Second malignancies in the context of lenalidomide treatment: an analysis of 2732 myeloma patients enrolled to the Myeloma XI trial.

We have carried out the largest randomised trial to date of newly diagnosed myeloma patients, in which lenalidomide has been used as an induction and maintenance treatment option and here report its impact on second primary malignancy (SPM) incidence and pathology. After review, 104 SPMs were confirmed in 96 of 2732 trial patients. The cumulative incidence of SPM was 0.7% (95% confidence interval (CI) 0.4-1.0%), 2.3% (95% CI 1.6-2.7%) and 3.8% (95% CI 2.9-4.6%) at 1, 2 and 3 years, respectively. Patients receiving maintenance lenalidomide had a significantly higher SPM incidence overall (P=0.011). Age is a risk factor with the highest SPM incidence observed in transplant non-eligible patients aged >74 years receiving lenalidomide maintenance. The 3-year cumulative incidence in this group was 17.3% (95% CI 8.2-26.4%), compared with 6.5% (95% CI 0.2-12.9%) in observation only patients (P=0.049). There was a low overall incidence of haematological SPM (0.5%). The higher SPM incidence in patients receiving lenalidomide maintenance therapy, especially in advanced age, warrants ongoing monitoring although the benefit on survival is likely to outweigh risk

Calculating Stage Duration Statistics in Multistage Diseases

Many human diseases are characterized by multiple stages of progression. While the typical sequence of disease progression can be identified, there may be large individual variations among patients. Identifying mean stage durations and their variations is critical for statistical hypothesis testing needed to determine if treatment is having a significant effect on the progression, or if a new therapy is showing a delay of progression through a multistage disease. In this paper we focus on two methods for extracting stage duration statistics from longitudinal datasets: an extension of the linear regression technique, and a counting algorithm. Both are non-iterative, non-parametric and computationally cheap methods, which makes them invaluable tools for studying the epidemiology of diseases, with a goal of identifying different patterns of progression by using bioinformatics methodologies. Here we show that the regression method performs well for calculating the mean stage durations under a wide variety of assumptions, however, its generalization to variance calculations fails under realistic assumptions about the data collection procedure. On the other hand, the counting method yields reliable estimations for both means and variances of stage durations. Applications to Alzheimer disease progression are discussed

Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival

<p>Abstract</p> <p>Background</p> <p>We have engaged in an international program designated the <it>Bank On A Cure</it>, which has established DNA banks from multiple cooperative and institutional clinical trials, and a platform for examining the association of genetic variations with disease risk and outcomes in multiple myeloma.</p> <p>We describe the development and content of a novel custom SNP panel that contains 3404 SNPs in 983 genes, representing cellular functions and pathways that may influence disease severity at diagnosis, toxicity, progression or other treatment outcomes. A systematic search of national databases was used to identify non-synonymous coding SNPs and SNPs within transcriptional regulatory regions. To explore SNP associations with PFS we compared SNP profiles of short term (less than 1 year, <it>n </it>= 70) versus long term progression-free survivors (greater than 3 years, <it>n </it>= 73) in two phase III clinical trials.</p> <p>Results</p> <p>Quality controls were established, demonstrating an accurate and robust screening panel for genetic variations, and some initial racial comparisons of allelic variation were done. A variety of analytical approaches, including machine learning tools for data mining and recursive partitioning analyses, demonstrated predictive value of the SNP panel in survival. While the entire SNP panel showed genotype predictive association with PFS, some SNP subsets were identified within drug response, cellular signaling and cell cycle genes.</p> <p>Conclusion</p> <p>A targeted gene approach was undertaken to develop an SNP panel that can test for associations with clinical outcomes in myeloma. The initial analysis provided some predictive power, demonstrating that genetic variations in the myeloma patient population may influence PFS.</p

Azithromycin reduces spontaneous and induced inflammation in ΔF508 cystic fibrosis mice

BACKGROUND: Inflammation plays a critical role in lung disease development and progression in cystic fibrosis. Azithromycin is used for the treatment of cystic fibrosis lung disease, although its mechanisms of action are poorly understood. We tested the hypothesis that azithromycin modulates lung inflammation in cystic fibrosis mice. METHODS: We monitored cellular and molecular inflammatory markers in lungs of cystic fibrosis mutant mice homozygous for the ΔF508 mutation and their littermate controls, either in baseline conditions or after induction of acute inflammation by intratracheal instillation of lipopolysaccharide from Pseudomonas aeruginosa, which would be independent of interactions of bacteria with epithelial cells. The effect of azithromycin pretreatment (10 mg/kg/day) given by oral administration for 4 weeks was evaluated. RESULTS: In naive cystic fibrosis mice, a spontaneous lung inflammation was observed, characterized by macrophage and neutrophil infiltration, and increased intra-luminal content of the pro-inflammatory cytokine macrophage inflammatory protein-2. After induced inflammation, cystic fibrosis mice combined exaggerated cellular infiltration and lower anti-inflammatory interleukin-10 production. In cystic fibrosis mice, azithromycin attenuated cellular infiltration in both baseline and induced inflammatory condition, and inhibited cytokine (tumor necrosis factor-α and macrophage inflammatory protein-2) release in lipopolysaccharide-induced inflammation. CONCLUSION: Our findings further support the concept that inflammatory responses are upregulated in cystic fibrosis. Azithromycin reduces some lung inflammation outcome measures in cystic fibrosis mice. We postulate that some of the benefits of azithromycin treatment in cystic fibrosis patients are due to modulation of lung inflammation

Synthetic Double-Stranded RNAs Are Adjuvants for the Induction of T Helper 1 and Humoral Immune Responses to Human Papillomavirus in Rhesus Macaques

Toll-like receptor (TLR) ligands are being considered as adjuvants for the induction of antigen-specific immune responses, as in the design of vaccines. Polyriboinosinic-polyribocytoidylic acid (poly I:C), a synthetic double-stranded RNA (dsRNA), is recognized by TLR3 and other intracellular receptors. Poly ICLC is a poly I:C analogue, which has been stabilized against the serum nucleases that are present in the plasma of primates. Poly I:C12U, another analogue, is less toxic but also less stable in vivo than poly I:C, and TLR3 is essential for its recognition. To study the effects of these compounds on the induction of protein-specific immune responses in an animal model relevant to humans, rhesus macaques were immunized subcutaneously (s.c.) with keyhole limpet hemocyanin (KLH) or human papillomavirus (HPV)16 capsomeres with or without dsRNA or a control adjuvant, the TLR9 ligand CpG-C. All dsRNA compounds served as adjuvants for KLH-specific cellular immune responses, with the highest proliferative responses being observed with 2 mg/animal poly ICLC (p = 0.002) or 6 mg/animal poly I:C12U (p = 0.001) when compared with immunization with KLH alone. Notably, poly ICLC—but not CpG-C given at the same dose—also helped to induce HPV16-specific Th1 immune responses while both adjuvants supported the induction of strong anti-HPV16 L1 antibody responses as determined by ELISA and neutralization assay. In contrast, control animals injected with HPV16 capsomeres alone did not develop substantial HPV16-specific immune responses. Injection of dsRNA led to increased numbers of cells producing the T cell–activating chemokines CXCL9 and CXCL10 as detected by in situ hybridization in draining lymph nodes 18 hours after injections, and to increased serum levels of CXCL10 (p = 0.01). This was paralleled by the reduced production of the homeostatic T cell–attracting chemokine CCL21. Thus, synthetic dsRNAs induce an innate chemokine response and act as adjuvants for virus-specific Th1 and humoral immune responses in nonhuman primates

The mechanisms by which polyamines accelerate tumor spread

Increased polyamine concentrations in the blood and urine of cancer patients reflect the enhanced levels of polyamine synthesis in cancer tissues arising from increased activity of enzymes responsible for polyamine synthesis. In addition to their de novo polyamine synthesis, cells can take up polyamines from extracellular sources, such as cancer tissues, food, and intestinal microbiota. Because polyamines are indispensable for cell growth, increased polyamine availability enhances cell growth. However, the malignant potential of cancer is determined by its capability to invade to surrounding tissues and metastasize to distant organs. The mechanisms by which increased polyamine levels enhance the malignant potential of cancer cells and decrease anti-tumor immunity are reviewed. Cancer cells with a greater capability to synthesize polyamines are associated with increased production of proteinases, such as serine proteinase, matrix metalloproteinases, cathepsins, and plasminogen activator, which can degrade surrounding tissues. Although cancer tissues produce vascular growth factors, their deregulated growth induces hypoxia, which in turn enhances polyamine uptake by cancer cells to further augment cell migration and suppress CD44 expression. Increased polyamine uptake by immune cells also results in reduced cytokine production needed for anti-tumor activities and decreases expression of adhesion molecules involved in anti-tumor immunity, such as CD11a and CD56. Immune cells in an environment with increased polyamine levels lose anti-tumor immune functions, such as lymphokine activated killer activities. Recent investigations revealed that increased polyamine availability enhances the capability of cancer cells to invade and metastasize to new tissues while diminishing immune cells' anti-tumor immune functions