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Comparison of EGFR Mutation Status in Matched Baseline Tumor and Plasma 1 Samples (Screened Population) results

J Thorac Oncol. 2014 Sep; 9(9): 1345–1353.

Comparison of EGFR Mutation Status in Matched Baseline Tumor and Plasma 1 Samples (Screened Population) Fewer patients were identified as having EGFR mutation-positive status using plasma 1-derived ctDNA (detection rate, 10.5%; 82 of 784 patients) than with tumor-derived DNA (detection rate, 13.7%, 118 of 859 patients). Due to technical problems with tumor samples (e.g., low tumor content, poor sample quality, insufficient quantity, poor/inappropriate fixation, no DNA), 201 of 1060 screened patients (19.0%) had an unknown EGFR mutation status; 12 of these patients were subsequently found to have a positive EGFR mutation status in their corresponding plasma 1 samples. A total of 652 patients provided matched baseline tumor and plasma 1 samples that were evaluable for EGFR mutation status using both sample types. A comparison of EGFR mutation status between tumor and plasma 1 samples is shown in Table ​Table1.1. Concordance between baseline tumor and plasma 1 EGFR mutation status for patients evaluable for both samples was 94.3% (95% CI, 92.3–96.0), with a sensitivity of 65.7% (95% CI, 55.8–74.7) and specificity of 99.8% (95% CI, 99.0–100.0). Positive-predictive value and negative-predictive value of EGFR mutation status detection between baseline tumor and plasma 1 samples for patients evaluable for both samples are also shown. A comparison of EGFR mutation status by mutation subtype for baseline tumor and plasma 1 samples is presented in Table ​Table2.2. When analyzed by mutation subtype, concordance between baseline tumor and plasma 1 EGFR mutation status for patients evaluable for both samples was 96.5% (95% CI, 94.8–97.8) for exon 19 deletions and 97.9% (95% CI, 96.4–98.8) for L858R point mutations; sensitivity was 67.6% (95% CI, 55.5–78.2) and 61.8% (95% CI, 43.6–77.8), and specificity was 100.0% (95% CI, 99.4–100.0) and 99.8% (95% CI, 99.1–100.0), respectively.

结果中的图与表的阐述 results

an overview of …the experimental data on X.the summary statistics for …the breakdown of X according to …the intercorrelations among the nine measures of X.the results obtained from the preliminary analysis of X.

阴性结果的表述 results

No increase in X was detected.No difference greater than X was observed.No significant differences were found between …None of these differences were statistically significant.No significant difference between the two groups was evident.No significant reduction in X was found compared with placebo.No evidence was found for non-linear associations between X and Y.No significant correlation was found between X scores and the Y scores (p = .274) X appeared to be unaffected by Y.Only trace amounts of X were detected in …There was no evidence that X has an influence on …The Chi-square test did not show any significant differences between …Overall, X did not affect males and females differently in these measures.A clear benefit of X in the prevention of Y could not be identified in this analysis.T-tests found no significant differences in mean scores on the X and Y subscales.

结果部分-研究目的和过程开头 results

Referring back to the research aims or procedures - close The first set of questions aimed to … To compare the difference between … The purpose of Experiment 3 was to … Simple statistical analysis was used to … The next question asked the informants … To assess X, the Y questionnaire was used. Changes in X and Y were compared using … Regression analysis was used to predict the … To distinguish between these two possibilities, … The first set of analyses examined the impact of … The correlation between X and Y was tested using … T-tests were used to analyse the relationship between … The average scores of X and Y were compared in order to … In order to assess Z, repeated-measures ANOVAs were used. Nine items on the questionnaire measured the extent to which …

linear amplification PCR (LAM-PCR) followed by sequence analyses results

To confirm editing at the molecular level, we employed linear amplification PCR (LAM-PCR) followed by sequence analyses. LAM-PCR was initiated in the chromosomal sequences external to the HAs, spanning both HAs and reading into the luciferase ORF. Sequence analyses confirmed accurate insertion into the intended location, intron 1 of the Rosa26 gene (Fig. 5C). No indel mutations or AAV ITRs were detected in the edited genomes. We further confirmed TI of the luciferase cassette into the Rosa26 locus by Southern blot analysis of mouse liver DNA, harvested 70 d after injection of AAVHSC15 Rosa26-Luc. The expected 7-kb band was visualized following hybridization of SpeI-digested DNA with a luciferase-specific probe (Fig. 5D). No luciferase-specific bands were detectable in untreated liver DNA from control mice (Fig. 5D), showing specificity. Interestingly, no 3,966-bp monomer-length free vector genomes were detected in the Southern blot analysis, possibly suggesting that the editing genome may either not have initiated second-strand synthesis or not formed double-stranded concatamers commonly observed following AAV transduction (70). Digestion of double-stranded concatamers with a single cutter enzyme would be expected to yield monomer-length AAV vector genomes, which were not observed, suggesting that such concatamers were absent. If any single-stranded AAV genomes were present, they would likely have formed “snapback” structures due to the complementarity of the ITRs and may have migrated faster in nondenaturing gels. If free vector genomes persisted as double-stranded monomers, SpeI digestion would yield fragments of 2,783 bp and 1,183 bp (Fig. 5D), which were not observed. It is also possible that the number of free vector genomes was below the limit of detection for the Southern blot assay (71). However, the presence of a 7-kb band on the Southern blot analysis, together with in vivo expression and sequence analysis, confirmed the accurate targeted insertion of the luciferase ORF into intron 1 of Rosa26 following a single i.v. injection of the AAVHSC15 editing vector. Southern blot analysis also revealed no discernible off-target bands, suggesting the absence of off-target integrations within the limits of detection of the assay.

Luciferase expression results

Luciferase expression was detectable as early as day 3 after injection with the AAVHSC15 Rosa26-Luc editing vector, and was stable to day 112 postinjection, the last time point assayed. Expression gradually increased after injection and plateaued within ∼4–6 wk. Luciferase expression was observed systemically, consistent with the expected ubiquitous expression of Rosa26 (69). In vivo imaging indicated strong widespread systemic luciferase expression (Fig. 5B). Organ-specific expression was assessed in isolated organs at the end of the experiment. Quantitation of flux in isolated organs revealed the highest luciferase expression, as measured by flux, in the liver, followed by muscle (SI Appendix, Table S8). Luciferase expression was also detected in the heart, lungs, kidney, and brain. Quantitation of vector was performed for isolated organs by ddPCR specific for the luciferase gene relative to a single-copy endogenous gene, apoB. The liver showed the most copies of the luciferase gene at 0.737 copies per cell, followed by muscle (0.398 copies per cell) and heart (0.317 copies per cell) (SI Appendix, Table S8). Notably, no toxicity due to AAVHSC editing was noted for up to 6 mo postinjection, the end of the study.

Genome Editing by AAVHSC Requires BRCA2. results

Genome Editing by AAVHSC Requires BRCA2.To identify the mechanism of AAVHSC editing, we tested the hypothesis that mutations in specific genes known to mediate DNA damage response and maintain genome integrity would result in altered editing outcomes (47–59). Targeted insertion of the promoterless GFP ORF into PPP1R12C was quantitated in each of 12 patient-derived B LCLs that harbor loss-of-function mutations in selected DNA repair genes and compared with that in CD34+cells (Fig. 4AandSI Appendix, Table S7). Cumulative averages of editing for each AAV serotype across mutant cell lines revealed a spectrum of impacts (49–59) (Fig. 4BandSI Appendix, Fig. S9A). Cell lines with certain mutations displayed potentiated HR, while others displayed diminished HR (Fig. 4AandBandSI Appendix, Fig. S9). However, since the LCLs were derived from different patients and therefore not congenic, this precluded precise conclusions on the role of each repair gene. Interestingly, however, the overall pattern of each AAV serotype was similar for each mutation, suggesting that the impact of specific repair genes on genome editing was similar for each AAV serotype (Fig. 4B).

两组间的比较 results

Mitochondria-Endoplasmic Reticulum Contact Sites Function as Immunometabolic Hubs that Orchestrate the Rapid Recall Response of Memory CD8+ T Cells

There was,however, an approximately 50% reduction in Akt-Ser473 phosphorylation in MEJ fractions from activated rictor–/– memory cells, compared to WT counterparts (Figure 3D).

结果描述 results

Mitochondria-Endoplasmic Reticulum Contact Sites Function as Immunometabolic Hubs that Orchestrate the Rapid Recall Response of Memory CD8+ T Cells

To further verify these results, we perturbed mitochondria-ER appositions by treating activated EM CD8+ T cells with the ER stress blocker, 4-PBA, since reduction of ER stress has been shown to reduce mitochondria-ER interaction in non-immune cells (Prasad et al.,2016).

Rankogram results

Medicine (Baltimore). 2017 Feb96(6):e5947.

Rankogram based on SUCRA was shown in Figure ​Figure6.6. Mobi-C, Secure-C, and Prodisc-C ranked the best, the second best, the third best, respectively, with minor discrepancy SUCRA value (0.826, 0.816, and 0.815, respectively).

Direct pairwise meta-analysis results

Medicine (Baltimore). 2017 Feb96(6):e5947.

Direct pairwise meta-analysis showed that the rates of secondary surgical procedures were significantly lower in Mobi-C (P  0.05) (Supplementary Digital Content, Figures 1–8). Estimated effects of CDAs in the network meta-analysis on the primary outcome are shown in the forest plot and league table (Fig. ​(Fig.44 and Fig. ​Fig.5).5). Convergence was reached in all analyses (data not shown). Compared with ACDF, CDAs with Mobi-C, Prodisc-C, Secure-C, and Prestige were associated with significantly lower rates of secondary surgical procedures. Discover was significantly inferior to ACDF with regard to the primary outcome. No significant difference was shown between Bryan, PCM, Kineflex-C, and ACDF. On comparative durability of network meta-analysis, all devices except Kineflex-C were superior to Discover. Mobi-C, Prodisc-C, Secure-C, and Prestige were seen to be better than PCM and Kineflex-C. There was no significant difference among Mobi-C, Prodisc-C, Secure-C, Prestige, and Bryan.

回归的描述 results

Univariate comparison of demographic and anatomical factors between normal facets and degenerated facets are summarized in Table 5. All included demographic and anatomical factors between normal facets and degenerated facets were significantly different (P < 0.05). Overall association of demographic and anatomical factors is demonstrated in Table 6. Results from multivariate logistic regression suggested that age, gender, cervical levels, tropism-T and tropism-S were associated with facet degeneration. Association of demographic and anatomical factors at individual level with facet degeneration are listed in Table 7. Gender was not associated with facet degeneration except for C2-C3 level, whereas age was related to facet degeneration at all sub-axial levels except for C6-C7 level. Tropism-S were related to facet degeneration at all levels, whereas tropism-T was noted only related to facet degeneration at C2-C3 level.

结果第一段 results

A total of 200 patients were retrospectively enrolled in this study. The mean age was 46.23 years old (ranging from 30 to 64 years old). There were 114 males with the mean age of 45.95 years old (ranging from 30 to 64 years old) and 86 females with the mean age of 46.60 years old (ranging from 31 to 61 years old). No significant difference was noted between the genders (P > 0.05). The degrees of facet degeneration varied according to levels (Table 1, P  0.000). Degenerated facet joints were most common at C2-C3 level. The degrees of facet degeneration varied according to ages (Table 2, P  0.000). Facet degenerative changes were more common in patients above 50 years old. The intra-observer reliability was 0.867 (95%CI: 0.841 to 0.890) and the inter-observer reliability was 0.757 (95%CI: 0.711 to 0.797), which were of good reliability.

结果中最令人感兴趣的点的表达 results

Interestingly, the X was observed to …This result is somewhat counterintuitive.Interestingly, this correlation is related to …The more surprising correlation is with the …Surprisingly, only a minority of respondents …The most surprising aspect of the data is in the …The correlation between X and Y is interesting because …The most striking result to emerge from the data is that …Interestingly, there were also differences in the ratios of …The single most striking observation to emerge from the data comparison was … This is a/an (rather) surprisingsignificantinterestingremarkableunexpecteddisappointing result.outcome.

Patients results

J Thorac Oncol. 2014 Sep; 9(9): 1345–1353.

Patients Of 1060 patients screened from 13 countries, 1033 (97.5%) provided baseline tumor samples. Of these, EGFR mutation status could be determined for 859 patients (81.0%), and 118 patients (11.1%) were assigned an eligible EGFR mutation-positive status (mutation frequency, 13.7%) and enrolled in the study from September 8, 2010, to February 15, 2012; gefitinib treatment was started in 106 of these patients (FAS population) (Fig. ​(Fig.1).1). One additional patient of EGFR mutation-positive ineligible status was treated with gefitinib in error. Of the 201 patients (19%) for whom tumor EGFR mutation status could not be determined (unevaluable/unavailable), tissue was not provided from 27 patients (2.6%) who consented, and 174 patients (16.4%) could not be evaluated for EGFR mutation status (100 [9.4%] failed histopathology, 42 [4.0%] yielded insufficient DNA, 2 [0.2%] failed EGFR mutation analysis, and 30 [2.8%] were not shipped from the study site in time). A flow diagram of the accountability of tumor samples is presented in Figure ​Figure22.

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