Use of new radiochromic devices for peripheral dose measurement: potential in-vivo dosimetry application

The authors have studied the feasibility of using three new high-sensitivity radiochromic devices in measuring the doses to peripheral points outside the primary megavoltage photon beams. The three devices were GAFCHROMIC® EBT film, prototype Low Dose (LD) Film, and prototype LD Card. The authors performed point dosimetry using these three devices in water-equivalent solid phantoms at x = 3,5,8,10, and 15 cm from the edge of 6 MV and 15 MV photon beams of 10x10 cm2, and at depths of 0, 0.5 cm, and depth of maximum dose. A full sheet of EBT film was exposed with 5000 MU. The prototype LD film pieces were 1.5x2 cm2 in size. Some LD films were provided in the form of a card in 1.8x5 cm2 holding an active film in 1.8x2 cm2. These are referred to as “LD dosimeter cards”. The small LD films and cards were exposed with 500 MU. For each scanned film, a 6 mm circular area centered at the measurement point was sampled and the mean pixel value was obtained. The calibration curves were established from the calibration data for each combination of film/cards and densitometer/scanner. The doses at the peripheral points determined from the films were compared with those obtained using ion chamber at respective locations in a water phantom and general agreements were found. It is feasible to accurately measure peripheral doses of megavoltage photon beams using the new high-sensitivity radiochromic devices. This near real-time and inexpensive method can be applied in a clinical setting for dose measurements to critical organs and sensitive patient implant devices

Which biomarker predicts benefit from EGFR-TKI treatment for patients with lung cancer?

Subsets of patients with non-small cell lung cancer respond remarkably well to small molecule tyrosine kinase inhibitors (TKI) specific for epidermal growth factor receptor (EGFR) such as gefitinib or erlotinib. In 2004, it was found that EGFR mutations occurring in the kinase domain are strongly associated with EGFR-TKI sensitivity. However, subsequent studies revealed that this relationship was not perfect and various predictive markers have been reported. These include EGFR gene copy numbers, status of ligands for EGFR, changes in other HER family genes or molecules downstream to EGFR including KRAS or AKT. In this review, we would like to review current knowledge of predictive factors for EGFR-TKI. As all but one phase III trials failed to show a survival advantage of the treatment arm involving EGFR-TKIs, it is necessary to select patients by these biomarkers in future clinical trials. Through these efforts, it would be possible to individualise EGFR-TKI treatment for patients suffering from lung cancer

Anesthetic Propofol Reduces Endotoxic Inflammation by Inhibiting Reactive Oxygen Species-regulated Akt/IKKβ/NF-κB Signaling

BACKGROUND: Anesthetic propofol has immunomodulatory effects, particularly in the area of anti-inflammation. Bacterial endotoxin lipopolysaccharide (LPS) induces inflammation through toll-like receptor (TLR) 4 signaling. We investigated the molecular actions of propofol against LPS/TLR4-induced inflammatory activation in murine RAW264.7 macrophages. METHODOLOGY/PRINCIPAL FINDINGS: Non-cytotoxic levels of propofol reduced LPS-induced inducible nitric oxide synthase (iNOS) and NO as determined by western blotting and the Griess reaction, respectively. Propofol also reduced the production of tumor necrosis factor-α (TNF-α), interleukin (IL)-6, and IL-10 as detected by enzyme-linked immunosorbent assays. Western blot analysis showed propofol inhibited LPS-induced activation and phosphorylation of IKKβ (Ser180) and nuclear factor (NF)-κB (Ser536); the subsequent nuclear translocation of NF-κB p65 was also reduced. Additionally, propofol inhibited LPS-induced Akt activation and phosphorylation (Ser473) partly by reducing reactive oxygen species (ROS) generation; inter-regulation that ROS regulated Akt followed by NF-κB activation was found to be crucial for LPS-induced inflammatory responses in macrophages. An in vivo study using C57BL/6 mice also demonstrated the anti-inflammatory properties against LPS in peritoneal macrophages. CONCLUSIONS/SIGNIFICANCE: These results suggest that propofol reduces LPS-induced inflammatory responses in macrophages by inhibiting the interconnected ROS/Akt/IKKβ/NF-κB signaling pathways

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes) by modeling their effects on the activity of transcription factors, RNA-binding proteins, and microRNAs in 5,185 TCGA tumors and 1,019 ENCODE assays. Our predictions included hundreds of candidate onco- and tumor-suppressor lncRNAs (cancer lncRNAs) whose somatic alterations account for the dysregulation of dozens of cancer genes and pathways in each of 14 tumor contexts. To demonstrate proof of concept, we showed that perturbations targeting OIP5-AS1 (an inferred tumor suppressor) and TUG1 and WT1-AS (inferred onco-lncRNAs) dysregulated cancer genes and altered proliferation of breast and gynecologic cancer cells. Our analysis indicates that, although most lncRNAs are dysregulated in a tumor-specific manner, some, including OIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergistically dysregulate cancer pathways in multiple tumor contexts. Chiu et al. present a pan-cancer analysis of lncRNA regulatory interactions. They suggest that the dysregulation of hundreds of lncRNAs target and alter the expression of cancer genes and pathways in each tumor context. This implies that hundreds of lncRNAs can alter tumor phenotypes in each tumor context

A Comprehensive Pan-Cancer Molecular Study of Gynecologic and Breast Cancers

We analyzed molecular data on 2,579 tumors from The Cancer Genome Atlas (TCGA) of four gynecological types plus breast. Our aims were to identify shared and unique molecular features, clinically significant subtypes, and potential therapeutic targets. We found 61 somatic copy-number alterations (SCNAs) and 46 significantly mutated genes (SMGs). Eleven SCNAs and 11 SMGs had not been identified in previous TCGA studies of the individual tumor types. We found functionally significant estrogen receptor-regulated long non-coding RNAs (lncRNAs) and gene/lncRNA interaction networks. Pathway analysis identified subtypes with high leukocyte infiltration, raising potential implications for immunotherapy. Using 16 key molecular features, we identified five prognostic subtypes and developed a decision tree that classified patients into the subtypes based on just six features that are assessable in clinical laboratories. By performing molecular analyses of 2,579 TCGA gynecological (OV, UCEC, CESC, and UCS) and breast tumors, Berger et al. identify five prognostic subtypes using 16 key molecular features and propose a decision tree based on six clinically assessable features that classifies patients into the subtypes