Impact of HPV infection on the clinical outcome of p-CAIR trial in head and neck cancer

The purpose of the study was to analyse the influence of HPV infection on the outcome of a randomized clinical trial of conventional (CF) versus 7-days-a-week postoperative radiotherapy (p-CAIR) for squamous cell cancer of the head and neck (SCCHN). Between 2001 and 2004, 279 patients with high-risk SCC of the larynx or cancer of the oral cavity/oropharynx were randomized to receive 63 Gy in fractions of 1.8 Gy given 5 days a week or 7 days a week (Radiother Oncol 87:155–163, 2008). The presence of HPV DNA in 131 archival paraffin blocks was assessed with multiplex quantitative real-time PCR using five consensus primers for the conservative L1 region and molecular beacon probes targeting 14 high-risk HPV subtypes. Following the RT-PCR procedure, we could determine the presence and type of HPV16, HPV18 and the other 12 less frequent oncogenic subtypes. Out of 131 samples, 9 were positive for HPV infection (6.9%), all of them with HPV16 subtype. None of the 65 laryngeal tumours was HPV positive. The 5-year LRC in HPV-positive patients was 100%, compared to 58% in the HPV-negative group (p = 0.02, log-rank test). Amongst 122 patients with HPV-negative tumours, 5-year LRC was 50.3% in p-CF versus 65.2 in p-CAIR (p = 0.37). HPV infection was associated with low expression of EGFR and cyclin D. This study demonstrates a favourable outcome for HPV-positive patients with SCCHN treated with postoperative radiotherapy. While considering the small number of HPV+ tumours, the data set can be considered as hypothesis generating only, the outcome raises new questions on the necessity of aggressive postoperative treatment in HPV+ patients

The JPSS-1 CrIS Instrument: Successful First-Year On-Orbit

No abstract availabl

Transformation pathways of 2,2-dimethyloxirane on aluminosilicates: the effects of catalyst structure and reaction conditions

The ring transformation reactions of 2,2-dimethyloxirane were studied over various aluminosilicates (HZSM-5, CuZSM-5, HY, AIMCM-41 or NaNa-loaded A1MCM-41) in a pulse reactor at 423 K. The main reactions identified were isomerisation and cyclic dimerisation. The product formation selectivities could be tuned by varying the pore size of the molecular sieves and/or altering the reaction parameters. Large pore size and mild conditions favoured isomerisation, while an optimally constrained environment and overloading the catalyst with the epoxide (increased pulse size) was advantageous for cyclic dimerisation

Noise Performance of the CrIS Instrument

The Cross-track Infrared Sounder (CrIS) is a spaceborne Fourier transform spectrometer (FTS) that was launched into orbit on 28 October 2011 onboard the Suomi National Polar-orbiting Partnership satellite. CrIS is a sophisticated sounding sensor that accurately measures upwelling infrared radiance at high spectral resolution. Data obtained from this sensor are used for atmospheric profiles retrieval and assimilation by numerical weather prediction models. Optimum vertical sounding resolution is achieved with high spectral resolution and multiple spectral channels; however, this can lead to increased noise. The CrIS instrument is designed to overcome this problem. Noise Equivalent Differential Radiance (NEdN) is one of the key parameters of the Sensor Data Record product. The CrIS on-orbit NEdN surpassesmission requirements with margin and has comparable or better performance when compared to heritage hyperspectral sensors currently on orbit. This paper describes CrIS noise performance through the characterization of the sensor’s NEdN and compares it to calibration data obtained during ground test. In addition, since FTS sensors can be affected by vibration that leads to spectrally correlated noise on top of the random noise inherent to infrared detectors, this paper also characterizes the CrIS NEdN with respect to the correlated noise contribution to the total NEdN. Lastly, the noise estimated from the imaginary part of the complex FTS spectra is extremely useful to assess andmonitor in-flight FTS sensor health. Preliminary results on the imaginary spectra noise analysis are also presented

Estimation for paired binomial data with application to radiation therapy

We compare and contrast several different methods for estimating the effect of treatment when responses are paired binomial observations. The ratio of binomial probabilities is the parameter of interest, while the binomial probabilities are nuisance parameters which may vary between pairs. The application is a meta-analysis of the treatment of rectal cancer, with observations in each study indicating the number of recurrences of the cancer in each of two groups, one with radiation therapy and one without. The ratio of the probabilities of recurrence in the radiation to non-radiation groups is of substantive interest, and is modelled as a logistic or complementary log-log function of an unknown linear combination of the covariates. The three methods we consider are maximum likelihood, a Bayesian approach and an approach based on estimating equations. For the MLE and Bayesian approach the potentially large number of nuisance parameters are estimated together with the parameters of interest, whereas for the estimating equation approach only the parameters of interest are estimated. A simulation study is performed to compare the methods and evaluate the impact of overdispersion. Copyright 2001 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34858/1/890_ftp.pd

The JPSS CrIS Instrument and the Evolution of Space-Based Infrared Sounders

This paper will summarize the development of infrared sounders since the 1970s, describe the technological hurdles that were overcome to provide ever-increasing performance capabilities, and highlight the radiometric performance of the CrIS instrument on JPSS-1 (CrIS-JPSS1). This includes details of the CrIS-JPSS1 measured noise-equivalent spectral radiance (NEdN) performance, radiometric uncertainty performance utilizing a new and improved internal calibration target, short-term and long-term repeatability, spectral uncertainty, and spectral stability. In addition, the full-resolution operating modes for CrIS-JPSS1 will be reviewed, including a discussion of how these modes will be used during on-orbit characterization tests. We will provide a brief update of CrIS-SNPP on-obit performance and the production status of the CrIS instruments for JPSS-2 through JPSS-4. Current technological challenges will also be reviewed, including how ongoing research and development is enabling improvements to future sounders. The expanding usage of infrared sounding data will also be discussed, including demonstration of value via data assimilation, the roles of the public/private sector in communicating the importance of sounding data for long-term observations, and the long road to success from research to operational data products

PTEN as a Prognostic and Predictive Marker in Postoperative Radiotherapy for Squamous Cell Cancer of the Head and Neck

BACKGROUND: Tumor suppressor PTEN is known to control a variety of processes related to cell survival, proliferation, and growth. PTEN expression is considered as a prognostic factor in some human neoplasms like breast, prostate, and thyroid cancer. METHODOLOGY/PRINCIPAL FINDINGS: In this study we analyzed the influence of PTEN expression on the outcome of a randomized clinical trial of conventional versus 7-days-a-week postoperative radiotherapy for squamous cell cancer of the head and neck. The patients with cancer of the oral cavity, oropharynx, and larynx were randomized to receive 63 Gy in fractions of 1.8 Gy given 5 days a week (CF) or 7 days a week (p-CAIR). Out of 279 patients enrolled in the study, 147 paraffin blocks were available for an immunohistochemical assessment of PTEN. To evaluate the prognostic value of PTEN expression and the effect of fractionation relative to PTEN, the data on the outcome of a randomized clinical trial were analyzed. Tumors with a high intensity of PTEN staining had significant gain in the loco-regional control (LRC) from p-CAIR (5-year LRC 92.7% vs. 70.8%, for p-CAIR vs. CF, p = 0.016, RR = 0.26). By contrast, tumors with low intensity of PTEN did not gain from p-CAIR (5-year LRC 56.2% vs. 47.2%, p = 0.49, RR = 0.94). The intensity of PTEN highly affected the LRC in a whole group of 147 patients (5-year LRC 80.9% vs. 52.3% for high vs. low PTEN, p = 0.0007, RR = 0.32). In multivariate Cox analysis, including neck node involvement, EGFR, nm23, Ki-67, p53, cyclin D1, tumor site and margins, PTEN remained an independent predictor of LRC (RR = 2.8 p = 0.004). CONCLUSIONS/SIGNIFICANCE: These results suggest that PTEN may serve as a potent prognostic and predictive marker in postoperative radiotherapy for high-risk squamous cell cancer of the head and neck

Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics

There is a growing attention toward personalized medicine. This is led by a fundamental shift from the ‘one size fits all’ paradigm for treatment of patients with conditions or predisposition to diseases, to one that embraces novel approaches, such as tailored target therapies, to achieve the best possible outcomes. Driven by these, several national and international genome projects have been initiated to reap the benefits of personalized medicine. Exome and targeted sequencing provide a balance between cost and benefit, in contrast to whole genome sequencing (WGS). Whole exome sequencing (WES) targets approximately 3% of the whole genome, which is the basis for protein-coding genes. Nonetheless, it has the characteristics of big data in large deployment. Herein, the application of WES and its relevance in advancing personalized medicine is reviewed. WES is mapped to Big Data “10 Vs” and the resulting challenges discussed. Application of existing biological databases and bioinformatics tools to address the bottleneck in data processing and analysis are presented, including the need for new generation big data analytics for the multi-omics challenges of personalized medicine. This includes the incorporation of artificial intelligence (AI) in the clinical utility landscape of genomic information, and future consideration to create a new frontier toward advancing the field of personalized medicine