Construction and optimization of gene expression signatures for prediction of survival in two-arm clinical trials.

BACKGROUND: Gene expression signatures for the prediction of differential survival of patients undergoing anti-cancer therapies are of great interest because they can be used to prospectively stratify patients entering new clinical trials, or to determine optimal treatment for patients in more routine clinical settings. Unlike prognostic signatures however, predictive signatures require training set data from clinical studies with at least two treatment arms. As two-arm studies with gene expression profiling have been rarer than similar one-arm studies, the methodology for constructing and optimizing predictive signatures has been less prominently explored than for prognostic signatures. RESULTS: Focusing on two "use cases" of two-arm clinical trials, one for metastatic colorectal cancer (CRC) patients treated with the anti-angiogenic molecule aflibercept, and the other for triple negative breast cancer (TNBC) patients treated with the small molecule iniparib, we present derivation steps and quantitative and graphical tools for the construction and optimization of signatures for the prediction of progression-free survival based on cross-validated multivariate Cox models. This general methodology is organized around two more specific approaches which we have called subtype correlation (subC) and mechanism-of-action (MOA) modeling, each of which leverage a priori knowledge of molecular subtypes of tumors or drug MOA for a given indication. The tools and concepts presented here include the so-called differential log-hazard ratio, the survival scatter plot, the hazard ratio receiver operating characteristic, the area between curves and the patient selection matrix. In the CRC use case for instance, the resulting signature stratifies the patient population into "sensitive" and "relatively-resistant" groups achieving a more than two-fold difference in the aflibercept-to-control hazard ratios across signature-defined patient groups. Through cross-validation and resampling the probability of generalization of the signature to similar CRC data sets is predicted to be high. CONCLUSIONS: The tools presented here should be of general use for building and using predictive multivariate signatures in oncology and in other therapeutic areas.

Large-scale transcriptomic analysis reveals that pridopidine reverses aberrant gene expression and activates neuroprotective pathways in the YAC128 HD mouse.

BACKGROUND: Huntington Disease (HD) is an incurable autosomal dominant neurodegenerative disorder driven by an expansion repeat giving rise to the mutant huntingtin protein (mHtt), which is known to disrupt a multitude of transcriptional pathways. Pridopidine, a small molecule in development for treatment of HD, has been shown to improve motor symptoms in HD patients. In HD animal models, pridopidine exerts neuroprotective effects and improves behavioral and motor functions. Pridopidine binds primarily to the sigma-1 receptor, (IC50 ~ 100 nM), which mediates its neuroprotective properties, such as rescue of spine density and aberrant calcium signaling in HD neuronal cultures. Pridopidine enhances brain-derived neurotrophic factor (BDNF) secretion, which is blocked by putative sigma-1 receptor antagonist NE-100, and was shown to upregulate transcription of genes in the BDNF, glucocorticoid receptor (GR), and dopamine D1 receptor (D1R) pathways in the rat striatum. The impact of different doses of pridopidine on gene expression and transcript splicing in HD across relevant brain regions was explored, utilizing the YAC128 HD mouse model, which carries the entire human mHtt gene containing 128 CAG repeats. METHODS: RNAseq was analyzed from striatum, cortex, and hippocampus of wild-type and YAC128 mice treated with vehicle, 10 mg/kg or 30 mg/kg pridopidine from the presymptomatic stage (1.5 months of age) until 11.5 months of age in which mice exhibit progressive disease phenotypes. RESULTS: The most pronounced transcriptional effect of pridopidine at both doses was observed in the striatum with minimal effects in other regions. In addition, for the first time pridopidine was found to have a dose-dependent impact on alternative exon and junction usage, a regulatory mechanism known to be impaired in HD. In the striatum of YAC128 HD mice, pridopidine treatment initiation prior to symptomatic manifestation rescues the impaired expression of the BDNF, GR, D1R and cAMP pathways. CONCLUSIONS: Pridopidine has broad effects on restoring transcriptomic disturbances in the striatum, particularly involving synaptic transmission and activating neuroprotective pathways that are disturbed in HD. Benefits of treatment initiation at early disease stages track with trends observed in the clinic.