CCND1 as a Predictive Biomarker of Neoadjuvant Chemotherapy in Patients with Locally Advanced Head and Neck Squamous Cell Carcinoma

BACKGROUND: Cyclin D1 (CCND1) has been associated with chemotherapy resistance and poor prognosis. In this study, we tested the hypothesis that CCND1 expression determines response and clinical outcomes in locally advanced head and neck squamous cell carcinoma (HNSCC) patients treated with neoadjuvant chemotherapy followed by surgery and radiotherapy. METHODOLOGY AND FINDINGS: 224 patients with HNSCC were treated with either cisplatin-based chemotherapy followed by surgery and radiotherapy (neoadjuvant group, n = 100) or surgery and radiotherapy (non-neoadjuvant group, n = 124). CCND1 expression was assessed by immunohistochemistry. CCND1 levels were analyzed with chemotherapy response, disease-free survival (DFS) and overall survival (OS). There was no significant difference between the neoadjuvant group and non-neoadjuvant group in DFS and OS (p = 0.929 and p = 0.760) when patients treated with the indiscriminate administration of cisplatin-based chemotherapy. However, in the neoadjuvant group, patients whose tumors showed a low CCND1 expression more likely respond to chemotherapy (p<0.001) and had a significantly better OS and DFS than those whose tumors showed a high CCND1 expression (73% vs 8%, p<0.001; 63% vs 6%, p<0.001). Importantly, patients with a low CCND1 expression in neoadjuvant group received more survival benefits than those in non-neoadjuvant group (p = 0.016), however patients with a high CCND1 expression and treated with neoadjuvant chemotherapy had a significantly poor OS compared to those treated with surgery and radiotherapy (p = 0.032). A multivariate survival analysis also showed CCND1 expression was an independent predictive factor (p<0.001). CONCLUSIONS: This study suggests that some but not all patients with HNSCC may benefit from neoadjuvant chemotherapy with cisplatin-based regimen and CCND1 expression may serve as a predictive biomarker in selecting patients undergo less than two cycles of neoadjuvant chemotherapy

An Adaptive Chaotic Sine Cosine Algorithm for Constrained and Unconstrained Optimization

Sine cosine algorithm (SCA) is a new meta-heuristic approach suggested in recent years, which repeats some random steps by choosing the sine or cosine functions to find the global optimum. SCA has shown strong patterns of randomness in its searching styles. At the later stage of the algorithm, the drop of diversity of the population leads to locally oriented optimization and lazy convergence when dealing with complex problems. Therefore, this paper proposes an enriched SCA (ASCA) based on the adaptive parameters and chaotic exploitative strategy to alleviate these shortcomings. Two mechanisms are introduced into the original SCA. First, an adaptive transformation parameter is proposed to make transformation more flexible between global search and local exploitation. Then, the chaotic local search is added to augment the local searching patterns of the algorithm. The effectiveness of the ASCA is validated on a set of benchmark functions, including unimodal, multimodal, and composition functions by comparing it with several well-known and advanced meta-heuristics. Simulation results have demonstrated the significant superiority of the ASCA over other peers. Moreover, three engineering design cases are employed to study the advantage of ASCA when solving constrained optimization tasks. The experimental results have shown that the improvement of ASCA is beneficial and performs better than other methods in solving these types of problems

A new data processing technique for Rayleigh-Taylor instability growth experiments

Typical face-on experiments for Rayleigh-Taylor instability study involve the time-resolved radiography of an accelerated foil with line-of-sight of the radiography along the direction of motion. The usual method which derives perturbation amplitudes from the face-on images reverses the actual image transmission procedure, so the obtained results will have a large error in the case of large optical depth. In order to improve the accuracy of data processing, a new data processing technique has been developed to process the face-on images. This technique based on convolution theorem, refined solutions of optical depth can be achieved by solving equations. Furthermore, we discuss both techniques for image processing, including the influence of modulation transfer function of imaging system and the backlighter spatial profile. Besides, we use the two methods to the process the experimental results in Shenguang-II laser facility and the comparison shows that the new method effectively improve the accuracy of data processing

Two typical cases with low and high cyclin D1 expression were tested by cytokeratin stain.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0026399#pone-0026399-g001" target="_blank">Figs. A–D</a>: The low cyclin D1 expression case. A. HE stain (400cyclin D1 expression were tested by cytok D1 stain (400 case. P-CK stain (40000 cases. E–H: The high cyclin D1 expression case. E. HE stain (400cyclin D1 expression were tested by cytok D1 stain (400×); H. P-CK stain (40000×).</p

Characteristics of surgical specimens.

<p>Note: neoadjuvant group: cisplatin-based neoadjuvant chemotherapy followed by surgery and radiotherapy. Non-neoadjuvant group: surgery followed by radiotherapy. Lower cervical metastases: cervical metastases below the plane of cricoid cartilage inferior margin.</p

Kaplan-Meier survival curves for different treatment protocols and biomarker as well as the impact of treatment procedure according to CCND1 expression.

<p>Kaplan-Meier survival curves for different treatment protocols and biomarker as well as the impact of treatment procedure according to CCND1 expression.</p

Baseline demographics for the 224 patients who participated in the study.

<p>Abbreviations: SD: standard deviation; neoadjuvant group: cisplatin-based neoadjuvant chemotherapy followed by surgery and radiotherapy group. Non-neoadjuvant group: surgery followed by radiotherapy group.</p

Cox proportional hazards regression models in estimating overall survival.

<p>Note: Site (cat).</p><p>*: categorical co-variable.</p>†<p>: Interaction.</p

CCND1 protein expression and clinical response in patients with HNSCC who were treated with cisplatin-based regimens.

<p>Note: Low expression: IOD score of CCND1 protein expression <31388.459;</p><p>High expression: IOD score of CCND1 protein expression ≥31388.459.</p