Head and neck squamous cell carcinoma (HNSCC) is a common, morbid, and frequently lethal malignancy. To uncover its mutational spectrum, we analyzed whole-exome sequencing data from 74 tumor-normal pairs. The majority exhibited a mutational profile consistent with tobacco exposure; human papillomavirus was detectable by sequencing DNA from infected tumors. In addition to identifying previously known HNSCC genes (TP53, CDKN2A, PTEN, PIK3CA, and HRAS), our analysis revealed many genes not previously implicated in this malignancy. At least 30% of cases harbored mutations in genes that regulate squamous differentiation (for example, NOTCH1, IRF6, and TP63), implicating its dysregulation as a major driver of HNSCC carcinogenesis. More generally, the results indicate the ability of large-scale sequencing to reveal fundamental tumorigenic mechanisms.

/pdf/the-mutational-landscape-of-head-and-neck-squamous-cell-oc5uxdfntk.pdf

The Mutational Landscape of Head and Neck Squamous Cell Carcinoma

The text consists of two sections, one for those studying or practicing diagnostic radiology, nuclear medicine and radiation oncology; the other for those engaged in the study or clinical practice of radiation oncology--a new chapter, on radiologic terrorism, is specifically for those in the radiation sciences who would manage exposed individuals in the event of a terrorist event. The 17 chapters in Section I represent a general introduction to radiation biology and a complete, self-contained course especially for residents in diagnostic radiology and nuclear medicine that follows the Syllabus in Radiation Biology of the RSNA. The 11 chapters in Section II address more in-depth topics in radiation oncology, such as cancer biology, retreatment after radiotherapy, chemotherapeutic agents and hyperthermia.

Radiobiology for the Radiologist

Updated 2016 EAU Guidelines on Muscle-invasive and Metastatic Bladder Cancer

Mixed linear models are emerging as a method of choice for conducting genetic association studies in humans and other organisms. The advantages of the mixed-linear-model association (MLMA) method include the prevention of false positive associations due to population or relatedness structure and an increase in power obtained through the application of a correction that is specific to this structure. An underappreciated point is that MLMA can also increase power in studies without sample structure by implicitly conditioning on associated loci other than the candidate locus. Numerous variations on the standard MLMA approach have recently been published, with a focus on reducing computational cost. These advances provide researchers applying MLMA methods with many options to choose from, but we caution that MLMA methods are still subject to potential pitfalls. Here we describe and quantify the advantages and pitfalls of MLMA methods as a function of study design and provide recommendations for the application of these methods in practical settings.

/pdf/advantages-and-pitfalls-in-the-application-of-mixed-model-3dn5v7uflg.pdf

Advantages and pitfalls in the application of mixed-model association methods

Background.
Therapy for head and neck cancers has evolved over the past decade, but few detailed analyses of recent developments in survival on the population level have been published.

Changes in Survival in Head and Neck Cancers in the Late 20th and Early 21st Century: A Period Analysis

Nonparametric methods have attracted less attention than their parametric counterparts for cure rate analysis. In this paper, we study a general nonparametric mixture model. The proportional hazards assumption is employed in modeling the effect of covariates on the failure time of patients who are not cured. The EM algorithm, the marginal likelihood approach, and multiple imputations are employed to estimate parameters of interest in the model. This model extends models and improves estimation methods proposed by other researchers. It also extends Cox's proportional hazards regression model by allowing a proportion of event-free patients and investigating covariate effects on that proportion. The model and its estimation method are investigated by simulations. An application to breast cancer data, including comparisons with previous analyses using a parametric model and an existing nonparametric model by other researchers, confirms the conclusions from the parametric model but not those from the existing nonparametric model.

A Nonparametric Mixture Model for Cure Rate Estimation

Cure rate estimation is an important issue in clinical trials for diseases such as lymphoma and breast cancer and mixture models are the main statistical methods. In the last decade, mixture models under different distributions, such as exponential, Weibull, log-normal and Gompertz, have been discussed and used. However, these models involve stronger distributional assumptions than is desirable and inferences may not be robust to departures from these assumptions. In this paper, a mixture model is proposed using the generalized F distribution family. Although this family is seldom used because of computational difficulties, it has the advantage of being very flexible and including many commonly used distributions as special cases. The generalised F mixture model can relax the usual stronger distributional assumptions and allow the analyst to uncover structure in the data that might otherwise have been missed. This is illustrated by fitting the model to data from large-scale clinical trials with long follow-up of lymphoma patients. Computational problems with the model and model selection methods are discussed. Comparison of maximum likelihood estimates with those obtained from mixture models under other distributions are included.

A generalized F mixture model for cure rate estimation

The Ontario Cancer Registry (OCR) and the Surveillance, Epidemiology and End Results (SEER) databases were used to describe temporal trends in the incidence and survival of squamous cancers of the upper aerodigestive tract (UADT) in Ontario and the US between 1984 and 2001. Between the 1984-86 and 1999-01 periods, the age-adjusted incidence rate of all first primary cancers of the UADT decreased from 11.6 (11.2-12.0) to 8.8 (8.5-9.1) in Ontario and 13.0 (12.7-13.3) to 10.2 (10.0-10.4) in the US. Significant decreases in incidence were observed in many UADT sites but there was no significant change in the incidence of cancer of the oropharynx in either the US or Canada. Over the same period, the 5-year relative survival for all UADT cancers increased from 49.2% (47.2-51.2%) to 57.1%(55.0-59.1%) in Ontario and from 48.1% (46.9-49.3%) to 52.4% (51.2-53.6%) in the US. This significant improvement in the outcome of UADT cancer was largely due to a dramatic increase in the 5-year relative survival for cancers of the oropharynx from 31.1% (27.1-35.1%) to 53.6% (49.3-57.9%) in Ontario and from 35.3% (32.9-37.8%) to 51.0% (48.7-53.3%) in the US. Smaller increases in survival were observed in cancers of the oral cavity, nasopharynx, and hypopharynx, but there was no evidence of any increase in survival for cancer of the larynx. These results are consistent with the hypothesis that there has been a major change in the etiology of cancer of the oropharynx in Canada and the US and a concomitant change in its response to therapy.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ijc.24533

Temporal trends in the incidence and survival of cancers of the upper aerodigestive tract in Ontario and the United States.

smcure: An R-package for estimating semiparametric mixture cure models

In this article, we present a frailty model using the generalized gamma distribution as the frailty distribution. It is a power generalization of the popular gamma frailty model. It also includes other frailty models such as the lognormal and Weibull frailty models as special cases. The flexibility of this frailty distribution makes it possible to detect a complex frailty distribution structure which may otherwise be missed. Due to the intractable integrals in the likelihood function and its derivatives, we propose to approximate the integrals either by Monte Carlo simulation or by a quadrature method and then determine the maximum likelihood estimates of the parameters in the model. We explore the properties of the proposed frailty model and the computation method through a simulation study. The study shows that the proposed model can potentially reduce errors in the estimation, and that it provides a viable alternative for correlated data. The merits of proposed model are demonstrated in analysing the effects of sublingual nitroglycerin and oral isosorbide dinitrate on angina pectoris of coronary heart disease patients based on the data set in Danahy et al. (sustained hemodynamic and antianginal effect of high dose oral isosorbide dinitrate. Circulation 1977; 55:381-387).

Yingwei Peng

Papers

A Nonparametric Mixture Model for Cure Rate Estimation

A generalized F mixture model for cure rate estimation

Temporal trends in the incidence and survival of cancers of the upper aerodigestive tract in Ontario and the United States.

smcure: An R-package for estimating semiparametric mixture cure models

Generalized gamma frailty model