榄香烯治疗非小细胞肺癌的作用机制研究进展

榄香烯注射液是从天然中草药姜科植物温郁金中提取获得的萜烯类化合物,其主要生物学活性为降低肿瘤细胞有丝分裂能力,诱导肿瘤细胞凋亡,抑制肿瘤细胞的生长,从而改善NSCLC患者的临床症状,增强患者免疫力.本文主要从杀灭癌细胞、诱导癌细胞凋亡、抑制癌细胞血管形成、增强患者免疫力等几方面综述榄香烯注射液对非小细胞肺癌的作用机制.     

Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units

Background

Arsenic in drinking water, a major health hazard to millions of people in South and East Asia and in other parts of the world, is ingested primarily as trivalent inorganic arsenic (iAs), which then undergoes hepatic methylation to methylarsonic acid (MMAs) and a second methylation to dimethylarsinic acid (DMAs). Although MMAs and DMAs are also known to be toxic, DMAs is more easily excreted in the urine and therefore methylation has generally been considered a detoxification pathway. A collaborative modeling project between epidemiologists, biologists, and mathematicians has the purpose of explaining existing data on methylation in human studies in Bangladesh and also testing, by mathematical modeling, effects of nutritional supplements that could increase As methylation.

Methods

We develop a whole body mathematical model of arsenic metabolism including arsenic absorption, storage, methylation, and excretion. The parameters for arsenic methylation in the liver were taken from the biochemical literature. The transport parameters between compartments are largely unknown, so we adjust them so that the model accurately predicts the urine excretion rates of time for the iAs, MMAs, and DMAs in single dose experiments on human subjects.

Results

We test the model by showing that, with no changes in parameters, it predicts accurately the time courses of urinary excretion in mutiple dose experiments conducted on human subjects. Our main purpose is to use the model to study and interpret the data on the effects of folate supplementation on arsenic methylation and excretion in clinical trials in Bangladesh. Folate supplementation of folate-deficient individuals resulted in a 14% decrease in arsenicals in the blood. This is confirmed by the model and the model predicts that arsenicals in the liver will decrease by 19% and arsenicals in other body stores by 26% in these same individuals. In addition, the model predicts that arsenic methyltransferase has been upregulated by a factor of two in this population. Finally, we also show that a modification of the model gives excellent fits to the data on arsenic metabolism in human cultured hepatocytes.

Conclusions

The analysis of the Bangladesh data using the model suggests that folate supplementation may be more effective at reducing whole body arsenic than previously expected. There is almost no data on the upregulation of arsenic methyltransferase in populations chronically exposed to arsenic. Our model predicts upregulation by a factor of two in the Bangladesh population studied. This prediction should be verified since it could have important public health consequences both for treatment strategies and for setting appropriate limits on arsenic in drinking water. Our model has compartments for the binding of arsenicals to proteins inside of cells and we show that these comparments are necessary to obtain good fits to data. Protein-binding of arsenicals should be explored in future biochemical studies.     

Overexpression of cyclin Y in non-small cell lung cancer is associated with cancer cell proliferation

Cyclin Y (CCNY) is a key cell cycle regulator that acts as a growth factor sensor to integrate extracellular signals with the cell cycle machinery. The expression status of CCNY in lung cancer and its clinical significance remain unknown. The data indicates that CCNY may be deregulated in non-small cell lung cancer, where it may act to promote cell proliferation. These studies suggest that CCNY may be a candidate biomarker of NSCLC and a possible therapeutic target for lung cancer treatment.     

Shining a light on metabolic vulnerabilities in non-small cell lung cancer

Metabolic reprogramming is a hallmark of cancer which contributes to essential processes required for cell survival, growth, and proliferation. Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and its genomic classification has given rise to the design of therapies targeting tumors harboring specific gene alterations that cause aberrant signaling. Lung tumors are characterized with having high glucose and lactate use, and high heterogeneity in their metabolic pathways. Here we review how NSCLC cells with distinct mutations reprogram their metabolic pathways and highlight the potential metabolic vulnerabilities that might lead to the development of novel therapeutic strategies.     

Validation of a blood protein signature for non-small cell lung cancer

Background

CT screening for lung cancer is effective in reducing mortality, but there are areas of concern, including a positive predictive value of 4% and development of interval cancers. A blood test that could manage these limitations would be useful, but development of such tests has been impaired by variations in blood collection that may lead to poor reproducibility across populations.

Results

Blood-based proteomic profiles were generated with SOMAscan technology, which measured 1033 proteins. First, preanalytic variability was evaluated with Sample Mapping Vectors (SMV), which are panels of proteins that detect confounders in protein levels related to sample collection. A subset of well collected serum samples not influenced by preanalytic variability was selected for discovery of lung cancer biomarkers. The impact of sample collection variation on these candidate markers was tested in the subset of samples with higher SMV scores so that the most robust markers could be used to create disease classifiers. The discovery sample set (n = 363) was from a multi-center study of 94 non-small cell lung cancer (NSCLC) cases and 269 long-term smokers and benign pulmonary nodule controls. The analysis resulted in a 7-marker panel with an AUC of 0.85 for all cases (68% adenocarcinoma, 32% squamous) and an AUC of 0.93 for squamous cell carcinoma in particular. This panel was validated by making blinded predictions in two independent cohorts (n = 138 in the first validation and n = 135 in the second). The model was recalibrated for a panel format prior to unblinding the second cohort. The AUCs overall were 0.81 and 0.77, and for squamous cell tumors alone were 0.89 and 0.87. The estimated negative predictive value for a 15% disease prevalence was 93% overall and 99% for squamous lung tumors. The proteins in the classifier function in destruction of the extracellular matrix, metabolic homeostasis and inflammation.

Conclusions

Selecting biomarkers resistant to sample processing variation led to robust lung cancer biomarkers that performed consistently in independent validations. They form a sensitive signature for detection of lung cancer, especially squamous cell histology. This non-invasive test could be used to improve the positive predictive value of CT screening, with the potential to avoid invasive evaluation of nonmalignant pulmonary nodules.     

Tumor vasculature as a therapeutic target in non-small cell lung cancer

Despite developments in conventional (chemo)radiotherapy and surgery, survival of non-small cell lung cancer (NSCLC) patients remains poor. Treatments with targeted molecular drugs offer novel therapeutic strategies. Bevacizumab, a recombinant anti-vascular endothelial growth factor (VEGF) antibody, is the antiangiogenic drug at the most advanced stage of development in the therapy of NSCLC. However, a number of questions and future challenges relating to the use of bevacizumab in NSCLC remain. Furthermore, novel agents targeting the pre-existing NSCLC vasculature (i.e. vascular disrupting agents, VDAs) or multiple tyrosine kinase inhibitors have emerged as unique drug classes delivering promising results in several preclinical and clinical studies. Herein, we review the most recent data using these novel targeted agents either alone or in combination with chemotherapy in NSCLC.     

Genetic and epigenetic analysis of non-small cell lung cancer with NotI-microarrays

This study aimed to clarify genetic and epigenetic alterations that occur during lung carcinogenesis and to design perspective sets of newly identified biomarkers. The original method includes chromosome 3 specific NotI-microarrays containing 180 NotI clones associated with genes for hybridization with 40 paired normal/tumor DNA samples of primary lung tumors: 28 squamous cell carcinomas (SCC) and 12 adenocarcinomas (ADC). The NotI-microarray data were confirmed by qPCR and bisulfite sequencing analyses. Forty-four genes showed methylation and/or deletions in more than 15% of non–small cell lung cancer (NSCLC) samples. In general, SCC samples were more frequently methylated/deleted than ADC. Moreover, the SCC alterations were observed already at stage I of tumor development, whereas in ADC many genes showed tumor progression specific methylation/deletions. Among genes frequently methylated/deleted in NSCLC, only a few were already known tumor suppressor genes: RBSP3 (CTDSPL), VHL and THRB. The RPL32, LOC285205, FGD5 and other genes were previously not shown to be involved in lung carcinogenesis. Ten methylated genes, i.e., IQSEC1, RBSP3, ITGA9, FOXP1, LRRN1, GNAI2, VHL, FGD5, ALDH1L1 and BCL6 were tested for expression by qPCR and were found downregulated in the majority of cases. Three genes (RBSP3, FBLN2 and ITGA9) demonstrated strong cell growth inhibition activity. A comprehensive statistical analysis suggested the set of 19 gene markers, ANKRD28, BHLHE40, CGGBP1, RBSP3, EPHB1, FGD5, FOXP1, GORASP1/TTC21, IQSEC1, ITGA9, LOC285375, LRRC3B, LRRN1, MITF, NKIRAS1/RPL15, TRH, UBE2E2, VHL, WNT7A, to allow early detection, tumor progression, metastases and to discriminate between SCC and ADC with sensitivity and specificity of 80–100%.     

Drug-induced cell cycle perturbation in chemotherapy of patients with non-small cell lung cancer

To observe in vivo cell cycle perturbation in the chemotherapy of lung cancer, tumour cell kinetics during the first course of chemotherapy were measured in seven patients with histologically-verified non-small cell lung cancer. The tumour cells were aspirated from six lymph nodes and one subcutaneous nodule both prior to treatment and twice weekly after the administration of chemotherapeutic agents. The nuclear DNA content of aspirated tumour cells was measured with a scanning microdensitometer at a wavelength of 550 nm after the modified Feulgen reaction. The cell population in cell cycle was estimated with a cumulated percentage scale. Marked cell cycle perturbation occurred within one week after initiation of chemotherapy. There was a decrease in the G1 cell population, from 70.6 +/- 9.1% to 26.1 +/- 11.4%, and a corresponding increase of cells in G2-M phase, from 21.4 +/- 8.7% to 63.7 +/- 10.0%. The proportion of cells in S phase was slightly increased from 8.0 +/- 1.5% to 10.1 +/- 3.2% during this period. The degree of cell cycle changes was unrelated to the clinical response to chemotherapy.     

Initial medical attention on patients with early-stage non-small cell lung cancer

Background

Detection of early stage non-small cell lung cancer (NSCLC) is commonly believed to be incidental. Understanding the reasons that caused initial detection of these patients is important for early diagnosis. However, these reasons are not well studied.

Methods

We retrospectively reviewed medical records of patients diagnosed with stage I or II NSCLC between 2000 and 2009 at UT MD Anderson Cancer Center. Information on suggestive LC-symptoms or other reasons that caused detection were extracted from patients'' medical records. We applied univariate and multivariate analyses to evaluate the association of suggestive LC-symptoms with tumor size and patient survival.

Results

Of the 1396 early stage LC patients, 733 (52.5%) presented with suggestive LC-symptoms as chief complaint. 347 (24.9%) and 287 (20.6%) were diagnosed because of regular check-ups and evaluations for other diseases, respectively. The proportion of suggestive LC-symptom-caused detection had a linear relationship with the tumor size (correlation 0.96; with p<.0001). After age, gender, race, smoking status, therapy, and stage adjustment, the symptom-caused detection showed no significant difference in overall and LC-specific survival when compared with the other (non-symptom-caused) detection.

Conclusion

Symptoms suggestive of LC are the number one reason that led to detection in early NSCLC. They were also associated with tumor size at diagnosis, suggesting early stage LC patients are developing symptoms. Presence of symptoms in early stages did not compromise survival. A symptom-based alerting system or guidelines may be worth of further study to benefit NSCLC high risk individuals.     

Application of radiography of computed tomography in non-small cell lung cancer using prognosis model

ObjectiveStudying the diagnostic value of CT imaging in non-small cell lung cancer (NSCLC), and establishing a prognosis model combined with clinical characteristics is the objective, so as to provide a reference for the survival prediction of NSCLC patients.MethodCT scan data of NSCLC 200 patients were taken as the research object. Through image segmentation, the radiology features of CT images were extracted. The reliability and performance of the prognosis model based on the optimal feature number of specific algorithm and the prognosis model based on the global optimal feature number were compared.Results30-RELF-NB (30 optimal features, RELF feature selection algorithm and NB classifier) has the highest accuracy and AUC (area under the subject characteristic curve) in the prognosis model based on the optimal features of specific algorithm. Among the prognosis models based on global optimal features, 25-NB (25 global optimal features, naive Bayes classification algorithm classifier) has the highest accuracy and AUC. Compared with the prediction model based on feature training of specific feature selection algorithm, the overall performance and stability of the prediction model based on global optimal feature are higher.ConclusionThe prognosis model based on the global optimal feature established in this paper has good reliability and performance, and can be applied to the CT radiology of NSCLC.     

MiRNA调控非小细胞肺癌转移的研究进展

微小RNA是内源性的非编码小RNA分子,通过与靶mRNA的结合在转录后水平调控基因的表达,从而参与众多生命活动的调控。NSCLC是严重威胁人类健康的恶性肿瘤,侵袭转移是其主要特征,也是其治疗失败和死亡的主要原因。miRNA可以通过促进上皮-间质转化、金属基质蛋白酶表达,以及血管生成来促进NSCLC转移,而且miRNA在调节肺癌干细胞特性中也发挥着重要作用。转移相关的miRNA已成为肺癌靶向治疗的新靶点。     

CD10 expression in non-small cell lung cancer.

CD10 is a cell surface endopeptidase that inactivates various potentially growth stimulatory peptides. In lung cancer cell lines this downregulation has been associated with increased proliferation. Downregulation of CD10 in lung cancer tissue is described, suggesting a potential role in carcinogenesis and a possible use of CD10 as a prognostic marker. We aimed to determine the rate of CD10 expression in our non-small cell lung cancer (NSCLC) collection and to clarify its correlation with clinicopathological parameters and patient survival. 114 NSCLC were analysed immunohistochemically using a monoclonal CD10 antibody (clone NCL-CD10-270) on an NSCLC tissue micro array. The staining was semiquantitatively scored. CD10 expression was observed in 19% of cases, without any significant association with tumour type, -size, -grading, nodal status, clinical stage, and patient survival time. We conclude that a diagnostic use of CD10 immunostaining in NSCLC is unlikely.