The Effectiveness of Data Augmentation for Bone Suppression in Chest Radiograph using Convolutional Neural Network

Objective: Bone suppression of chest radiograph holds great promise to improve the localization accuracy in Image-Guided Radiation Therapy (IGRT). However, data scarcity has long been considered as the prime culprit of developing Convolutional Neural Networks (CNNs) models for the task of bone suppression. In this study, we explored the effectiveness of various data augmentation techniques for the task of bone suppression. Methods: In this study, chest radiograph and bone-free chest radiograph are derived from 59 high-resolution CT scans. Two CNN models (U-Net and Generative Adversarial Network (GAN)) were adapted to explore the effectiveness of various data augmentation techniques for bone signal suppression in the chest radiograph. Lung radiograph and bone-free radiograph were used as the input and target label, respectively. Impacts of six typical data augmentation techniques (flip, cropping, noise injection, rotation, shift and zoom) on model performance were investigated. A series of statistical evaluating metrics, including Peak Signal-To-Noise Ratio (PSNR), Structural Similarity (SSIM) and Mean Absolute Error (MAR), were deployed to comprehensively assess the prediction performance of the two networks under the six data augmentation strategies. Quantitative comparative results showed that different data augmentation techniques exhibited a varying degree of influence on the performance of CNN models in the task of CR bone signal suppression. Results: For the U-Net model, flips, rotation (10 to 20 degrees), all the shifts, and zoom (1/8) resulted in improved model prediction accuracy. By contrast, other studied augmentation techniques showed adverse impacts on the model performance. For the GAN model, it was found to be more sensitive to the studied augmentation techniques than the U-Net. Vertical flip was the only augmentation method that yielded enhanced model performance. Conclusion: In this study, we found that different data augmentation techniques resulted in a varying degree of impacts on the prediction performance of U-Net and GAN models in the task of bone suppression in CR. However, it remains challenging to determine the optimal parameter settings for each augmentation technique. In the future, a more comprehensive evaluation is still warranted to evaluate the effectiveness of different augmentation techniques in task-specific image synthesis.

Molecular Evidence of Anticancer Activity of Camel Milk Combined with Camel Urine

Department of Biological and Environmental Sciences, College of Arts and Sciences, Qatar University, Doha, Qatar

Stem Cell Technology in Regenerative Medicines and Cancer Treatment: Towards Revolution in Clinical Success

Stem cells are undifferentiated, immature, and unspecialized cells having huge potential for differentiation and proliferation into the specialized functionalized cells. More recently, CSC has been described in breast cancer and brain tumors where they make up as few as 1% of the cells in a tumor. The features of cancer stem cells are just like normal stem cells but their replication rate many times faster than normal cells. Regenerative medicines are based on stem cells, are potentially useful to regenerate damaged cells, tissues, organs and replace cancer cells with normal cells. Induced pluripotent stem cells are the most important candidates for regenerative medicines, tissue engineering, cell reprogramming, and 3D printing. Cancer Stem Cells (CSCs) have a tumorinitiating capacity and play crucial roles in tumor metastasis, relapse and chemo/ radioresistance. Because CSCs are resistant to chemotherapeutic drugs and cause recurrence of cancer and also have the ability to be regenerated; they can cause serious problems in the treatment of various cancers. Numerous biocompatible biomaterials, miRNAs, nanomaterial, artificial intelligence, and machine learning are uses to reprograms stem cells into regenerative medicines for the treatment of cancer. The present paper describes the applications and importance of stem cells in regenerative medicines, cancer stem cells targeting therapies, and the role of miRNAs in cancer stem cells targeting.

The Dual Effects of Silibinin on Human Pancreatic Cells

Objective: Silibinin is a flavonoid with antihepatotoxic properties, and exhibits pleiotropic anticancer effects. However, the molecular mechanisms responsible for its anticancer actions in pancreatic cancer cells, and the effects on such cells and normal pancreatic cells, remain unclear. The objective of this study was to determine the effect of silibinin on human pancreatic cancer cells and normal ductal cells. Methods: Human pancreatic cancer cells (MIA PaCa-2 and PANC-1) and normal ductal cells (hTERT-HPNE) were cultured with 0-400 μM silibinin for 48 h. Thereafter, the proliferation, invasion, apoptosis, and signaling pathways of the pancreatic cells were evaluated. Results: Silibinin significantly inhibited the proliferation, invasion, and spheroid formation of human pancreatic cancer cells in vitro in a dosedependent manner (p<0.05). It also induced apoptosis in a dose-dependent manner. Western blot analysis showed that silibinin downregulated extracellular signaling-regulated kinase (ERK) and serine/threonine protein kinase (AKT) in human pancreatic cancer cells. It also upregulated microtubule associated protein 1 light chain 3 β (LC3B) and cleaved caspase-3 via c-Jun N-terminal kinases (JNK) signaling. On the other hand, silibinin increased the mRNA and protein levels of c-Jun, Twist-related protein 1, and Snail. It also decreased exogenous p53 levels, but increased endogenous c-Jun protein levels in human pancreatic cancer cells. However, silibinin did not affect cell viability and endogenous c-Jun levels in pancreatic normal ductal cells. It increased exogenous p53 levels, but decreased stemness-related gene expression in pancreatic normal ductal cells. Silibinin increased Ki-67 levels in pancreatic cancer cells, but decreased them in pancreatic normal ductal cells. Conclusion: Silibinin not only exerted anticancer effects by inhibiting AKTERK and JNK signaling, but also upregulated cancer stemness-related genes in human pancreatic cancer cells. These results suggest that silibinin should be used as a therapeutic agent for human pancreatic cancer with caution.

Antitumor Activities of Immune Costimulatory Molecules of TNF Superfamily in Colorectal and Lung Cancers

Cancer immunotherapy has emerged as a promising treatment that utilizes the innate or adaptive immunity to generate a robust killing of malignant cells. However, only a limited number of cancer patients showed responsiveness to immunotherapies such as checkpoint inhibitors, suggesting the need for potent alternative strategies. In the present study, we explored the therapeutic potentials of costimulatory molecules including TNF superfamily member 4 (TNFSF4), member 9 (TNFSF9), and member 18 (TNFSF18). In tumor samples from human colorectal and lung cancer patients, expression of these factors positively correlated with lymphocyte infiltration and expression of several immune effector genes. In syngeneic mouse tumor models, overexpression of the TNF superfamily costimulatory factors in murine colorectal or lung cancer cells significantly suppressed tumor progression. Especially, TNFSF9 and 18 showed stronger antitumor effects than TNFSF4. Together, our study demonstrated the great potential of cancer immunotherapy targeting these immune costimulatory molecules.

MYBL1 Knockdown in a Triple Negative Breast Cancer Line: Evidence of Down-Regulation of MYBL2, TCF19 and KIF18b Expression

Purpose: The MYBL1 gene is a strong transcriptional activator, associated with cell cycle signaling and differentiation. Data show the gene is overexpressed in triple negative breast cancers. Considering the possibility that MYBL1 might be involved in events associated with the pathogenesis of these cancers, we sought to identify genes associated with MYBL1 expression in triple negative breast cancer. Methods: shRNA lentiviral knockdown was used to down-regulate the MYBL1 gene. Microarray analyses were used to identify genes either directly or indirectly affected by targeting MYBL1 knockdown. Data analyses was performed utilizing Affymetrix TAC 4.0, Chip X transcription factor analyses, Target Scan miRNA analyses, and STRING analyses was used to determine protein: protein interaction and pathway analyses. Web Gestalt and Gene Ontology were used to determine pathway and gene-set enrichments. Publicly available patient and cell line datasets were retrieved and processed using resources available in Gene Expression Omnibus and Oncomine. The polymerase chain reaction and western analyses were used to determine transcript and protein levels, respectively. Results: Knockdown of MYBL1 in a triple negative breast cell line led to down-regulation of MYBL2, TCF19, KIF18b along with an enrichment of cell cycle signaling genes. Gene expression analyses show that MYBL1, MYBL2, TCF19 and KIF18b display a similar pattern of expression in breast cell lines and many of the archival patient datasets examined. Conclusion: TNBC is a heterogeneous subtype, so these data suggest that cancers that over-express MYBL1, express MYBL2, TCF19 and KIF18b. Bioinformatic analyses suggest MYBL1 regulates MYBL2 which leads to regulation of TCF19 and KIF18b.

Identification of Novel GSK-3β Inhibitors through Docking Based Virtual Screening and Biological Evaluation

GSK-3β is a key regulator in insulin, Wnt and NF-κB signaling pathways. Dysregulation of GSK-3β is often related to tumors and diabetes. Inhibiting it might provide cure for diabetes, tumors, neurodegeneration and brain ischemia. Although there are a number of reported GSK-3β inhibitors, the scaffold is limited. Herein we report a discriminatory analysis-based molecular docking on the Specs database, and identified 3 novel GSK-3β inhibitors with moderate IC50 (ranging from 17.42 μM to 6.74 μM) in the following in vitro biological test. Further dynamic simulations and docking pose analysis were performed to give a better understanding on the binding conformation of 3 hit compounds AK- 777/09836064, AK-968/37185006 and AN-698/41607072, which would provide basis for further optimization.

Association of Physical Activity and Derived Neutrophilto-Lymphocyte Ratio with Outcome in Patients with Recurrent and/or Metastatic Squamous Cell Carcinoma of Head and Neck Treated with Immunotherapy

Regular Physical Activity (PA) improves the outcomes of patients with cancer mainly by enhancing the immune system. The relationship of PA and the derived Neutrophil-to-Lymphocyte Ratio (dNLR) with the evolution of 31 consecutive patients with Recurrent and/or Metastatic Squamous Cell Carcinoma of Head and Neck (R/M SCCHN) treated with immunotherapy was determined in this retrospective study. Seventeen patients (55%) performed PA and 14 (45%) did not. The time to progression and Overall Survival (OS) was significantly better in the first compared to the second group (p=0.002 and 0.0019, respectively). In patients with a dNLR less than 3.5 the survival was significantly longer than in patients with a higher dNLR (p=0.004). Our results suggest that there is an association between PA and improved outcomes in R/M SCCHN patients treated with immunotherapy and that the dNLR is a predictive marker of good response to treatment.