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Correlating phosphoproteomic signaling with castration resistant prostate cancer survival through regression analysis.

ABSTRACT: Prostate cancer most commonly presents as initially castration dependent, however in a minority of patients the disease will progress to a state of castration resistance. Here, approaches for correlating alterations in the phosphoproteome with androgen independent cell survival in the LNCaP, PC3, and MDa-PCa-2b cell lines are discussed. The performance of the regression techniques multiple linear, ridge, principal component, and partial least squares regression is compared. The predictive performance of these algorithms over randomized data sets and using the Akaike Information Criterion is explored, and principal component and partial least squares regression are found to outperform other regression approaches. The effect of altering the number of features versus observations on the R(2) value and predictive performance is also examined using the partial least squares regression model. Utilizing these approaches "drivers" of castration resistant disease can be identified whose modulation alters phenotypic outcomes. These data provide an empirical comparison of the various considerations when statistically analyzing phosphorylation data with the aim of correlating with phenotypic outcomes.

SUBMITTER: Lescarbeau R

PROVIDER: S-EPMC3967742 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Correlating phosphoproteomic signaling with castration resistant prostate cancer survival through regression analysis.

Lescarbeau Reynald R Kaplan David L DL

Molecular bioSystems 20140110 3

Prostate cancer most commonly presents as initially castration dependent, however in a minority of patients the disease will progress to a state of castration resistance. Here, approaches for correlating alterations in the phosphoproteome with androgen independent cell survival in the LNCaP, PC3, and MDa-PCa-2b cell lines are discussed. The performance of the regression techniques multiple linear, ridge, principal component, and partial least squares regression is compared. The predictive perfor ...[more]

PMID: 24413303

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Project description:BackgroundAlthough recent progress has been made in treating castration resistant prostate cancer, the interplay of signaling pathways which enable castration resistant growth is incompletely understood. A data driven, multivariate approach, was used in this study to predict prostate cancer cell survival based on the phosphorylation levels of key proteins in PC3, LNCaP, and MDA-PCa-2b cell lines in response to EGF, IGF1, IL6, TNF?, dihydrotestosterone, and docetaxel treatment.MethodsThe prostate cancer cell lines were treated with ligands or inhibitors, cell lyates were collected, and the amount of phosphoprotein quantified using 384 well ELISA assays. In separate experiments, relative cell viability was determined using an MTT assay. Normalized data was imported into Matlab where regression analysis was performed.ResultsBased on a linear model developed using partial least squares regression, p-Erk1/2 was found to correlate with castration resistant survival along with p-RPS6, and this model was determined to have a leave-one-out cross validated R2 value of 0.61. The effect of androgen on the phosphoproteome was examined, and increases in PI3K related phosphoproteins (p-Akt, p-RPS6, and p-GSK3) were observed which accounted for the majority of the significant increase in androgen-mediated cell survival. Simultaneous inhibition of the PI3K pathway and treatment with androgen resulted in a non-significant increase in survival. Given the strong effect of PI3K related signaling in enabling castration resistant survival, the specific effect of mTor versus complete inhibition was examined using targeted inhibitors. It was determine that mTor inhibition accounts for 52% of the effect of complete PI3K inhibition on cell survival. The differences in signaling between the cell lines were explored it was observed that MDA-PCa-2b exhibited far less activation of p-Erk in response to varying treatments, explaining one of the reasons for the lack of castration resistance.ConclusionIn this work, regression analysis to the phosphoproteome was used to illustrate the sources of castration resistance between the cell lines including reduced p-Erk signaling in MDA-PCa-2b and variations in p-JNK across the cell lines, as well as studying the signaling pathways which androgen acts through, and determining the response to treatment with targeted inhibitors.

Project description:From March through August 2015, nearly 60 teams from around the world participated in the Prostate Cancer Dream Challenge (PCDC). Participating teams were faced with the task of developing prediction models for patient survival and treatment discontinuation using baseline clinical variables collected on metastatic castrate-resistant prostate cancer (mCRPC) patients in the comparator arm of four phase III clinical trials. In total, over 2,000 mCRPC patients treated with first-line docetaxel comprised the training and testing data sets used in this challenge. In this paper we describe: (a) the sub-challenges comprising the PCDC, (b) the statistical metrics used to benchmark prediction performance, (c) our analytical approach, and finally (d) our team's overall performance in this challenge. Specifically, we discuss our curated, ad-hoc, feature selection (CAFS) strategy for identifying clinically important risk-predictors, the ensemble-based Cox proportional hazards regression framework used in our final submission, and the adaptation of our modeling framework based on the results from the intermittent leaderboard rounds. Strong predictors of patient survival were successfully identified utilizing our model building approach. Several of the identified predictors were new features created by our team via strategically merging collections of weak predictors. In each of the three intermittent leaderboard rounds, our prediction models scored among the top four models across all participating teams and our final submission ranked 9 th place overall with an integrated area under the curve (iAUC) of 0.7711 computed in an independent test set. While the prediction performance of teams placing between 2 nd- 10 th (iAUC: 0.7710-0.7789) was better than the current gold-standard prediction model for prostate cancer survival, the top-performing team, FIMM-UTU significantly outperformed all other contestants with an iAUC of 0.7915. In summary, our ensemble-based Cox regression framework with CAFS resulted in strong overall performance for predicting prostate cancer survival and represents a promising approach for future prediction problems.

Project description:BackgroundProstate cancer that recurs after initial treatment inevitably progresses to castration-resistant prostate cancer (CRPC), the lethal stage of the disease. Despite improvements in outcomes from next generation androgen receptor (AR)-axis inhibitors, CRPC remains incurable. Therapeutic strategies to target AR antagonist resistance are urgently needed to improve outcomes for men with this lethal form of prostate cancer.MethodsApoptosis and BCL2 family signaling were characterized in cell line models of CRPC. Quantitative real-time polymerase chain reaction and Western blot analysis were used to determine BCL2 expression levels. Drug sensitivity was determined by proliferation, survival and apoptosis analysis. Protein-protein interactions were evaluated by coimmunoprecipitation followed by Western blot detection.ResultsIn the present study, we identify antiapoptotic BCL2 protein signaling as a mechanism of resistance to AR antagonist enzalutamide. In CRPC cell line models, we found that BCL-xL and MCL-1 proteins block apoptosis through binding and sequestering proapoptotic proteins BIM and BAX, resulting in cell survival in response to enzalutamide. Treatment with BH3-mimetics targeting BCL-xL or MCL-1 disrupts these interactions and activates apoptosis, sensitizing CRPC cells to enzalutamide. Importantly, we demonstrate that PI3K/Akt signaling is activated in response to enzalutamide and mediates apoptosis evasion through inactivation of BAD, a BH3-only protein that activates proapoptotic signlaing through inhbition of BCL-xL. Inhibition of Akt activates BAD, resulting in increased apoptosis and sensitivity to enzalutamide, demonstrating an alternative therapeutic strategy to target drug resistance.ConclusionsThese results demonstrate that CRPC cells employ multiple mechanisms to mediate apoptosis evasion through BCL2 signaling, suggesting this pathway is critical for survival. This study provides a strong preclinical rationale for developing therapeutic strategies to target antiapoptotic BCL2 signaling in combination with AR antagonists to improve treatment options for patients with advanced prostate cancer.

Dataset Information

Correlating phosphoproteomic signaling with castration resistant prostate cancer survival through regression analysis.

Publications

Correlating phosphoproteomic signaling with castration resistant prostate cancer survival through regression analysis.

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