EPHA5 mutation

However, this RHOA mutation (R129W) was not found in index patients in other families. The RHOA mutation (R129W) emerges as a potential causative gene for HDGC, but only in one family, indicating a need for further studies to understand its role in HDGC pathogenesis fully.

PI3K/mTOR dual inhibition, PI3Kalpha inhibitor, AKT inhibitor, FGFR inhibitor, ALK/IGF1R inhibitor, CDK4/6 inhibitor, BCl2 inhibitor, WEE1 inhibitor, ATR inhibitor, DNA-PK inhibitor, AT2AR inhibitor, Mcl-1 inhibitor, MEK1/2 inhibitor, EZH2 inhibitor, HDAC inhibitor, CDK9 inhibitor, DNMT3 inhibitor, BRD4/BET inhibitor, JAK2 inhibitor, CXCR4 inhibitor, FAK inhibitor, BTK inhibitor, eribulin, & VEGFR2/ PDGFR/FGFR or VEGFR2/c-MET/Axl triple blockage might be effective on TW2.6 and reverse treatment refractoriness, maybe through the inhibition of mesenchymal transformation, pRB, & PI3K/AKT /mTOR signaling and the modulation of stemness & PD1/PDL1 pathway...All cell lines will be tried to be categorized as TCGA subtypes for the reference of future drug combinations.Cell linesSCC25KBSASCAL27FaDuSCC15SCC9SCC4TW2.6Differ- entiationWellPoorPoorPoorPoorWellWellWellWell, but rapidly replicated, with high hyper-diploidy & complex rearrangementsHPV statusHPV 16/18HPV18--HPV 16/18--HPV 6/11-EGFR statusMediumLowHighHighMediumHighLowMedium to highUnknownDocetaxel sensitivity+++++++++++++ to +++++-+Cisplatin sensitivity+++++++++++++- to +-- to +5-FU sensitivity+++++++++++-+ to ++-- to +Afatinib sensitivity+++- to +-+++++ to +++++++++-Polo-like kinase Inhibitor sensitivity+++++++++++++ to +++- to +-- to +VEGFR2 Inhibitor sensitivity----+++++--++PI3K/ mTOR inhibitorAll cell lines sensitiveCDK4/6 Inhibitor response+++- to ++++++ to +++++++++++++ to +++Western blotsWeak p-AKT & VEGF-A, mild PDL1 and BMI-1, Gli-1(+)Weak p-AKT, mild PDL1 and strong VEGF-A & BMI-1, p16(+)Moderate p-AKT & BMI-1, high PDL1, mild VEGF-AHigh p-AKT & VEGF-A, mild PDL1 & BMI-1High VEGF-A, moderate p-AKT & PDL1, weak BMI-1, Gli-1(+)Weak p-AKT & VEGF-A, mild PDL1 & BMI-1Weak p-AKT, VEGF-A, & BMI-1, moderate PDL1Moderate p-AKT & VEGF-A, strong BMI-1, mild PDL1, Gli-1(+)High p-AKT, PDL1, & VEGF-A and moderate BMI-1NGSCCND1 gain, CDKN2A deletion, FRG1 mutation, HGF mutation, p53 mutation, ATR mutation, SMO mutation, RUNX1T1 mutationSTK11 mutation, PDGFRA mutation, IGF1 mutation, BCOR mutation, EGFR mutation, NOTCH1 mutation, MET mutation, IKZF1 mutation, NFKB1 mutation, DPYD mutation, FGFR4 mutation, BRCA1 mutation, MSH2 mutation, DNMT3A mutationKRAS mutation, MDM2 mutation, TMB-H, AXIN1 loss, RAD51D mutation, NOTCH1/2 mutation, ERBB4 mutation, PALB2 mutation, p53 mutation, POLE mutation, CASP8 mutation, BRCA2 mutation, RNF43 mutation, LRP1B mutation, MET mutationCDKN2A deletion, EGFR amplification, SMAD4 mutation, TMB-H, LRP1B mutation, APC mutation, CASP8 mutation, CREBBP mutation, PIK3CG mutation, NRAS mutation, ABL1 mutation, FGF23 mutation, HGF mutation, ATRX mutation, p53 mutation, ERBB2 mutation, ROS1 mutation, EP300 mutation, NRAS mutation, CDKN1A mutation, KDM6A mutation, FLT4 mutationCCND1 gain, CDKN2A deletion, FLCN mutation, TMB-H, LRP1B mutation, SMAD4 loss, SF3B1 mutation, FAT1 mutation, VHL mutation, NOTCH3 mutation, EPHA5 mutation, p53 mutation, ERCC2 mutationCCND1 gain, EGFR amplification, SMO mutation, ATR mutation, FAT1 loss, NTRK1 mutation, KMT2D mutation, p53 mutation, NOTCH3 mutationCDKN2A deletion, AXIN2 amplification, SMAD3 loss, HRAS mutation, ATR mutation, NF1 mutation. IGF1R mutation, FLCN mutation, KEAP1 mutation, ASXL1 mutation, PMS2 mutationCCND1 gain, NF1 loss, LRP1B mutation, NSD1 mutation, KMT2D mutation, p53 mutation, EPHA2 mutationFAT1 loss, CCND3/FGF10 amplification, PIK3CA H1047R mutation, STK11 mutation, RICTOR/FLCN amplification, VEGF-A amplification , TSC2 mutation, EPHB1 mutation, MAP2K4 mutation, KDM5A mutation, PDGFRB mutation, SETD2 mutation, RPTOR mutation, APC mutation, DDR2 mutation, ATM mutation, MDM2 mutation, p53 mutation, CDK12 mutation, HRAS mutation, MYC mutation, CDK8 mutation, ARID1B lossOutcomesBest; like TCGA CL (HPV+) subtypeLike TCGA basal subtype, but responded to particular treatments eachBasalBasalLike TCGA mesen-chymal subtype (HPV+)Like TCGA CL(HPV-) subtype, different characters between these 3 cell linesCL(HPV-) subtypeCL(HPV-) subtypeWorse; like TCGA EMT subtype (HPV-)Potential treatmentsAll sensitive maybe; Hedgehog inhibitor , HGF/c-MET inhibitor, and I/O could be tried(1) Taxane, cisplatin, PLKi (2) mTORi (3) IGF1Ri, METi, PDGFRi, FGFRi (4) Epigenetics (5) I/O(1) Taxane, cisplatin, 5-FU, PLKi (2) CDK4/6i (3) I/O (4) DDRi (5) KRASi, METi, HERi (6) p53 reactivator and MDM2/Mcl-1 inhibitor(1) Taxane, cisplatin, 5-FU, PLKi (2) CDK4/6i (3) Mild EGFRi response (4) I/O (5) NRASi, FGFRi, HGF/c-METi/ROS1i/HERi (6) p53 reactivator/DDRi/Epigenetics(1) Cisplatin, 5-FU (2) EGFRi and VEGFR2i (3) Weak to PLKi & CDK4/6i (4) I/O (5) mTORi (6) Ephi (7) DDR/Epigenetics (8) p53 reactivator (9) HIFi(1) Taxane and PLKi (2) EGFRi, VEGFR2i, CDK4/6i (3) NTRKi (4) Hedgehog inhibitor (5) DDRi, epigenetics,& p53 reactivator(1) Taxane &5-FU (2) EGFRi (3) HRASi (4) DDRi/Epigenetics (5) I/O (6) IGF1Ri (7) mTORi(1) EGFRi (2) CDK4/6i (3) I/O (4) Epigenetics (5) Ephi (6) p53 reactivator(1) CDK4/6 inhibitor (2) Multi-targeted VEGFR TKI (3) PI3K/AKT/mTOR inhibitor (4) ICIs combination (5) p53 reactivator/ DDR interventions/Epigenetics (6) Dasatinib, HRASi, EphB1/B4 interventions Further NGS analysis may translate these HNSCC cell lines to represent TCGA subtypes for the reference of future drug combinations, esp... Further NGS analysis may translate these HNSCC cell lines to represent TCGA subtypes for the reference of future drug combinations, esp. immunotherapy, basic/translational research, and animal models. LRP1B will be a potential ICIs efficacy biomarker in HNSCC.

We have identified a 3-gene signature (EPHA5, BCL6, and ERBB2) that is predictive of response to neoadjuvant chemoradiotherapy and a separate prognostic 9-gene classifier that predicts survival outcomes. These panels provide significant potential for personalized management of locally advanced esophageal cancer.

EPHA5 mutant NSCLC may represent a subpopulation which showed worse response after treatment of atezolizumab compared to wild-type ones.

Materials/ We assembled a cohort of 34 patients with locally advanced esophageal adenocarcinoma, with the majority (21) receiving concurrent chemoradiotherapy with carboplatin/paclitaxel. We have identified a 3-gene signature (EPHA5, BCL6 and ERBB2) that is predictive of response to neoadjuvant therapy and a separate 9 gene classifier which prognosticates for survival outcomes. These provide significant potential for personalized management of locally advanced esophageal cancer.

We have identified a 3-gene signature (EPHA5, BCL6 and ERBB2) that is predictive of response to neoadjuvant therapy and a separate 9 gene classifier which prognosticates for survival outcomes. These provide significant potential for personalized management of locally advanced esophageal cancer.

Most importantly, clinical analysis of a Memorial Sloan Kettering Cancer Center (MSKCC) immunotherapy cohort indicated that LUAD patients with EPHA5 mutations who were treated with immunotherapy had markedly prolonged survival times. Our results revealed the correlation of EPHA5 mutations with tumor immune microenvironment and predictive factors for immunotherapy, implying the potential of EPHA5 mutations as a prognostic marker for the prognosis of LUAD patients to immune checkpoint blockade therapy.

Different high frequency gene mutations could be found between the patients with high and negative PDL1. PDL1 expression combined with specific gene mutation may better predict the survival for patients receiving atezolizumab.

With recent advances in the treatment of cancer, there is increased emphasis on the importance of identifying molecular markers to predict treatment response and outcomes, thereby allowing precision oncology. In this study, we hypothesized that there is a "specific biologic signature" in the biology of the cancer in long-term survivors that allows sensitivity to systemic therapy and durability of response. We found that DNA damage repair pathway alterations, combined with favorable anticancer immunity, may have contributed to exceptional responses to standard anticancer therapies in exceptional responders analyzed in this single-center retrospective study. It is very likely that an in-depth examination of outlier responses will become a standard component of drug development in the future.