{"doi":"10.1200/jco.2019.37.15_suppl.e15565","title":"<i>KRAS</i> amplification and mutation as independent events in gastroesophageal adenocarcinomas (GEA).","abstract":"<jats:p> e15565 </jats:p><jats:p> Background: KRAS mutations are common oncogenic events across cancers, but effective RAS-directed therapies are lacking. However, recent studies support use of PD-1 blockade in most subsets of lung cancer with KRAS short variant mutations (KRAS<jats:sup>SV</jats:sup>) (PMID: 28039262), and preclinical data supports combined MEK and SHP2 inhibition in KRAS amplified ( KRAS<jats:sup>a</jats:sup>) GEA (PMID: 30093730). We sought to explore the landscape of KRAS altered GEA and compare genomic profiles of KRAS-altered and KRAS wild-type (WT) cases for biomarkers of response to targeted therapies and immune checkpoint inhibitors. Methods: 6,667 tissue specimens from patients with advanced GEA were assayed using hybrid capture-based comprehensive genomic profiling. Tumor mutational burden (TMB) was determined on up to 1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined on 95 or 114 loci. Descriptive statistics were used to compare among subgroups. Results: KRAS<jats:sup>SV</jats:sup> and KRAS<jats:sup>a</jats:sup> were identified in 11% and 5.8% of gastric adenocarcinoma (GA), respectively, and in 7.2% and 17% of esophageal adenocarcinoma (EA), respectively. KRAS<jats:sup>a</jats:sup> and KRAS<jats:sup>SV</jats:sup> were nearly mutually exclusive, co-occurring in only 4.4% of KRAS altered cases. ERBB2 alterations were less common in KRAS<jats:sup>SV</jats:sup> and KRAS<jats:sup>a</jats:sup> GEA (both 9%) as compared with KRAS WT GEA (19%) (p = 1.9E-16). EGFR<jats:sup>a</jats:sup> was less common in KRAS<jats:sup>SV</jats:sup> vs KRAS<jats:sup>a</jats:sup> GEA (1.9% vs 9.3%, p = 2.6E-8), whereas PIK3CA<jats:sup>SV</jats:sup> was more common in KRAS<jats:sup>SV</jats:sup> vs KRAS<jats:sup>a</jats:sup> (16% vs 5.0%, p = 1.5E-11). Median TMB for all groups was similar; however, KRAS<jats:sup>SV</jats:sup> GEA had a higher mean TMB (9.7 mut/Mb) as compared to KRAS<jats:sup>a</jats:sup> (5.1 mut/Mb, p = 5.0E-12) and KRAS WT cases (5.8 mut/Mb, p = 2.2E-07). KRAS codon 12/13 accounted for &gt; 80% of predicted pathogenic mutations. MSI-high was also more prevalent in KRAS<jats:sup>SV</jats:sup> (11.3%) vs KRAS<jats:sup>a</jats:sup> (0.9%, p = 4.8E-15) and KRAS WT GEA (2.4%, p = 1.8E-25). MSI-high KRAS<jats:sup>SV</jats:sup> GEA was associated with older patient age (median 72 years) and with high TMB (median 40.9 mut/mb). Conclusions: GA was enriched for KRAS mutation whereas EA was enriched for KRAS amplification. KRAS WT vs KRAS<jats:sup>SV</jats:sup> vs KRAS<jats:sup>a</jats:sup> each presented distinct genomic profiles. KRAS<jats:sup>a</jats:sup> in the absence of KRAS mutation exists in 11% of GEA and warrants further exploration to inform combination treatment strategies. </jats:p>","journal":"Journal of Clinical Oncology","year":2019,"id":594127,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1118546,"name":"Russell Madison","orcid":null,"position":1,"is_corresponding":false},{"id":258755,"name":"Jeffrey S. Ross","orcid":"0000-0001-8494-2596","position":2,"is_corresponding":false},{"id":1272,"name":"Vincent A. Miller","orcid":"0000-0003-1667-3771","position":3,"is_corresponding":false},{"id":1520751,"name":"Siraj Mahamed Ali","orcid":null,"position":4,"is_corresponding":false},{"id":1520752,"name":"Alexa Betzig Schrock","orcid":null,"position":5,"is_corresponding":false},{"id":1520753,"name":"Samuel Jacob Klempner","orcid":null,"position":6,"is_corresponding":false},{"id":505233,"name":"Joseph Chao","orcid":"0000-0002-1809-504X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"<i>KRAS</i> amplification and mutation as independent events in gastroesophageal adenocarcinomas (GEA).","abstract":"<jats:p> e15565 </jats:p><jats:p> Background: KRAS mutations are common oncogenic events across cancers, but effective RAS-directed therapies are lacking. However, recent studies support use of PD-1 blockade in most subsets of lung cancer with KRAS short variant mutations (KRAS<jats:sup>SV</jats:sup>) (PMID: 28039262), and preclinical data supports combined MEK and SHP2 inhibition in KRAS amplified ( KRAS<jats:sup>a</jats:sup>) GEA (PMID: 30093730). We sought to explore the landscape of KRAS altered GEA and compare genomic profiles of KRAS-altered and KRAS wild-type (WT) cases for biomarkers of response to targeted therapies and immune checkpoint inhibitors. Methods: 6,667 tissue specimens from patients with advanced GEA were assayed using hybrid capture-based comprehensive genomic profiling. Tumor mutational burden (TMB) was determined on up to 1.1 Mbp of sequenced DNA and microsatellite instability (MSI) was determined on 95 or 114 loci. Descriptive statistics were used to compare among subgroups. Results: KRAS<jats:sup>SV</jats:sup> and KRAS<jats:sup>a</jats:sup> were identified in 11% and 5.8% of gastric adenocarcinoma (GA), respectively, and in 7.2% and 17% of esophageal adenocarcinoma (EA), respectively. KRAS<jats:sup>a</jats:sup> and KRAS<jats:sup>SV</jats:sup> were nearly mutually exclusive, co-occurring in only 4.4% of KRAS altered cases. ERBB2 alterations were less common in KRAS<jats:sup>SV</jats:sup> and KRAS<jats:sup>a</jats:sup> GEA (both 9%) as compared with KRAS WT GEA (19%) (p = 1.9E-16). EGFR<jats:sup>a</jats:sup> was less common in KRAS<jats:sup>SV</jats:sup> vs KRAS<jats:sup>a</jats:sup> GEA (1.9% vs 9.3%, p = 2.6E-8), whereas PIK3CA<jats:sup>SV</jats:sup> was more common in KRAS<jats:sup>SV</jats:sup> vs KRAS<jats:sup>a</jats:sup> (16% vs 5.0%, p = 1.5E-11). Median TMB for all groups was similar; however, KRAS<jats:sup>SV</jats:sup> GEA had a higher mean TMB (9.7 mut/Mb) as compared to KRAS<jats:sup>a</jats:sup> (5.1 mut/Mb, p = 5.0E-12) and KRAS WT cases (5.8 mut/Mb, p = 2.2E-07). KRAS codon 12/13 accounted for &gt; 80% of predicted pathogenic mutations. MSI-high was also more prevalent in KRAS<jats:sup>SV</jats:sup> (11.3%) vs KRAS<jats:sup>a</jats:sup> (0.9%, p = 4.8E-15) and KRAS WT GEA (2.4%, p = 1.8E-25). MSI-high KRAS<jats:sup>SV</jats:sup> GEA was associated with older patient age (median 72 years) and with high TMB (median 40.9 mut/mb). Conclusions: GA was enriched for KRAS mutation whereas EA was enriched for KRAS amplification. KRAS WT vs KRAS<jats:sup>SV</jats:sup> vs KRAS<jats:sup>a</jats:sup> each presented distinct genomic profiles. KRAS<jats:sup>a</jats:sup> in the absence of KRAS mutation exists in 11% of GEA and warrants further exploration to inform combination treatment strategies. </jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":"https://openalex.org/W4229670017","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://ascopubs.org/doi/pdfdirect/10.1200/JCO.2019.37.15_suppl.e15565","host_type":"publisher"},{"url":"https://doi.org/10.1200/jco.2019.37.15_suppl.e15565","host_type":"journal"}],"fields_of_study":["Lung Cancer Treatments and Mutations","Colorectal Cancer Treatments and Studies","Cancer Genomics and Diagnostics"],"mesh_terms":[],"keywords":["KRAS","Medicine","Cancer research","Adenocarcinoma","Microsatellite instability","Cancer","Colorectal cancer","Internal medicine","Oncology","Biology","Gene","Genetics"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-27T13:35:31.473006Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}