Pareto Optimization Identifies Diverse Set of Phosphorylation Signatures Predicting Response to Treatment with Dasatinib.
ABSTRACT: Multivariate biomarkers that can predict the effectiveness of targeted therapy in individual patients are highly desired. Previous biomarker discovery studies have largely focused on the identification of single biomarker signatures, aimed at maximizing prediction accuracy. Here, we present a different approach that identifies multiple biomarkers by simultaneously optimizing their predictive power, number of features, and proximity to the drug target in a protein-protein interaction network. To this end, we incorporated NSGA-II, a fast and elitist multi-objective optimization algorithm that is based on the principle of Pareto optimality, into the biomarker discovery workflow. The method was applied to quantitative phosphoproteome data of 19 non-small cell lung cancer (NSCLC) cell lines from a previous biomarker study. The algorithm successfully identified a total of 77 candidate biomarker signatures predicting response to treatment with dasatinib. Through filtering and similarity clustering, this set was trimmed to four final biomarker signatures, which then were validated on an independent set of breast cancer cell lines. All four candidates reached the same good prediction accuracy (83%) as the originally published biomarker. Although the newly discovered signatures were diverse in their composition and in their size, the central protein of the originally published signature - integrin ?4 (ITGB4) - was also present in all four Pareto signatures, confirming its pivotal role in predicting dasatinib response in NSCLC cell lines. In summary, the method presented here allows for a robust and simultaneous identification of multiple multivariate biomarkers that are optimized for prediction performance, size, and relevance.
Project description:The ability to predict the efficacy of molecularly targeted therapies for non-small cell lung cancer (NSCLC) for an individual patient remains problematic. The purpose of this study was to identify, using a refined "coexpression extrapolation (COXEN)" algorithm with a continuous spectrum of drug activity, tumor biomarkers that predict drug sensitivity and therapeutic efficacy in NSCLC to Vorinostat, a histone deacetylase inhibitor, and Velcade, a proteasome inhibitor. Using our refined COXEN algorithm, biomarker prediction models were discovered and trained for Vorinostat and Velcade based on the in vitro drug activity profiles of nine NSCLC cell lines (NCI-9). Independently, a panel of 40 NSCLC cell lines (UVA-40) were treated with Vorinostat or Velcade to obtain 50% growth inhibition values. Genome-wide expression profiles for both the NCI-9 and UVA-40 cell lines were determined using the Affymetrix HG-U133A platform. Modeling generated multigene expression signatures for Vorinostat (45-gene; P = 0.002) and Velcade (15-gene; P = 0.0002), with one overlapping gene (CFLAR). Examination of Vorinostat gene ontogeny revealed a predilection for cellular replication and death, whereas that of Velcade suggested involvement in cellular development and carcinogenesis. Multivariate regression modeling of the refined COXEN scores significantly predicted the activity of combination therapy in NSCLC cells (P = 0.007). Through the refinement of the COXEN algorithm, we provide an in silico method to generate biomarkers that predict tumor sensitivity to molecularly targeted therapies. Use of this refined COXEN method has significant implications for the a priori examination of targeted therapies to more effectively streamline subsequent clinical trial design and cost.
Project description:Epidermal growth factor receptor - tyrosine kinase inhibitor (EGFR-TKI) is the first choice of treatment for advanced non-small cell lung cancer (NSCLC) patients harbouring activating EGFR mutations. However, single agent usually has limited efficacy due to heterogeneous resistant mechanisms of cancer cells. Thus drug combination therapy would offer more benefits by synergistic interactions and avoidance of resistance emergence. In this study, we selected 8 NSCLC cell lines with different genetic characteristics as research models to investigate the efficacy of 4 agents (gefitinib, cetuximab, afatinib and dasatinib) and their combinations. As a single agent, both afatinib and dasatinib showed more inhibition against cell proliferation than gefitinib and cetuximab. Afatinib combined with dasatinib demonstrated significantly high efficacy against 7 gefitinib-resistant NSCLC cell lines. Moreover, it reversed the resistance to the 4 studied single agents in PTEN mutated NSCLC cells. By studying the activity of EGFR, Src and their downstream signalling pathways including PI3K/PTEN/Akt, Ras/Raf/MEK/ERK, Src/FAK and JAK/Stat, we demonstrated the synergistic interaction between afatinib and dasatinib was not only due to their blockage of different signalling pathways but also the complemental inhibition of the related signalling molecules such as Stat3. We also found that the level of Src, Stat3, and MAPK may be useful biomarkers predicating synergism between afatinib and dasatinib for the treatment of gefitinib-resistant NSCLC cells.
Project description:Insulin-like growth factor (IGF)-binding protein-2 (IGFBP2) expression is increased in various types of cancers, including in a subset of patients with lung cancer. Because IGFBP2 is involved in signal transduction of some critical cancer-related pathways, we analyzed the association between IGFBP2 and response to pathway-targeted agents in seven human non-small cell lung cancer (NSCLC) cell lines. Western blot analysis and ELISA showed that four of the seven NSCLC cell lines analyzed expressed high levels of IGFBP2, whereas the remaining three had barely detectable IGFBP2. Susceptibilities of those seven cell lines to nine anticancer agents targeting to IGF1R, Src, FAK, MEK, and AKT were determined by a dose-dependent cell viability assay. The results showed that high IGFBP2 levels were associated with resistance to dasatinib and, to a lesser degree, to sacaratinib, but not to other agents. Ectopic IGFBP2 overexpression or knockdown revealed that changing IGFBP2 expression levels reversed dasatinib susceptibility phenotype, suggesting a causal relationship between IGFBP2 expression and dasatinib resistance. Molecular characterization revealed that focal adhesion kinase (FAK) activation was associated with increased IGFBP2 expression and partially contributed to IGFBP2-mediated dasatinib resistance. Treatment with a combination of dasatinib and FAK inhibitor led to enhanced antitumor activity in IGFBP2-overexpressing and dasatinib-resistant NSCLC cells in vitro and in vivo. Our results showed that the IGFBP2/FAK pathway is causally associated with dasatinib resistance and may be used as biomarkers for identification of dasatinib responders among patients with lung cancer. Simultaneous targeting on Src and FAK will likely improve the therapeutic efficacy of dasatinib for treatment of lung cancer.
Project description:miR-3127-5p is a primate-specific miRNA which is down-regulated in recurrent NSCLC tissue vs. matched primary tumor tissue (N = 15) and in tumor tissue vs. normal lung tissue (N = 177). Reduced miR-3127-5p expression is associated with a higher Ki-67 proliferation index and unfavorable prognosis in NSCLC. Overexpression of miR-3127-5p significantly reduced NSCLC cells proliferation, migration, and motility in vitro and in vivo. The oncogene ABL1 was a direct miR-3127-5p target, and miR-3127-5p regulated the activation of the Abl/Ras/ERK pathway and transactivated downstream proliferation/metastasis-associated molecules. Overexpression of miR-3127-5p in A549 or H292 cells resulted in enhanced resistance to dasatinib, an Abl/src tyrosine kinase inhibitor. miR-3127-5p expression levels were correlated with dasatinib sensitivity in NSCLC cell lines without K-Ras G12 mutation. In conclusion, miR-3127-5p acts as a tumor suppressor gene and is a potential biomarker for dasatinib sensitivity in the non-mutated Ras subset of NSCLC.
Project description:EGFR and Src are frequently activated in non-small cell lung cancer (NSCLC). In preclinical models, combining EGFR and Src inhibition has additive synergistic effects. We conducted a phase I/II trial of the combination of Src inhibitor dasatinib with EGFR inhibitor erlotinib to determine the maximum tolerated dose (MTD), pharmacokinetic drug interactions, biomarkers, and efficacy in NSCLC.The phase I 3+3 dose-escalation study enrolled patients with solid tumors to determine the MTD. The phase II trial enrolled patients with advanced NSCLC who had undergone no previous treatments to determine progression-free survival (PFS) and response. Pharmacokinetic and tissue biomarker analyses were performed.MTD was 150 mg of erlotinib and 70 mg of dasatinib daily based on 12 patients treated in the phase I portion. No responses were observed in phase I. The 35 NSCLC patients treated in phase II had an overall disease control rate of 59% at 6 weeks. Five patients (15%) had partial responses; all had activating EGFR mutations. Median PFS was 3.3 months. Epithelial-mesenchymal transition markers did not correlate with outcomes.The combination of erlotinib and dasatinib is safe and feasible in NSCLC. The results of this study do not support use of this combination in molecularly unselected NSCLC.
Project description:Background: Increases in expression of ADAM10 and ADAM17 genes and proteins are inconsistently found in cancer lesions, and are not validated as clinically useful biomarkers. The enzyme-specific proteolytic activities, which are solely mediated by the active mature enzymes, directly reflect enzyme cellular functions and might be superior biomarkers than the enzyme gene or protein expressions, which comprise the inactive proenzymes and active and inactivated mature enzymes. Methods: Using a recent modification of the proteolytic activity matrix analysis (PrAMA) measuring specific enzyme activities in cell and tissue lysates, we examined the specific sheddase activities of ADAM10 (ADAM10sa) and ADAM17 (ADAM17sa) in human non-small cell lung-carcinoma (NSCLC) cell lines, patient primary tumors and blood exosomes, and the noncancerous counterparts. Results: NSCLC cell lines and patient tumors and exosomes consistently showed significant increases of ADAM10sa relative to their normal, inflammatory and/or benign-tumor controls. Additionally, stage IA-IIB NSCLC primary tumors of patients who died of the disease exhibited greater increases of ADAM10sa than those of patients who survived 5 years following diagnosis and surgery. In contrast, NSCLC cell lines and patient tumors and exosomes did not display increases of ADAM17sa. Conclusions: This study is the first to investigate enzyme-specific proteolytic activities as potential cancer biomarkers. It provides a proof-of-concept that ADAM10sa could be a biomarker for NSCLC early detection and outcome prediction. To ascertain that ADAM10sa is a useful cancer biomarker, further robust clinical validation studies are needed.
Project description:Targeted drugs are less toxic than traditional chemotherapeutic therapies; however, the proportion of patients that benefit from these drugs is often smaller. A marker that confidently predicts patient response to a specific therapy would allow an individual therapy selection most likely to benefit the patient. Here, we used quantitative mass spectrometry to globally profile the basal phosphoproteome of a panel of non-small cell lung cancer cell lines. The effect of the kinase inhibitor dasatinib on cellular growth was tested against the same panel. From the phosphoproteome profiles, we identified 58 phosphorylation sites, which consistently differ between sensitive and resistant cell lines. Many of the corresponding proteins are involved in cell adhesion and cytoskeleton organization. We showed that a signature of only 12 phosphorylation sites is sufficient to accurately predict dasatinib sensitivity. Four of the phosphorylation sites belong to integrin ?4, a protein that mediates cell-matrix or cell-cell adhesion. The signature was validated in cross-validation and label switch experiments and in six independently profiled breast cancer cell lines. The study supports that the phosphorylation of integrin ?4, as well as eight further proteins comprising the signature, are candidate biomarkers for predicting response to dasatinib in solid tumors. Furthermore, our results show that identifying predictive phosphorylation signatures from global, quantitative phosphoproteomic data is possible and can open a new path to discovering molecular markers for response prediction.
Project description:Advances in molecular biology and bioinformatics have resulted in the identification of a number of potential biomarkers that could be relevant in the management of patients with non-small-cell lung cancer (NSCLC). Although there is an increasing amount of literature related to these biomarkers, major issues need to be resolved including validity and reproducibility of results. Additionally, in order to interpret the existing literature accurately, a clear distinction must be made between the prognostic and predictive value of biomarkers. The practical applicability of biomarker discovery for patients with lung cancer includes the identification of patients with early-stage NSCLC who are most likely to benefit from adjuvant therapy. Information gleaned from biomarkers has the potential to help in evaluating the role of targeted therapies including immunotherapy in the neoadjuvant and adjuvant setting. The role of gene signatures and the use of newer platforms such as RNA, methylation, and protein signatures is being explored in patients with early-stage NSCLC. This review focuses on the applications of biomarker discovery in patients with early-stage NSCLC.
Project description:Dasatinib has anti-proliferative and anti-invasive effects in melanoma cell lines. However clinical trials have shown modest activity for dasatinib in metastatic melanoma. Although dasatinib targets SRC kinase, neither expression nor phosphorylation of SRC appears to predict response to dasatinib. Identification of predictive biomarkers for dasatinib may facilitate selection of melanoma patients who are more likely to respond to dasatinib. We correlated the anti-proliferative effects of dasatinib in 8 melanoma cell lines with expression of a previously identified 6-gene biomarker panel. We examined the relationship between response to dasatinib and expression of each gene at both the mRNA and protein level. Dasatinib inhibited growth in 3 of the 8 cell lines tested. mRNA expression of the panel of 6 biomarkers did not correlate with response, whilst elevated protein expression of ANXA1, CAV-1 and EphA2 correlated significantly with response to dasatinib in the panel of cell lines. Expression of ANXA1, CAV-1 and EphA2 were analysed in 124 melanoma samples by immunohistochemistry. ANXA1 protein was detected in 81 % (97/120) of tumours, CAV-1 in 44 % (54/122) of tumours and EphA2 in 74 % (90/121) of tumours. Thirty one % (35/113) of tumours tested expressed all three markers and 19 % (21/112) had moderate or strong expression of ANXA1, CAV-1 and EphA2. Seventeen percent (19/112) of melanoma samples were positive for SRC kinase expression, combined with high expression of ANXA1, CAV-1 and EphA2. This subgroup may represent a population of melanoma patients who would be more likely to derive clinical benefit from dasatinib treatment.
Project description:Therapies targeting SRC family kinases (SFKs) have shown efficacy in treating non-small cell lung cancer (NSCLC). However, recent clinical trials have found that the SFK inhibitor dasatinib is ineffective in some patient cohorts. Regardless, dasatinib treatment may benefit some NSCLC patient subgroups. Here, we investigated whether expression of LYN, a member of the SFK family, is associated with patient survival, the efficacy of dasatinib, and/or NSCLC cell viability. LYN expression was associated with poor overall survival in a multivariate analysis, and this association was strongest in non-smoker female patients with adenocarcinoma (ADC). In lung ADC cells, LYN expression enhanced cell proliferation, migration, and invasion. Dasatinib inhibited LYN activity and decreased cell viability in LYN-positive ADC cell lines and xenografts. Additionally, we identified the SFKs SRC and YES as candidate dasatinib targets in LYN-negative ADC cell lines. Our findings suggest that LYN is a useful prognostic marker and a selective target of dasatinib therapy in the lung ADC subpopulation especially in female non-smokers with lung ADC.