104 research outputs found

    SWOG 1815: A phase III randomized trial of gemcitabine, cisplatin, and nab-paclitaxel versus gemcitabine and cisplatin in newly diagnosed, advanced biliary tract cancers

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    Background: Biliary tract cancers (BTCs) are a heterogeneous group of malignancies with a dismal prognosis. Gemcitabine-based regimens are the standard of care in advanced disease, but median overall survival (OS) is roughly 12 months. The addition of albumin-bound paclitaxel to gemcitabine and cisplatin (GAP) demonstrated promising efficacy in a 60 patient, single-arm phase II study (Shroff et al, JAMA Oncol 2019), with observed median OS of 19.2 months. Methods: SWOG 1815 is a randomized, open-label, phase III trial comparing GAP to gemcitabine/cisplatin (GC). The study included newly diagnosed advanced BTC patients (pts), randomized 2:1 to GAP vs. GC. GAP included gemcitabine at 800 mg/m2, cisplatin at 25 mg/m2 and albumin-bound paclitaxel at 100 mg/m2 on days 1 and 8 of a 21-day cycle. GC included standard dosing of gemcitabine at 1000 mg/m2 and cisplatin at 25 mg/m2 on days 1 and 8 of a 21-day cycle. Pts were treated until progression. The primary endpoint was overall survival (OS) with a target hazard ratio of 0.7 with 90% power and a 1-sided alpha of 0.025; randomization was stratified by disease site (intrahepatic cholangiocarcinoma [CCA] vs gallbladder adenocarcinoma [GBC] vs extrahepatic CCA), disease stage (locally advanced vs metastatic), and Zubrod PS 0 vs 1. Results: Of 441 eligible pts randomized, 55% were female. 67% of patients had intrahepatic CCA, 16% had GBC and 17% had extrahepatic CCA. Most pts had metastases (73%). Median OS with GAP vs. GC was 14 vs. 12.7 mo respectively (HR 0.93, 95% CI 0.74-1.19, p=0.58), ORR (confirmed and unconfirmed) 34% vs25% (p=0.11) and median PFS 8.2 vs 6.4 mo (HR 0.92, 95% CI 0.72-1.16, p=0.47), respectively. Grade 3 and 4 treatment related adverse events (TRAEs) in ≥10% of pts for GAP and GC were anemia, neutropenia, and thrombocytopenia. GAP had more ≥ grade 3 hematologic AEs compared to the GC arm (60% vs. 45%, p=0.003). Discontinuation due to toxicity was at 24% vs 19% (p=0.26) with GAP vs GC. In exploratory subset analyses, GAP vs GC improved OS in pts with locally advanced disease (medians 19.2 vs 13.7 mo; HR 0.67, 95% CI 0.42- 1.06, p=0.09) and in GBC pts (medians 17.0 vs 9.3 mo; HR 0.74, 95% CI 0.41-1.35, p=0.33). ORR for GAP vs GC in GBC was 50% vs 24% (p=0.09) and for locally advanced disease 28 vs 21% p=0.74. Conclusions: SWOG 1815 did not result in a statistically significant improvement in median OS with GAP vs. GC. The GAP regimen had higher rates of TRAEs without a statistically significant difference in discontinuation rates. Pts with locally advanced disease and GBC may benefit from the use of GAP. Further analyses are ongoing to understand potential benefit of GAP in subsets of BTC pts. Funding: NIH/National Cancer Institute grants CA180888, CA180819, CA180820, CA180821, and CA180868; and in part by Celgene Corporation, Summit, NJ (subsidiary of Bristol Myer Squibb)

    Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

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    Background: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. Methodology: We developed and implemented an optimized mutation profiling platform (“OncoMap”) to interrogate ∼400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. Conclusions: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of “actionable” cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents

    Changes in Employment Uncertainty and the Fertility Intention-Realization Link: An Analysis Based on the Swiss Household Panel.

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    How do changes in employment uncertainty matter for fertility? Empirical studies on the impact of employment uncertainty on reproductive decision-making offer a variety of conclusions, ranging from gender and socio-economic differences in the effect of employment uncertainty on fertility intentions and behaviour, to the effect of employment on changes in fertility intentions. This article analyses the association between a change in subjective employment uncertainty and fertility intentions and behaviour by distinguishing male and female partners' employment uncertainty, and examines the variation in these associations by education. Using a sample of men and women living in a couple from the Swiss Household Panel (SHP 2002-2011), we examine through multinomial analysis how changes in employment uncertainty and selected socio-demographic factors are related to individual childbearing decisions. Our results show strong gendered effects of changes in employment uncertainty on the revision of reproductive decisions among the highly educated population

    Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples

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    BACKGROUND: Detection of critical cancer gene mutations in clinical tumor specimens may predict patient outcomes and inform treatment options; however, high-throughput mutation profiling remains underdeveloped as a diagnostic approach. We report the implementation of a genotyping and validation algorithm that enables robust tumor mutation profiling in the clinical setting. METHODOLOGY: We developed and implemented an optimized mutation profiling platform ("OncoMap") to interrogate approximately 400 mutations in 33 known oncogenes and tumor suppressors, many of which are known to predict response or resistance to targeted therapies. The performance of OncoMap was analyzed using DNA derived from both frozen and FFPE clinical material in a diverse set of cancer types. A subsequent in-depth analysis was conducted on histologically and clinically annotated pediatric gliomas. The sensitivity and specificity of OncoMap were 93.8% and 100% in fresh frozen tissue; and 89.3% and 99.4% in FFPE-derived DNA. We detected known mutations at the expected frequencies in common cancers, as well as novel mutations in adult and pediatric cancers that are likely to predict heightened response or resistance to existing or developmental cancer therapies. OncoMap profiles also support a new molecular stratification of pediatric low-grade gliomas based on BRAF mutations that may have immediate clinical impact. CONCLUSIONS: Our results demonstrate the clinical feasibility of high-throughput mutation profiling to query a large panel of "actionable" cancer gene mutations. In the future, this type of approach may be incorporated into both cancer epidemiologic studies and clinical decision making to specify the use of many targeted anticancer agents

    Evidence That Two ATP-Dependent (Lon) Proteases in Borrelia burgdorferi Serve Different Functions

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    The canonical ATP-dependent protease Lon participates in an assortment of biological processes in bacteria, including the catalysis of damaged or senescent proteins and short-lived regulatory proteins. Borrelia spirochetes are unusual in that they code for two putative ATP-dependent Lon homologs, Lon-1 and Lon-2. Borrelia burgdorferi, the etiologic agent of Lyme disease, is transmitted through the blood feeding of Ixodes ticks. Previous work in our laboratory reported that B. burgdorferi lon-1 is upregulated transcriptionally by exposure to blood in vitro, while lon-2 is not. Because blood induction of Lon-1 may be of importance in the regulation of virulence factors critical for spirochete transmission, the clarification of functional roles for these two proteases in B. burgdorferi was the object of this study. On the chromosome, lon-2 is immediately downstream of ATP-dependent proteases clpP and clpX, an arrangement identical to that of lon of Escherichia coli. Phylogenetic analysis revealed that Lon-1 and Lon-2 cluster separately due to differences in the NH2-terminal substrate binding domains that may reflect differences in substrate specificity. Recombinant Lon-1 manifested properties of an ATP-dependent chaperone-protease in vitro but did not complement an E. coli Lon mutant, while Lon-2 corrected two characteristic Lon-mutant phenotypes. We conclude that B. burgdorferi Lons -1 and -2 have distinct functional roles. Lon-2 functions in a manner consistent with canonical Lon, engaged in cellular homeostasis. Lon-1, by virtue of its blood induction, and as a unique feature of the Borreliae, may be important in host adaptation from the arthropod to a warm-blooded host

    Refinement of Light-Responsive Transcript Lists Using Rice Oligonucleotide Arrays: Evaluation of Gene-Redundancy

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    Studies of gene function are often hampered by gene-redundancy, especially in organisms with large genomes such as rice (Oryza sativa). We present an approach for using transcriptomics data to focus functional studies and address redundancy. To this end, we have constructed and validated an inexpensive and publicly available rice oligonucleotide near-whole genome array, called the rice NSF45K array. We generated expression profiles for light- vs. dark-grown rice leaf tissue and validated the biological significance of the data by analyzing sources of variation and confirming expression trends with reverse transcription polymerase chain reaction. We examined trends in the data by evaluating enrichment of gene ontology terms at multiple false discovery rate thresholds. To compare data generated with the NSF45K array with published results, we developed publicly available, web-based tools (www.ricearray.org). The Oligo and EST Anatomy Viewer enables visualization of EST-based expression profiling data for all genes on the array. The Rice Multi-platform Microarray Search Tool facilitates comparison of gene expression profiles across multiple rice microarray platforms. Finally, we incorporated gene expression and biochemical pathway data to reduce the number of candidate gene products putatively participating in the eight steps of the photorespiration pathway from 52 to 10, based on expression levels of putatively functionally redundant genes. We confirmed the efficacy of this method to cope with redundancy by correctly predicting participation in photorespiration of a gene with five paralogs. Applying these methods will accelerate rice functional genomics
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