<p>Supplementary Figure 4. Kaplan-Meier estimates of survival by dual TMB and PD-L1 CPS cutoffs for pembrolizumab plus chemotherapy versus chemotherapy. <b>A</b>, PFS. <b>B,</b> OS.</p>
Therapeutic interventions to eradicate latent HIV in ART-treated infection have yet to show efficacy. We used a systems biology approach to identify a subset of ART-treated individuals with immune-dysfunction that had the highest frequencies of cells with inducible HIV. Contrary to the prevailing notion that immune activation drives HIV persistence, blood from these individuals was enriched in senescence-inducing genes (high FOXO3, SMAD2 and IRF3), Treg frequencies and TGF-β signaling expression. In these "Senescent-INRs", high Firmicute phylum plasma nucleotides and butyrate/bile acids (like a-ketobutyrate) correlated with Treg frequencies and inducible HIV levels. Stimulation of naive CD4 T-cells with a-ketobutyrate led to TGF-β producing Treg differentiation, and PD-1 up-regulation on less differentiated cells. A dose dependent increase in latent HIV-infected memory CD4 T-cells was observed after TGF-β stimulation. Senescence cascades identified here can be targeted by PD-1/TGF-β specific interventions that have shown safety/efficacy in cancer, and can be crucial for HIV eradication.
We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for communication. We assume that the nodes use joint entropy coding based on explicit communication between sensor nodes, and consider both maximum and average distortion bounds. The optimization is complex since it involves an interplay between the spaces of possible transmission structures given radio reachability limitations, and feasible placements satisfying distortion bounds. We address this problem by first looking at the simplified problem of optimal placement in the onedimensional case. An analytical solution is derived for the case when there is a simple aggregation scheme, and numerical results are provided for the cases when joint entropy encoding is used. We use the insight from our 1-D analysis to extend our results to the 2-D case, and show that our algorithm for two-dimensional placement and transmission structure provides significant power
Supplementary Table from Association of Tumor Mutational Burden with Efficacy of Pembrolizumab±Chemotherapy as First-Line Therapy for Gastric Cancer in the Phase III KEYNOTE-062 Study
Supplementary Data from Putative Biomarkers of Clinical Benefit With Pembrolizumab in Advanced Urothelial Cancer: Results from the KEYNOTE-045 and KEYNOTE-052 Landmark Trials
<p>We ran 8 titration point curves (shown in gray) and then picked 4 concentration points that cover best the response curve for all cell lines (shown in red). The first point is the top plateau, the last is the bottom plateau and the other 2 are in between.</p>
We consider the joint optimization of sensor placement and transmission structure for data gathering, where a given number of nodes need to be placed in a field such that the sensed data can be reconstructed at a sink within specified distortion bounds while minimizing the energy consumed for communication.
Abstract Increased PD-L1 expression has been associated with clinical activity of anti-PD-1/PD-L1 therapies in both melanoma and non-small cell lung cancer (NSCLC). Our objective was to identify other cancers that show increased PD-L1 expression in order to target them for treatment with the PD-1 inhibitor pembrolizumab (MK-3475). A collaboration between Merck and the Moffitt Cancer Center was previously established to build a molecular profiling database of >16,000 primary and >3000 metastatic tumors representing 25 different cancers. All tumor samples were profiled on a standardized platform (Affymetrix-Merck Custom GeneChip). For each profiled sample, the PD-L1 cutpoint determined for positivity was defined as the Affymetrix pan-cancer 75th percentile of PD-L1 probes mean. This cutpoint was projected for each specific tumor type and percentages of tumors with PD-L1 above the cutpoint were determined. Cancer indications were rank ordered from highest to lowest percentage of PD-L1 positivity. The analysis identified NSCLC (42% PD-L1+) and melanoma (41% PD-L1+) among the top indications for which single-agent clinical activity of anti-PD1/PD-L1 therapies has been reported. At the bottom of the rankings were prostate cancer (14% PD-L1+) and pancreatic cancer (4% PD-L1+), indications for which limited clinical activity had been reported. This observation confirmed that ranking tumor types by PD-L1 expression across the profiling database could be used to identify other cancers that may respond to anti-PD-1 therapy. Of interest were the tumor types with high PD-L1 expression for which no clinical studies evaluating an anti-PD-1/PD-L1 agent had been initiated. Among the indications with high PD-L1 expression were head and neck (59% PD-L1+), urothelial (42% PD-L1+), and triple-negative (TN) breast (29% PD-L1+) cancer; these indications were chosen for evaluation with pembrolizumab in the KEYNOTE-012 study. By accessing cohorts of Asian patients with lung, liver, and gastric cancer and use of similar gene expression microarray profiling, we were able to extrapolate the PD-L1 rankings for these cancers; this resulted in the addition of gastric cancer to KEYNOTE-012. Recently, clinical results from KEYNOTE-012 have shown strong clinical activity for pembrolizumab in all 4 selected indications: head and neck, 20% ORR; urothelial, 21% ORR; TN breast, 18% ORR; and gastric, 31% ORR. The strategy of using a tumor profiling gene expression database for evaluation of PD-L1 expression enabled rapid expansion of pembrolizumab development into indications for which the likelihood of demonstrating clinical activity was high. In turn, this should help accelerate the approval of pembrolizumab for additional indications and, ultimately, provide help to patients suffering from cancer. Citation Format: Mark D. Ayers, Michael Nebozhyn, Razvan Cristescu, Terrill K. McClanahan, Heather A. Hirsch, Jonathan D. Cheng, Andrey Loboda. Identification of additional cancers likely to respond to anti-PD-1 therapy (pembrolizumab): Evaluation of PD-L1 expression in a large molecular tumor profiling gene expression database. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 256. doi:10.1158/1538-7445.AM2015-256
