Project description:CDK4/6 kinase inhibitors have shown great promise in clinical trials in various cancer types and have recently entered clinical trial for advanced prostate cancer. Although patients are expected to respond well to this class of drugs, development of resistance in some patients is anticipated. To pre-empt this and study how prostate cancer may evade CDK4/6 inhibition, new resistance models were generated from LNCaP and LAPC4 prostate cancer cells cells by prolonged culturing in presence of 0.5uM palbociclib. A shotgun phosphoproteomics approach was utilized and integrated with RNA sequencing data to unravel the molecular underpinnings of acquired resistance to palbociclib and resultant broad CDK4/6 inhibitor resistance.
Project description:The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents. Keywords: Gene expression profiling; correlation with outcome in clinical trials of the proteasome inhibitor bortezomib
Project description:The aims of this study were to assess the feasibility of prospective pharmacogenomics research in multicenter international clinical trials of bortezomib in multiple myeloma and to develop predictive classifiers of response and survival with bortezomib. Patients with relapsed myeloma enrolled in phase 2 and phase 3 clinical trials of bortezomib and consented to genomic analyses of pretreatment tumor samples. Bone marrow aspirates were subject to a negative-selection procedure to enrich for tumor cells, and these samples were used for gene expression profiling using DNA microarrays. Data quality and correlations with trial outcomes were assessed by multiple groups. Gene expression in this dataset was consistent with data published from a single-center study of newly diagnosed multiple myeloma. Response and survival classifiers were developed and shown to be significantly associated with outcome via testing on independent data. The survival classifier improved on the risk stratification provided by the International Staging System. Predictive models and biologic correlates of response show some specificity for bortezomib rather than dexamethasone. Informative gene expression data and genomic classifiers that predict clinical outcome can be derived from prospective clinical trials of new anticancer agents. Experiment Overall Design: Purified myeloma samples were collected prior to enrolment in clinical trials of bortezomib (PS-341). Samples were subject to replicate gene expression profiling using the Affymetrix 133A/B microarray. Data was normalized in MAS5.0 and the median of replicates is reported. Data was normalized to a Ttimmed mean of 15o and is NOT log transformed. Various patient parameters are reported as well as response, TTP and survival upon treatment with bortezomib or dexamethasone.
Project description:CDK4/6 kinase inhibitors have shown great promise in clinical trials in various cancer types and have recently entered clinical trial for advanced prostate cancer. Although patients are expected to respond well to this class of drugs, development of resistance in some patients is anticipated. To pre-empt this and study how prostate cancer may evade CDK4/6 inhibition, new resistance models were generated from LNCaP and LAPC4 prostate cancer cells cells by prolonged culturing in presence of 0.5uM palbociclib. RNA sequencing data was integrated with phospho-proteomics to unravel the molecular underpinnings of acquired resistance to palbociclib and resultant broad CDK4/6 inhibitor resistance.
Project description:Cyclin-dependent kinases 4 and 6 (CDK4/6) are essential drivers of the cell cycle and are also critical for the initiation and progression of diverse malignancies. Pharmacological inhibitors targeting CDK4/6 have demonstrated significant activity against various tumor types such as breast cancer. However, resistance to CDK4/6 inhibitors (CDK4/6i) (such as palbociclib) remains an immense obstacle in clinical and the underlying mechanisms have not been fully understood. Using quantitative high-throughput combinational screen (qHTCS) and genomic sequencing, we report that the Microphthalmia-associated transcription factor (MITF), was significantly elevated in palbociclib-resistance cells. Inhibition of MITF can enhance the therapeutic efficacy of Palbociclib and surmount Palbociclib resistance both in vitro and in vivo. Mechanistically, we found that O-GlcNAc transferase (OGT) modifies MITF with O-GlcNAcylation at Serine 49 (Ser49) within its nuclear localization signal (NLS), thereby promoting MITF binding to importin α/ β and facilitating its nuclear transportation, which is crucial in regulating senescence. Significantly, clinical studies also confirm that MITF was elevated in palbociclib-resistance patients. Collectively, these results reveal a previously unrecognized mechanism by which MITF-mediated palbociclib resistance, and provide valuable insights for the development of innovative therapeutic strategies in future clinical contexts.
Project description:We have analyzed gene expression microarray datasets from four different clinical trials to assess accuracy of gene expression based signature in predicting treatment complete response in patients with multiple myeloma. Two of four datasets were made available via The Intergroupe Francophone du Myélome (IFM) group, and remaining two datasets were downloaded from NCBI GEO portal with accession IDs: GSE19784 (HOVON65/GMMG-HD4 trial) and GSE9782 (APEX/SUMMIT trial). Analysis UUID: datasets_archive--2afcd42a-7e12-11e3-9145-5fcc1e060548--15-Jan-2014-12-23-44-CST. Following dataset provides gene expression microarray dataset for IFM-2005 trial involving 67 newly diagnosed patients with MM. A second and larger dataset involving 136 newly diagnosed patients with MM from IFM-2005 trial can be accessed via NCBI GSE ID: GSE39754. CD-138 purified plasma cells from 67 newly diagnosed patients with MM were profiled using Affymetrix Exon-1.0 ST microarray platform. Pre-processing and normalization of dataset was carried out using dChip (http://www.hsph.harvard.edu/cli/complab/dchip/exon.htm#expressio) and R package - aroma.affymetrx (http://www.aroma-project.org/vignettes/FIRMA-HumanExonArrayAnalsis). Patients subsequently received bortezomib based induction therapy, followed by autologus stem cell transplant. Post-induction treatment response is attached in metadata file.
Project description:Here we characterise the response of models of ER-positive breast cancer to treatment with the small molecule MDM2 inhibitor NVP-CGM097, a dihydroisoquinolinone derivative currently evaluated in a phase I clinical trial. We show that NVP-CGM097 reduces tumour cell viability of in vitro and in vivo models of endocrine sensitive, endocrine resistant and palbociclib (CDK4/6 inhibitor) resistant p53 wildtype (p53wt) ER-positive breast cancer. NVP-CGM097 synergises with both fulvestrant and palbociclib in models of therapy resistance. Importantly, we identify the key mechanisms of the synergistic interactions between NVP-CGM097 and endocrine therapy, which occurs through the inhibition of E2F Targets and G2M Checkpoint signalling and induction of senescence, rather than depending upon upregulation of p53 dependent apoptotic pathways. Moreover, we find these same pathways are synergistically targeted during the combination treatment of ER positive breast cancer models with NVP-CGM097 and palbociclib. This indicates the genuine potential of MDM2 inhibition as therapy in advanced ER-positive breast cancer as combination endocrine therapy and CDK4/6 inhibitor treatment becomes embedded as standard of care.