Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

<p>Abstract</p> <p>Background</p> <p>Few overlap between independently developed gene signatures and poor inter-study applicability of gene signatures are two of major concerns raised in the development of microarray-based prognostic gene signatures. One recent study suggested that thousands of samples are needed to generate a robust prognostic gene signature.</p> <p>Results</p> <p>A data set of 1,372 samples was generated by combining eight breast cancer gene expression data sets produced using the same microarray platform and, using the data set, effects of varying samples sizes on a few performances of a prognostic gene signature were investigated. The overlap between independently developed gene signatures was increased linearly with more samples, attaining an average overlap of 16.56% with 600 samples. The concordance between predicted outcomes by different gene signatures also was increased with more samples up to 94.61% with 300 samples. The accuracy of outcome prediction also increased with more samples. Finally, analysis using only Estrogen Receptor-positive (ER+) patients attained higher prediction accuracy than using both patients, suggesting that sub-type specific analysis can lead to the development of better prognostic gene signatures</p> <p>Conclusion</p> <p>Increasing sample sizes generated a gene signature with better stability, better concordance in outcome prediction, and better prediction accuracy. However, the degree of performance improvement by the increased sample size was different between the degree of overlap and the degree of concordance in outcome prediction, suggesting that the sample size required for a study should be determined according to the specific aims of the study.</p

Investigation of Semiconductor Quantum Dots for Waveguide Electroabsorption Modulator

In this work, we investigated the use of 10-layer InAs quantum dot (QD) as active region of an electroabsorption modulator (EAM). The QD-EAM is a p-i-n ridge waveguide structure with intrinsic layer thickness of 0.4 μm, width of 10 μm, and length of 1.0 mm. Photocurrent measurement reveals a Stark shift of ~5 meV (~7 nm) at reverse bias of 3 V (75 kV/cm) and broadening of the resonance peak due to field ionization of electrons and holes was observed for E-field larger than 25 kV/cm. Investigation at wavelength range of 1,300–1320 nm reveals that the largest absorption change occurs at 1317 nm. Optical transmission measurement at this wavelength shows insertion loss of ~8 dB, and extinction ratio of ~5 dB at reverse bias of 5 V. Consequently, methods to improve the performance of the QD-EAM are proposed. We believe that QDs are promising for EAM and the performance of QD-EAM will improve with increasing research efforts

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting

Decellularized Matrix from Tumorigenic Human Mesenchymal Stem Cells Promotes Neovascularization with Galectin-1 Dependent Endothelial Interaction

BACKGROUND: Acquisition of a blood supply is fundamental for extensive tumor growth. We recently described vascular heterogeneity in tumours derived from cell clones of a human mesenchymal stem cell (hMSC) strain (hMSC-TERT20) immortalized by retroviral vector mediated human telomerase (hTERT) gene expression. Histological analysis showed that cells of the most vascularized tumorigenic clone, -BD11 had a pericyte-like alpha smooth muscle actin (ASMA+) and CD146+ positive phenotype. Upon serum withdrawal in culture, -BD11 cells formed cord-like structures mimicking capillary morphogenesis. In contrast, cells of the poorly tumorigenic clone, -BC8 did not stain for ASMA, tumours were less vascularized and serum withdrawal in culture led to cell death. By exploring the heterogeneity in hMSC-TERT20 clones we aimed to understand molecular mechanisms by which mesenchymal stem cells may promote neovascularization. METHODOLOGY/PRINCIPAL FINDINGS: Quantitative qRT-PCR analysis revealed similar mRNA levels for genes encoding the angiogenic cytokines VEGF and Angiopoietin-1 in both clones. However, clone-BD11 produced a denser extracellular matrix that supported stable ex vivo capillary morphogenesis of human endothelial cells and promoted in vivo neovascularization. Proteomic characterization of the -BD11 decellularized matrix identified 50 extracellular angiogenic proteins, including galectin-1. siRNA knock down of galectin-1 expression abrogated the ex vivo interaction between decellularized -BD11 matrix and endothelial cells. More stable shRNA knock down of galectin-1 expression did not prevent -BD11 tumorigenesis, but greatly reduced endothelial migration into -BD11 cell xenografts. CONCLUSIONS: Decellularized hMSC matrix had significant angiogenic potential with at least 50 angiogenic cell surface and extracellular proteins, implicated in attracting endothelial cells, their adhesion and activation to form tubular structures. hMSC -BD11 surface galectin-1 expression was required to bring about matrix-endothelial interactions and for xenografted hMSC -BD11 cells to optimally recruit host vasculature