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© Oxford University Press 2008.
IN THIS ISSUE
Method to Visualize Length of Survival in Time-to-Event StudiesBecause individuals who have not experienced the event of interest must be censored in time-to-event studies, standard methods of plotting individual survival times are invalid and data are thus usually plotted using Kaplan–Meier survival curves. However, these curves can make differences between groups appear larger than they actually are. To address this problem, Royston et al. (p. 92) developed a log-normal modeling technique to make dot plots and scatter plots of survival data, and they used an imputation method to provide the missing data for censored patients. They applied their technique to data from a randomized trial in patients with renal cancer. Their plots show considerable overlap in survival times between treatment groups, unlike the Kaplan–Meier plots of the same data. The authors conclude that their plots may usefully complement Kaplan–Meier plots in survival analyses.
In an editorial, Wittes (p. 80) points out that situations in which relatively few patients are censored appear to be well suited for this method. However, the method may be less useful when censoring is high because the graphs will reflect increasing uncertainty as censoring increases and more data imputation is applied. She encourages researchers working with time-to-event data to extend this method to datasets with many censored patients or to settings other than survival to investigate its strengths and limitations.
The Neuropilin NRP2 and Its Role in Anti-Tumor Therapy
The neuropilins (NRP1 and NRP2) participate in neuronal pathfinding, vascularization, and lymphangiogenesis. They bind to semaphorins and VEGF and have been shown to mediate signaling by VEGF-receptor tyrosine kinases. Gray et al. (p. 109) now report that NRP2 is selectively expressed in tumor cells and mediates many properties of tumor progression. To determine whether NRP2 is a potential therapeutic target for inhibition of human tumor growth, the authors implanted human colorectal cancer cells into the livers of nude mice and injected liposomes carrying short-interfering RNAs for NRP2 or control siRNAs intraperitoneally. Tumor volume was substantially reduced in the presence of NRP2 siRNA. The authors conclude that NRP2 may be a promising target for cancer therapeutics.
In an editorial, Narazaki et al. (p. 81) review the physiological roles of neuropilins, including the roles of NRP1 and of sempahorins in tumor development. They highlight the contributions of Gray et al. in furthering our understanding of the role of NRP2 in cancer.
Regulation of Telomerase Activity by Human Tumor Viruses
RNA and DNA tumor viruses vary in their strategies to commandeer host cell regulatory mechanisms that promote proliferation and prevent apoptosis. The viruses also have various means to increase telomerase activity, without which senescence and cell cycle arrest might kill the host cell as the telomeres shorten with repeated cell division. In a review, Nicot and Bellon (p. 98) examine the various mechanisms used by human tumor viruses to regulate telomerase activity. Most commonly, viral proteins increase the transcription of telomerase. Additional mechanisms to increase telomerase expression, post-transcriptional controls, and even some negative controls are also present.
Doxorubicin and Docetaxel for Breast Cancer Therapy
Previous work has shown that docetaxel is more effective than doxorubicin for patients with advanced breast cancer. The Breast International Group 02-98 randomized trial tested the effect of incorporating docetaxel into doxorubicin-based adjuvant chemotherapy regimens, either sequentially or concurrently, for treatment in women with lymph node–positive disease. Francis et al. (p. 121) report that patients receiving docetaxel had slightly better 5-year disease-free survival (DFS) than patients in the control arms. DFS was better in the sequential docetaxel arm than in the concurrent docetaxel arm or the control arm. The authors conclude that differences in antitumor effect may be related to the administration schedule of doxorubicin and docetaxel; sequential administration appears to produce better DFS than concurrent administration.
Statins and Cancer Risk Among VA Health System Patients
The association between statin use and the risk of cancer has been inconsistent. Farwell et al. (p. 134) compared the incidence of all cancers among patients in the Veterans Affairs healthcare system who were using statins with that in patients who were using other antihypertensive medications but not statins. The total cancer incidence was 9.4% among statin users and 13.2% among nonusers. The statistically significantly lower risk of all cancers among statin users was maintained in a multivariable analysis that adjusted for age and for multiple potential confounders. There was also a statistically significant dose–response relationship between increased statin doses and decreased risk of all cancers. The authors conclude that statin users may be at lower risk for developing cancer.
Gene Knockout Model of Renal Carcinogenesis
Birt-Hogge-Dubé (BHD) syndrome patients have mutations in the BHD gene that are associated with an increased risk of kidney cancer. To study the cellular mechanisms of renal carcinogenesis, Baba et al. (p. 140) used a kidney-targeted BHD gene knockout mouse model. They compared the kidneys of mice with the gene knockout with those of mice with the normal gene. Mice with the BHD knockout had enlarged cystic kidneys and died from renal failure by the time they were 3 weeks old. Signal transduction pathways involved in cell growth and proliferation were activated in the kidneys of BHD knockout mice. BHD knockout mice that were treated with rapamycin, an inhibitor of cell growth and proliferation, lived longer than untreated BHD knockout mice. The authors conclude that loss of BHD gene expression may initiate renal tumorigenesis in the mouse and that the BHD knockout model may be useful for future studies of kidney cancer.
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J Natl Cancer Inst 2008 100: 92-97.
J Natl Cancer Inst 2008 100: 98-108.
J Natl Cancer Inst 2008 100: 109-120.
J Natl Cancer Inst 2008 100: 134-139.
J Natl Cancer Inst 2008 100: 121-133.
J Natl Cancer Inst 2008 100: 140-154.
J Natl Cancer Inst 2008 100: 80-81.
J Natl Cancer Inst 2008 100: 81-83.
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