Actionable Alterations for Molecular Targeted Therapy in Esophageal Cancer: An AACR Project GENIE Review

Actionable Alterations for Molecular Targeted Therapy in Esophageal Cancer: An AACR Project GENIE Review | 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 Actionable Alterations for Molecular Targeted Therapy in Esophageal Cancer: An AACR Project GENIE Review Hunter Stecko, Jad Daw, Robert E. Merritt, Desmond M. D’Souza, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6754101/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 Objective: Prognosis after curative intent resection for esophageal cancer remains low and only few targeted therapy options exist. We sought to analyze the full scope of potential actionable genomic alterations in esophageal cancer to better understand the potential for molecular targeted adjuvant therapy. Methods: We queried the American Association for Cancer Research (AACR) Project GENIE (v17.0) to identify clinically relevant, actionable genomic alterations in 3,605 patients with esophageal adenocarcinoma, gastroesophageal junction (GEJ) adenocarcinoma, or esophageal squamous cell carcinoma (ESCC). Additional data from The Cancer Genome Atlas (TCGA) were analyzed to assess protein overexpression of EGFR and HER2/ERBB2. Prevalence of targetable alterations was compared across histologic subtypes, and co-occurrence analyses using log-odds ratios with false discovery rate correction were performed on the most frequent alterations to identify potential resistance mechanisms. Results: Potentially small-molecule targetable alterations were identified in 64.3% of esophageal adenocarcinomas and 63.6% of GEJ adenocarcinomas, whereas 55.7% of ESCCs carried at least one actionable alteration. HER2/ERBB2 amplification was most common in adenocarcinomas, while PIK3CA mutations were most common in SCCs with no alteration unique present in a plurality of patients. Co-amplification of HER2 and CDK12 emerged as a potential mechanism of resistance to HER2-directed therapies. In addition, numerous genes implicated in PARP inhibitor or PIK3CA-targeted strategies were frequently altered across all histologies. Conclusions: Over half of patients in this large genomic dataset exhibited at least one actionable alteration, although distinct molecular profiles emerged by histology. These findings underscore the potential of using precision oncology to expand adjuvant therapeutic options. esophageal adenocarcinoma actionable targets adjuvant therapy Project GENIE coalteration Figures Figure 1 Figure 2 Figure 3 Introduction Esophageal cancer is the eighth most common type of cancer and sixth leading cause of cancer-related mortality globally. 1 While incidence of esophageal cancer in the United States has marginally declined since 2004, the case-fatality rate has remained high with a 5-year relative survival estimate of 21.6%. 2 Currently, the standard-of-care for locally advanced, resectable esophageal adenocarcinoma or gastroesophageal junction (GEJ) adenocarcinoma includes, or neoadjuvant chemoradiation supported by the CROSS trial 3 or perioperative cytotoxic chemotherapy and surgical resection under the FLOT 4 protocol. For squamous cell carcinoma, chemoradiotherapy with or without surgical resection remains the standard of care. 5 However, high distant recurrence rates of 27–50% following curative intent resection with current cytotoxic treatment regimens highlights the need for better systemic therapies. 6 Despite the rapid proliferation of targeted therapies against a variety of moieties across cancer types, 7 – 9 few targeted therapies have been studied or approved for use in esophageal cancer. 10 , 11 Clinical trials examining the efficacy of these targeted treatments have demonstrated mixed results. Trials of anti- HER2 targeted therapies failed to demonstrate an survival benefit for patients with esophageal adenocarcinoma. 12 In contrast, immune checkpoint inhibitor nivolumab demonstrated a distinct disease-free survival advantage when used as adjuvant therapy after resection (22.4 months vs 11.0 months for the placebo group; p < 0.001). 13 The expanded availability of next-generation sequencing (NGS) has allowed for rapid characterization of a large number of single nucleotide polymorphisms (SNPs) and other genomic alterations. 14 As of 2024, there are no less than 30 genomic loci for which specific targeted therapies are FDA approved. 15 However, there is limited understanding of the genomic landscape of esophageal cancer among non-Asian populations, in particular with respect to actionable targets with approved molecular therapies. The objectives of the present study were to assess the frequency of small-molecule targetable alterations in esophageal cancer subpopulations in a large international database, as well as examine the tumor biology for coalterations that could potentially impact targeted treatment response. Methods Data Source The AACR Project GENIE is a publicly accessible cancer registry of real-world clinico-genomic data assembled through data sharing between 19 leading cancer centers in the US, Europe and Korea. 16 The dataset comprises over 3,000 sequenced esophageal cancer samples. De-identified clinicodemographic and genomic data from GENIE v17.0 were accessed directly via cBioPortal. 17 – 19 A complete description of genomic profiling and AACR Project GENIE data dictionary is summarized within the Consortium’s data guide. 16 Cohort Selection Patients with a primary diagnosis of esophageal adenocarcinoma, cancer of the gastroesophageal junction (GEJ)/esophagogastric cancer and esophageal squamous cell carcinoma were identified in AACR Project GENIE (v17.0). 16 No patients were initially excluded (“GENIE cohort”). Institutions included in the GENIE consortium employed NGS to detect a variable set of genomic alterations in somatic tumor cells. For a subset of patients and genomic loci, variations in gene copy number and structure were also reported. A second cohort of patients was identified via The Cancer Genomic Atlas (TCGA). 20 De-identified clinicodemographic and genomic data were gathered. In addition, for select genomic loci, information regarding protein expression was gathered. Targeted Therapy Analysis OncoKB, a database containing information on actionable and clinically important genomic loci, was accessed to identify FDA-approved targeted therapies and their associated genomic treatment indications. 21 , 22 Additionally, clinical indications for 80 FDA approved small-molecule protein kinase inhibitors were reviewed. 8 A list of treatment indications was compiled and converted to Onco Query Language ( Supplemental Table 1 ). For those treatment indications that involved genomic alteration, the GENIE cohort was queried. For those treatment indications associated with protein overexpression ( HER2/ERBB2 and EGFR based therapies), the TCGA cohort was separately queried. “Overexpression” was defined as those patients with somatic tumor cells having protein concentrations of > 0.5 standard deviations above the mean of surrounding, non-malignant cells. Statistical Analyses Summary statistics (median, interquartile range (IQR)) and prevalence (%) were calculated for continuous and categorical variables (i.e. presence of genomic alteration), respectively. Chi-squared and Fisher’s exact test were used to determine genomic alteration prevalence differences between subpopulations. For coalteration analysis, log odds ratios were generated for the 48 most prevalent genomic alterations, and false discovery rate (q-value) was calculated. Genomic loci that were assessed in less than 50% of patients were excluded from coalteration analysis. Patients or samples without information regarding the analyzed attribute were excluded. Custom Python code was generated to compare coalteration differences between subpopulations. Results Prevalence of Treatment-Indicating Alterations Among the GENIE cohort, 3,605 patients with esophageal adenocarcinoma (n = 1,784), adenocarcinoma of the gastroesophageal junction (GEJ) (n = 1,462), or esophageal squamous cell carcinoma (n = 456) were identified. There were 97 patients with both esophageal adenocarcinoma and GEJ adenocarcinoma. Demographic characteristics of the GENIE cohort are noted in Table 1 . While the majority (79.7%) of patients with all histological patterns of esophageal cancer were male, only 53.3% of those with squamous cell carcinoma were male (n = 243) while 45.4% were female (n = 207). The median fraction of the genome altered in esophageal and GEJ adenocarcinoma was similar, with a median of 0.18 (IQR: 0.05–0.35) and 0.17 (0.04–0.34) respectively. Patients with squamous cell carcinoma had a higher fraction of the genome altered and mutation count than patients with adenocarcinoma histology (p < 0.001). A targetable mutation was detected in 64.3% (n = 1,147) of patients with esophageal adenocarcinoma, 63.6% of GEJ cancer (n = 930), and 55.7% (n = 254) of esophageal squamous cell carcinoma ( Supplemental Fig. 1 ). Table 1 The demographic makeup of the AACR Project GENIE esophageal malignancy cohort. Esophageal Adenocarcinoma GEJ/Esophagogastric Adenocarcinoma Esophageal Squamous Cell Carcinoma (n = 1784) (n = 1462) (n = 456) Sex Male 1518 (85.1%) 1191 (81.5%) 243 (53.3%) Female 251 (14.1%) 263 (18.0%) 207 (45.4%) Unknown 15 (0.8%) 8 (0.6%) 6 (1.3%) Primary Race White 1363 (76.4%) 1203 (82.3%) 277 (60.8%) Black 22 (1.2%) 31 (2.1%) 29 (6.4%) Asian 27 (1.5%) 49 (3.4%) 55 (12.1%) Other/Unknown 372 (20.9%) 179 (12.2%) 95 (20.8%) Ethnicity Non-Spanish/Non-Hispanic 1296 (72.6%) 1161 (79.4%) 325 (71.3%) Spanish/Hispanic 59 (3.3%) 103 (7.1%) 24 (5.3%) Unknown 429 (24.0%) 198 (13.5%) 107 (23.5%) Fraction Genome Altered 0.18 (0.05–0.35) 0.17 (0.04–0.34) 0.28 (0.09–0.48) Mutation Count 7 (4–11) 7 (4–11) 9 (5–12) Targetable Alteration 1147 (64.3%) 930 (63.6%) 254 (55.7%) Mutation 775 (41.4%) 604 (39.2%) 219 (47.8%) Amplification 126 (6.7%) 121 (7.9%) 5 (1.1%) Structural Variant 18 (1.0%) 24 (1.6%) 1 (0.2%) Deletion 7 (0.4%) 13 (0.8%) 1 (0.2%) Multiple 221 (11.8%) 168 (10.9%) 28 (6.1%) The most common small-molecule targetable alteration for adenocarcinoma was HER2/ERBB2 amplification (17.9%), followed by alpelisib/fulvestrant-targetable PIK3CA mutations (8.3%), BRCA2 mutations (6.7%), ATM mutations (6.3%) capivasertib/fulvestrant-targetable PIK3CA mutations (5.4%), and NF1 mutations (5.3%). Among patients with gastroesophageal junction adenocarcinoma, the most common small-molecule targetable alteration was HER2/ERBB2 amplification (17.2%), followed by alpelisib/fulvestrant-targetable PIK3CA mutations (7.1%), ATM mutations (7.0%), BRCA2 mutations (5.1%), NF1 mutations (5.0%), and ERBB2/HER2 mutations (4.7%). Among the queried genomic aberrations ( Supplemental Table 1 ), there was a high degree of concordance between genomic alteration rates in the esophageal adenocarcinoma and GEJ adenocarcinoma alterations, with no statistical difference between alteration rates of the 50 most-prevalent targetable loci (Table 2 ). A pooled representation of the most commonly altered targetable alterations in both esophageal and GEJ adenocarcinoma is displayed in Fig. 1 . Among the queried patients, the most commonly indicated pharmacologic class was poly-(ADP-ribose) polymerase (PARP) inhibitor. Table 2 The rate of alterations in targetable genomic loci within the AACR GENIE cohort. Gene Esophageal Adeno GEJ Adeno Esophageal SCC p-Value q-Value Most enriched in N = 1784 N = 1462 N = 456 AKT1: MUT 10 (0.6%) 23 (1.6%) 2 (0.4%) 7.00E-03 0.096 GEJ Adeno ARAF: MUT 12 (0.7%) 14 (1%) 6 (1.3%) 0.325 0.805 ESCC ATM: MUT 117 (6.6%) 106 (7.3%) 22 (4.8%) 0.262 0.735 GEJ Adeno ATR: MUT 70 (3.9%) 47 (3.2%) 21 (4.6%) 0.177 0.625 ESCC BARD1: MUT 25 (1.4%) 23 (1.6%) 6 (1.3%) 0.961 0.982 GEJ Adeno BRAF: MUT 34 (1.9%) 42 (2.9%) 9 (2%) 0.187 0.64 GEJ Adeno BRCA1: MUT 45 (2.5%) 32 (2.2%) 10 (2.2%) 0.738 0.881 Esophageal Adeno BRCA2: MUT 116 (6.5%) 75 (5.1%) 33 (7.2%) 0.0551 0.35 ESCC BRIP1: MUT 33 (1.8%) 37 (2.5%) 13 (2.9%) 0.229 0.695 ESCC CDK12: MUT 45 (2.5%) 37 (2.5%) 13 (2.9%) 0.815 0.925 ESCC CHEK1: MUT 14 (0.8%) 15 (1%) 10 (2.2%) 0.0214 0.209 ESCC CHEK2: MUT 20 (1.1%) 21 (1.4%) 18 (3.9%) < 0.001 < 0.001 ESCC EGFR: MUT 46 (2.6%) 37 (2.5%) 11 (2.4%) 0.993 0.997 Esophageal Adeno ERBB2: MUT 97 (5.4%) 72 (4.9%) 9 (2%) 0.0126 0.146 Esophageal Adeno ESR1: MUT 41 (2.3%) 40 (2.7%) 8 (1.8%) 0.607 0.86 GEJ Adeno EZH1: MUT 9 (0.5%) 5 (0.3%) 2 (0.4%) 0.414 0.843 Esophageal Adeno FANCA: MUT 51 (2.9%) 34 (2.3%) 16 (3.5%) 0.232 0.695 ESCC FANCL: MUT 17 (1%) 12 (0.8%) 4 (0.9%) 1 1 ESCC FGFR3: MUT 16 (0.9%) 21 (1.4%) 8 (1.8%) 0.181 0.632 ESCC IDH1: MUT 17 (1%) 8 (0.5%) 5 (1.1%) 0.308 0.781 ESCC KIT: MUT 39 (2.2%) 39 (2.7%) 10 (2.2%) 0.681 0.872 GEJ Adeno MAP2K1: MUT 16 (0.9%) 11 (0.8%) 3 (0.7%) 0.81 0.923 Esophageal Adeno MAP2K2: MUT 19 (1.1%) 12 (0.8%) 3 (0.7%) 0.596 0.86 Esophageal Adeno MLH1: MUT 34 (1.9%) 28 (1.9%) 8 (1.8%) 0.993 0.997 Esophageal Adeno MRE11: MUT 33 (1.8%) 17 (1.2%) 5 (1.1%) 0.169 0.607 Esophageal Adeno NBN: MUT 24 (1.3%) 25 (1.7%) 5 (1.1%) 0.658 0.872 GEJ Adeno NF1: MUT 92 (5.2%) 74 (5.1%) 15 (3.3%) 0.349 0.831 Esophageal Adeno PALB2: MUT 37 (2.1%) 40 (2.7%) 15 (3.3%) 0.202 0.65 ESCC PDGFRA: MUT 28 (1.6%) 29 (2%) 11 (2.4%) 0.375 0.836 ESCC PIK3CA: MUT 155 (8.7%) 109 (7.5%) 49 (10.7%) 0.04 0.29 ESCC POLD1: MUT 51 (2.9%) 48 (3.3%) 12 (2.6%) 0.86 0.936 GEJ Adeno POLE: MUT 77 (4.3%) 61 (4.2%) 12 (2.6%) 0.294 0.778 Esophageal Adeno PTEN: MUT 35 (2%) 41 (2.8%) 17 (3.7%) 0.049 0.327 ESCC RAD51B: MUT 6 (0.3%) 8 (0.5%) 1 (0.2%) 0.558 0.86 GEJ Adeno RAD51C: MUT 15 (0.8%) 15 (1%) 8 (1.8%) 0.199 0.65 ESCC RAD51D: MUT 8 (0.4%) 6 (0.4%) 0 (0%) 0.372 0.836 Esophageal Adeno RAD54L: MUT 12 (0.7%) 10 (0.7%) 1 (0.2%) 0.554 0.86 Esophageal Adeno RAF1: MUT 14 (0.8%) 11 (0.8%) 1 (0.2%) 0.459 0.846 Esophageal Adeno RET: MUT 56 (3.1%) 56 (3.8%) 5 (1.1%) 0.02 0.207 GEJ Adeno TSC1: MUT 28 (1.6%) 28 (1.9%) 13 (2.9%) 0.139 0.554 ESCC TSC2: MUT 61 (3.4%) 43 (2.9%) 13 (2.9%) 0.623 0.86 Esophageal Adeno ABL1: FUSION 3 (0.2%) 1 (0.1%) 0 (0%) 0.518 0.684 Esophageal Adeno ALK: FUSION 2 (0.1%) 1 (0.1%) 0 (0%) 0.734 0.785 Esophageal Adeno BRAF: FUSION 1 (0.1%) 6 (0.4%) 2 (0.4%) 0.087 0.684 ESCC FGFR1: FUSION 3 (0.2%) 3 (0.2%) 1 (0.2%) 0.959 0.961 ESCC FGFR2: FUSION 13 (0.7%) 10 (0.7%) 1 (0.2%) 0.501 0.684 Esophageal Adeno FGFR3: FUSION 6 (0.3%) 1 (0.1%) 0 (0%) 0.125 0.684 Esophageal Adeno JAK2: FUSION 3 (0.2%) 1 (0.1%) 0 (0%) 0.512 0.684 Esophageal Adeno NRG1: FUSION 7 (0.4%) 3 (0.2%) 1 (0.2%) 0.687 0.758 Esophageal Adeno NTRK1: FUSION 6 (0.3%) 8 (0.5%) 0 (0%) 0.265 0.684 GEJ Adeno NTRK2: FUSION 1 (0.1%) 0 (0%) 0 (0%) 0.578 0.684 Esophageal Adeno NTRK3: FUSION 4 (0.2%) 1 (0.1%) 0 (0%) 0.332 0.684 Esophageal Adeno PDGFB: FUSION 0 (0%) 1 (0.1%) 0 (0%) 0.338 0.684 GEJ Adeno PDGFRA: FUSION 1 (0.1%) 2 (0.1%) 1 (0.2%) 0.568 0.684 ESCC RARA: FUSION 7 (0.4%) 6 (0.4%) 0 (0%) 0.426 0.684 GEJ Adeno RET: FUSION 2 (0.1%) 4 (0.3%) 0 (0%) 0.377 0.684 GEJ Adeno ROS1: FUSION 0 (0%) 0 (0%) 1 (0.2%) 0.0224 0.525 Esophageal SCC ERBB2: AMP 249 (14%) 217 (14.8%) 8 (1.8%) < 0.001 < 0.001 Esophageal Adeno MET: AMP 59 (3.3%) 45 (3.1%) 3 (0.7%) 0.0128 0.13 Esophageal Adeno FLT3: D835 I836 1 (0.1%) 0 (0%) 0 (0%) 0.784 1 Esophageal Adeno AKT1: E17K 0 (0%) 6 (0.4%) 0 (0%) < 0.001 < 0.001 GEJ Adeno PIK3CA: E545Q G1049R M1043I M1043V N345K Q546K Q546P R88Q C420R E542K E545A E545D E545G E545K H1047L H1047R H1047Y Q546E Q546R 100 (5.6%) 69 (4.7%) 36 (7.9%) 0.044 0.158 ESCC KRAS: G12 65 (3.6%) 60 (4.1%) 2 (0.4%) 2.00E-03 9.00E-03 GEJ Adeno SMARCB1: DELETION 3 (0.2%) 1 (0.1%) 0 (0%) 0.48 0.749 Esophageal Adeno IDH2 2 (0.1%) 1 (0.1%) 0 (0%) 0.554 1 Esophageal Adeno BRAF: V600 2 (0.1%) 2 (0.1%) 0 (0%) 1 1 GEJ Adeno Among 87 sequenced patients with esophageal/esophagogastric adenocarcinoma in the TCGA cohort, EGFR overexpression was rare, with only 5 patients demonstrating overexpression of EGFR (5.7%). In contrast, 58 of 87 patients (67.0%) demonstrated overexpression of HER2/ERBB2. For patients with esophageal squamous cell carcinoma, the most common small-molecule targetable alteration was alpelisib/fulvestrant-targetable PIK3CA mutation (10.7%), prevalence of which was higher than in patients with adenocarcinoma histology (p = 0.040). BRCA2 (7.9%), capivasertib/fulvestrant-targetable PIK3CA mutations (7.9%), ATR mutations, (5.4%), ATM mutations (4.9%), and CHEK2 mutations (4.3%) were also prevalent in the cohort ( Table 2 ) . Among 95 patients with esophageal squamous cell carcinoma sequenced in the TCGA cohort, EGFR overexpression was noted in 54 (57.0%) patients while ERBB2/HER2 overexpression was noted in only 18 (19.0%) patients. Coalterations Among Treatment-Indicating and Resistance-Conferring Loci Overall, coalterations in targetable genomic loci were uncommon amongst the GENIE cohort for patients with esophageal/GEJ adenocarcinoma (Fig. 2 ). Notably, there was no statistically significant relationship between EGFR and NRAS or KRAS alterations in the adenocarcinoma subcohort. Coalterations tended to occur in genomic loci associated with genome maintenance, such as CHEK1/ATM, CHEK1/ATR , or CHEK2/PALB2 (all q < 0.05) or in a targetable genomic locus with a genomic locus associated with genome maintenance, such as PIK3CA coalteration with ATR, BRCA1 , and BRCA2 (all q < 0.05). A selected analysis of coalterations between HER2/ERBB2 amplifications and known- resistance-conferring alterations is presented in Supplemental Fig. 2. Amplifications in the HER2 locus were highly-co-occurrent with amplifications in the CDK12 locus (q < 0.001). CDK12 alterations were prevalent among patients with adenocarcinoma (Table 3 ). A non-statistically significant positive correlation was demonstrated between HER2 amplification and anti- HER2 therapy resistance-conferring mutations (q ~ 0.01). Table 3 Common resistance-conferring alterations for currently approved targeted therapies for esophageal cancer and FDA-approved therapies explored in the present study. Gene Esophageal Adeno GEJ Adeno ESCC p-Value q-Value Most enriched in KRAS 283 (15.13%) 246 (15.95%) 14 (3.06%) 4.32E-12 1.48E-10 GEJ Adeno NRAS 29 (1.55%) 13 (0.84%) 4 (0.87%) 0.132 0.635 Esophageal Adeno CDK12: AMP 118 (9.46%) 118 (10.09%) 5 (1.62%) 1.15E-05 2.91E-04 GEJ Adeno AKT1: AMP 1 (0.07%) 2 (0.16%) 0 (0.00%) 0.648 0.787 GEJ Adeno ERBB2: L755S V842I K753I D769Y 11 (0.59%) 6 (0.39%) 0 (0.00%) 0.224 0.999 Esophageal Adeno PIK3CA 161 (8.61%) 117 (7.59%) 67 (14.63%) 1.69E-05 3.00E-04 ESCC SRC 20 (1.37%) 16 (1.38%) 1 (0.27%) 0.207 0.763 GEJ Adeno STAT3 24 (1.44%) 31 (2.17%) 8 (1.93%) 0.307 0.763 GEJ Adeno ARID1A 294 (17.06%) 237 (16.28%) 33 (7.93%) 1.88E-05 3.30E-04 Esophageal Adeno Among patients with esophageal squamous cell carcinoma, coalterations among targetable loci were exceedingly rare (Fig. 3 ). Like esophageal adenocarcinoma, a relationship between CDK12 and ERBB2/HER2 alteration was demonstrated (q = 0.018). No other statistically significant relationships were demonstrated. Discussion Esophageal cancer (ECa) remains a significant cause of global mortality. Even after curative intent resection, 5-year survival remains poor, ranging from 12.3% 23 to 59% 24 depending on stage and histologic pattern, emphasizing the need for effective adjuvant therapies. While the use of next-generation sequencing has increased in recent years across cancer types, 25 utility for such information has remained limited given the small number of molecular targeted therapies approved for esophageal cancer. 10 , 26 The current study was important as we explored the full potential of targeted therapy for actionable genomic alterations with small-molecule agents that are currently approved and have demonstrated efficacy for other solid malignancies with analogous genetic alterations. In this large clinically-annotated genomic database study, we found that small-molecule targetable alterations were detected in more than half of esophageal adenocarcinoma and GEJ adenocarcinoma patients in this Western population ( Supplemental Fig. 1 ). Furthermore, while the genomic profile of esophageal SCC is well-examined in Asian populations, characterization of the genomic profile of esophageal SCC among non-Asian populations has thus far been limited. The present study demonstrated a similarly high rate of potentially targetable alterations among squamous cell carcinomas as well. Coalterations associated with resistance varied based on histology, except for a relationship between CDK12 and ERBB2/HER2 , which was detected for both adenocarcinoma and squamous cell subtypes. Among potentially targetable surface receptors, the most frequently altered locus in esophageal adenocarcinoma remains HER2/ERBB2. While HER2- targeted trastuzumab is an approved therapy for ECa, treatment efficacy remains in-doubt. Safran et al. failed to demonstrate efficacy of adjuvant trastuzumab in HER2 + esophageal adenocarcinoma compared to traditional chemoradiation protocols alone. 12 Given the importance of HER2 signaling in the pathogenesis of breast cancer, such a model may provide insights into the underlying mechanism of trastuzumab resistance in ECa. CDK12 overexpression in breast cancer has been demonstrated to confer HER2 -targeted therapy resistance by downregulating both local immune response and by independently modulating tumor progression through an alternative PI3K pathway. 27 Interaction of HER2 and CDK12 appears to be independent of disease location. Indeed, in two cases of urothelial carcinoma, HER2 and CDK12 co-overexpression was linked to rapid progression and aggressive disease behavior. 28 Of significance, in the present study, we demonstrated significant coalteration and co-amplification between the HER2 and CDK12 loci. This finding, paired with modest results for single agent anti- HER2 therapy in the treatment of esophageal adenocarcinoma, supports the hypothesis that a CDK12 -inhibiting treatment may improve outcomes in HER2 + disease. Promisingly, in a cohort of breast cancer patients, CDK12 co-inhibition restored sensitivity to anti- HER2 tyrosine kinase inhibitors in those who had previously stopped responding to trastuzumab. 27 In a cohort of esophageal adenocarcinoma patients, co-administration of an immune checkpoint inhibitor with trastuzumab likewise resulted in improved results over anti- HER2 therapy alone. 29 Given that immune modulation is a primary evasion mechanism driven by CDK12 , 30 this result may provide limited clinical evidence of the role of CDK12 in solid tumor biology, including ECa. Among esophageal squamous cell carcinoma, EGFR remains an important, potentially targetable surface receptor. Initial trials of EGFR -targeted cetuximab in ECa failed to demonstrate improved disease-free progression or overall survival in those with localized disease. 31 In both colorectal 32 and non-small cell lung cancer (NSCLC), 33 disease processes in which EGFR is commonly overexpressed or mutated, EGFR- targeted treatment resistance can commonly be explained by co-occurrent alterations in the NRAS and KRAS loci. In the present study, no such coalteration pattern was observed. Importantly, despite having a higher mean mutation count, the sole coalteration between the studied loci in ESCC was HER2/CDK12 , a coalteration pair observed in esophageal adenocarcinoma. No other coalteration pairs were observed, in stark contrast to EAC, in which numerous coalteration pairs were observed. Such a finding may be consistent with the hypothesis that esophageal squamous cell carcinoma represents a more diverse disease process with more unique alteration combinations than disease processes with similar histology. Furthermore, such a finding may be consistent with the hypothesis that EGFR- targeted therapies should be trialed with greater focus on the ~ 2–3% of patients with mutations in that gene and/or the ~ 30% of EAC patients with EGFR overexpression (Table 2 ). The results of this study also suggest a possible application of small-molecule targeted therapy as adjuncts to neoadjuvant chemoradiation treatment for esophageal adenocarcinoma or SCC. In a recent meta-analysis, Gaber et al. examined the rate of pathologic complete response (pCR), frequently used as a proxy for treatment efficacy, among over 6400 patients with esophageal carcinoma. Just 32% of patients with ESCC experienced pCR with neoadjuvant chemoradiation while only 22% of patients with esophageal adenocarcinoma experienced pCR. 34 Poly-(ADP-Ribose) Polymerase (PARP), a key enzyme involved in the repair of single strand DNA breaks and – by extension – cellular survival, is frequently implicated in resistance to traditional chemoradiation. In the present study, we demonstrated that alterations associated with PARP inhibitor (PARPi) response were most frequently found among patients with esophageal adenocarcinoma. Indeed, Kageyama et al demonstrated in vitro that esophageal SCC cell lines treated with PARP inhibitor olaparib demonstrated greater sensitivity to proton beam radiation compared to those cells which were untreated. 35 These results, paired with a high prevalence of PARPi-responsive alterations warrants the initiation of new clinical trials pairing PARPi’s with present chemoradiation in the neoadjuvant setting. While the large cohort and number of included institutions were a strength of the current study, the results should be interpreted in light of several limitations. Genomic and clinicodemographic data were collected from various institutions employing varied next-generation sequencing (NGS) arrays. Lack of genomic data may have excluded some patients in a non-random manner, thereby introducing bias. Similarly, loci were classified as “clinically relevant,” and hence included in the analysis, if any alteration in the locus was classified as a treatment-determining alteration according to OncoKB. However, such treatments may or may not have efficacy across cancer types. Conclusions The majority of patients with esophageal adenocarcinoma, GEJ adenocarcinoma, or squamous cell carcinoma harbor clinically targetable alterations, yet the composition and frequency of these alterations—and their co-occurrence—differ across histologic subtypes. HER2/ERBB2 amplification and PIK3CA mutations predominate in esophageal and GEJ adenocarcinoma, while EGFR overexpression is especially common in squamous cell carcinoma. Importantly, we identified HER2/CDK12 coalterations as a potential mechanism of resistance to HER2-directed therapies. Collectively, these findings underscore the need to account for distinct genomic and coalteration signatures when considering neoadjuvant targeted therapies, and they highlight opportunities for novel combination regimens (e.g., PARP inhibition plus standard chemoradiation) to improve outcomes in diverse esophageal cancer populations. Abbreviations AACR - American Association for Cancer Research EAC - esophageal adenocarcinoma ECa - esophageal cancer ESCC - esophageal squamous cell carcinoma GEJ - gastroesophageal junction NGS - next-generation sequencing pCR - pathologic complete response SNP - single nucleotide polymorphisms TCGA - The Cancer Genome Atlas Declarations Acknowledgements The authors would like to acknowledge the American Association for Cancer Research and its financial and material support in the development of the AACR Project GENIE registry, as well as members of the consortium for their commitment to data sharing. Interpretations are the responsibility of study authors. References Abbas G, Krasna M. Overview of esophageal cancer. Ann Cardiothorac Surg . 2017;6(2):131-136. doi:10.21037/acs.2017.03.03 Cancer of the Esophagus - Cancer Stat Facts. SEER. Accessed January 28, 2025. https://seer.cancer.gov/statfacts/html/esoph.html Al-Batran SE, Homann N, Pauligk C, et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): a randomised, phase 2/3 trial. Lancet Lond Engl . 2019;393(10184):1948-1957. doi:10.1016/S0140-6736(18)32557-1 van Hagen P, Hulshof MCCM, van Lanschot JJB, et al. Preoperative chemoradiotherapy for esophageal or junctional cancer. N Engl J Med . 2012;366(22):2074-2084. doi:10.1056/NEJMoa1112088 Puhr HC, Prager GW, Ilhan-Mutlu A. How we treat esophageal squamous cell carcinoma. ESMO Open . 2023;8(1):100789. doi:10.1016/j.esmoop.2023.100789 Boerner T, Carr RA, Hsu M, et al. Incidence and Management of Esophageal Cancer Recurrence to Regional Lymph Nodes After Curative Esophagectomy. Int J Cancer . 2023;152(10):2109-2122. doi:10.1002/ijc.34417 Underwood PW, Ruff SM, Pawlik TM. Update on Targeted Therapy and Immunotherapy for Metastatic Colorectal Cancer. Cells . 2024;13(3):245. doi:10.3390/cells13030245 Roskoski R. Properties of FDA-approved small molecule protein kinase inhibitors: A 2024 update. Pharmacol Res . 2024;200:107059. doi:10.1016/j.phrs.2024.107059 Besse B, Pons-Tostivint E, Park K, et al. Biomarker-directed targeted therapy plus durvalumab in advanced non-small-cell lung cancer: a phase 2 umbrella trial. Nat Med . 2024;30(3):716-729. doi:10.1038/s41591-024-02808-y Yang YM, Hong P, Xu WW, He QY, Li B. Advances in targeted therapy for esophageal cancer. Signal Transduct Target Ther . 2020;5(1):1-11. doi:10.1038/s41392-020-00323-3 Acharya R, Mahapatra A, Verma HK, Bhaskar LVKS. Unveiling Therapeutic Targets for Esophageal Cancer: A Comprehensive Review. Curr Oncol . 2023;30(11):9542-9568. doi:10.3390/curroncol30110691 Safran HP, Winter K, Ilson DH, et al. Trastuzumab with trimodality treatment for oesophageal adenocarcinoma with HER2 overexpression (NRG Oncology/RTOG 1010): a multicentre, randomised, phase 3 trial. Lancet Oncol . 2022;23(2):259-269. doi:10.1016/S1470-2045(21)00718-X Kelly RJ, Ajani JA, Kuzdzal J, et al. Adjuvant Nivolumab in Resected Esophageal or Gastroesophageal Junction Cancer. N Engl J Med . 2021;384(13):1191-1203. doi:10.1056/NEJMoa2032125 Nielsen R, Paul JS, Albrechtsen A, Song YS. Genotype and SNP calling from next-generation sequencing data. Nat Rev Genet . 2011;12(6):443-451. doi:10.1038/nrg2986 Waarts MR, Stonestrom AJ, Park YC, Levine RL. Targeting mutations in cancer. J Clin Invest . 132(8):e154943. doi:10.1172/JCI154943 AACR Project GENIE Consortium. AACR Project GENIE: Powering Precision Medicine through an International Consortium. Cancer Discov . 2017;7(8):818-831. doi:10.1158/2159-8290.CD-17-0151 Cerami E, Gao J, Dogrusoz U, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov . 2012;2(5):401-404. doi:10.1158/2159-8290.CD-12-0095 de Bruijn I, Kundra R, Mastrogiacomo B, et al. Analysis and Visualization of Longitudinal Genomic and Clinical Data from the AACR Project GENIE Biopharma Collaborative in cBioPortal. Cancer Res . 2023;83(23):3861-3867. doi:10.1158/0008-5472.CAN-23-0816 Gao J, Aksoy BA, Dogrusoz U, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal . 2013;6(269):pl1. doi:10.1126/scisignal.2004088 Weinstein JN, Collisson EA, Mills GB, et al. The Cancer Genome Atlas Pan-Cancer Analysis Project. Nat Genet . 2013;45(10):1113-1120. doi:10.1038/ng.2764 Chakravarty D, Gao J, Phillips SM, et al. OncoKB: A Precision Oncology Knowledge Base. JCO Precis Oncol . 2017;2017:PO.17.00011. doi:10.1200/PO.17.00011 Suehnholz SP, Nissan MH, Zhang H, et al. Quantifying the Expanding Landscape of Clinical Actionability for Patients with Cancer. Cancer Discov . 2024;14(1):49-65. doi:10.1158/2159-8290.CD-23-0467 Su XD, Zhang DK, Zhang X, Lin P, Long H, Rong TH. Prognostic factors in patients with recurrence after complete resection of esophageal squamous cell carcinoma. J Thorac Dis . 2014;6(7). doi:10.3978/j.issn.2072-1439.2014.07.14 Nuytens F, Dabakuyo-Yonli TS, Meunier B, et al. Five-Year Survival Outcomes of Hybrid Minimally Invasive Esophagectomy in Esophageal Cancer. JAMA Surg . 2021;156(4):323-332. doi:10.1001/jamasurg.2020.7081 Ferreira-Gonzalez A, Hocum B, Ko G, Shuvo S, Appukkuttan S, Babajanyan S. Next-Generation Sequencing Trends among Adult Patients with Select Advanced Tumor Types: A Real-World Evidence Evaluation. J Mol Diagn . 2024;26(4):292-303. doi:10.1016/j.jmoldx.2024.01.005 Bregni G, Beck B. Toward Targeted Therapies in Oesophageal Cancers: An Overview. Cancers . 2022;14(6):1522. doi:10.3390/cancers14061522 Li H, Wang J, Yi Z, et al. CDK12 inhibition enhances sensitivity of HER2+ breast cancers to HER2-tyrosine kinase inhibitor via suppressing PI3K/AKT. Eur J Cancer Oxf Engl 1990 . 2021;145:92-108. doi:10.1016/j.ejca.2020.11.045 Yanai Y, Kosaka T, Nakamura K, et al. CDK12 and HER2 coamplification in two urothelial carcinomas with rapid and aggressive clinical progression. Cancer Sci . 2020;111(12):4652-4655. doi:10.1111/cas.14672 Stein A, Paschold L, Tintelnot J, et al. Efficacy of Ipilimumab vs FOLFOX in Combination With Nivolumab and Trastuzumab in Patients With Previously Untreated ERBB2-Positive Esophagogastric Adenocarcinoma: The AIO INTEGA Randomized Clinical Trial. JAMA Oncol . 2022;8(8):1150-1158. doi:10.1001/jamaoncol.2022.2228 Lu KQ, Li ZL, Zhang Q, et al. CDK12 is a potential biomarker for diagnosis, prognosis and immunomodulation in pan-cancer. Sci Rep . 2024;14(1):6574. doi:10.1038/s41598-024-56831-7 Suntharalingam M, Winter K, Ilson D, et al. Effect of the Addition of Cetuximab to Paclitaxel, Cisplatin, and Radiation Therapy for Patients With Esophageal Cancer: The NRG Oncology RTOG 0436 Phase 3 Randomized Clinical Trial. JAMA Oncol . 2017;3(11):1520-1528. doi:10.1001/jamaoncol.2017.1598 De Roock W, Claes B, Bernasconi D, et al. Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. Lancet Oncol . 2010;11(8):753-762. doi:10.1016/S1470-2045(10)70130-3 Leonetti A, Sharma S, Minari R, Perego P, Giovannetti E, Tiseo M. Resistance mechanisms to osimertinib in EGFR-mutated non-small cell lung cancer. Br J Cancer . 2019;121(9):725-737. doi:10.1038/s41416-019-0573-8 Gaber C, Sarker J, Abdelaziz A, et al. Pathologic complete response among patients with esophageal cancer receiving neoadjuvant chemotherapy or chemoradiation: A meta-analysis. J Clin Oncol . 2024;42(3_suppl):305-305. doi:10.1200/JCO.2024.42.3_suppl.305 Kageyama SI, Junyan D, Hojo H, et al. PARP inhibitor olaparib sensitizes esophageal carcinoma cells to fractionated proton irradiation. J Radiat Res (Tokyo) . 2020;61(2):177-186. doi:10.1093/jrr/rrz088 Additional Declarations No competing interests reported. Supplementary Files SupplementalTable1.docx SupplementalFigure1.tiff Supplemental Figure 1: Frequency of any targetable genomic alteration in esophageal adenocarcinoma (left) and squamous cell carcinoma (right). SupplementalFigure2.png Supplemental Figure 2. Heatmap demonstrating the log odds of HER2 alteration and alterations in another genomic locus known to confer resistance to anti- HER2 therapy. Relationships found to be statistically significant in false discovery analysis are demarcated using an asterisk Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6754101","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":462777810,"identity":"fc837123-90a8-46e7-9998-432e4188121f","order_by":0,"name":"Hunter Stecko","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Hunter","middleName":"","lastName":"Stecko","suffix":""},{"id":462777812,"identity":"1e94413f-bc84-4fde-b5b9-de37a642331b","order_by":1,"name":"Jad Daw","email":"","orcid":"","institution":"The Ohio State University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jad","middleName":"","lastName":"Daw","suffix":""},{"id":462777813,"identity":"63599705-9306-41d2-a4d3-ea47b41be9f9","order_by":2,"name":"Robert E. Merritt","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"E.","lastName":"Merritt","suffix":""},{"id":462777814,"identity":"8edcf1ea-a818-4577-ba0f-b30bcbce2a85","order_by":3,"name":"Desmond M. D’Souza","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Desmond","middleName":"M.","lastName":"D’Souza","suffix":""},{"id":462777815,"identity":"8f84f844-77d2-4316-8918-95ba2b72a13b","order_by":4,"name":"Ioana Baiu","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Ioana","middleName":"","lastName":"Baiu","suffix":""},{"id":462777816,"identity":"f98b61a5-c851-4e3c-abab-0da797957595","order_by":5,"name":"Jenna Aziz","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Jenna","middleName":"","lastName":"Aziz","suffix":""},{"id":462777817,"identity":"912f08c8-339d-42ff-ac8d-e36153de4ac2","order_by":6,"name":"Christopher Rutter","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Rutter","suffix":""},{"id":462777818,"identity":"d27abfd9-482c-44f7-8927-0359041eec75","order_by":7,"name":"Divyaam Satija","email":"","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":false,"prefix":"","firstName":"Divyaam","middleName":"","lastName":"Satija","suffix":""},{"id":462777819,"identity":"81ea6828-1a2a-4986-a26a-db13eea2ec12","order_by":8,"name":"Timothy M. 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Kneuertz","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYPCCBBjDBsZgxqOaGUnLAYY00rUcJqzFnL3/4OMKhrQ8fonkY58//DkvJz8jO/EDQ4V1YgMOLZY9h5kNzzDkFEvOSEuecYDntrHBjdzNEgxn0nFqMbiRzCbZwFCRuOFGjjHDAYnbiRskcrcxMLYdxq3l/mP2nyAt+2/kf2Y4YHAucf4MkJZ/eLTcYGZjbGDIARqew8xwIOFAYsMNkJYG3Fose5KNJRsM0hJnnHlmzHDmQLKxwZm3myUSjqUb49Jizn7w4ceGiuTE/vbkxwwVf+zk5NtzN374UGMti9NhSCQSSMChHKviUTAKRsEoGAUYAACVZlvG6KO3gwAAAABJRU5ErkJggg==","orcid":"","institution":"The Ohio State University Wexner Medical Center and James Comprehensive Cancer Center","correspondingAuthor":true,"prefix":"","firstName":"Peter","middleName":"J.","lastName":"Kneuertz","suffix":""}],"badges":[],"createdAt":"2025-05-27 00:38:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6754101/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6754101/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83658320,"identity":"b46df3aa-ed24-4f23-bcab-b54676ee5e2a","added_by":"auto","created_at":"2025-05-30 09:18:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":414248,"visible":true,"origin":"","legend":"\u003cp\u003eBar chart detailing the subset of patients with targetable mutation in esophageal adenocarcinoma, gastroesophageal junction (GEJ) adenocarcinoma and esophageal squamous cell carcinoma.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/8f409e9e592aff6bbcdd476e.png"},{"id":83658325,"identity":"f35a0549-2500-4f0e-b9d5-592095a64f14","added_by":"auto","created_at":"2025-05-30 09:18:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":176416,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the log odds probability of targetable alterations and coalterations in esophageal adenocarcinoma. Relationships found to be statistically significant in false discovery analysis are demarcated using an asterisk.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/8b1b33e26e135472989997cf.png"},{"id":83658943,"identity":"caf833e7-7334-4868-97b8-b22847fbb34b","added_by":"auto","created_at":"2025-05-30 09:26:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":109241,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap of the log odds probability of targetable alterations and their coalterations in esophageal squamous cell carcinoma. Relationships found to be statistically significant in false discovery analysis are demarcated using an asterisk.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/f47f52ca4df8f2f9abee015d.png"},{"id":101962860,"identity":"14f9d160-4274-41d1-8fde-39151a4e33f4","added_by":"auto","created_at":"2026-02-05 12:58:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1848937,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/19fa61d2-ba08-4845-af55-9bf922bbf6ca.pdf"},{"id":83658945,"identity":"286327b3-3467-4208-b4c6-591b91781404","added_by":"auto","created_at":"2025-05-30 09:26:47","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20029,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplementalTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/e4327352dca487d608c7ca56.docx"},{"id":83658328,"identity":"081f34c0-eb26-4c96-8fee-ffd1bc111775","added_by":"auto","created_at":"2025-05-30 09:18:47","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1558686,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Figure 1: \u003c/strong\u003eFrequency of any targetable genomic alteration in esophageal adenocarcinoma (left) and squamous cell carcinoma (right).\u003c/p\u003e","description":"","filename":"SupplementalFigure1.tiff","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/fecd94c9b830e23d76c2ba0c.tiff"},{"id":83658322,"identity":"59bc4a21-3cf1-4c6d-bcd2-69a3395644c0","added_by":"auto","created_at":"2025-05-30 09:18:47","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":41440,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Figure 2. \u003c/strong\u003eHeatmap demonstrating the log odds of \u003cem\u003eHER2 \u003c/em\u003ealteration and alterations in another genomic locus known to confer resistance to anti-\u003cem\u003eHER2\u003c/em\u003e therapy. Relationships found to be statistically significant in false discovery analysis are demarcated using an asterisk\u003c/p\u003e","description":"","filename":"SupplementalFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6754101/v1/77c907475ea225433219e216.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Actionable Alterations for Molecular Targeted Therapy in Esophageal Cancer: An AACR Project GENIE Review","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEsophageal cancer is the eighth most common type of cancer and sixth leading cause of cancer-related mortality globally.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e While incidence of esophageal cancer in the United States has marginally declined since 2004, the case-fatality rate has remained high with a 5-year relative survival estimate of 21.6%.\u003csup\u003e2\u003c/sup\u003e Currently, the standard-of-care for locally advanced, resectable esophageal adenocarcinoma or gastroesophageal junction (GEJ) adenocarcinoma includes, or neoadjuvant chemoradiation supported by the CROSS trial\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e or perioperative cytotoxic chemotherapy and surgical resection under the FLOT\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e protocol. For squamous cell carcinoma, chemoradiotherapy with or without surgical resection remains the standard of care.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e However, high distant recurrence rates of 27\u0026ndash;50% following curative intent resection with current cytotoxic treatment regimens highlights the need for better systemic therapies.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite the rapid proliferation of targeted therapies against a variety of moieties across cancer types,\u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e few targeted therapies have been studied or approved for use in esophageal cancer.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Clinical trials examining the efficacy of these targeted treatments have demonstrated mixed results. Trials of anti-\u003cem\u003eHER2\u003c/em\u003e targeted therapies failed to demonstrate an survival benefit for patients with esophageal adenocarcinoma.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In contrast, immune checkpoint inhibitor nivolumab demonstrated a distinct disease-free survival advantage when used as adjuvant therapy after resection (22.4 months vs 11.0 months for the placebo group; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe expanded availability of next-generation sequencing (NGS) has allowed for rapid characterization of a large number of single nucleotide polymorphisms (SNPs) and other genomic alterations.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e As of 2024, there are no less than 30 genomic loci for which specific targeted therapies are FDA approved.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e However, there is limited understanding of the genomic landscape of esophageal cancer among non-Asian populations, in particular with respect to actionable targets with approved molecular therapies.\u003c/p\u003e \u003cp\u003eThe objectives of the present study were to assess the frequency of small-molecule targetable alterations in esophageal cancer subpopulations in a large international database, as well as examine the tumor biology for coalterations that could potentially impact targeted treatment response.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eThe AACR Project GENIE is a publicly accessible cancer registry of real-world clinico-genomic data assembled through data sharing between 19 leading cancer centers in the US, Europe and Korea.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e The dataset comprises over 3,000 sequenced esophageal cancer samples. De-identified clinicodemographic and genomic data from GENIE v17.0 were accessed directly via cBioPortal.\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e A complete description of genomic profiling and AACR Project GENIE data dictionary is summarized within the Consortium\u0026rsquo;s data guide.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCohort Selection\u003c/h3\u003e\n\u003cp\u003ePatients with a primary diagnosis of esophageal adenocarcinoma, cancer of the gastroesophageal junction (GEJ)/esophagogastric cancer and esophageal squamous cell carcinoma were identified in AACR Project GENIE (v17.0).\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e No patients were initially excluded (\u0026ldquo;GENIE cohort\u0026rdquo;). Institutions included in the GENIE consortium employed NGS to detect a variable set of genomic alterations in somatic tumor cells. For a subset of patients and genomic loci, variations in gene copy number and structure were also reported. A second cohort of patients was identified via The Cancer Genomic Atlas (TCGA).\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e De-identified clinicodemographic and genomic data were gathered. In addition, for select genomic loci, information regarding protein expression was gathered.\u003c/p\u003e\n\u003ch3\u003eTargeted Therapy Analysis\u003c/h3\u003e\n\u003cp\u003eOncoKB, a database containing information on actionable and clinically important genomic loci, was accessed to identify FDA-approved targeted therapies and their associated genomic treatment indications.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Additionally, clinical indications for 80 FDA approved small-molecule protein kinase inhibitors were reviewed.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e A list of treatment indications was compiled and converted to Onco Query Language (\u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e). For those treatment indications that involved genomic alteration, the GENIE cohort was queried. For those treatment indications associated with protein overexpression (\u003cem\u003eHER2/ERBB2\u003c/em\u003e and \u003cem\u003eEGFR\u003c/em\u003e based therapies), the TCGA cohort was separately queried. \u0026ldquo;Overexpression\u0026rdquo; was defined as those patients with somatic tumor cells having protein concentrations of \u0026gt;\u0026thinsp;0.5 standard deviations above the mean of surrounding, non-malignant cells.\u003c/p\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eSummary statistics (median, interquartile range (IQR)) and prevalence (%) were calculated for continuous and categorical variables (i.e. presence of genomic alteration), respectively. Chi-squared and Fisher\u0026rsquo;s exact test were used to determine genomic alteration prevalence differences between subpopulations. For coalteration analysis, log odds ratios were generated for the 48 most prevalent genomic alterations, and false discovery rate (q-value) was calculated. Genomic loci that were assessed in less than 50% of patients were excluded from coalteration analysis. Patients or samples without information regarding the analyzed attribute were excluded. Custom Python code was generated to compare coalteration differences between subpopulations.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Treatment-Indicating Alterations\u003c/h2\u003e \u003cp\u003eAmong the GENIE cohort, 3,605 patients with esophageal adenocarcinoma (n\u0026thinsp;=\u0026thinsp;1,784), adenocarcinoma of the gastroesophageal junction (GEJ) (n\u0026thinsp;=\u0026thinsp;1,462), or esophageal squamous cell carcinoma (n\u0026thinsp;=\u0026thinsp;456) were identified. There were 97 patients with both esophageal adenocarcinoma and GEJ adenocarcinoma. Demographic characteristics of the GENIE cohort are noted in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. While the majority (79.7%) of patients with all histological patterns of esophageal cancer were male, only 53.3% of those with squamous cell carcinoma were male (n\u0026thinsp;=\u0026thinsp;243) while 45.4% were female (n\u0026thinsp;=\u0026thinsp;207). The median fraction of the genome altered in esophageal and GEJ adenocarcinoma was similar, with a median of 0.18 (IQR: 0.05\u0026ndash;0.35) and 0.17 (0.04\u0026ndash;0.34) respectively. Patients with squamous cell carcinoma had a higher fraction of the genome altered and mutation count than patients with adenocarcinoma histology (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A targetable mutation was detected in 64.3% (n\u0026thinsp;=\u0026thinsp;1,147) of patients with esophageal adenocarcinoma, 63.6% of GEJ cancer (n\u0026thinsp;=\u0026thinsp;930), and 55.7% (n\u0026thinsp;=\u0026thinsp;254) of esophageal squamous cell carcinoma (\u003cb\u003eSupplemental Fig.\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe demographic makeup of the AACR Project GENIE esophageal malignancy cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEsophageal Adenocarcinoma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGEJ/Esophagogastric Adenocarcinoma\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEsophageal Squamous Cell Carcinoma\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1462)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;456)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1518 (85.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1191 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e243 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e251 (14.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e263 (18.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e207 (45.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary Race\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1363 (76.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1203 (82.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e277 (60.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55 (12.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e372 (20.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179 (12.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95 (20.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-Spanish/Non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1296 (72.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1161 (79.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e325 (71.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpanish/Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429 (24.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e198 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFraction Genome Altered\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.18 (0.05\u0026ndash;0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.17 (0.04\u0026ndash;0.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28 (0.09\u0026ndash;0.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMutation Count\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (4\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (5\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTargetable Alteration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1147 (64.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e930 (63.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e254 (55.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e775 (41.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e604 (39.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219 (47.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmplification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructural Variant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeletion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e221 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168 (10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe most common small-molecule targetable alteration for adenocarcinoma was \u003cem\u003eHER2/ERBB2\u003c/em\u003e amplification (17.9%), followed by alpelisib/fulvestrant-targetable \u003cem\u003ePIK3CA\u003c/em\u003e mutations (8.3%), \u003cem\u003eBRCA2\u003c/em\u003e mutations (6.7%), \u003cem\u003eATM\u003c/em\u003e mutations (6.3%) capivasertib/fulvestrant-targetable \u003cem\u003ePIK3CA\u003c/em\u003e mutations (5.4%), and \u003cem\u003eNF1\u003c/em\u003e mutations (5.3%). Among patients with gastroesophageal junction adenocarcinoma, the most common small-molecule targetable alteration was \u003cem\u003eHER2/ERBB2\u003c/em\u003e amplification (17.2%), followed by alpelisib/fulvestrant-targetable \u003cem\u003ePIK3CA\u003c/em\u003e mutations (7.1%), \u003cem\u003eATM\u003c/em\u003e mutations (7.0%), \u003cem\u003eBRCA2\u003c/em\u003e mutations (5.1%), \u003cem\u003eNF1\u003c/em\u003e mutations (5.0%), and \u003cem\u003eERBB2/HER2\u003c/em\u003e mutations (4.7%). Among the queried genomic aberrations (\u003cb\u003eSupplemental Table\u0026nbsp;1\u003c/b\u003e), there was a high degree of concordance between genomic alteration rates in the esophageal adenocarcinoma and GEJ adenocarcinoma alterations, with no statistical difference between alteration rates of the 50 most-prevalent targetable loci (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). A pooled representation of the most commonly altered targetable alterations in both esophageal and GEJ adenocarcinoma is displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Among the queried patients, the most commonly indicated pharmacologic class was poly-(ADP-ribose) polymerase (PARP) inhibitor.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe rate of alterations in targetable genomic loci within the AACR GENIE cohort.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEsophageal SCC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eq-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMost enriched in\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1784\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1462\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;456\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKT1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.00E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARAF: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATM: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e117 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.262\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eATR: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBARD1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRAF: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRCA1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRCA2: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRIP1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDK12: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHEK1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHEK2: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEGFR: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERBB2: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eESR1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEZH1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFANCA: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.695\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFANCL: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFGFR3: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (1.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.632\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDH1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKIT: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (2.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAP2K1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAP2K2: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMLH1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRE11: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNBN: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNF1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePALB2: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDGFRA: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIK3CA: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOLD1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOLE: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.294\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.778\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTEN: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAD51B: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAD51C: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAD51D: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAD54L: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRAF1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRET: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSC1: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSC2: MUT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABL1: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALK: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRAF: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFGFR1: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFGFR2: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFGFR3: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJAK2: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRG1: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNTRK1: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNTRK2: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNTRK3: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDGFB: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDGFRA: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRARA: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRET: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eROS1: FUSION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal SCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERBB2: AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e249 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e217 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMET: AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFLT3: D835 I836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKT1: E17K\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIK3CA: E545Q G1049R M1043I M1043V N345K Q546K Q546P R88Q C420R E542K E545A E545D E545G E545K H1047L H1047R H1047Y Q546E Q546R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKRAS: G12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.00E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.00E-03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSMARCB1: DELETION\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIDH2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBRAF: V600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAmong 87 sequenced patients with esophageal/esophagogastric adenocarcinoma in the TCGA cohort, \u003cem\u003eEGFR\u003c/em\u003e overexpression was rare, with only 5 patients demonstrating overexpression of \u003cem\u003eEGFR\u003c/em\u003e (5.7%). In contrast, 58 of 87 patients (67.0%) demonstrated overexpression of \u003cem\u003eHER2/ERBB2.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eFor patients with esophageal squamous cell carcinoma, the most common small-molecule targetable alteration was alpelisib/fulvestrant-targetable \u003cem\u003ePIK3CA\u003c/em\u003e mutation (10.7%), prevalence of which was higher than in patients with adenocarcinoma histology (p\u0026thinsp;=\u0026thinsp;0.040). \u003cem\u003eBRCA2\u003c/em\u003e (7.9%), capivasertib/fulvestrant-targetable \u003cem\u003ePIK3CA\u003c/em\u003e mutations (7.9%), \u003cem\u003eATR\u003c/em\u003e mutations, (5.4%), \u003cem\u003eATM\u003c/em\u003e mutations (4.9%), and \u003cem\u003eCHEK2\u003c/em\u003e mutations (4.3%) were also prevalent in the cohort \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Among 95 patients with esophageal squamous cell carcinoma sequenced in the TCGA cohort, \u003cem\u003eEGFR\u003c/em\u003e overexpression was noted in 54 (57.0%) patients while \u003cem\u003eERBB2/HER2\u003c/em\u003e overexpression was noted in only 18 (19.0%) patients.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCoalterations Among Treatment-Indicating and Resistance-Conferring Loci\u003c/h3\u003e\n\u003cp\u003eOverall, coalterations in targetable genomic loci were uncommon amongst the GENIE cohort for patients with esophageal/GEJ adenocarcinoma (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Notably, there was no statistically significant relationship between \u003cem\u003eEGFR\u003c/em\u003e and \u003cem\u003eNRAS\u003c/em\u003e or \u003cem\u003eKRAS\u003c/em\u003e alterations in the adenocarcinoma subcohort. Coalterations tended to occur in genomic loci associated with genome maintenance, such as \u003cem\u003eCHEK1/ATM, CHEK1/ATR\u003c/em\u003e, or \u003cem\u003eCHEK2/PALB2\u003c/em\u003e (all q\u0026thinsp;\u0026lt;\u0026thinsp;0.05) or in a targetable genomic locus with a genomic locus associated with genome maintenance, such as \u003cem\u003ePIK3CA\u003c/em\u003e coalteration with \u003cem\u003eATR, BRCA1\u003c/em\u003e, and \u003cem\u003eBRCA2\u003c/em\u003e (all q\u0026thinsp;\u0026lt;\u0026thinsp;0.05). A selected analysis of coalterations between \u003cem\u003eHER2/ERBB2\u003c/em\u003e amplifications and known- resistance-conferring alterations is presented in \u003cb\u003eSupplemental Fig.\u0026nbsp;2.\u003c/b\u003e Amplifications in the \u003cem\u003eHER2\u003c/em\u003e locus were highly-co-occurrent with amplifications in the \u003cem\u003eCDK12\u003c/em\u003e locus (q\u0026thinsp;\u0026lt;\u0026thinsp;0.001). \u003cem\u003eCDK12\u003c/em\u003e alterations were prevalent among patients with adenocarcinoma (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e A non-statistically significant positive correlation was demonstrated between \u003cem\u003eHER2\u003c/em\u003e amplification and anti-\u003cem\u003eHER2\u003c/em\u003e therapy resistance-conferring mutations (q\u0026thinsp;~\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCommon resistance-conferring alterations for currently approved targeted therapies for esophageal cancer and FDA-approved therapies explored in the present study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eq-Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMost enriched in\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKRAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e283 (15.13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e246 (15.95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (3.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.32E-12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.48E-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (1.55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13 (0.84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (0.87%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCDK12: AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e118 (9.46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118 (10.09%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (1.62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.15E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.91E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAKT1: AMP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.07%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eERBB2: L755S V842I K753I D769Y\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (0.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6 (0.39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.00%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePIK3CA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e161 (8.61%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117 (7.59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e67 (14.63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.69E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.00E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eESCC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (1.37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (1.38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTAT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (1.44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (2.17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (1.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGEJ Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eARID1A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e294 (17.06%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e237 (16.28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e33 (7.93%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.88E-05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.30E-04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEsophageal Adeno\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong patients with esophageal squamous cell carcinoma, coalterations among targetable loci were exceedingly rare (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e Like esophageal adenocarcinoma, a relationship between \u003cem\u003eCDK12\u003c/em\u003e and \u003cem\u003eERBB2/HER2\u003c/em\u003e alteration was demonstrated (q\u0026thinsp;=\u0026thinsp;0.018). No other statistically significant relationships were demonstrated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEsophageal cancer (ECa) remains a significant cause of global mortality. Even after curative intent resection, 5-year survival remains poor, ranging from 12.3%\u003csup\u003e23\u003c/sup\u003e to 59%\u003csup\u003e24\u003c/sup\u003e depending on stage and histologic pattern, emphasizing the need for effective adjuvant therapies. While the use of next-generation sequencing has increased in recent years across cancer types,\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e utility for such information has remained limited given the small number of molecular targeted therapies approved for esophageal cancer.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e The current study was important as we explored the full potential of targeted therapy for actionable genomic alterations with small-molecule agents that are currently approved and have demonstrated efficacy for other solid malignancies with analogous genetic alterations.\u003c/p\u003e \u003cp\u003eIn this large clinically-annotated genomic database study, we found that small-molecule targetable alterations were detected in more than half of esophageal adenocarcinoma and GEJ adenocarcinoma patients in this Western population (\u003cb\u003eSupplemental Fig.\u0026nbsp;1\u003c/b\u003e). Furthermore, while the genomic profile of esophageal SCC is well-examined in Asian populations, characterization of the genomic profile of esophageal SCC among non-Asian populations has thus far been limited. The present study demonstrated a similarly high rate of potentially targetable alterations among squamous cell carcinomas as well. Coalterations associated with resistance varied based on histology, except for a relationship between \u003cem\u003eCDK12\u003c/em\u003e and \u003cem\u003eERBB2/HER2\u003c/em\u003e, which was detected for both adenocarcinoma and squamous cell subtypes.\u003c/p\u003e \u003cp\u003eAmong potentially targetable surface receptors, the most frequently altered locus in esophageal adenocarcinoma remains \u003cem\u003eHER2/ERBB2.\u003c/em\u003e While \u003cem\u003eHER2-\u003c/em\u003etargeted trastuzumab is an approved therapy for ECa, treatment efficacy remains in-doubt. Safran et al. failed to demonstrate efficacy of adjuvant trastuzumab in \u003cem\u003eHER2\u003c/em\u003e\u0026thinsp;+\u0026thinsp;esophageal adenocarcinoma compared to traditional chemoradiation protocols alone.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e Given the importance of \u003cem\u003eHER2\u003c/em\u003e signaling in the pathogenesis of breast cancer, such a model may provide insights into the underlying mechanism of trastuzumab resistance in ECa. \u003cem\u003eCDK12\u003c/em\u003e overexpression in breast cancer has been demonstrated to confer \u003cem\u003eHER2\u003c/em\u003e-targeted therapy resistance by downregulating both local immune response and by independently modulating tumor progression through an alternative \u003cem\u003ePI3K\u003c/em\u003e pathway.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Interaction of \u003cem\u003eHER2\u003c/em\u003e and \u003cem\u003eCDK12\u003c/em\u003e appears to be independent of disease location. Indeed, in two cases of urothelial carcinoma, \u003cem\u003eHER2\u003c/em\u003e and \u003cem\u003eCDK12\u003c/em\u003e co-overexpression was linked to rapid progression and aggressive disease behavior.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e Of significance, in the present study, we demonstrated significant coalteration and co-amplification between the \u003cem\u003eHER2\u003c/em\u003e and \u003cem\u003eCDK12\u003c/em\u003e loci. This finding, paired with modest results for single agent anti-\u003cem\u003eHER2\u003c/em\u003e therapy in the treatment of esophageal adenocarcinoma, supports the hypothesis that a \u003cem\u003eCDK12\u003c/em\u003e-inhibiting treatment may improve outcomes in \u003cem\u003eHER2\u003c/em\u003e\u0026thinsp;+\u0026thinsp;disease. Promisingly, in a cohort of breast cancer patients, \u003cem\u003eCDK12\u003c/em\u003e co-inhibition restored sensitivity to anti-\u003cem\u003eHER2\u003c/em\u003e tyrosine kinase inhibitors in those who had previously stopped responding to trastuzumab.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e In a cohort of esophageal adenocarcinoma patients, co-administration of an immune checkpoint inhibitor with trastuzumab likewise resulted in improved results over anti-\u003cem\u003eHER2\u003c/em\u003e therapy alone.\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Given that immune modulation is a primary evasion mechanism driven by \u003cem\u003eCDK12\u003c/em\u003e,\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e this result may provide limited clinical evidence of the role of \u003cem\u003eCDK12\u003c/em\u003e in solid tumor biology, including ECa.\u003c/p\u003e \u003cp\u003eAmong esophageal squamous cell carcinoma, \u003cem\u003eEGFR\u003c/em\u003e remains an important, potentially targetable surface receptor. Initial trials of \u003cem\u003eEGFR\u003c/em\u003e-targeted cetuximab in ECa failed to demonstrate improved disease-free progression or overall survival in those with localized disease.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e In both colorectal\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and non-small cell lung cancer (NSCLC),\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e disease processes in which \u003cem\u003eEGFR\u003c/em\u003e is commonly overexpressed or mutated, \u003cem\u003eEGFR-\u003c/em\u003etargeted treatment resistance can commonly be explained by co-occurrent alterations in the \u003cem\u003eNRAS\u003c/em\u003e and \u003cem\u003eKRAS\u003c/em\u003e loci. In the present study, no such coalteration pattern was observed. Importantly, despite having a higher mean mutation count, the sole coalteration between the studied loci in ESCC was \u003cem\u003eHER2/CDK12\u003c/em\u003e, a coalteration pair observed in esophageal adenocarcinoma. No other coalteration pairs were observed, in stark contrast to EAC, in which numerous coalteration pairs were observed. Such a finding may be consistent with the hypothesis that esophageal squamous cell carcinoma represents a more diverse disease process with more unique alteration combinations than disease processes with similar histology. Furthermore, such a finding may be consistent with the hypothesis that \u003cem\u003eEGFR-\u003c/em\u003etargeted therapies should be trialed with greater focus on the ~\u0026thinsp;2\u0026ndash;3% of patients with mutations in that gene and/or the ~\u0026thinsp;30% of EAC patients with \u003cem\u003eEGFR\u003c/em\u003e overexpression (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe results of this study also suggest a possible application of small-molecule targeted therapy as adjuncts to neoadjuvant chemoradiation treatment for esophageal adenocarcinoma or SCC. In a recent meta-analysis, Gaber et al. examined the rate of pathologic complete response (pCR), frequently used as a proxy for treatment efficacy, among over 6400 patients with esophageal carcinoma. Just 32% of patients with ESCC experienced pCR with neoadjuvant chemoradiation while only 22% of patients with esophageal adenocarcinoma experienced pCR.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e Poly-(ADP-Ribose) Polymerase (PARP), a key enzyme involved in the repair of single strand DNA breaks and \u0026ndash; by extension \u0026ndash; cellular survival, is frequently implicated in resistance to traditional chemoradiation. In the present study, we demonstrated that alterations associated with PARP inhibitor (PARPi) response were most frequently found among patients with esophageal adenocarcinoma. Indeed, Kageyama et al demonstrated \u003cem\u003ein vitro\u003c/em\u003e that esophageal SCC cell lines treated with PARP inhibitor olaparib demonstrated greater sensitivity to proton beam radiation compared to those cells which were untreated.\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e These results, paired with a high prevalence of PARPi-responsive alterations warrants the initiation of new clinical trials pairing PARPi\u0026rsquo;s with present chemoradiation in the neoadjuvant setting.\u003c/p\u003e \u003cp\u003eWhile the large cohort and number of included institutions were a strength of the current study, the results should be interpreted in light of several limitations. Genomic and clinicodemographic data were collected from various institutions employing varied next-generation sequencing (NGS) arrays. Lack of genomic data may have excluded some patients in a non-random manner, thereby introducing bias. Similarly, loci were classified as \u0026ldquo;clinically relevant,\u0026rdquo; and hence included in the analysis, if any alteration in the locus was classified as a treatment-determining alteration according to OncoKB. However, such treatments may or may not have efficacy across cancer types.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe majority of patients with esophageal adenocarcinoma, GEJ adenocarcinoma, or squamous cell carcinoma harbor clinically targetable alterations, yet the composition and frequency of these alterations\u0026mdash;and their co-occurrence\u0026mdash;differ across histologic subtypes. HER2/ERBB2 amplification and PIK3CA mutations predominate in esophageal and GEJ adenocarcinoma, while EGFR overexpression is especially common in squamous cell carcinoma. Importantly, we identified HER2/CDK12 coalterations as a potential mechanism of resistance to HER2-directed therapies. Collectively, these findings underscore the need to account for distinct genomic and coalteration signatures when considering neoadjuvant targeted therapies, and they highlight opportunities for novel combination regimens (e.g., PARP inhibition plus standard chemoradiation) to improve outcomes in diverse esophageal cancer populations.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAACR - American Association for Cancer Research\u003c/p\u003e\n\u003cp\u003eEAC - esophageal adenocarcinoma\u003c/p\u003e\n\u003cp\u003eECa - esophageal cancer\u003c/p\u003e\n\u003cp\u003eESCC - esophageal squamous cell carcinoma\u003c/p\u003e\n\u003cp\u003eGEJ - gastroesophageal junction\u003c/p\u003e\n\u003cp\u003eNGS - next-generation sequencing\u003c/p\u003e\n\u003cp\u003epCR - pathologic complete response\u003c/p\u003e\n\u003cp\u003eSNP - single nucleotide polymorphisms\u003c/p\u003e\n\u003cp\u003eTCGA - The Cancer Genome Atlas\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge the American Association for Cancer Research and its financial and material support in the development of the AACR Project GENIE registry, as well as members of the consortium for their commitment to data sharing. Interpretations are the responsibility of study authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbbas G, Krasna M. Overview of esophageal cancer. \u003cem\u003eAnn Cardiothorac Surg\u003c/em\u003e. 2017;6(2):131-136. doi:10.21037/acs.2017.03.03\u003c/li\u003e\n\u003cli\u003eCancer of the Esophagus - Cancer Stat Facts. SEER. Accessed January 28, 2025. https://seer.cancer.gov/statfacts/html/esoph.html\u003c/li\u003e\n\u003cli\u003eAl-Batran SE, Homann N, Pauligk C, et al. Perioperative chemotherapy with fluorouracil plus leucovorin, oxaliplatin, and docetaxel versus fluorouracil or capecitabine plus cisplatin and epirubicin for locally advanced, resectable gastric or gastro-oesophageal junction adenocarcinoma (FLOT4): a randomised, phase 2/3 trial. \u003cem\u003eLancet Lond Engl\u003c/em\u003e. 2019;393(10184):1948-1957. doi:10.1016/S0140-6736(18)32557-1\u003c/li\u003e\n\u003cli\u003evan Hagen P, Hulshof MCCM, van Lanschot JJB, et al. 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Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. \u003cem\u003eLancet Oncol\u003c/em\u003e. 2010;11(8):753-762. doi:10.1016/S1470-2045(10)70130-3\u003c/li\u003e\n\u003cli\u003eLeonetti A, Sharma S, Minari R, Perego P, Giovannetti E, Tiseo M. Resistance mechanisms to osimertinib in EGFR-mutated non-small cell lung cancer. \u003cem\u003eBr J Cancer\u003c/em\u003e. 2019;121(9):725-737. doi:10.1038/s41416-019-0573-8\u003c/li\u003e\n\u003cli\u003eGaber C, Sarker J, Abdelaziz A, et al. Pathologic complete response among patients with esophageal cancer receiving neoadjuvant chemotherapy or chemoradiation: A meta-analysis. \u003cem\u003eJ Clin Oncol\u003c/em\u003e. 2024;42(3_suppl):305-305. doi:10.1200/JCO.2024.42.3_suppl.305\u003c/li\u003e\n\u003cli\u003eKageyama SI, Junyan D, Hojo H, et al. PARP inhibitor olaparib sensitizes esophageal carcinoma cells to fractionated proton irradiation. \u003cem\u003eJ Radiat Res (Tokyo)\u003c/em\u003e. 2020;61(2):177-186. doi:10.1093/jrr/rrz088\u003c/li\u003e\n\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":"esophageal adenocarcinoma, actionable targets, adjuvant therapy, Project GENIE, coalteration","lastPublishedDoi":"10.21203/rs.3.rs-6754101/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6754101/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003ePrognosis after curative intent resection for esophageal cancer remains low and only few targeted therapy options exist. We sought to analyze the full scope of potential actionable genomic alterations in esophageal cancer to better understand the potential for molecular targeted adjuvant therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe queried the American Association for Cancer Research (AACR) Project GENIE (v17.0) to identify clinically relevant, actionable genomic alterations in 3,605 patients with esophageal adenocarcinoma, gastroesophageal junction (GEJ) adenocarcinoma, or esophageal squamous cell carcinoma (ESCC). Additional data from The Cancer Genome Atlas (TCGA) were analyzed to assess protein overexpression of EGFR and HER2/ERBB2. Prevalence of targetable alterations was compared across histologic subtypes, and co-occurrence analyses using log-odds ratios with false discovery rate correction were performed on the most frequent alterations to identify potential resistance mechanisms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003ePotentially small-molecule targetable alterations were identified in 64.3% of esophageal adenocarcinomas and 63.6% of GEJ adenocarcinomas, whereas 55.7% of ESCCs carried at least one actionable alteration. HER2/ERBB2 amplification was most common in adenocarcinomas, while PIK3CA mutations were most common in SCCs with no alteration unique present in a plurality of patients. Co-amplification of HER2 and CDK12 emerged as a potential mechanism of resistance to HER2-directed therapies. In addition, numerous genes implicated in PARP inhibitor or PIK3CA-targeted strategies were frequently altered across all histologies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOver half of patients in this large genomic dataset exhibited at least one actionable alteration, although distinct molecular profiles emerged by histology. These findings underscore the potential of using precision oncology to expand adjuvant therapeutic options.\u003c/p\u003e","manuscriptTitle":"Actionable Alterations for Molecular Targeted Therapy in Esophageal Cancer: An AACR Project GENIE Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-30 09:18:42","doi":"10.21203/rs.3.rs-6754101/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":"5fdd051c-8972-48de-a6bc-7fc16d6f9e66","owner":[],"postedDate":"May 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-05T12:56:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-30 09:18:42","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6754101","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6754101","identity":"rs-6754101","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}