transcript-dependent cDNA coordinates to identify variants reported as least once from either TSO500, OCP or both (Table 1). Among 272 variants, 94 (34.6%) were identifiable by both platforms, consequently the concordance rate was slightly more than one-third based on original reports. In order to understand the mechanisms underpinning the high discordance between TSO500 and OCP, manual review of conflicting variants was conducted with all binary alignment map (BAM) files visualized through integrative genomic viewer (IGV), by an expert in precision oncology and bioinformatics (YCY, ref. 21). Table 1. Actionable variants (n=202) reported from both the TruSight Oncology 500 (TSO500) and Oncomine Comprehensive Assay Panel v3 (OCP). Gene Variant ESCAT Both platforms TSO500 only AKT1 E17K II-B 3 BRCA1 S405* III-A 1 R1203* III-A 1 S1286fs III-A 1 S632fs III-A 1 c.5470-1G>A III-A 1 G1350C III-A 1 M1783L III-A 2 N909S III-A 1 R1583K III-A 1 R762S III-A 1 S1389N III-A 1 V191I III-A 1 c.1A>G III-A 1 BRCA2 S521* III-A 1 E1571fs III-A 1 N2135fs III-A 1 C315S III-A 1 F2254Yfs*6 III-A 1 G2508S III-A 1 G2901D III-A 1 H523R III-A 1 I1929V III-A 4 N72S III-A 2 P3292L,V2109I III-A 1 R2108C III-A 5 R2842H III-A 1 V2109I III-A 1 V2151Ffs*17 III-A 1 V783A III-A 1 ERBB2 L811V,L839R II-B 1 L725S 1 P1140A 1 V743_M744insHV 1 Y742_A745dup 1 NTRK1 K167R 1 M530T 1 R190Q 1 R190W 1 NTRk3 D611E 2 PALB2 K353fs 1 A38G 1 D498Y 2 R825T 2 PIK3CA E542K I-A 3 E542K,E726K I-A 1 E542Q,H1047R I-A 1 E545K I-A 3 E545Q,H1047Y I-A 1 E726K 1 G1049R 1 H1047L I-A 2 H1047R I-A 9 N345I 1 Q546R 1 D350N 1 + D725N 1 ++ PTEN E150* II-A 1 E43fs II-A 1 P38fs II-A 1 R130* II-A 1 Q245* II-A 1 c.1026+1G>A II-A 1 V290Sfs*8 II-A 1 G127_G129del,G129E II-A 1 TP53 C176R IV-A 1 C242Afs IV-A 1 C275Y IV-A 1 E271* IV-A 1 E56Kfs IV-A 2 F109Sfs IV-A 1 G108Vfs IV-A 4 G245S IV-A 2 H179R IV-A 2 H179Y IV-A 1 H193P IV-A 1 H193R IV-A 1 H193Y IV-A 1 H214Qfs IV-A 1 K132N IV-A 1 L111Dfs,R196* IV-A 1 L111Ffs IV-A 1 L194H IV-A 1 L252Hfs IV-A 1 P151S IV-A 1 Q192* IV-A 1 R158Lfs IV-A 1 R175H IV-A 2 R196* IV-A 2 R248Q IV-A 4 R248W IV-A 1 R273H IV-A 4 R282W IV-A 1 R333Vfs IV-A 1 R342* IV-A 1 S149Pfs IV-A 1 S166* IV-A 1 S241F IV-A 1 T253Pfs IV-A 1 V147* IV-A 1 W146* IV-A 1 W53* IV-A 1 W91* IV-A 1 Y103Afs IV-A 1 Y107* IV-A 1 Y205D IV-A 1 c.560-2A>T IV-A 1 c.993+1G>A IV-A 1 c.994-2A>C IV-A 1 c.993+1G>A,526T>A IV-A 1 c.920-2A>G IV-A 1 c.993+1G>T IV-A 1 c.560-1G>A IV-A 1 c.919+1G>T IV-A 1 c.993+2T>G IV-A 1 c.993+1G>A IV-A 1 D281_K292del IV-A 1 E271Q IV-A 1 F113V IV-A 1 I251L IV-A 1 L265P IV-A 1 N131del IV-A 1 P190L IV-A 1 Q333E,R213* IV-A 1 R213* IV-A 4 T140_C141delinsS IV-A 1 V157_R158insL IV-A 1 + with additional H1047R noted by TSO500 and OCP ++ with additional E453Q and E545K noted by TSO500 and OCP Figure 2 shows the interpretation categories: 25 (9.2%) were in fact the same variants with different annotations, 34 (12.5%) were beyond the OCP targeted regions, 21 (7.7%) were benign polymorphisms called by OCP but filtered out by TSO500, 15 (5.5%) were discordant variants with low variant allele frequency (VAF < 10%) while TSO500 outperformed in 83 cases (30.5%, more details in Discussion section). After discarding out-of-targeted region variants, benign and low-VAF variants, the concordance rate approached sixty percent (119 out of 202 variants, 58.9%) and the large-sized panel, TSO500, detected more variants even for the same set of actionable genes (i.e., ESCAT-defined breast cancer actionable genes) and TP53 . It deserves notice that there were variants called by OCP but ignored by TSO500, which were proved to be homopolymer regions including variants in BRCA1 (n=2), BRCA2 (n=2), PALB2 (n=1) and TP53 (n=3) as well as misalignment from one case with PTEN and two with TP53 (data not shown). Discussion To achieve the goal of personalized and precision medicine, CGP has been recognized as a key tool that can potentially transform cancer risk prediction, detection, diagnosis, treatment, and monitoring. CGP can augment clinical decision making in the form of either In vitro diagnostic (IVD) or companion diagnostics (CDx), and most importantly, the continuous price reduction across small- to large-sized CGP panels has improved patient access [ 22 ]. Consequently, therapy assignment for newly-diagnosed breast cancers and monitoring of patients who are in treatment are expected to benefit from CGP. In this study we compare the performance of medium- to large-sized gene panels in a TNBC patient cohort. A total of 108 breast cancers previously assayed with the OCP v3 with sufficient nucleic acid left were re-sequenced with TSO500, a large-sized CGP panel. Nowadays there are plenty of commercial and in-house targeted sequencing panels for cancer research as well as for clinical application. In the project AACR GENIE which integrated genomic data from panels varying in size from approximately 50 to 500 genes, a core of 44 genes had been recognized across various platforms [ 23 ]. A large-scale basket study, the NCI-MATCH, adapted the Oncomine AmpliSeq panel (ThermoFisher Scientific) targeting 143 genes with more than four thousand variants annotated [ 24 – 26 ]. On the other hand, the MSI-IMPACT trial developed a customized and hybridization capture-based 468-gene panel, which was Clinical Laboratory Improvement Amendments (CLIA) compatible and was advocated for the potential of identifying variants with clinical significance [ 27 ]. Commercial products such as the FoundationOne CDx, ActOnco and TruSight Tumor 170 followed [ 28 – 30 ]. Tumor tissues from the VGH-TAYLOR study were sequenced with the OCP v3 assay, which was designed as a research use only (RUO) assay and detected thousands of variants across 161 cancer-relevant genes [ 31 ]. Types of mutations detected such as frameshift, missense, synonymous, SNV, Indel, and CNV observed in individual breast cancer patients were reported [ 11 ]. Contrary to the OCP v3, TSO500 assay interrogates 523 cancer-related genes as well as multi-gene biomarkers such as microsatellite instability (MSI), tumor mutational burden (TMB) and homologous recombination deficiency (HRD) [ 32 ]. Both platforms performed tumor-only sequencing, which meant that reflex germline testing might be needed if the differentiation of somatic from germline origin was needed, such as the case of PARP inhibition [ 33 – 34 ]. On the other hand, the Todai OncoPanel reimbursed in Japan did provide paired tumor-normal test [ 35 – 37 ]. The four HER2-positive breast cancers provided an opportunity to evaluate the correlation between clinical HER2-status and NGS-based ERBB2 CNV. None of these cases were reported as HER2-amplified by OCP while two out of three HER2-amplified cases reported by TSO500 coincided with the four clinically HER2-positive breast cancers (Figs. 1 , bracket). More HER2 gained breast cancers were identified by TSO500. As NTRK translocation was not listed as the targeted alteration of OCP, we did not compare the detectability of structure variants (CNV and fusion) further. Table 1 details the genes and variants reported from either OCP v3 or TSO500 when genomic, cDNA and protein coordinates were used for variant sorting. This subset represented the most actionable variants revealed by medium- and large-sized CGP. AKT1 is an intra-cellular kinase and is predominantly altered in breast and endometrium cancer. The AKT1 E17K is the most common alteration across various tumor types [ 38 – 39 ]. The oral competitive kinase domain inhibitor capivasertib (AZD5363) has been shown to inhibit AKT1 E17K-mutated breast cancer. The CAPItello-291 phase III trial demonstrated that capivasertib and fulvestrant combination therapy resulted in significantly longer progression-free survival than treatment with fulvestrant alone among HR-positive/HER2-negative advanced breast cancer patients whose disease had progressed during or after previous aromatase inhibitor therapy with or without a cyclin-dependent kinase (CDK) 4/6 inhibitor [ 40 ]. The three AKT1 E17K-mutant cases were identified by both panels (Table 1 ). There were two BRCA1 (S405* and R1203*) and one BRCA2 (S521*) truncating mutations; reflex germline testing should be proceeded if PARP inhibitior was considered for these patients [ 41 ]. The BRCA1 c.5470-1G > A SNP has been recognized as pathogenic by both the Breast Cancer Information Core (BIC) and Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). The BRCA2 S521* truncating mutation impairs nuclear localization of BRCA2, which is essential for normal BRCA2 function [ 42 ]. Despite common truncating and frameshift mutations (5 for BRCA1 and 3 for BRCA2 ) called by both panels, only TSO500 did reveal more suspicious variants (8 variants among 9 cases for BRCA1 and 13 variants among 21 subjects) while OCP was flawed by spurious mutations ( BRCA1 : S1180fs, T1376fs and BRCA2 : S538fs, T598fs, S973fs, E33*, T912fs, S3041fs, S3147fs). PALB2 K353fs is a truncating mutation in a tumor suppressor gene, and therefore is likely oncogenic. The phase II TBCRC 048 study also ascertained the predictive power of germline PALB2 mutation as high response rate (82%) was observed when olaparib, a PARP inhibitor, was used [ 43 ]. TSO500 identified 3 additional variants in 5 cases (Table 1 ) while OCP reported one false positive case with up to 4 variants (D1125fs, N368fs, S357fs and N342fs). In current study, no reflex germline testing was performed and the germline/somatic origin of such mutations remained unknown. One patient harbored two mutations in ERBB2 (L811V and L839R) and another with L725S mutation was recognized by both platforms, none of which were among the oncogenic mutations approved by FDA for the use of neratinib, a pan-HER kinase inhibitor that binds irreversibly to the ATP-kinase domain of HER2 inhibiting the downstream phosphorylation of AKT and MAPK [ 44 ]. TSO500 identified three additional ERBB2 mutations (P1140A, V743_M744insHV and Y742_A745dup). It deserved notice that TSO500 detected more complex mutations, i.e. Y742_A745dup and V743_M744insHV, both classified as VUS, than OCP. A couple of PIK3CA hotspot mutations have been identified from the SOLAR-1 trial for the usage of alpelisib, a selective PI3K-alpha inhibitor, namely C420R, E542K, E545A, E545D, E545G, E545K, Q546E, Q546R, H1047L, H1047R and H1047Y [ 45 ]. Our previous study also observed double mutations of PIK3CA among Taiwanese population [ 14 ]. Only four cases with E726K, G1049R, N345I and Q546R mutations were outside the hotspot region, while two cases with D350N or D725N were co-mutant with other hotspots, which were only reported by TSO500 (Table 1 ). Consequently, both platforms identified the same number of PIK3CA -altered breast cancers. On the other hand, selective PI3K-beta inhibitor, GSK2636771 and AZD8186, are ATP-competitors and have shown preclinical anti-tumor response and durability for PTEN loss (deficiency) solid tumors including TNBC [ 46 ]. The PTEN c.1026 + 1G > A SNP has been reported as clinically pathogenic at least twice (Invitae and ClinGen PTEN Variant Curation Expert Panel) with germline origin [ 47 – 48 ]. The remaining 5 consensual variants were truncating mutations; TSO500 identified two additional cases with PTEN mutations (G127_G129del and V290Sfs*8) and OCP called one inappropriate variant due to malalignment (c.386G > A). A plethora of TP53 alterations were identified by both OCP and TSO500. Despite not being currently druggable, TP53 may act as an independent prognostic factor for early and advanced-stage cancer with a wide range of mutational frequency [ 49 ]. It has been argued that all TP53 mutations from tumor-only sequencing are somatic, and rarely representative of the germline Li-Fraumeni syndrome [ 41 ]. TSO500 identified more variants than OCP, while the latter reported three cases with V73fs in homopolymer region and one case with mal-aligned V73fs mutation, both of which were fictitious. Figure 2 shows 272 variants identified among actionable genes and TP53 from at least one panel. Interestingly, the concordance rate was low at slightly more than one-third (34.6%). With extensive bioinformatics analyses and manual curation, three-fifths of concordance (58.9% of 202 variants) was achieved after exclusion of unfiltered polymorphisms, low VAF variants and those beyond the targeted scope of OCP. An example of such analysis is given in Supplementary Fig. 1. Table 1 also highlights missed opportunities by OCP as an additional 62 variants were revealed by TSO500. Fundamental discrepancy in sequencing technology may provide some explanation. The amplicon-based OCP used PCR amplification of target regions while the hybrid capture-based TSO500 used hybridization with biotinylated probes to capture target regions. Inherited methodology indicates that PCR amplification can introduce biases and artifacts, potentially affecting the accuracy of the results. Among inconsistent variants, some were identical after manual inspections, further indicating the necessity of analytical abilities and domain knowledge in genomic nomenclature [ 50 ]. Despite being one of the pioneers directly comparing two commercialized targeted panels, there were some limitations of the study. First, sequencing was not conducted concurrently, and the 1–2 years of lag of TSO500 analysis following OCP might introduce some bias from nucleic acid degradation, despite all samples being stored under temperature-controlled conditions. Second, variants called by each panel were considered as they were based on the standard or formal algorithm of each platform (Ion Reporter/Oncomine Knowledgebase Reporter for OCP and PierianDx for TSO500), which limited the comparability between distinct platforms. For unbiased comparison, the same aligner, caller and annotator should be applied. However, BED files were unavailable from manufacturers to confirm the jointly interrogated regions. On the other hand, all commercial CGP solutions are under regulation as either laboratory developed tests (LDTs) or in vitro diagnostics (IVDs), and practically these pre-set algorithms should not be modified arbitrarily to enhance reproducibility. Despite this, we were able to conduct an exhaustive bioinformatic analysis from BAM files to dissect the conflicting results from the same samples. Third, NTRK is not within the targeted fusion genes of OCP and therefore a comparison with TSO500 is not possible. Moreover, NTRK sequence variants, amplifications or fusions are not actionable for breast cancer. As larotrectinib and entrectinib are approved in many countries, the importance of tumor-agnostic marker NTRK fusion cannot be overemphasized, and its detection ability should be incorporated into CGP for breast cancer [ 51 ]. In conclusion, this study compared the yield of actionable mutations between two CGP commercial assays that vary in size and found that three-fifths could be detected by both platforms. TSO500, the larger panel, detected more variants than OCP even from the same set of ESCAT-defined actionable genes and TP53 . On the other hand, a proportion of inconsistent variants could be manually curated and were identical with aliasing coordinates or starting positions. Finally, there were variants detectable only by TSO500, indicating potential and fundamental differences in sequencing technology, bioinformatic algorithms and variant filtering. The value of a large-sized panel in clinical usage is ascertained. Given the experience from this study, the updated Oncomine Comprehensive Assay Plus with more than 500 genes profiled are anticipated in future studies. Declarations Acknowledgement he authors wound like to thank the Taiwan Clinical Oncology Research Foundation, Melissa Lee Cancer Foundation, and Dr. Morris Chang for their kind assistance during the study. Ethical Approval The entire study protocol has been reviewed and approved by the Institute Review Board of Taipei Veterans General Hospital (access number: 2021-01-007B). Informed consent was obtained with permission signed before enrollment for all participants. Funding This work was supported in part by VGH-TPE (grant numbers: V110E-005-3, V111E-006-3, V112E-004-3 and V112C-013) and National Science and Technology Council (grant number: NSTC 111-2314-B-075-063-MY3). Availability of data and materials The datasets used and analyzed during the current study are available from the corresponding author (LMT) on reasonable request. References Huang CC, Yeh YC, Ho HL, Liu CY, Tsai YF, Tseng LM. Comprehensive genomic profiling of Taiwanese patients with breast cancer using a novel targeted panel: Preliminary analyses from a prospective triple-negative cohort. J Clin Oncol. 2023;41:e12553–12553. Wang L, Zhai Q, Lu Q, Lee K, Zheng Q, Hong R, Wang S. Clinical genomic profiling to identify actionable alterations for very early relapsed triple-negative breast cancer patients in the Chinese population. Ann Med. 2021;53:1358–69. 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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-4638838","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":325669291,"identity":"c525271f-8df7-41ea-adbc-d949c8d1fbcd","order_by":0,"name":"Chi-Cheng Huang","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chi-Cheng","middleName":"","lastName":"Huang","suffix":""},{"id":325669292,"identity":"cce0a8a3-f633-4e80-9d1a-264b58e751e7","order_by":1,"name":"Yi-Chen Yeh","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Chen","middleName":"","lastName":"Yeh","suffix":""},{"id":325669293,"identity":"6c40ea48-df7d-4d1e-a6f6-0451bd0a8108","order_by":2,"name":"Yi-Fang Tsai","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Fang","middleName":"","lastName":"Tsai","suffix":""},{"id":325669294,"identity":"e81b28ee-d3ce-4e7d-aa11-1e6b19bfc816","order_by":3,"name":"Yen-Shu Lin","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yen-Shu","middleName":"","lastName":"Lin","suffix":""},{"id":325669295,"identity":"dd9fdbbc-cb9c-4e15-83ec-09303d742d70","order_by":4,"name":"Ta-Chung Chao","email":"","orcid":"","institution":"National Yang Ming Chiao Tung University","correspondingAuthor":false,"prefix":"","firstName":"Ta-Chung","middleName":"","lastName":"Chao","suffix":""},{"id":325669296,"identity":"58c3dd49-8e45-4e57-96ea-84b9cd1a4d22","order_by":5,"name":"Chun-Yu Liu","email":"","orcid":"","institution":"National Yang Ming Chiao Tung University","correspondingAuthor":false,"prefix":"","firstName":"Chun-Yu","middleName":"","lastName":"Liu","suffix":""},{"id":325669297,"identity":"a01d5cec-ffbf-435d-a2ab-114158babc1d","order_by":6,"name":"Hsiang-Ling Ho","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hsiang-Ling","middleName":"","lastName":"Ho","suffix":""},{"id":325669298,"identity":"c1c201d5-5b1d-41ef-888f-daf1b9bba24e","order_by":7,"name":"Ling-Ming Tseng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYBACPigtZ3+8AUgZWBDWwsbADKaNGc4cAGmRIF5LYsONBBBNjBax84c/fNxRa8w48/nVDT8KJBj427sT8GuRTmaTnHnmuByzdE7ZzR6gwyTOnN1AUAszb9sxYzbpnLQbPEAtBhK5BLUwf/7bdiyxR/JM2s0/RGphkGZsq0mcIcF+7DaxtphJ9rYdMDbgyWG7LWMgwUPQL/zSiY8//GyrkzNgP/7s5ps/NnL87b34tUDBYSDmMQCxeIhRDgJ1QMz+gFjVo2AUjIJRMMIAAJQWQ3oBZroEAAAAAElFTkSuQmCC","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Ling-Ming","middleName":"","lastName":"Tseng","suffix":""}],"badges":[],"createdAt":"2024-06-25 22:32:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4638838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4638838/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60634249,"identity":"96222d75-64b5-493a-9851-c610a594471d","added_by":"auto","created_at":"2024-07-19 01:45:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":269355,"visible":true,"origin":"","legend":"\u003cp\u003eMutational landscape of 108 Taiwanese breast cancer patients assayed with the TruSight Oncology 500 (TSO500, top) and the Oncomine Comprehensive Assay Panel v3 (OCP, Oncomine Comprehensive Assay Panel v3 (OCP), bottom) for actionable genes (HER2: human epidermal growth factor receptor II, ER: estrogen receptor, PR: progesterone receptor). The bracket indicates four clinically HER2-positive breast cancers.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4638838/v1/3f17fc6f8d5783d67973c704.png"},{"id":60634248,"identity":"26a0344b-9102-48b2-91d2-0b75ff939074","added_by":"auto","created_at":"2024-07-19 01:45:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":44027,"visible":true,"origin":"","legend":"\u003cp\u003eInterpretation categories of 272 variants called at least once by either TSO500, OCP or both (TSO500: TruSight Oncology 500, OCP: Oncomine Comprehensive Assay Panel v3, VAF: variant allele frequency).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4638838/v1/4063c5a107adf9e504b64cc3.png"},{"id":65838257,"identity":"42ba1c5a-d178-436c-a16b-10afaf4a8d50","added_by":"auto","created_at":"2024-10-03 11:17:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1017571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4638838/v1/5655ef13-29eb-4617-8498-39127cc1b5e5.pdf"},{"id":60634247,"identity":"f9670664-4742-4426-ba2c-844978230fa5","added_by":"auto","created_at":"2024-07-19 01:45:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20088,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4638838/v1/9d264b2d2c5150028b60ddb0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive genomic profiling of Taiwanese triple negative breast cancers with medium- and large-sized sequencing panels: a comparative study of actionable genes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eComprehensive genomic profiling (CGP) is a sophisticated molecular diagnostic tool, based on next-generation sequencing (NGS) technology, used in the field of cancer research and treatment. It involves the comprehensive analysis of an individual's cancerous cells to identify various genetic alterations and mutations within the tumor [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Results from CGP guide oncologists to make decisions about treatment options and select targeted therapies tailored to the specific genetic alterations present within the tumor. CGP examines a broad panel of genes, allowing it to detect a wide range of genomic alterations. This includes point mutations, insertions/deletions (indels), copy number variations (CNVs), and gene fusions. CGP provides precise information about the genetic drivers of a patient's cancer, enabling personalized treatment plans. It can detect multiple genetic alterations in a single test, reducing the need for multiple individual tests. CGP is an application of NGS that specifically focuses on a detailed analysis of a cancer patient's genetic profile. It provides a broad overview of the genomic alterations in a tumor. Consequently, precision, efficiency and therapeutic guidance are potential advantages of CGP, which has been advocated for cancers with advanced-stages [\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTriple-negative breast cancer (TNBC) is a specific subtype of breast cancer characterized by the absence of three deterministic receptors commonly found in other breast cancers: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). TNBC cells lack the expression of these three receptors and does not rely on them for growth. TNBC accounts for about 10\u0026ndash;20% of all breast cancer cases. It is more commonly diagnosed in younger women, African American women, and those with a family history of breast cancer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. TNBC is known for its aggressive behavior and tends to grow and spread quickly. It is associated with a higher risk of recurrence and metastasis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Treatment options for TNBC often involve chemotherapy, as endocrine therapies and anti-HER2 targeted therapies that work on ER, PR, or HER2 receptors are not effective due to their absence. The prognosis for TNBC varies depending on factors such as the diagnosed stage and response to treatment. Therefore, TNBC is aggressive in nature and is typically treated with chemotherapy due to the lack of targeted therapies based on receptor status. There is an unmet need to identify actionable targets for TNBC patients.\u003c/p\u003e \u003cp\u003eRecent and ongoing research focusing on developing targeted therapies specifically for TNBC continues to improve treatment outcomes and broaden therapeutic options [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Biomarker-driven therapies for are becoming a reality with the advent of immune checkpoint inhibitor, poly-adenosine-diphosphate-ribose polymerase (PARP) inhibitor, selective PIK3CA and AKT inhibitors, and antibody-drug conjugate, which are corresponding to immune-enriched, DNA repair deficiency, PI3K/AKT/mTOR activated, and surface antigen over-expressed TNBC, respectively. Commercialized CGP assays may be beneficial, however which size panel should be employed to deliver the most optimal coverage of actionable genes for TNBC remains to be explored.\u003c/p\u003e \u003cp\u003eThere were some studies comparing distinct CGP platforms and resulting biomarkers, but seldom were conducted for TNBC [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In this study, we took advantage of the VGH-TAYLOR study which included a subgroup of TNBC patients [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. TNBC patients were initially assayed by a medium-sized CGP panel, and the remaining specimens of nucleic acid were re-sequenced with a large-sized GCP panel. Molecular profiling between medium- and large-sized panels was compared. Both the Oncomine Comprehensive Assay v3 and the TruSight Oncology 500 panel are used worldwide, while there were very few direct comparison studies for breast cancer actionable genes in the literature.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eVGH-TAYLOR study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe VGH-TAYLOR study was designed to understand the genetic profiling of different subtypes of breast cancer in Taiwan and define the molecular risk factors for breast cancer recurrence [10]. The prospective study was made up of diverse clinical scenarios of breast cancer, namely Group 1: planned to receive first-line surgery followed by adjuvant therapy (1A) or early relapse within 3 years (1B), Group 2 planned to receive first-line neoadjuvant therapy followed by surgery, and Group 3-I: de novo stage IV or recurrence beyond 3 years (3-II) [11-13]. In addition, a retrospective cohort with biobank samples from recurrent/metastatic breast cancers or non-pathological complete response (non-pCR) patients following neoadjuvant therapy was also included [14].\u003c/p\u003e\n\n\u003cp\u003eEnrolled subjects were treated according to contemporary guidelines with regular follow up. Regarding immunohistochemistry (IHC) testing, ER and PR were scored by percentage of nuclear labeling (0-100%). HER2 expression was scored using a 0 to 3+ membrane staining intensity score. Hormone receptor (HR) positivity was defined by either ER or PR with at least 1% of tumor cells exhibiting nuclear staining. HER2 over-expression was indicated by either IHC 3+ (positive) or 2+ (equivocal) with fluorescence in situ hybridization (FISH)-amplification [15].\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eSamples and nucleic acid preparation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFormalin-fixed paraffin-embedded (FFPE) samples were collected after obtaining participants\u0026rsquo; consent. At least 7 unstained tumor sections were retrieved with one for hematoxylin and eosin (H\u0026amp;E) staining and 6 unstained sections were prepared for nucleic acid extraction. H\u0026amp;E-stained slides were reviewed to ascertain the presence of adequate breast cancer cells (more than 70%).\u003c/p\u003e\n\n\u003cp\u003eParaffin was removed by xylene extraction and then by ethanol washes. Nucleic acid was extracted from 5 \u0026mu;m sections with the QIAmp DNA FFPE Tissue Kit or AllPrep DNA/RNA FFPE Kit (Qiagen, Valencia, CA, USA), while the quality control and concentration was checked and determined by the Qubit fluorimeter (Invitrogen, part of Thermo Fisher Scientific, Waltham, MA, USA), Qubit dsDNA HS (High Sensitivity) and Qubit dsDNA BR (Broad Range) Assay Kits (Thermo Fisher Scientific). GAPDH polymerase chain reaction (PCR) fragments were used to evaluate nucleic acid integration for downstream amplification and sequencing. In current study, treatment-na\u0026iuml;ve cancerous tissue was used for NGS.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eOncomine Comprehensive Panel \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Ion Torrent Oncomine Comprehensive Assay Panel v3 (OCP, Thermo Fisher Scientific) was used as the default CGP for the VGH-TAYLOR study, which enabled the detection of 161 cancer-related genes and the identification of single nucleotide variants (SNVs), CNVs, gene fusions and indels. 10 ng of DNA and RNA sample input was required. Libraries were generated followed the standard protocols and were multiplexed for templating on the Ion OneTouch 2 System and subsequently sequenced on the Ion GeneStudio S5 Prime System (Thermo Fisher Scientific) using the Ion 318 Chip Kit. Sequencing data were analyzed, aligned and annotated through Torrent Suite (Thermo Fisher Scientific, v5.10.0) and Ion Reporter (Thermo Fisher Scientific, v5.10) software with the default Coverage Analysis (v5.10.0.3), SampleID (v5.10.0.1) and VariantCaller (v5.10.0.18) plugin. Variants were further analyzed and interpreted for clinical actionability using the Oncomine Knowledgebase Reporter (Thermo Fisher Scientific) database. The coverage metrics indicated that the number of mapped reads ranged from 4 to 6 million, with a mean depth of approximately 1100 to 1600.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eTruSight Oncology 500\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe TruSight Oncology 500 (TSO500, Illumina Inc., San Diego, CA, USA) was designed to identify known and emerging tumor biomarkers, using both DNA and RNA from tumor samples to identify key somatic variants underlying tumor progression, such as small DNA variants, fusions and splice variants. TSO500 delivered pan-cancer biomarkers aligned with key guidelines and clinical trials, including 523 genes for assessment of all DNA and RNA variant types, plus microsatellite instability (MSI), tumor mutational burden (TMB) and homologous recombination deficiency (HRD, optional).\u003c/p\u003e\n\n\u003cp\u003eLibraries were prepared according to the manufacturer\u0026rsquo;s guidance from up to 80 ng DNA and 40 ng of RNA. Adapter ligation with unique molecular identifiers (UMIs) was performed with target fragments amplified and indexed. NGS was performed with a NextSeq 2000 sequencing system operated by the Department of Pathology and Laboratory Medicine of the Taipei Veterans General Hospital using the NextSeq 1000/2000 P2 Reagents (300 Cycles) v3. Data were analyzed with the TSO500 Local App v2.2 (Illumina), with VCF files further processed and annotated with the PierianDx software (Pierian, St. Louis, MO, USA). The read collapsing analysis step executes an algorithm that collapses sets of reads (known as families) with very similar genomic locations into representative sequences using UMI tags. Median exon fragment coverage across all exon bases \u0026ge;150.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eBenchmark comparisons\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinal reports from the medium-sized (OCP) and large-sized (TSO500) panels and accompanied TSV files were collected. Genes and variants reported as being actionable were the primary endpoints in the current study. Clinical actionability was defined by the joint consensus of AMP/ASCO/CAP published in 2017 [16]. Additional annotations for actionability and OncoPrinter visualization were carried out using the OncoKB database and ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) criteria [17-19]. By this definition, clinical actionability was categorized as Tier I, actionability indicated an alteration-drug match associated with improved outcome in clinical trials; Tier II, antitumor activity associated with the matched alteration-drug but lacks prospective outcome data and Tier III, the matched drug-alteration led to clinical benefit in another tumor type other than the tumor of interest. The limit of detection (LOD) was set to 5% for SNVs/indels and a VAF\u003cu\u003e\u0026lt;\u003c/u\u003e10% was considered a low VAF status. An average copy number \u0026ge;4 was interpreted as a gain (amplification) and \u0026lt;1 as a loss (deletion).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eStudy population and targeted actionable genes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 108 TNBC patients from the VGH-TAYLOR study with adequate remaining nucleic acid (both DNA and RNA) were recalled. After explaining the purpose of this re-sequencing study, all participants signed informed consent form and their specimens were recruited and assayed with the large-sized CGP, TSO500 panel. There were 54 included in Group 1A, 6 included in Group 1B, 25 included in Group 2, 5 included in Group 3-I, 7 included in Group 3-II, and 11 biobank/retrospective cohort breast cancer samples. Early-stage breast cancer (Group IA and Group II) constituted the majority (73.1%, n=79) of the study population. Four patients initially classified as TNBC at the time of enrollment were then re-tested by FISH and found to be HER2-positive.\u003c/p\u003e\n\u003cp\u003eDue to discrepancy in interrogated genes (523 versus 161 genes), only actionable genes listed by the ESCAT criteria for breast cancer were analyzed, namely Tier IA: \u003cem\u003eERBB2\u003c/em\u003e amplification, \u003cem\u003eBRCA1/2\u0026nbsp;\u003c/em\u003egermline mutation, and \u003cem\u003ePIK3CA\u0026nbsp;\u003c/em\u003emutation, Tier 1C: \u003cem\u003eNTRK\u003c/em\u003e translocation, Tier IIA: \u003cem\u003ePTEN\u003c/em\u003e loss and \u003cem\u003eESR1\u003c/em\u003e mutation, Tier IIB: \u003cem\u003eAKT1\u003c/em\u003e mutation, \u003cem\u003eERBB2\u003c/em\u003e mutation, Tier IIIA: \u003cem\u003eBRCA1/2\u003c/em\u003e somatic mutation, \u003cem\u003eMDM2\u003c/em\u003e amplification and Tier IIIB: \u003cem\u003eERBB3\u003c/em\u003e mutation [20].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMutational landscape of actionable genes with TSO500\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 (top) shows the mutational landscape of ESCAT-defined actionable genes among Taiwanese TNBC patients interrogated with TSO500. Among 108 Taiwanese breast cancer patients (all were TNBC except 4 were HER2-positive breast cancers), \u003cem\u003ePIK3CA\u003c/em\u003e was the most common actionable gene (39%, n=42), including fusion, amplification, copy number gain and point mutation, followed by \u003cem\u003eBRCA2\u003c/em\u003e including fusion, copy number gain, heterozygous loss, truncating and point mutation (24%, n=26). \u003cem\u003eBRCA1\u003c/em\u003e variants, including fusions, truncating, and point mutations were detected in 12% (n=13) of samples. \u003cem\u003eERBB2\u0026nbsp;\u003c/em\u003eamplification, copy number gain, in-frame and point mutations were identified in 13% (n=14) of the study population. It deserves notice that among three breast cancer samples with HER2 amplification reported by TSO500, two out of three coincided in the four clinically HER2-positive (over-expression) cases.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePTEN\u0026nbsp;\u003c/em\u003emutations including hetero-/homozygous loss and truncating/in-frame/point mutations were reported in 15% (n=16) of breast cancer samples. Copy number gain and point mutations in \u003cem\u003eERBB3\u0026nbsp;\u003c/em\u003ewere identified in 10% (n=11) of the samples, while \u003cem\u003eESR1\u003c/em\u003e (2.8%, n=3, copy number gain/heterozygous loss and point mutation) and \u003cem\u003eMDM2\u003c/em\u003e variants (1.9%, n=2, amplification and heterozygous loss) were infrequently mutated in Taiwanese population. There were no \u003cem\u003eNTRK\u003c/em\u003e translocations reported. Supplementary Table 1 summarizes actionable mutations among Taiwanese breast cancer patients assayed with TSO500 CGP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMutational landscape of actionable genes with OCP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 (bottom) shows the mutational landscape of actionable genes reported by OCP. Compared with TSO500, OCP reported a higher number of \u003cem\u003eERBB2\u003c/em\u003e variants (19% versus 13%), most of which came from higher proportion of missense mutations with unknown significance. Of the four clinical HER2-positive breast cancer samples, none reported HER2 alteration except another HER2-equivocal case was associated with an \u003cem\u003eERBB2\u003c/em\u003e I665V missense mutation, which was a variant of uncertain significance (VUS). On the other hand, both the frequency of \u003cem\u003eBRCA1\u003c/em\u003e and \u003cem\u003eBRCA2\u003c/em\u003e variants were lower than those reported from TSO500 (\u003cem\u003eBRCA1\u003c/em\u003e: 6% versus 12% and \u003cem\u003eBRCA2\u003c/em\u003e: 5% versus 24%). \u003cem\u003ePIK3CA\u003c/em\u003e variants and \u003cem\u003ePTEN\u0026nbsp;\u003c/em\u003emutations\u003cem\u003e\u0026nbsp;\u003c/em\u003ewere also less frequent than with TSO500 (28% versus 39% and 6% versus 15%, respectively). No alterations were identified by OCP for \u003cem\u003eESR1\u003c/em\u003e, \u003cem\u003eMDM2\u003c/em\u003e and \u003cem\u003eERBB3\u003c/em\u003e. Supplementary Table 2 details actionable mutations reported with OCP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparisons of reported actionable variants between OCP and TSO500\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor benchmark comparisons, we excluded the four HER2-positive samples and focused on tumor DNA sequence variants from actionable genes. We used amino acid change (protein coordinate), genomic and transcript-dependent cDNA coordinates to identify variants reported as least once from either TSO500, OCP or both (Table 1). Among 272 variants, 94 (34.6%) were identifiable by both platforms, consequently the concordance rate was slightly more than one-third based on original reports. In order to understand the mechanisms underpinning the high discordance between TSO500 and OCP, manual review of conflicting variants was conducted with all binary alignment map (BAM) files visualized through integrative genomic viewer (IGV), by an expert in precision oncology and bioinformatics (YCY, ref. 21).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eActionable variants (n=202) reported from both the TruSight Oncology 500 (TSO500) and Oncomine Comprehensive Assay Panel v3 (OCP).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"495\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eVariant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eESCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003eBoth platforms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003eTSO500 only\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAKT1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE17K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eII-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eS405*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eR1203*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eS1286fs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eS632fs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.5470-1G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eG1350C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eM1783L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eN909S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eR1583K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eR762S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eS1389N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eV191I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003ec.1A\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u003cem\u003eBRCA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eS521*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE1571fs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eN2135fs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eC315S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eF2254Yfs*6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eG2508S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eG2901D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH523R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eI1929V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eN72S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eP3292L,V2109I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR2108C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR2842H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eV2109I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eV2151Ffs*17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eV783A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u003cem\u003eERBB2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eL811V,L839R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eII-B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eL725S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eP1140A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.024193548387096%\" valign=\"top\"\u003e\n \u003cp\u003eV743_M744insHV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eY742_A745dup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u003cem\u003eNTRK1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eK167R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eM530T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR190Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR190W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u003cem\u003eNTRk3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eD611E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n 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\u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eD498Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR825T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u003cem\u003ePIK3CA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE542K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE542K,E726K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE542Q,H1047R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE545K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE545Q,H1047Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eE726K\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eG1049R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eH1047L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eH1047R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eI-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eN345I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eQ546R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eD350N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eD725N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003csup\u003e++\u003c/sup\u003e\u003c/p\u003e\n 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\u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003eQ245*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.1026+1G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eV290Sfs*8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.024193548387096%\" valign=\"top\"\u003e\n \u003cp\u003eG127_G129del,G129E\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eII-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.741935483870968%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u003cem\u003eTP53\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eC176R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eC242Afs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eC275Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n 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width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eF109Sfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eG108Vfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eG245S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH179R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH179Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH193P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH193R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH193Y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eH214Qfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eK132N\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eL111Dfs,R196*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eL111Ffs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eL194H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eL252Hfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eP151S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eQ192*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR158Lfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR175H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR196*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR248Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR248W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR273H\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR282W\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR333Vfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR342*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eS149Pfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eS166*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eS241F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eT253Pfs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eV147*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eW146*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eW53*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eW91*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eY103Afs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eY107*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eY205D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.560-2A\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.993+1G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.994-2A\u0026gt;C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.993+1G\u0026gt;A,526T\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.920-2A\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.993+1G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.560-1G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.919+1G\u0026gt;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.993+2T\u0026gt;G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\"\u003e\n \u003cp\u003ec.993+1G\u0026gt;A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eD281_K292del\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eE271Q\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eF113V\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eI251L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eL265P\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eN131del\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eP190L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eQ333E,R213*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eR213*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eT140_C141delinsS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.88888888888889%\" colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eV157_R158insL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\" valign=\"top\"\u003e\n \u003cp\u003eIV-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.77777777777778%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e+\u003c/sup\u003ewith additional H1047R noted by TSO500 and OCP\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e++\u003c/sup\u003ewith additional E453Q and E545K noted by TSO500 and OCP\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the interpretation categories: 25 (9.2%) were in fact the same variants with different annotations, 34 (12.5%) were beyond the OCP targeted regions, 21 (7.7%) were benign polymorphisms called by OCP but filtered out by TSO500, 15 (5.5%) were discordant variants with low variant allele frequency (VAF\u003cu\u003e\u0026lt;\u003c/u\u003e10%) while TSO500 outperformed in 83 cases (30.5%, more details in Discussion section). After discarding out-of-targeted region variants, benign and low-VAF variants, the concordance rate approached sixty percent (119 out of 202 variants, 58.9%) and the large-sized panel, TSO500, detected more variants even for the same set of actionable genes (i.e., ESCAT-defined breast cancer actionable genes) and \u003cem\u003eTP53\u003c/em\u003e. It deserves notice that there were variants called by OCP but ignored by TSO500, which were proved to be homopolymer regions including variants in \u003cem\u003eBRCA1\u003c/em\u003e (n=2), \u003cem\u003eBRCA2\u003c/em\u003e (n=2), \u003cem\u003ePALB2\u003c/em\u003e (n=1) and \u003cem\u003eTP53\u003c/em\u003e (n=3) as well as misalignment from one case with \u003cem\u003ePTEN\u003c/em\u003e and two with \u003cem\u003eTP53\u0026nbsp;\u003c/em\u003e(data not shown).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo achieve the goal of personalized and precision medicine, CGP has been recognized as a key tool that can potentially transform cancer risk prediction, detection, diagnosis, treatment, and monitoring. CGP can augment clinical decision making in the form of either In vitro diagnostic (IVD) or companion diagnostics (CDx), and most importantly, the continuous price reduction across small- to large-sized CGP panels has improved patient access [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Consequently, therapy assignment for newly-diagnosed breast cancers and monitoring of patients who are in treatment are expected to benefit from CGP. In this study we compare the performance of medium- to large-sized gene panels in a TNBC patient cohort.\u003c/p\u003e \u003cp\u003eA total of 108 breast cancers previously assayed with the OCP v3 with sufficient nucleic acid left were re-sequenced with TSO500, a large-sized CGP panel. Nowadays there are plenty of commercial and in-house targeted sequencing panels for cancer research as well as for clinical application. In the project AACR GENIE which integrated genomic data from panels varying in size from approximately 50 to 500 genes, a core of 44 genes had been recognized across various platforms [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. A large-scale basket study, the NCI-MATCH, adapted the Oncomine AmpliSeq panel (ThermoFisher Scientific) targeting 143 genes with more than four thousand variants annotated [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. On the other hand, the MSI-IMPACT trial developed a customized and hybridization capture-based 468-gene panel, which was Clinical Laboratory Improvement Amendments (CLIA) compatible and was advocated for the potential of identifying variants with clinical significance [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Commercial products such as the FoundationOne CDx, ActOnco and TruSight Tumor 170 followed [\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTumor tissues from the VGH-TAYLOR study were sequenced with the OCP v3 assay, which was designed as a research use only (RUO) assay and detected thousands of variants across 161 cancer-relevant genes [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Types of mutations detected such as frameshift, missense, synonymous, SNV, Indel, and CNV observed in individual breast cancer patients were reported [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Contrary to the OCP v3, TSO500 assay interrogates 523 cancer-related genes as well as multi-gene biomarkers such as microsatellite instability (MSI), tumor mutational burden (TMB) and homologous recombination deficiency (HRD) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Both platforms performed tumor-only sequencing, which meant that reflex germline testing might be needed if the differentiation of somatic from germline origin was needed, such as the case of PARP inhibition [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. On the other hand, the Todai OncoPanel reimbursed in Japan did provide paired tumor-normal test [\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe four HER2-positive breast cancers provided an opportunity to evaluate the correlation between clinical HER2-status and NGS-based \u003cem\u003eERBB2\u003c/em\u003e CNV. None of these cases were reported as HER2-amplified by OCP while two out of three HER2-amplified cases reported by TSO500 coincided with the four clinically HER2-positive breast cancers (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e1\u003c/span\u003e, bracket). More HER2 gained breast cancers were identified by TSO500. As \u003cem\u003eNTRK\u003c/em\u003e translocation was not listed as the targeted alteration of OCP, we did not compare the detectability of structure variants (CNV and fusion) further.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e details the genes and variants reported from either OCP v3 or TSO500 when genomic, cDNA and protein coordinates were used for variant sorting. This subset represented the most actionable variants revealed by medium- and large-sized CGP. \u003cem\u003eAKT1\u003c/em\u003e is an intra-cellular kinase and is predominantly altered in breast and endometrium cancer. The \u003cem\u003eAKT1\u003c/em\u003e E17K is the most common alteration across various tumor types [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The oral competitive kinase domain inhibitor capivasertib (AZD5363) has been shown to inhibit \u003cem\u003eAKT1\u003c/em\u003e E17K-mutated breast cancer. The CAPItello-291 phase III trial demonstrated that capivasertib and fulvestrant combination therapy resulted in significantly longer progression-free survival than treatment with fulvestrant alone among HR-positive/HER2-negative advanced breast cancer patients whose disease had progressed during or after previous aromatase inhibitor therapy with or without a cyclin-dependent kinase (CDK) 4/6 inhibitor [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The three \u003cem\u003eAKT1\u003c/em\u003e E17K-mutant cases were identified by both panels (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere were two \u003cem\u003eBRCA1\u003c/em\u003e (S405* and R1203*) and one \u003cem\u003eBRCA2\u003c/em\u003e (S521*) truncating mutations; reflex germline testing should be proceeded if PARP inhibitior was considered for these patients [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The \u003cem\u003eBRCA1\u003c/em\u003e c.5470-1G\u0026thinsp;\u0026gt;\u0026thinsp;A SNP has been recognized as pathogenic by both the Breast Cancer Information Core (BIC) and Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). The \u003cem\u003eBRCA2\u003c/em\u003e S521* truncating mutation impairs nuclear localization of BRCA2, which is essential for normal BRCA2 function [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Despite common truncating and frameshift mutations (5 for \u003cem\u003eBRCA1\u003c/em\u003e and 3 for \u003cem\u003eBRCA2\u003c/em\u003e) called by both panels, only TSO500 did reveal more suspicious variants (8 variants among 9 cases for \u003cem\u003eBRCA1\u003c/em\u003e and 13 variants among 21 subjects) while OCP was flawed by spurious mutations (\u003cem\u003eBRCA1\u003c/em\u003e: S1180fs, T1376fs and \u003cem\u003eBRCA2\u003c/em\u003e: S538fs, T598fs, S973fs, E33*, T912fs, S3041fs, S3147fs).\u003c/p\u003e \u003cp\u003e \u003cem\u003ePALB2\u003c/em\u003e K353fs is a truncating mutation in a tumor suppressor gene, and therefore is likely oncogenic. The phase II TBCRC 048 study also ascertained the predictive power of germline \u003cem\u003ePALB2\u003c/em\u003e mutation as high response rate (82%) was observed when olaparib, a PARP inhibitor, was used [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. TSO500 identified 3 additional variants in 5 cases (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) while OCP reported one false positive case with up to 4 variants (D1125fs, N368fs, S357fs and N342fs). In current study, no reflex germline testing was performed and the germline/somatic origin of such mutations remained unknown.\u003c/p\u003e \u003cp\u003eOne patient harbored two mutations in \u003cem\u003eERBB2\u003c/em\u003e (L811V and L839R) and another with L725S mutation was recognized by both platforms, none of which were among the oncogenic mutations approved by FDA for the use of neratinib, a pan-HER kinase inhibitor that binds irreversibly to the ATP-kinase domain of HER2 inhibiting the downstream phosphorylation of AKT and MAPK [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. TSO500 identified three additional \u003cem\u003eERBB2\u003c/em\u003e mutations (P1140A, V743_M744insHV and Y742_A745dup). It deserved notice that TSO500 detected more complex mutations, i.e. Y742_A745dup and V743_M744insHV, both classified as VUS, than OCP.\u003c/p\u003e \u003cp\u003eA couple of \u003cem\u003ePIK3CA\u003c/em\u003e hotspot mutations have been identified from the SOLAR-1 trial for the usage of alpelisib, a selective PI3K-alpha inhibitor, namely C420R, E542K, E545A, E545D, E545G, E545K, Q546E, Q546R, H1047L, H1047R and H1047Y [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our previous study also observed double mutations of \u003cem\u003ePIK3CA\u003c/em\u003e among Taiwanese population [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Only four cases with E726K, G1049R, N345I and Q546R mutations were outside the hotspot region, while two cases with D350N or D725N were co-mutant with other hotspots, which were only reported by TSO500 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Consequently, both platforms identified the same number of \u003cem\u003ePIK3CA\u003c/em\u003e-altered breast cancers.\u003c/p\u003e \u003cp\u003eOn the other hand, selective PI3K-beta inhibitor, GSK2636771 and AZD8186, are ATP-competitors and have shown preclinical anti-tumor response and durability for \u003cem\u003ePTEN\u003c/em\u003e loss (deficiency) solid tumors including TNBC [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The \u003cem\u003ePTEN\u003c/em\u003e c.1026\u0026thinsp;+\u0026thinsp;1G\u0026thinsp;\u0026gt;\u0026thinsp;A SNP has been reported as clinically pathogenic at least twice (Invitae and ClinGen PTEN Variant Curation Expert Panel) with germline origin [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The remaining 5 consensual variants were truncating mutations; TSO500 identified two additional cases with \u003cem\u003ePTEN\u003c/em\u003e mutations (G127_G129del and V290Sfs*8) and OCP called one inappropriate variant due to malalignment (c.386G\u0026thinsp;\u0026gt;\u0026thinsp;A).\u003c/p\u003e \u003cp\u003eA plethora of \u003cem\u003eTP53\u003c/em\u003e alterations were identified by both OCP and TSO500. Despite not being currently druggable, \u003cem\u003eTP53\u003c/em\u003e may act as an independent prognostic factor for early and advanced-stage cancer with a wide range of mutational frequency [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. It has been argued that all \u003cem\u003eTP53\u003c/em\u003e mutations from tumor-only sequencing are somatic, and rarely representative of the germline Li-Fraumeni syndrome [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. TSO500 identified more variants than OCP, while the latter reported three cases with V73fs in homopolymer region and one case with mal-aligned V73fs mutation, both of which were fictitious.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows 272 variants identified among actionable genes and \u003cem\u003eTP53\u003c/em\u003e from at least one panel. Interestingly, the concordance rate was low at slightly more than one-third (34.6%). With extensive bioinformatics analyses and manual curation, three-fifths of concordance (58.9% of 202 variants) was achieved after exclusion of unfiltered polymorphisms, low VAF variants and those beyond the targeted scope of OCP. An example of such analysis is given in Supplementary Fig.\u0026nbsp;1. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e also highlights missed opportunities by OCP as an additional 62 variants were revealed by TSO500. Fundamental discrepancy in sequencing technology may provide some explanation. The amplicon-based OCP used PCR amplification of target regions while the hybrid capture-based TSO500 used hybridization with biotinylated probes to capture target regions. Inherited methodology indicates that PCR amplification can introduce biases and artifacts, potentially affecting the accuracy of the results. Among inconsistent variants, some were identical after manual inspections, further indicating the necessity of analytical abilities and domain knowledge in genomic nomenclature [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite being one of the pioneers directly comparing two commercialized targeted panels, there were some limitations of the study. First, sequencing was not conducted concurrently, and the 1\u0026ndash;2 years of lag of TSO500 analysis following OCP might introduce some bias from nucleic acid degradation, despite all samples being stored under temperature-controlled conditions. Second, variants called by each panel were considered as they were based on the standard or formal algorithm of each platform (Ion Reporter/Oncomine Knowledgebase Reporter for OCP and PierianDx for TSO500), which limited the comparability between distinct platforms. For unbiased comparison, the same aligner, caller and annotator should be applied. However, BED files were unavailable from manufacturers to confirm the jointly interrogated regions. On the other hand, all commercial CGP solutions are under regulation as either laboratory developed tests (LDTs) or in vitro diagnostics (IVDs), and practically these pre-set algorithms should not be modified arbitrarily to enhance reproducibility. Despite this, we were able to conduct an exhaustive bioinformatic analysis from BAM files to dissect the conflicting results from the same samples. Third, \u003cem\u003eNTRK\u003c/em\u003e is not within the targeted fusion genes of OCP and therefore a comparison with TSO500 is not possible. Moreover, \u003cem\u003eNTRK\u003c/em\u003e sequence variants, amplifications or fusions are not actionable for breast cancer. As larotrectinib and entrectinib are approved in many countries, the importance of tumor-agnostic marker \u003cem\u003eNTRK\u003c/em\u003e fusion cannot be overemphasized, and its detection ability should be incorporated into CGP for breast cancer [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn conclusion, this study compared the yield of actionable mutations between two CGP commercial assays that vary in size and found that three-fifths could be detected by both platforms. TSO500, the larger panel, detected more variants than OCP even from the same set of ESCAT-defined actionable genes and \u003cem\u003eTP53\u003c/em\u003e. On the other hand, a proportion of inconsistent variants could be manually curated and were identical with aliasing coordinates or starting positions. Finally, there were variants detectable only by TSO500, indicating potential and fundamental differences in sequencing technology, bioinformatic algorithms and variant filtering. The value of a large-sized panel in clinical usage is ascertained. Given the experience from this study, the updated Oncomine Comprehensive Assay Plus with more than 500 genes profiled are anticipated in future studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ehe authors wound like to thank the Taiwan Clinical Oncology Research Foundation, Melissa Lee Cancer Foundation, and Dr. Morris Chang for their kind\u0026nbsp;assistance during the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe entire study protocol has been reviewed and approved by the Institute Review Board of Taipei Veterans General Hospital (access number: 2021-01-007B).\u0026nbsp;Informed consent was obtained with permission signed before enrollment for all participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported in part by VGH-TPE (grant numbers: V110E-005-3, V111E-006-3, V112E-004-3 and V112C-013) and National Science and Technology Council (grant number: NSTC 111-2314-B-075-063-MY3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author (LMT) on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHuang CC, Yeh YC, Ho HL, Liu CY, Tsai YF, Tseng LM. 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J Mol Diagn. 2022;24:600\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"comprehensive genomic profiling, targeted sequencing, triple negative breast cancer, VGH-TAYLOR study, Taiwanese breast cancer","lastPublishedDoi":"10.21203/rs.3.rs-4638838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4638838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eComprehensive genomic profiling (CGP) is a molecular diagnostic tool with increasing use in cancer research and treatment. There are several commercialized CGP assays with variable targeted genes, however, how large a panel should be used for breast cancer remains undetermined.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eTriple negative breast cancer (TNBC) patients from the VGH-TAYLOR study were initially assayed by a medium-sized CGP panel (Oncomine Comprehensive Panel, OCP, v3), and the remaining nucleic acid specimens were re-sequenced with a large-sized CGP panel (TruSight Oncology 500, TSO500). Molecular profiling between the two sequencing panels was compared and reported.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eA total of 108 breast cancers were successfully assayed using both platforms and 272 variants were reported at least once by OCP or TSO500. Variants reported were among actionable genes (\u003cem\u003eAKT1\u003c/em\u003e, \u003cem\u003eBRCA1/2\u003c/em\u003e, \u003cem\u003ePALB2\u003c/em\u003e, \u003cem\u003eERBB2\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003ePTEN\u003c/em\u003e) and \u003cem\u003eTP53\u003c/em\u003e. Concordance rate between TSO500 and OCP was 34.6% and was enhanced to 58.9% after excluding polymorphisms, out-of-targeted region variants and those with low variant allele frequency (\u0026lt;\u0026thinsp;10%).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOnly one-third of actionable mutations could be detected consistently between the medium- and the large-sized CGP panels using the default analytical pipelines, while extensive bioinformatics analyses improved variant calling consistency substantially. TSO500, the larger panel, detected more variants than OCP from the same set of actionable genes.\u003c/p\u003e","manuscriptTitle":"Comprehensive genomic profiling of Taiwanese triple negative breast cancers with medium- and large-sized sequencing panels: a comparative study of actionable genes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 01:45:16","doi":"10.21203/rs.3.rs-4638838/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"97f1b590-51b7-4ce2-b182-2a92fd261409","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-03T11:09:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-19 01:45:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4638838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4638838","identity":"rs-4638838","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}