Efficacy of concurrent chemoradiotherapy alone for loco-regionally advanced nasopharyngeal carcinoma: long-term follow-up analysis.

BACKGROUND: To analysis the clinical outcomes of concurrent chemoradiotherapy (CCRT) alone based on 10-year results for loco-regionally advanced nasopharyngeal carcinoma (LANPC), so as to provide evidence for individualized treatment strategy and designing appropriate clinical trial for different risk LANPC patients. METHODS: Consecutive patients with stage III-IVa (AJCC/UICC 8th) were enrolled in this study. All patients received radical intensity-modulated radiotherapy (IMRT) and concurrent cisplatin chemotherapy (CDDP). The hazard ratios (HRs) of death risk in patients with T3N0 was used as baseline, relative HRs were calculated by a Cox proportional hazard model to classify different death risk patients. Survival curves for the time-to-event endpoints were analyzed by the Kaplan-Meier method and compared using the log-rank test. All statistical tests were conducted at a two-sided level of significance of 0.05. RESULTS: A total of 456 eligible patients were included. With 12-year median follow-up, 10-year overall survival (OS) was 76%. 10-year loco-regionally failure-free survival (LR-FFS), distant failure-free survival (D-FFS) and failure-free survival (FFS) were 72%, 73% and 70%, respectively. Based on the relative hazard ratios (HRs) of death risk, LANPC patients were classified into 3 subgroups, low-risk group (T1-2N2 and T3N0-1) contained 244 patients with HR < 2; medium-risk group (T3N2 and T4N0-1) contained 140 patients with HR of 2 - 5; high-risk group (T4N2 and T1-4N3) contained 72 patients with HR > 5. The 10-year OS for patients in low-, medium-, and high-risk group were 86%, 71% and 52%, respectively. Significantly differences of OS rates were found between each of the two groups (low-risk group vs. medium-risk group, P < 0.001; low-risk group vs. high-risk group, P < 0.001; and medium-risk group vs. high-risk group, P = 0.002, respectively). Grade 3-4 late toxicities included deafness/otitis (9%), xerostomia (4%), temporal lobe injury (5%), cranial neuropathy (4%), peripheral neuropathy (2%), soft tissue damage (2%) and trismus (1%). CONCLUSIONS: Our classification criteria demonstrated that significant heterogeneity in death risk among TN substages for LANPC patients. IMRT plus CDDP alone maybe suitable for low-risk LANPC (T1-2N2 or T3N0-1), but not for medium- and high-risk patients. These prognostic groupings provide a practicable anatomic foundation to guide individualized treatment and select optimal targeting in the future clinical trials.

Increased MCL-1 synthesis promotes irradiation-induced nasopharyngeal carcinoma radioresistance via regulation of the ROS/AKT loop.

Worldwide, nasopharyngeal carcinoma (NPC) is a rare head and neck cancer; however, it is a common malignancy in southern China. Radiotherapy is the most important treatment strategy for NPC. However, although radiotherapy is a strong tool to kill cancer cells, paradoxically it also promotes aggressive phenotypes. Therefore, we mimicked the treatment process in NPC cells in vitro. Upon exposure to radiation, a subpopulation of NPC cells gradually developed resistance to radiation and displayed cancer stem-cell characteristics. Radiation-induced stemness largely depends on the accumulation of the antiapoptotic myeloid cell leukemia 1 (MCL-1) protein. Upregulated MCL-1 levels were caused by increased stability and more importantly, enhanced protein synthesis. We showed that repeated ionizing radiation resulted in persistently enhanced reactive oxygen species (ROS) production at a higher basal level, further promoting protein kinase B (AKT) signaling activation. Intracellular ROS and AKT activation form a positive feedback loop in the process of MCL-1 protein synthesis, which in turn induces stemness and radioresistance. AKT/MCL-1 axis inhibition attenuated radiation-induced resistance, providing a potential target to reverse radiation therapy-induced radioresistance.

Whole-body hyperthermia combined with chemotherapy and intensity-modulated radiotherapy for treatment of advanced nasopharyngeal carcinoma: a retrospective study with propensity score matching.

BACKGROUND: Several studies have reported the combination of intracavity or cervical lymph node hyperthermia with chemoradiotherapy (CRT) to improve clinical outcomes in nasopharyngeal carcinoma (NPC), but the combination with whole-body hyperthermia (WBH) for treating NPC is unexplored. We aimed to assess the efficacy of the combination of radiotherapy, chemotherapy and WBH in patients with locoregionally advanced NPC. METHODS: Between July 2008 and November 2012, 239 newly diagnosed NPC patients were enrolled in a pre-propensity score-matched cohort, including 193 patients who received CRT (CRT group) and 46 who underwent CRT with WBH (HCRT group). The feasibility and clinical outcomes of both groups were evaluated and toxicities assessed. Survival rates were assessed using the Kaplan-Meier method, log-rank test and Cox regression. RESULTS: Following propensity score matching, 46 patients from each group were included. The 5-year overall survival (OS) rates were 65.2% in the CRT group and 80.3% in the HCRT group (p=.027). In contrast, the other survival outcomes at 5 years were similar between the groups: locoregional recurrence-free survival (LRRFS), 74.7% vs. 87.6% (p=.152); distant metastasis-free survival (DMFS), 67.4% vs. 77.9% (p=.125); and progression-free survival (PFS), 53.1% vs. 69.2% (p=.115). In the multivariate analyses, the only two independent predictors of OS were clinical stage and HCRT. CONCLUSIONS: These results suggest that WBH, when combined with CRT, can improve the OS of patients with advanced NPC.

RASSF1A inhibits PDGFB-driven malignant phenotypes of nasopharyngeal carcinoma cells in a YAP1-dependent manner.

Nasopharyngeal carcinoma (NPC) is a highly aggressive tumor characterized by distant metastasis. Deletion or down-regulation of the tumor suppressor protein ras-association domain family protein1 isoform A (RASSF1A) has been confirmed to be a key event in NPC progression; however, little is known about the effects or underlying mechanism of RASSF1A on the malignant phenotype. In the present study, we observed that RASSF1A expression inhibited the malignant phenotypes of NPC cells. Stable silencing of RASSF1A in NPC cell lines induced self-renewal properties and tumorigenicity in vivo/in vitro and the acquisition of an invasive phenotype in vitro. Mechanistically, RASSF1A inactivated Yes-associated Protein 1 (YAP1), a transcriptional coactivator, through actin remodeling, which further contributed to Platelet Derived Growth Factor Subunit B (PDGFB) transcription inhibition. Treatment with ectopic PDGFB partially increased the malignancy of NPC cells with transient knockdown of YAP1. Collectively, these findings suggest that RASSF1A inhibits malignant phenotypes by repressing PDGFB expression in a YAP1-dependent manner. PDGFB may serve as a potential interest of therapeutic regulators in patients with metastatic NPC.

Double-Granule Conditional-Entropies Based on Three-Level Granular Structures.

Rough set theory is an important approach for data mining, and it refers to Shannon's information measures for uncertainty measurements. The existing local conditional-entropies have both the second-order feature and application limitation. By improvements of hierarchical granulation, this paper establishes double-granule conditional-entropies based on three-level granular structures (i.e., micro-bottom, meso-middle, macro-top ), and then investigates the relevant properties. In terms of the decision table and its decision classification, double-granule conditional-entropies are proposed at micro-bottom by the dual condition-granule system. By virtue of successive granular summation integrations, they hierarchically evolve to meso-middle and macro-top, to respectively have part and complete condition-granulations. Then, the new measures acquire their number distribution, calculation algorithm, three bounds, and granulation non-monotonicity at three corresponding levels. Finally, the hierarchical constructions and achieved properties are effectively verified by decision table examples and data set experiments. Double-granule conditional-entropies carry the second-order characteristic and hierarchical granulation to deepen both the classical entropy system and local conditional-entropies, and thus they become novel uncertainty measures for information processing and knowledge reasoning.

RASSF6-mediated inhibition of Mcl-1 through JNK activation improves the anti-tumor effects of sorafenib in renal cell carcinoma.

Ras association domain family member 6 (RASSF6) has been shown to act as a tumor suppressor and predictor of poor prognosis in renal cell carcinoma (RCC). However, little is known about the effects of RASSF6 on sorafenib resistance or the underlying mechanism. Here, we show that RASSF6 expression positively correlates with sorafenib sensitivity in RCC cells and human samples. Stable ectopic overexpression of RASSF6 in RCC cell lines reduces resistance to sorafenib in vitro and in vivo. At a molecular level, RASSF6 activates the JNK signaling pathway, which further contributes to Mcl-1 inhibition. Suppression of the JNK pathway can partially restore Mcl-1 expression and sorafenib resistance. Together, these findings suggest that RASSF6 inhibits sorafenib resistance by repressing Mcl-1 through the JNK-dependent pathway. RASSF6 may serve as a novel regulator for sorafenib therapy in RCC.

[A method of QRS complexes detection based on complex wavelet decomposing].

The extraction and identification of ECG (electrocardiogram) signal characteristic parameters are the basic steps toward ECG analysis and diagnosis. The fast and precise detection of QRS complexes is very important in ECG signal analysis, for it is the precondition of the correlative parameters calculation and diagnosis. In our work, firstly, we used the modulus value of complex wavelet decomposition to detect QRS complexes from ECG signal. As the shape and amplitude of ECG signal varies from person to person, we utilized the self-learning algorithm for adjusting the threshold to adapt the changes. The correct detection rate of QRS complexes is up to 99.81% based on MIT-BIH ECG data. Finally, we used the similar methods to detect the P and T waves, after QRS complexes detection.

[An algorithm for quick fitting of linear approximation distance thresholding].

In this paper is proposed a new method that approximates line segment with angle to control line as a basis for improving radial fitting. Experiments on selected records from the Massachusettes Institute of Technology and Boston's Beth Isral Hospital (MIT-BIH) arrhythmia database have revealed that the improved algorithm not only increases computation quantity, but also improves approximating quality and potentiates Real-time application of the linear approximation distance thresholding (LADT).

[Detection of QRS complexes using wavelet transformation and golden section search algorithm].

The extraction and identification of ECG (electrocardiogram) signal characteristic parameters are the basis of ECG analysis and diagnosis. The fast and precise detection of QRS complexes is very important in ECG signal analysis; for it is a pre-requisite for the correlative parameters calculation as well as for correct diagnosis. In our work, firstly, the modulus maximum of wavelet transform is applied to the QRS complexes detection from ECG signal. Once there are mis-detections or missed detections happening, we utilize the Golden Section Search algorithm to adjust the threshold of maxima determination. The correct detection rate of the QRS complexes is up to 99.6% based on MIT-BIH ECG data.

Computational study on the conformation and vibration frequencies of ß-sheet of ε-polylysine in vacuum.

Two oligomers, each containing 3 l-lysine residues, were used as model molecules for the simulation of the beta-sheet conformation of varepsilon-polylysine (varepsilon-PLL) chains. Their C terminals were capped with ethylamine and N terminals were capped with alpha-l-aminobutanoic acid, respectively. The calculations were carried out with the hybrid two-level ONOIM (B3LYP/6-31G:PM3) computational chemistry method. The optimized conformation was obtained and IR frequencies were compared with experimental data. The result indicated that the two chains were winded around each other to form a distinct cyclohepta structure through bifurcated hydrogen bonds. The groups of amide and alpha-amidocyanogen coming from one chain and the carbonyl group from the other chain were involved in the cyclohepta structure. The bond angle of the bifurcated hydrogen bonds was 66.6 degrees . The frequency analysis at ONIOM [B3LYP/6-31G (d):PM3] level showed the IR absorbances of the main groups, such as the amide and amidocyanogen groups, were in accordance with the experimental data.

[Similarity measures between vague sets and their application to electrocardiogram auto-recognition].

The similarity measures between Vague sets are one of the most important technologies in Vague sets, In this paper, the new similarity measures based on Huang Guoshun's related works are presented and applied in electrocardiogram auto-recognition. Based on medical requiresments, in this paper, the characteristic parameters of signals from Massachusettes Institute of Technology (database) have been picked up and studied with BP neural network. In the end, the electrocardiogram samples are classified with the use of those characteristic parameters. The result shows that the accuracy of recognition goes up to 99.04%.

[A strategy of ECG classification based on SVM].

Electrocardiogram (ECG) signal is important for physician to diagnose diseases. Various existing techniques on ECG classification have been reported. Generally, these techniques classify only two or three arrhythmias and need significantly long processing time. A new algorithm based on Support vector machine (SVM) is presented to solve the problem in this paper, which has been successfully applied to the classification of ECG. And in this paper are clarified the fundamental ideas of the classification of ECG based on SVM. Compared with the traditional neural network, this method is superior to it in theory. Because this new method deals with the minimization of the test samples, not the training samples.

[A multi-lead ECG classification network system based on modified LADT].

An electrocardiogram (ECG) classify system based on the features of the ECG and neural network classification, which is the simulation of the real world situation, was present. First, a modified approach of the linear approximation distance thresholding (LADT) algorithm was studied and the features of the ECG were obtained. Then a neural network which can classify the multi-lead ECG data was trained with these features along the theory of the ECG diagnosis and the situation of ECG diagnosis in practice. Thus take a new idea for the ECG automatic analysis. The algorithm was tested using several ECG signals of MIT-BIH, and the performance was good. The correct rate of the trained wave is 100%, untrained is 78.2%.

[QRS complexes detection based on Mexican-hat wavelet].

In this paper, we using Mexican-hat wavelet transform to detect characteristic points of ECG signal based on the characteristic points corresponding with the extremes of Mexican-hat wavelet transform. It offers a new detection method of ECG signal analysis. This method is simple and it is proved to be accurate and reliable. The correct rate of QRS detection rate examined by the MIT-BIT arrhythmia database rises up to 99.9%.

[Number of classes from ECG and its application to ECG analysis].

The aim of this study was to detect QRS complex powers accurately. ECG was approximated by lines. It produced number of classes with main features of the whole ECG. Then these number of classes were analyzed in detail. The QRS detection rate reached 99.9% as validated by using single lead signals from MIT/BIH database. Complex powers can be recognized accurately with this method.