Evaluation of pre-analytical factors affecting plasma DNA analysis.

Pre-analytical factors can significantly affect circulating cell-free DNA (cfDNA) analysis. However, there are few robust methods to rapidly assess sample quality and the impact of pre-analytical processing. To address this gap and to evaluate effects of DNA extraction methods and blood collection tubes on cfDNA yield and fragment size, we developed a multiplexed droplet digital PCR (ddPCR) assay with 5 short and 4 long amplicons targeting single copy genomic loci. Using this assay, we compared 7 cfDNA extraction kits and found cfDNA yield and fragment size vary significantly. We also compared 3 blood collection protocols using plasma samples from 23 healthy volunteers (EDTA tubes processed within 1 hour and Cell-free DNA Blood Collection Tubes processed within 24 and 72 hours) and found no significant differences in cfDNA yield, fragment size and background noise between these protocols. In 219 clinical samples, cfDNA fragments were shorter in plasma samples processed immediately after venipuncture compared to archived samples, suggesting contribution of background DNA by lysed peripheral blood cells. In summary, we have described a multiplexed ddPCR assay to assess quality of cfDNA samples prior to downstream molecular analyses and we have evaluated potential sources of pre-analytical variation in cfDNA studies

Surface defects incorporated diamond machining of silicon

Abstract This paper reports the performance enhancement benefits in diamond turning of the silicon wafer by incorporation of the surface defect machining (SDM) method. The hybrid micromachining methods usually require additional hardware to leverage the added advantage of hybrid technologies such as laser heating, cryogenic cooling, electric pulse or ultrasonic elliptical vibration. The SDM method tested in this paper does not require any such additional baggage and is easy to implement in a sequential micro-machining mode. This paper made use of Raman spectroscopy data, average surface roughness data and imaging data of the cutting chips of silicon for drawing a comparison between conventional single-point diamond turning (SPDT) and SDM while incorporating surface defects in the (i) circumferential and (ii) radial directions. Complementary 3D finite element analysis (FEA) was performed to analyse the cutting forces and the evolution of residual stress on the machined wafer. It was found that the surface defects generated in the circumferential direction with an interspacing of 1 mm revealed the lowest average surface roughness (Ra) of 3.2 nm as opposed to 8 nm Ra obtained through conventional SPDT using the same cutting parameters. The observation of the Raman spectroscopy performed on the cutting chips showed remnants of phase transformation during the micromachining process in all cases. FEA was used to extract quantifiable information about the residual stress as well as the sub-surface integrity and it was discovered that the grooves made in the circumferential direction gave the best machining performance. The information being reported here is expected to provide an avalanche of opportunities in the SPDT area for low-cost machining solution for a range of other nominal hard, brittle materials such as SiC, ZnSe and GaAs as well as hard steels.</jats:p

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Optimising medication data collection in a large-scale clinical trial

© 2019 Lockery et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective: Pharmaceuticals play an important role in clinical care. However, in community-based research, medication data are commonly collected as unstructured free-text, which is prohibitively expensive to code for large-scale studies. The ASPirin in Reducing Events in the Elderly (ASPREE) study developed a two-pronged framework to collect structured medication data for 19,114 individuals. ASPREE provides an opportunity to determine whether medication data can be cost-effectively collected and coded, en masse from the community using this framework. Methods: The ASPREE framework of type-to-search box with automated coding and linked free text entry was compared to traditional method of free-text only collection and post hoc coding. Reported medications were classified according to their method of collection and analysed by Anatomical Therapeutic Chemical (ATC) group. Relative cost of collecting medications was determined by calculating the time required for database set up and medication coding. Results Overall, 122,910 participant structured medication reports were entered using the type-tosearch box and 5,983 were entered as free-text. Free-text data contributed 211 unique medications not present in the type-to-search box. Spelling errors and unnecessary provision of additional information were among the top reasons why medications were reported as freetext. The cost per medication using the ASPREE method was approximately USD $0.03 compared with USD$0.20 per medication for the traditional method. Conclusion Implementation of this two-pronged framework is a cost-effective alternative to free-text only data collection in community-based research. Higher initial set-up costs of this combined method are justified by long term cost effectiveness and the scientific potential for analysis and discovery gained through collection of detailed, structured medication data

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

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)

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment