Composite grading algorithm for the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE)

Background: The Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events is an item library designed for eliciting patient-reported adverse events in oncology. For each adverse event, up to three individual items are scored for frequency, severity, and interference with daily activities. To align the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events with other standardized tools for adverse event assessment including the Common Terminology Criteria for Adverse Events, an algorithm for mapping individual items for any given adverse event to a single composite numerical grade was developed and tested. Methods: A five-step process was used: (1) All 179 possible Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events score combinations were presented to 20 clinical investigators to subjectively map combinations to single numerical grades ranging from 0 to 3. (2) Combinations with <75% agreement were presented to investigator committees at a National Clinical Trials Network cooperative group meeting to gain majority consensus via anonymous voting. (3) The resulting algorithm was refined via graphical and tabular approaches to assure directional consistency. (4) Validity, reliability, and sensitivity were assessed in a national study dataset. (5) Accuracy for delineating adverse events between study arms was measured in two Phase III clinical trials (NCT02066181 and NCT01522443). Results: In Step 1, 12/179 score combinations had <75% initial agreement. In Step 2, majority consensus was reached for all combinations. In Step 3, five grades were adjusted to assure directional consistency. In Steps 4 and 5, composite grades performed well and comparably to individual item scores on validity, reliability, sensitivity, and between-arm delineation. Conclusion: A composite grading algorithm has been developed and yields single numerical grades for adverse events assessed via the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events, and can be useful in analyses and reporting

Effects of patient-reported outcome assessment order

Background: In clinical trials and clinical practice, patient-reported outcomes are almost always assessed using multiple patient-reported outcome measures at the same time. This raises concerns about whether patient responses are affected by the order in which the patient-reported outcome measures are administered. Methods: This questionnaire-based study of order effects included adult cancer patients from five cancer centers. Patients were randomly assigned to complete questionnaires via paper booklets, interactive voice response system, or tablet web survey. Linear Analogue Self-Assessment, Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events, and Patient-Reported Outcomes Measurement Information System assessment tools were each used to measure general health, physical function, social function, emotional distress/anxiety, emotional distress/depression, fatigue, sleep, and pain. The order in which the three tools, and domains within tools, were presented to patients was randomized. Rates of missing data, scale scores, and Cronbach’s alpha coefficients were compared by the order in which they were assessed. Analyses included Cochran–Armitage trend tests and mixed models adjusted for performance score, age, sex, cancer type, and curative intent. Results: A total of 1830 patients provided baseline patient-reported outcome assessments. There were no significant trends in rates of missing values by whether a scale was assessed earlier or later. The largest order effect for scale scores was due to a large mean score at one assessment time point. The largest difference in Cronbach’s alpha between the versions for the Patient-Reported Outcomes Measurement Information System scales was 0.106. Conclusion: The well-being of a cancer patient has many different aspects such as pain, fatigue, depression, and anxiety. These are assessed using a variety of surveys often collected at the same time. This study shows that the order in which the different aspects are collected from the patient is not important

Methane sources in gas hydrate-bearing cold-seeps : evidence from radiocarbon and stable isotopes

Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Marine Chemistry 115 (2009): 102-109, doi:10.1016/j.marchem.2009.07.001.Fossil methane from the large and dynamic marine gas hydrate reservoir has the potential to influence oceanic and atmospheric carbon pools. However, natural radiocarbon (14C) measurements of gas hydrate methane have been extremely limited, and their use as a source and process indicator has not yet been systematically established. In this study, gas hydrate-bound and dissolved methane recovered from six geologically and geographically distinct high-gas-flux cold seeps was found to be 98 to 100% fossil based on its 14C content. Given this prevalence of fossil methane and the small contribution of gas hydrate (≤1%) to the present-day atmospheric methane flux, non-fossil contributions of gas hydrate methane to the atmosphere are not likely to be quantitatively significant. This conclusion is consistent with contemporary atmospheric methane budget calculations. In combination with δ13C- and δD-methane measurements, we also determine the extent to which the low, but detectable, amounts of 14C (~ 1-2 percent modern carbon, pMC) in methane from two cold seeps might reflect in situ production from near-seafloor sediment organic carbon (SOC). A 14C mass balance approach using fossil methane and 14C-enriched SOC suggests that as much as 8 to 29% of hydrate-associated methane carbon may originate from SOC contained within the upper 6 meters of sediment. These findings validate the assumption of a predominantly fossil carbon source for marine gas hydrate, but also indicate that structural gas hydrate from at least certain cold seeps contains a component of methane produced during decomposition of non-fossil organic matter in near-surface sediment.This work was supported by the Office of Naval Research and Naval Research Laboratory (NRL). Partial support was also provided by the USGS Mendenhall Postdoctoral Research Fellowship Program to JWP, and NSF Chemical Oceanography (OCE-0327423) and Integrated Carbon Cycle Research (EAR- 0403949) program support to JEB

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

Growth Based Morphogenesis of Vertebrate Limb Bud

Many genes and their regulatory relationships are involved in developmental phenomena. However, by chemical information alone, we cannot fully understand changing organ morphologies through tissue growth because deformation and growth of the organ are essentially mechanical processes. Here, we develop a mathematical model to describe the change of organ morphologies through cell proliferation. Our basic idea is that the proper specification of localized volume source (e.g., cell proliferation) is able to guide organ morphogenesis, and that the specification is given by chemical gradients. We call this idea “growth-based morphogenesis.” We find that this morphogenetic mechanism works if the tissue is elastic for small deformation and plastic for large deformation. To illustrate our concept, we study the development of vertebrate limb buds, in which a limb bud protrudes from a flat lateral plate and extends distally in a self-organized manner. We show how the proportion of limb bud shape depends on different parameters and also show the conditions needed for normal morphogenesis, which can explain abnormal morphology of some mutants. We believe that the ideas shown in the present paper are useful for the morphogenesis of other organs

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Comparative Molecular Analysis of Gastrointestinal Adenocarcinomas

We analyzed 921 adenocarcinomas of the esophagus, stomach, colon, and rectum to examine shared and distinguishing molecular characteristics of gastrointestinal tract adenocarcinomas (GIACs). Hypermutated tumors were distinct regardless of cancer type and comprised those enriched for insertions/deletions, representing microsatellite instability cases with epigenetic silencing of MLH1 in the context of CpG island methylator phenotype, plus tumors with elevated single-nucleotide variants associated with mutations in POLE. Tumors with chromosomal instability were diverse, with gastroesophageal adenocarcinomas harboring fragmented genomes associated with genomic doubling and distinct mutational signatures. We identified a group of tumors in the colon and rectum lacking hypermutation and aneuploidy termed genome stable and enriched in DNA hypermethylation and mutations in KRAS, SOX9, and PCBP1. Liu et al. analyze 921 gastrointestinal (GI) tract adenocarcinomas and find that hypermutated tumors are enriched for insertions/deletions, upper GI tumors with chromosomal instability harbor fragmented genomes, and a group of genome-stable colorectal tumors are enriched in mutations in SOX9 and PCBP1

Machine Learning Detects Pan-cancer Ras Pathway Activation in The Cancer Genome Atlas

Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these \u201chidden responders\u201d may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq, copy number, and mutations from 33 different cancer types across The Cancer Genome Atlas (TCGA) PanCanAtlas project to predict aberrant molecular states in tumors. Applied to the Ras pathway, the method detects Ras activation across cancer types and identifies phenocopying variants. The model, trained on human tumors, can predict response to MEK inhibitors in wild-type Ras cell lines. We also present data that suggest that multiple hits in the Ras pathway confer increased Ras activity. The transcriptome is underused in precision oncology and, combined with machine learning, can aid in the identification of hidden responders. Way et al. develop a machine-learning approach using PanCanAtlas data to detect Ras activation in cancer. Integrating mutation, copy number, and expression data, the authors show that their method detects Ras-activating variants in tumors and sensitivity to MEK inhibitors in cell lines

The Immune Landscape of Cancer

We performed an extensive immunogenomic anal-ysis of more than 10,000 tumors comprising 33diverse cancer types by utilizing data compiled byTCGA. Across cancer types, we identified six im-mune subtypes\u2014wound healing, IFN-gdominant,inflammatory, lymphocyte depleted, immunologi-cally quiet, and TGF-bdominant\u2014characterized bydifferences in macrophage or lymphocyte signa-tures, Th1:Th2 cell ratio, extent of intratumoral het-erogeneity, aneuploidy, extent of neoantigen load,overall cell proliferation, expression of immunomod-ulatory genes, and prognosis. Specific drivermutations correlated with lower (CTNNB1,NRAS,orIDH1) or higher (BRAF,TP53,orCASP8) leukocytelevels across all cancers. Multiple control modalitiesof the intracellular and extracellular networks (tran-scription, microRNAs, copy number, and epigeneticprocesses) were involved in tumor-immune cell inter-actions, both across and within immune subtypes.Our immunogenomics pipeline to characterize theseheterogeneous tumors and the resulting data areintended to serve as a resource for future targetedstudies to further advance the field