scholarly journals Abstract 2800: The effect of surface protein adsorption on gold nanoparticle-intratumoral distribution and retention in a pre-clinical model of non-small cell lung cancer

Author(s):  
Rossana Terracciano ◽  
Brian E. Butler ◽  
Danilo Demarchi ◽  
Alessandro Grattoni ◽  
Carly S. Filgueira
2005 ◽  
Vol 23 (1) ◽  
pp. 175-183 ◽  
Author(s):  
Tien Hoang ◽  
Ronghui Xu ◽  
Joan H. Schiller ◽  
Philip Bonomi ◽  
David H. Johnson

Purpose (1) Identify clinical factors that can be used to predict survival in chemotherapy-naive patients with advanced non–small-cell lung cancer (NSCLC) treated with third-generation chemotherapy regimens, and (2) build a clinical model to predict survival in this patient population. Patients and Methods Using data from two randomized, phase III Eastern Cooperative Oncology Group (ECOG) trials (E5592/E1594), we performed univariate and multivariate stepwise Cox regression analyses to identify survival prognostic factors. We used 75% of randomly sampled data to build a prediction model for survival, and the remaining 25% of data to validate the model. Results From 1993 to 1999, 1,436 patients with stage IV or IIIB NSCLC with effusion were treated with platinum-based doublets (involving either paclitaxel, docetaxel, or gemcitabine). The response rate and median survival time were 20% and 8.2 months, respectively. One- and 2-year survivals were 33% and 11%, respectively. In multivariate analysis, six independent poor prognostic factors were identified: skin metastasis (hazard ratio [HR], 1.88), lower performance status (ECOG 1 or 2; HR, 1.46), loss of appetite (HR, 1.62), liver metastasis (HR, 1.32), ≥ four metastatic sites (HR, 1.20), and no prior surgery (HR, 1.16). A nomogram using six pretreatment prognostic factors was built to predict 1- and 2-year survival. Conclusion Six pretreatment factors can be used to predict survival in chemotherapy-naive NSCLC patients treated with standard chemotherapy. Using our prognostic nomogram, 1- and 2-year survival probability of NSCLC patients can be estimated before treatment. This prognostic model may help clinicians and patients in clinical decision making, as well as investigators in research planning.


Lung Cancer ◽  
2018 ◽  
Vol 123 ◽  
pp. 127-135 ◽  
Author(s):  
Zhuo Li ◽  
Daichi Maeda ◽  
Makoto Yoshida ◽  
Michinobu Umakoshi ◽  
Hiroshi Nanjo ◽  
...  

2008 ◽  
Vol 31 (1) ◽  
pp. 22-28 ◽  
Author(s):  
Boone Goodgame ◽  
Avinash Viswanathan ◽  
C Ryan Miller ◽  
Feng Gao ◽  
Bryan Meyers ◽  
...  

2013 ◽  
Vol 19 (19) ◽  
pp. 5523-5532 ◽  
Author(s):  
Kimberly L. Johung ◽  
Xiaopan Yao ◽  
Fangyong Li ◽  
James B. Yu ◽  
Scott N. Gettinger ◽  
...  

Open Biology ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 200247
Author(s):  
Robert E. Hynds ◽  
Kristopher K. Frese ◽  
David R. Pearce ◽  
Eva Grönroos ◽  
Caroline Dive ◽  
...  

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related deaths worldwide. Although advances are being made towards earlier detection and the development of impactful targeted therapies and immunotherapies, the 5-year survival of patients with advanced disease is still below 20%. Effective cancer research relies on pre-clinical model systems that accurately reflect the evolutionary course of disease progression and mimic patient responses to therapy. Here, we review pre-clinical models, including genetically engineered mouse models and patient-derived materials, such as cell lines, primary cell cultures, explant cultures and xenografts, that are currently being used to interrogate NSCLC evolution from pre-invasive disease through locally invasive cancer to the metastatic colonization of distant organ sites.


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