Radiation therapy for vaginal and perirectal lesions in recurrent ovarian cancer

The role for localized radiation to treat ovarian cancer (OC) patients with locally recurrent vaginal/perirectal lesions remains unclear, though we hypothesize these patients may be salvaged locally and gain long-term survival benefit. We describe our institutional outcomes using intensity modulated radiation therapy (IMRT) +/- high-dose rate (HDR) brachytherapy to treat this population. Our primary objectives were to evaluate complete response rates of targeted lesions after radiation and calculate our 5-year in-field control (IFC) rate. Secondary objectives were to assess radiation-related toxicities, chemotherapy free-interval (CFI), as well as post-radiation progression-free (PFS) and overall survival (OS). PFS and OS were defined from radiation start to either progression or death/last follow-up, respectively. This was a heavily pre-treated cohort of 17 recurrent OC patients with a median follow-up of 28.4 months (range 4.5-166.4) after radiation completion. 52.9% had high-grade serous histology and 4 (23.5%) had isolated vaginal/perirectal disease. Four (23.5%) patients had in-field failures at 3.7, 11.2, 24.5, and 27.5 months after start of radiation, all treated with definitive dosing of radiation therapy. Patients who were platinum-sensitive prior to radiation had similar median PFS (6.5 vs. 13.4 months, log-rank p = 0.75), but longer OS (71.1 vs 18.8 months, log-rank p = 0.05) than their platinum-resistant counterparts. Excluding patients with low-grade histology or who were treated with palliative radiation, median CFI was 14.2 months (range 4.7 - 33.0). Radiation was well tolerated with 2 (12.0%) experiencing grade 3/4 gastrointestinal/genitourinary toxicities. In conclusion, radiation to treat locally recurrent vaginal/perirectal lesions in heavily pre-treated OC patients is safe and may effectively provide IFC

Conoscopic patterns in photonic band gap of cholesteric liquid crystal cells with twist defects

We theoretically investigate into the effects of the incidence angles in light transmission of cholesteric liquid crystal two-layer sandwich structures with twist defects created by rotation of the one layer about the helical axis.The conoscopic images and polarization resolved patterns are obtained for thick layers by computing the intensity and the polarization parameters as a function of the incidence angles.In addition to the defect angle induced rotation of the pictures as a whole, the rings of defect mode resonances are found to shrink to the origin and disappear as the defect twist angle varies from zero to its limiting value and beyond.Comment: revtex4, 7 pages, 4 figure

High Affinity Antigen Recognition of the Dual Specific Variants of Herceptin Is Entropy-Driven in Spite of Structural Plasticity

The antigen-binding site of Herceptin, an anti-human Epidermal Growth Factor Receptor 2 (HER2) antibody, was engineered to add a second specificity toward Vascular Endothelial Growth Factor (VEGF) to create a high affinity two-in-one antibody bH1. Crystal structures of bH1 in complex with either antigen showed that, in comparison to Herceptin, this antibody exhibited greater conformational variability, also called “structural plasticity”. Here, we analyzed the biophysical and thermodynamic properties of the dual specific variants of Herceptin to understand how a single antibody binds two unrelated protein antigens. We showed that while bH1 and the affinity-improved bH1-44, in particular, maintained many properties of Herceptin including binding affinity, kinetics and the use of residues for antigen recognition, they differed in the binding thermodynamics. The interactions of bH1 and its variants with both antigens were characterized by large favorable entropy changes whereas the Herceptin/HER2 interaction involved a large favorable enthalpy change. By dissecting the total entropy change and the energy barrier for dual interaction, we determined that the significant structural plasticity of the bH1 antibodies demanded by the dual specificity did not translate into the expected increase of entropic penalty relative to Herceptin. Clearly, dual antigen recognition of the Herceptin variants involves divergent antibody conformations of nearly equivalent energetic states. Hence, increasing the structural plasticity of an antigen-binding site without increasing the entropic cost may play a role for antibodies to evolve multi-specificity. Our report represents the first comprehensive biophysical analysis of a high affinity dual specific antibody binding two unrelated protein antigens, furthering our understanding of the thermodynamics that drive the vast antigen recognition capacity of the antibody repertoire

Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p

A Minimal Fragment of MUC1 Mediates Growth of Cancer Cells

The MUC1 protein is aberrantly expressed on many solid tumor cancers. In contrast to its apical clustering on healthy epithelial cells, it is uniformly distributed over cancer cells. However, a mechanistic link between aberrant expression and cancer has remained elusive. Herein, we report that a membrane-bound MUC1 cleavage product, that we call MUC1*, is the predominant form of the protein on cultured cancer cells and on cancerous tissues. Further, we demonstrate that transfection of a minimal fragment of MUC1, MUC1*1110, containing a mere forty-five (45) amino acids of the extracellular domain, is sufficient to confer the oncogenic activities that were previously attributed to the full-length protein. By comparison of molecular weight and function, it appears that MUC1* and MUC1*1110 are approximately equivalent. Evidence is presented that strongly supports a mechanism whereby dimerization of the extracellular domain of MUC1* activates the MAP kinase signaling cascade and stimulates cell growth. These findings suggest methods to manipulate this growth mechanism for therapeutic interventions in cancer treatments