XLSX file - 243KB, This table summarizes all significant genetic features that differentiate sensitive versus insensitive cell lines for TNKSi/MEKi combination. The first sheet lists all cell lines for each group. The second sheet lists all genetic features that are enriched in the sensitive group, using a False Discovery Rate (FDR) p-value lower than 0.25.

PDF - 92K, NVP-BYL719 does not inhibit mTOR and PIKKs involved in DNA damage-repair processes. A. TSC1 -/- MEFs cells were grown in a 96-well format and treated for 1 h with increased concentrations of RAD001 or NVP-BYL719 (from 0.5 nmol/L to 10 ?mol/L in 1 third dilution steps) and immediately fixed. S235/236P-RPS6 levels were measured and IC50 determined with the Excel module XLfit. Background (no primary Ab incubated); BL, Baseline. B: TSC1 -/- MEFs cells were treated with increasing concentrations of NVP-BYL719 as indicated or RAD001 at 500 nmol/L or an equivalent DMSO concentration for 30 minutes. Levels of S235/236P-RPS6 and total RPS6 in protein- normalized lysates were detected by Western blot analyzis using an activation-state specific antibody, followed by incubation with species- specific HRP-labeled secondary antibody and signal development by ECL. C: 24 h post seeding, A549 cells were treated at the same time with Actinomycin D (Act D) at a concentration of 5 ?mol/L (an agent used to induce DNA damage), and with increasing concentrations of NVP-BYL719 as indicated or with the vehicle control (DMSO) for 1 h. Levels of S15P-p53 and tubulin in protein-normalized lysates were detected by Western blot analysis using an activation-state specific antibody, followed by incubation with species- specific HRP-labeled secondary antibody and signal development by ECL. D: 24 h post seeding, U2OS cells were pre-treated for 1 h with increased concentrations of NVP-BYL719 or KU55933 a specific small molecular mass inhibitor of ATM (Supplementary reference 1) at a concentration of 10 ?mol/L or with the vehicle control (DMSO). The cells were then irradiated with 15 Gy and re-incubated at 37 degrees C for 1 h and then lysed. Levels of S1981P-ATM in protein- normalized lysates were detected by Western blot analysis using an activation-state specific antibody, followed by incubation with species- specific HRP-labeled secondary antibody and signal development by ECL.

Description of additional methods and procedures used in the study. Also includes Supplementary References.

<p>PDF file - 54KB, Chemical inhibitors used in the study.</p>

Data for characterization of triple combination targeting MDM2, MEK, and BCL-2/-XL.

Selective single agents and combinations.

<p>XLSX file - 234KB, This table shows the features of all 138 cancer cell lines tested for the TNKSi/MEKi combination in the unbiased combination screen. Cell line name, lineage, RAS mutation status and synergy score for the TNKSi/MEKi combination are represented. Cell lines are ranked according to their synergy score.</p>

PDF file - 660KB, Supplementary Figure S1. All RAS mutant cell lines have a higher sensitivity to the TNKSi/MEKi combination. Supplementary Figure S2. Validation of TNKSi/MEKi combination in KRAS mutant cancer cells. Supplementary Figure S3. Combinations with MEK inhibitor in the SW480 cell line. Supplementary Figure S4. TNKSi/MEKi combination leads to enhanced inhibition of AKT signaling activity. Supplementary Figure S5. TNKSi potentiates MEKi by releasing a feedback loop on FGFR2 signaling. Supplementary Figure S6. Consequences of combined inhibition of TNKS and MEK on FGFR2 and AKT signaling pathways in KRAS mutant cell lines.

Legend for Supplementary Tables S1-S6 and Supplementary Figures S1-S15.

From images to synergies (S1); Reproducibility of data from two screens (S2); Single agent responses and selectivity (S3); Screen-wide comparison of Caspase 3/7 activation and growth inhibition (S4); Heatmaps of growth inhibition and Capase 3/7 activation, and examples of broadly synergistic combinations targeting RAS/MAPK and/or PI3K/AKT pathways (S5); Combinations targeting RAS/MAPK and PI3K/AKT pathways at different nodes show similar efficacies (S6); Combinations involving RTKs (S7); Heatmaps of growth inhibition and Capase 3/7 activation, and examples of combinations targeting RAS/MAPK or PI3K/AKT pathways and other cellular processes (S8); Synergies of triple combination increase with synergies of underlying drug pairs (S9); Heatmap of synergies, growth inhibition, and Caspase 3/7 activation for triple combinations after hierarchical clustering (S10); Triple combinations targeting RAS/MAPK and PI3K/AKT pathways (S11); Triple combinations targeting RAS/MAPK and/or PI3K/AKT pathways and other cellular processes (S12); Combination targeting MDM2 and MEK in p53 wild-type models (S13); Sequential treatment of p53 wild-type lines with triple combination targeting MDM2, MEK, and BCL-2/-XL (S14); High order combinations to kill 'robust' cell lines (S15).

<p>PDF file - 68KB, Sensitivity of KRAS mutant cancer cells to TNKSi/MEKi combination. Synergistic cell lines are in red (cut-off of synergy score of 2).</p>

PDF - 71K, Rat1-myr-p110alpha (blue), beta (green) or delta (red) cells were treated with increasing concentrations of NVP-BYL719 for 30 minutes. Levels of S473P-Akt in cell extracts were quantified by Reverse Phase Protein Array as described in (18) and plotted as percentage of untreated control cells. The graph illustrates n=3 independent experiments. IC50s (plus/minus) SD and IC80s (plus/minus) SD of n=3 independent experiments are reported..

Summarized results for high-order combinations in DLD-1, RKO, HT-29, and LS-180 cell lines.

PDF - 60K, Linear correlation observed between tumor growth inhibition (% T/C) or tumor regression and the fraction of time over the in vivo S473P-Akt IC80 in different cancer cell line-derived tumor xenografts implanted in nude mice (represented as dots) and nude rats (represented as triangles) following NVP-BYL719 treatment (R2=0.77, p<0.001, n=27).

PDF - 129K, Legends for Supplementary Figures 1 through 4 and Supplementary Tables 1 through 7. Supplementary Table 1. Determination of NVP-BYL719 in vitro effects on human protein kinases. Supplementary Table 2. Activity profile of NVP-BYL719 in the Invitrogen Kinase panel. Supplementary Table 3. Activity profile of NVP-BYL719 in the Ambit Kinase panel. Supplementary Table 4. NVP-BYL719 Kd (nmol/L) determination in the Ambit Kinase panel for the hits found to be inhibited >90%. Supplementary Table 5. NVP-BYL719 anti-tumor effects in diverse cancer cell line-derived xenograft models. Supplementary Table 6. CCLE cell lines responsive to NVP-BYL719. Supplementary Table 7 Anti-tumor effect of NVP-BYL719 in patient-derived xenograft models carrying PIK3CA genetic alterations.

PDF - 37K, NVP-BYL719 was tested at 10 different concentrations (from 0.5 nmol/L to 10 μmol/L in 1 third dilution steps) against CLK2 (A) and LRRK2 (B). SelectScreenTM Kinase Profiling Service uses XLfit from IDBS to determine the IC50 values (IC50 CLK2=621 nmol/L; IC50 LRRK2=3'220 nmol/L). The dose response curve is curve fit to model number 205 (sigmoidal dose-response model).

Summarized results of pair-wise and triple combination screens.

<p>PDF file - 81KB, List of identified synergistic cell lines for TNKSi/MEKi combination in the large-scale combination screen and their KRAS status. KRAS mutants are in red.</p>

Technological advances in passive digital phenotyping present the opportunity to quantify neurological diseases using new approaches that may complement clinical assessments. Here, we studied multiple sclerosis (MS) as a model neurological disease for investigating physiometric and environmental signals. The objective of this study was to assess the feasibility and correlation of wearable biosensors with traditional clinical measures of disability both in clinic and in free-living in MS patients. This is a single site observational cohort study conducted at an academic neurological center specializing in MS. A cohort of 25 MS patients with varying disability scores were recruited. Patients were monitored in clinic while wearing biosensors at nine body locations at three separate visits. Biosensor-derived features including aspects of gait (stance time, turn angle, mean turn velocity) and balance were collected, along with standardized disability scores assessed by a neurologist. Participants also wore up to three sensors on the wrist, ankle, and sternum for 8 weeks as they went about their daily lives. The primary outcomes were feasibility, adherence, as well as correlation of biosensor-derived metrics with traditional neurologist-assessed clinical measures of disability. We used machine-learning algorithms to extract multiple features of motion and dexterity and correlated these measures with more traditional measures of neurological disability, including the expanded disability status scale (EDSS) and the MS functional composite-4 (MSFC-4). In free-living, sleep measures were additionally collected. Twenty-three subjects completed the first two of three in-clinic study visits and the 8-week free-living biosensor period. Several biosensor-derived features significantly correlated with EDSS and MSFC-4 scores derived at visit two, including mobility stance time with MSFC-4 z-score (Spearman correlation −0.546; p = 0.0070), several aspects of turning including turn angle (0.437; p = 0.0372), and maximum angular velocity (0.653; p = 0.0007). Similar correlations were observed at subsequent clinic visits, and in the free-living setting. We also found other passively collected signals, including measures of sleep, that correlated with disease severity. These findings demonstrate the feasibility of applying passive biosensor measurement techniques to monitor disability in MS patients both in clinic and in the free-living setting.