FDA Drug Approval Summary: Bevacizumab (Avastin®) Plus Carboplatin and Paclitaxel as First-Line Treatment of Advanced/Metastatic Recurrent Nonsquamous Non-Small Cell Lung Cancer

Division of Biological Oncology Products, Office of Oncology Drug Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland 20993-0002, USA.
The Oncologist (Impact Factor: 4.54). 07/2007; 12(6):713-8. DOI: 10.1634/theoncologist.12-6-713
Source: PubMed

ABSTRACT On October 11, 2006, the U.S. Food and Drug Administration granted approval for bevacizumab (Avastin; Genentech, Inc., South San Francisco, CA), administered in combination with carboplatin and paclitaxel, for the initial treatment of patients with unresectable, locally advanced, recurrent, or metastatic, nonsquamous, non-small cell lung cancer (NSCLC). Approval is based on a significant improvement in overall survival (OS). A randomized, open label, multicenter clinical trial, conducted by the Eastern Cooperative Oncology Group (ECOG), in chemotherapy-naïve patients with stage IIIB/IV nonsquamous NSCLC, evaluated bevacizumab plus carboplatin and paclitaxel (BV/CP, n = 434) versus carboplatin and paclitaxel alone (CP, n = 444). Exclusion of patients with squamous or predominantly squamous histology was based on life-threatening or fatal hemoptysis occurring in 4 of 13 patients with squamous histology who received a BV/CP regimen in a phase II study. Among the 878 randomized patients, the median age was 63, 46% were female, 76% had stage IV disease, 12% had stage IIIB disease with malignant pleural effusion, 11% had recurrent disease, and 40% had an ECOG performance status score of 0. OS was significantly longer in patients receiving BV/CP than in those receiving CP alone (median OS, 12.3 versus 10.3 months; hazard ratio [HR], 0.80; p = .013, stratified log rank test). Although a consistent effect was observed across most subgroups, in an exploratory analysis, evidence of a survival benefit was not observed in women (HR, 0.99; 95% confidence interval, 0.79-1.25). Severe and life-threatening adverse events occurring more frequently in patients receiving BV/CP were neutropenia (27% versus 17%), fatigue (16% versus 13%), hypertension (8% versus 0.7%), infection without neutropenia (7% versus 3%), thrombosis/embolism (5% versus 3%), pneumonitis or pulmonary infiltrate (5% versus 3%), infection with grade 3 or 4 neutropenia (5% versus 2%), febrile neutropenia (5% versus 2%), hyponatremia (4% versus 1%), proteinuria (3% versus 0), and headache (3% versus 0.5%). Fatal, treatment-related adverse events in patients receiving bevacizumab were pulmonary hemorrhage (2.3% versus 0.5%), gastrointestinal hemorrhage, central nervous system infarction, gastrointestinal perforation, myocardial infarction, and neutropenic sepsis. The most serious, and sometimes fatal, bevacizumab toxicities are gastrointestinal perforation, wound healing complications, hemorrhage, arterial thromboembolic events, hypertensive crisis, nephrotic syndrome, congestive heart failure, and neutropenic sepsis. The most common adverse events in patients receiving bevacizumab are asthenia, pain, abdominal pain, headache, hypertension, diarrhea, nausea, vomiting, anorexia, stomatitis, constipation, upper respiratory infection, epistaxis, dyspnea, exfoliative dermatitis, and proteinuria.

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Available from: Joe Gootenberg, Aug 13, 2014
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    • "Targeted therapy at the check points by using drugs or monoclonal antibodies may block the growth and spread of cancer by interfering with specific molecules involved in tumor growth and progression. Bevacizumab (avastin) is an angiogenesis inhibitor used as a tumor growth inhibitor in colorectal cancer, rectal cancer, metastatic breast and lung cancer in combination with Capecitabine [35] [36] [37]. The presence of proteins in urinary exosomes likely to act with NF2 may suggest a role for Bevacizumab therapy in bladder cancer. "
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    ABSTRACT: Exosomes are rich sources of biological material (proteins and nucleic acids) secreted by both tumor and normal cells, and found in urine of urinary bladder cancer patients. The objective of the study was to identify interacting exosomal proteins in bladder cancer for future use in targeted therapy. The Exocarta database ( was mined for urinary bladder cancer specific exosomal proteins. The urinary bladder cancer specific exosomal proteins (n=248) were analyzed to identify enriched pathways by Onto-tool Pathway Express ( Enriched pathways included cellular architecture, motility, cell to cell adhesion, tumorigenesis and metastasis. Proteins in the 9 top-ranked pathways included CTNNA1 (alpha-catenin), CTNNB1 (beta-catenin), VSAP, ITGA4, PAK1, DDR1, CDC42, RHOA, NRAS, RHO, PIK3AR1, MLC1, MMRN1, and CTTNBP2 and network analysis revealed 10 important hub proteins and identified inferred interactor NF2. The importance of identifying interactors is that that they can be used as targets for therapy, for example, using Bevacizumab (avastin - an angiogenesis inhibitor) against NF2 to inhibit protein-protein interactions will inhibit tumor growth and progression by hindering the exosome biogenesis. Copyright © 2015. Production and hosting by Elsevier B.V.
    Journal of the Egyptian National Cancer Institute 02/2015; 101(2). DOI:10.1016/j.jnci.2015.02.002
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    • "Discriminating cancer subtypes helps in understanding the evolution of cancer and is used to find appropriate therapies. For example, angiogenesis inhibitors like bevacizumab are more effective in treating adenocarcinoma lung cancer than squamous phenotypes ([19], [20]). Also, breast cancer has an unpredictable response, and developing effective therapies remain a major challenge in the clinical management of breast cancer patients [21] "
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    ABSTRACT: miRNA and gene expression profiles have been proved useful for classifying cancer samples. Efficient classifiers have been recently sought and developed. A number of attempts to classify cancer samples using miRNA/gene expression profiles are known in literature. However, the use of semi-supervised learning models have been used recently in bioinformatics, to exploit the huge corpuses of publicly available sets. Using both labeled and unlabeled sets to train sample classifiers, have not been previously considered when gene and miRNA expression sets are used. Moreover, there is a motivation to integrate both miRNA and gene expression for a semi-supervised cancer classification as that provides more information on the characteristics of cancer samples. In this paper, two semi-supervised machine learning approaches, namely self-learning and co-training, are adapted to enhance the quality of cancer sample classification. These approaches exploit the huge public corpuses to enrich the training data. In self-learning, miRNA and gene based classifiers are enhanced independently. While in co-training, both miRNA and gene expression profiles are used simultaneously to provide different views of cancer samples. To our knowledge, it is the first attempt to apply these learning approaches to cancer classification. The approaches were evaluated using breast cancer, hepatocellular carcinoma (HCC) and lung cancer expression sets. Results show up to 20% improvement in F1-measure over Random Forests and SVM classifiers. Co-Training also outperforms Low Density Separation (LDS) approach by around 25% improvement in F1-measure in breast cancer.
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    • "Bevacizumab was the first approved angiogenesis inhibitor and was approved for use in combination treatment with cytotoxic chemotherapy for metastatic colorectal cancer in 2004 [10]. It was subsequently approved for patients with non-small cell lung cancer [11], glioblastoma [12], and renal cell cancer [13]. Its use was also approved for metastatic breast cancer when combined with a conventional chemotherapeutic agent, paclitaxel [14]. "
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    ABSTRACT: Antiangiogenesis is a promising antitumor strategy that inhibits tumor vascular formation to suppress tumor growth. Specifically, targeting VEGF has shown therapeutic benefits in many cancer types, leading to its approval as the first antiangiogenic drug by the Food and Drug Administration in the United States. It is known, however, that patients will experience unfavorable side effects as the VEGF and/or VEGF receptor signaling pathway is also required for homeostasis in normal tissues. Moreover, due to the cytostatic nature of antiangiogenic, cancer cells that are not killed by these drugs later develop an even more malignant phenotype, resulting in tumor invasion and metastasis. Although there have been many attempts to reduce drug resistance and increase therapeutic efficacy by combining antiangiogenic drugs with chemotherapy, the cumulative toxicity of antiangiogenic combinations limits their feasibility as treatments, as chronic angiogenesis inhibition typically reduces the antitumor effect of the co-administered chemotherapeutics. To overcome these problems, it is critical to explore new strategies that limit tumor resistance and side effects and also increase the exposure of chemotherapy drugs at the tumor site. Here, we review current understanding of antiangiogenic drugs and introduce a new combination strategy that links direct antiangiogenic protein and enzyme prodrug system with dual-targeting antiangiogenic and antiproliferative therapeutic effect in tumor microenvironment. This strategy has the potential to overcome these clinical hindrances and may serve as a paradigm for the next generation of antiangiogenic drugs.
    American Journal of Translational Research 01/2013; 5(4):393-403. · 3.23 Impact Factor
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