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Pathway-based analysis generates three distinct clusters based on enrichmen...
Published: 23 September 2022
FIGURE 1 Pathway-based analysis generates three distinct clusters based on enrichment profiles with clinical significance. Samples from TCGA were analyzed using either canonical pathways ( A ) or oncogenic pathways ( B ) from the GSEA to generate heatmaps based on the enrichment profile of each sample (column) with respect to each gene set (row) in both collections. C and D, Profiles from A and B , respectively, were used to generate PCA plots labeled by color and shape for each cluster. Circle lines represent the normal distribution of the samples in each cluster. E, TCGA samples were clustered on the basis of the original molecular subtypes described, and Kaplan–Meier curves were obtained. F and G , Samples clustered on the basis of enrichment profiles for canonical and oncogenic gene sets, respectively, were analyzed for survival using Kaplan–Meier curves. Tables at the bottom describe the distribution of the molecular subtypes for each cluster. Dotted lines represent median survival for each curve (also described in top tables). Time shown is in months. P values after post hoc analyses using Bonferroni–Hochberg correction. More
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Gene lists predict E2F1 as a main target in one of the clusters found in th...
Published: 23 September 2022
FIGURE 2 Gene lists predict E2F1 as a main target in one of the clusters found in the GS dataset. A, Enrichment profiles using gene lists were generated for GS samples. B, Each gene list was evaluated using IPA and top predicted activated (green arrows) and inhibited (red arrows) upstream regu... More
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Gene lists differentially correlate with cellular states and cell-specific ...
Published: 23 September 2022
FIGURE 3 Gene lists differentially correlate with cellular states and cell-specific markers. A, Scores generated for each cell in Supplementary Fig. S3 using gene lists were correlated with scores for cellular states and specific cell-type markers in development and adult brain. The presence o... More
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E2F1 silencing compromises self-renewal and proliferation <em>in vitro</em>...
Published: 23 September 2022
FIGURE 4 E2F1 silencing compromises self-renewal and proliferation in vitro and tumor formation in vivo. Samples from both clusters were treated with control (scrambled) or E2F1 siRNA ( A ) or were plated in regular media or media containing fulvestrant or calcitriol ( B ) under limiting dilution in a 96-well plate. Graphs depict the number of wells that did not form spheres after 10 days versus the number of cells plated (a vertical line implies all wells formed spheres). C, Cells treated with scrambled or E2F1 siRNA were plated at a density of 2,000 cells per well in a 96-well plate in quadruplicate, and their growth was evaluated using luminescence. Relative growth is the fold change compared with basal measurement. D–F , Cells treated with scrambled or E2F1 shRNA were intracranially injected in NSG mice. Kaplan–Meier survival curves for each group was calculated; dashed lines represent median survival and time shown is in weeks ( D ). Luminescence was assessed 2 weeks after transplantation ( E ). Quantification for each group is shown at 2, 5, and 8 weeks ( F ). Mice in both groups for HK408 did not reach the 8-week timepoint. Experiments in A–C were performed at least three times. Data are represented as mean ± SEM. **, P < 0.01 and ***, P < 0.001 as assessed by one-way ANOVA. More
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E2F1 silencing compromises DNA damage response induced after irradiation.  ...
Published: 23 September 2022
FIGURE 5 E2F1 silencing compromises DNA damage response induced after irradiation. A, Cells were treated with either C (control) or E (E2F1) shRNA, were subjected to irradiation (8 Gy) and fixed after 12 hours for γH2AX staining (red). Nuclei were counterstained using DAPI. B, Quantification for each group in A is shown. Experiment was performed at least two times. Data are represented as mean ± SEM. **, P < 0.01 as assessed by one-way ANOVA. More
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Adjusting for known treatment assignment imbalances, patients receiving sec...
Published: 21 September 2022
FIGURE 2 Adjusting for known treatment assignment imbalances, patients receiving second-line (2L) ICPI versus chemotherapy have more favorable outcomes when TMB ≥ 10 but not TMB < 10. Kaplan–Meier curves are adjusted for imbalances (propensity weights applied). TTNT is shown by drug class for TMB < 10 ( A ), and TMB ≥ 10 ( B ). OS is shown by drug class for TMB < 10 ( C ), and TMB ≥ 10 ( D ). x-axis is truncated at 36 months. OS estimates are left truncated to reflect delayed entry to at-risk table (see Materials and Methods). Visualizations are adjusted by propensity weights. Analyses unadjusted for propensity weights have similar results (see Supplementary Fig. S2 ). Interaction terms in interaction models (see Materials and Methods) for TTNT and OS, respectively. P < 0.0001 and 0.0028 (for full models, see Supplementary Fig. S4 ). More
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Patients receiving first-line (1L) chemotherapy followed by second-line (2L...
Published: 21 September 2022
FIGURE 3 Patients receiving first-line (1L) chemotherapy followed by second-line (2L) ICPI had more favorable outcomes on second-line IPCI compared to first-line chemotherapy when TMB ≥ 10 but not TMB < 10. TTNT on first-line platinum chemotherapy and subsequent second-line ICPI are shown as st... More
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TMB and MSI-H are stronger predictive biomarkers for ICPI versus chemothera...
Published: 21 September 2022
FIGURE 4 TMB and MSI-H are stronger predictive biomarkers for ICPI versus chemotherapy benefit than PD-L1. Point estimates and confidence intervals for biomarker-defined groups of patients are shown for TTNT in the second-line (2L) ICPI versus chemotherapy cohort ( A ), OS in the second-line ICPI ... More
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Adjusting for known treatment assignment imbalances, patients receiving fir...
Published: 21 September 2022
FIGURE 5 Adjusting for known treatment assignment imbalances, patients receiving first-line (1L) ICPI versus chemotherapy have more favorable outcomes when TMB ≥ 10 but not TMB < 10. Kaplan–Meier curves are adjusted for imbalances. TTNT is shown by drug class for TMB < 10 ( A ), and TMB ≥ 10 ( B ). OS is shown by drug class for TMB < 10 ( C ), and TMB ≥ 10 ( D ). x-axis is truncated at 36 months. OS estimates are left truncated to reflect delayed entry to at-risk table (see Materials and Methods). Visualizations are adjusted by propensity weights. Analyses unadjusted for propensity weights have similar results (see Supplementary Fig. S3 ). Interaction terms in interaction models (see Materials and Methods) for TTNT and OS, respectively. P < 0.0001 and P = 0.0292 (for full models, see Supplementary Fig. S7 ). More
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RCT and real-world cohorts have very different patient populations, similar...
Published: 21 September 2022
FIGURE 6 RCT and real-world cohorts have very different patient populations, similar drug-class specific TMB associations. The phase III randomized controlled trials KeyNote-061 (KN-061), KeyNote-062 (KN-062) and the second-line and first-line Comparative Effectiveness Cohorts are compared with re... More
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MSS only exploratory analysis. Patients testing MSS assigned ICPI from both...
Published: 21 September 2022
FIGURE 7 MSS only exploratory analysis. Patients testing MSS assigned ICPI from both the 1 L and 2 L comparative effectiveness cohorts were combined for an exploratory analysis, and stratified by TMB ≥ 10 for TTNT ( A ) and OS ( B ). Outcomes of patients testing both MSS and TMB ≥ 10 receiving ICPI or chemotherapy are shown for TTNT ( C ) and OS ( D ). x-axis is truncated at 30 months. OS estimates are left truncated (see Materials and Methods) with at-risk tables adjusted accordingly. Kaplan–Meier curves are not adjusted for propensity weights. aHR = adjusted hazard ratio, adjusted for line of therapy (1 L or 2L), age, ECOG, stage at diagnosis, abnormal laboratory values, and BMI. More
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CDM-dependent CAFs generate sEVs with unique protein cargo.  A,  Representa...
Published: 19 September 2022
FIGURE 1 CDM-dependent CAFs generate sEVs with unique protein cargo. A, Representative transmission electron micrograph of sEVs isolated from CM collected from human pancreatic CAFs cultured within a CDM. Red box highlights a structure with canonical exosome morphology and size. Scale bar = 100 nm. B, Representative Western blot analysis of CAF lysate and assorted fractions collected following differential ultracentrifugation probing for enrichment of sEV markers. Lysate corresponding to 5 μg protein obtained from the EV-generating CAFs served as loading control. Fractions shown are: large EVs pellet (from the 10,000 × g centrifuge step); sEV supernatant; and sEV pelleted (collected from the 120,000 × g centrifuge step (see Materials and Methods for details). Note that the sEV pellet is enriched with canonical exosome markers and lacks organelle contaminants. C, Representative NTA histogram of an sEV pellet fraction; using the NanoSight platform. D, Control Western blot analysis showing sEVs isolated from media containing FBS (+FBS) and undetected in serum-depleted (−FBS) media. E, Enriched gene ontology clusters from proteomic analysis of CDM-producing human CAF isolated sEVs, n = 3. Note that full proteomics and enriched pathway analysis can be found in Supplementary Data S1—Proteomics (Tabs = Total proteins CAF.sEV, Fig. 1E Pathway Analysis) More
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NetG1<sup>+</sup> CAFs generate sEVs that rescue PDAC cells from nutrient d...
Published: 19 September 2022
FIGURE 2 NetG1+ CAFs generate sEVs that rescue PDAC cells from nutrient deprivation-induced apoptosis. A, Representative confocal immunofluorescent images obtained from NLFs and CAFs cultured to produce a CDM. Shown are nuclei (SYBR green) and corresponding fibronectin ECM fibers (white). Scale bars = 50 μm; see Supplementary Fig. S1 for measurements. B, Representative Western blot analysis of CAF and NLF cell lysates, probing for expression of myofibroblastic activation marker, αSMA. GAPDH as protein loading control. C, Relative differences in total particle concentrations found in sEV fractions isolated from NLFs and CAFs, normalized to the mean NLF value; using the NanoSight platform. Bars = standard error. Statistics: Unpaired t test using Welch correction. n = 4. Comprehensive statistical readouts provided in Supplementary Data S2—Statistical Analysis (Tab = Fig. 2C). D, Representative NTA histograms of sEV fractions from NLF and CAFs, using the NanoSight platform. E, Cell viability assay of PANC-1 cells at 48 hours posttreatment with CM or sEV from NLFs and CAFs. n = 3 biological replicates; each replicate consists of six technical repeats. All repeats per replicate were normalized to the mean of the corresponding PBS-treated condition. Bars = standard error. Statistics: one-way ANOVA, with multiple comparisons using Tukey correction. *, Compared with PBS (negative control), # comparing between conditions noted by connecting lines. A comprehensive list of statistical readouts is provided in Supplementary Data S2—Statistical Analysis (Tabs = Fig. 2E). F, Representative Western blots of PANC-1 cell lysates collected 48 hours posttreatment with PBS, CM, or sEVs from NLF or CAF cells. Probing for Akt activation via phosphorylation at Serine 473 and apoptosis occurring via PARP cleavage (lower band). Pan Akt as pAkt control, GAPDH as protein loading control. G, Apoptosis occurring in PANC-1 cells as measured by the ratio of cleaved PARP: full-length PARP, quantified from the optical density of digitized Western blots in F using the software ImageJ. n = 6. H, Akt activation as measured via the ratio of phosphorylated Akt at Serine 473: Pan Akt, quantified from the optical density of digitized Western blots in F using the software ImageJ. n = 3. G and H, Results were normalized to the PBS-treated condition (negative control) for each replicate blot, represented by dotted line. Bars = standard error. Statistics: one-way ANOVA, with multiple comparisons using Tukey correction. * Compared with PBS, # comparing between conditions noted by connecting lines. A comprehensive list of statistical readouts is provided in Supplementary Data S2—Statistical Analysis (Tabs = Fig. 2G, 2H). I, Representative Western blots of NLF and CAF cell lysate and sEV fractions, probing for NetG1 and Int.α5. GAPDH as protein loading control in cell lysate fraction. CD81 as loading control in sEV fraction. More