ERBB4 mutation

NGS at diagnosis can be extremely useful in risk stratification of AML patients undergoing allo-HSCT, potentially allowing adequate post-transplant interventions. Notably, the 2-year LFS of 70% for patients harboring RUNX1 and/or ASXL1 and/or SRSF2 mutation indicates that allo-HSCT can overcome the adverse risk associated with these somatic mutations at diagnosis.

P2, N=0, Withdrawn, Yonsei University | N=50 --> 0 | Not yet recruiting --> Withdrawn

P1, N=93, Active, not recruiting, M.D. Anderson Cancer Center | Recruiting --> Active, not recruiting | Trial completion date: Oct 2023 --> Oct 2025 | Trial primary completion date: Oct 2023 --> Oct 2025

Patients with oncogenic ERBB4 mutations (n=3) harbored also TP53 alterations, which may contribute to the lack of response to neratinib, as has been suggested for ERBB2-mutant patients.ConclusionMany of the recurrent ERBB4 mutations are oncogenic. Further investigation into potential utility of clinically used pan-ERBB inhibitors, such as neratinib, for patients whose tumors harbor these ERBB4 mutations is warranted.

We then developed CRISPR/Cas9-modified selection-free melanoma cell lines for interrogating the role of these mutations as biomarkers of response to the oral, irreversible pan-HER (EGFR, HER2, HER4) tyrosine kinase inhibitor (TKI) neratinib (NER). Two melanoma cell lines (WM115, SKMEL24) were genome-edited by using a selection-free CRISPR/Cas9 approach... CRISPR/Cas9 technology can be utilised to introduce single-point mutations in HER4 to melanoma cell lines. In vitro functional characterisation of the isolated HER4 CRISPR/Cas9-edited melanoma cell lines will be performed in order to understand the activating potential of HER4 R106C and R711C and their sensitivity to NER.

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.

P1, N=120, Recruiting, M.D. Anderson Cancer Center | Trial primary completion date: Oct 2022 --> Oct 2023

In the present study we found mostly concordance concerning the ERBB4 mutation between both primary PCa samples and matched lymph node metastasis, underlining that the identification of alterations in the primary tumor is extremely important for cancer prognosis prediction.

P2, N=50, Not yet recruiting, Yonsei University

In E872K ErbB4-overexpressing cells, but not in wild-type ErbB4-overexpressing cells, the number of VM tubes was significantly decreased by low-dose treatment with the ErbB inhibitor afatinib. Taken together, our findings demonstrated the significance of ErbB4-mediated VM formation, and suggested the possibility of ErbB4 mutations as effective targets in breast cancer.

Furthermore, we are determining whether prioritized ERBB4 mutants found in BRAF-WT melanomas exhibit greater signaling and oncogenic activities than WT ERBB4. Consequently, these experiments will establish a functional role for ERBB4 mutations and expression in BRAF-WT melanomas and will identify potential strategies for disrupting oncogenic ERBB4 signaling in these tumors.

These data suggest that melanoma and EG cancers are the cancer types with the highest rate of HER4 mutations. In vitro functional characterization of the identified HER4 mutations is now required to further explore their value as biomarkers of response to NER.

In a prospective cohort of mCRC pts, we have shown how exosome-based liquid biopsy and some cytokines analysis might provide relevant clinical information to therapeutic stratification that must be investigated in wide studies.

ERBB4 mutations could serve as a predictive biomarker for the prognosis of ICIs treatment. The systematic nomogram was proven to have the great potential for evaluating the efficacy of ICIs therapy for advanced NSCLC patients.

CDK6 CNV, GRIN2A, BRCA2, EGFR D761N, EGFR Q791H, EGFR V843I, and ERBB4 mutation genes may possibly be new resistant mechanisms. Patients with undetectable cfDNA during the third-generation EGFR TKI treatment have superior clinical outcomes, and dynamic cfDNA analysis by NGS is valuable to explore potential resistant mechanisms.

Conclusion TP53, ERBB4, EZH2, KEAP1 gene accompanied may have less correlation with AKT1 mutation in NSCLC patients. We report different mutations than those previously reported, which emphasizes the importance of personalized medicine that could be empowered by the use of bioinformatics tools in the diagnostic process and therapeutic approaches.

Conclusions This finding broadened the clinical application of TKIs targeted to ERBB2 or pan-ERBB, suggesting that they may provide therapeutic benefits to GC patients with ERBB4 overexpression or mutations. Moreover, ERBB4 is supposed to be a significant biomarker for GC treatment.

In silico analyses of the TCGA-SKCM dataset indicate that ERBB4 mutant alleles function as drivers of BRAF WT MM. We will present our progress in developing and validating in vitro positive selection strategies to identify which of the 76 ERBB4 mutant alleles found in the TCGA-SKCM dataset function as bona fide drivers of BRAF WT MMs.

In silico analyses of the TCGA-SKCM dataset indicate that ERBB4 mutant alleles function as drivers of BRAF WT MM. We will present our progress in developing and validating in vitro positive selection strategies to identify which of the 76 ERBB4 mutant alleles found in the TCGA-SKCM dataset function as bona fide drivers of BRAF WT MMs.

Given the fact that ErbB4 mutation is one of the most common genetic alterations in melanoma cells, we demonstrated that a typical oncogenic ErbB4 mutant was resistant to the negative feedback regulation to maintain a highly active status of tyrosine kinase activity. Together, these findings indicate that feedback mechanisms are key switches determining oncogenic potentials of ErbB receptor kinases.

In silico analyses of the TCGA-SKCM dataset indicate that ERBB4 mutant alleles function as drivers of BRAF WT MM. We will present our progress in developing and validating positive selection strategies to identify which of the 76 ERBB4 mutant alleles found in the TCGA-SKCM dataset function as bona fide drivers of BRAF WT MMs.