GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization

Bioinformatics tools have been developed to interpret gene expression data at the gene set level, and these gene set based analyses improve the biologists' capability to discover functional relevance of their experiment design. While elucidating gene set individually, inter gene sets association is rarely taken into consideration. Deep learning, an emerging machine learning technique in computational biology, can be used to generate an unbiased combination of gene set, and to determine the biological relevance and analysis consistency of these combining gene sets by leveraging large genomic data sets. In this study, we proposed a gene superset autoencoder (GSAE), a multi-layer autoencoder model with the incorporation of a priori defined gene sets that retain the crucial biological features in the latent layer. We introduced the concept of the gene superset, an unbiased combination of gene sets with weights trained by the autoencoder, where each node in the latent layer is a superset. Trained with genomic data from TCGA and evaluated with their accompanying clinical parameters, we showed gene supersets' ability of discriminating tumor subtypes and their prognostic capability. We further demonstrated the biological relevance of the top component gene sets in the significant supersets. Using autoencoder model and gene superset at its latent layer, we demonstrated that gene supersets retain sufficient biological information with respect to tumor subtypes and clinical prognostic significance. Superset also provides high reproducibility on survival analysis and accurate prediction for cancer subtypes.Comment: Presented in the International Conference on Intelligent Biology and Medicine (ICIBM 2018) at Los Angeles, CA, USA and published in BMC Systems Biology 2018, 12(Suppl 8):14

Predicting drug response of tumors from integrated genomic profiles by deep neural networks

The study of high-throughput genomic profiles from a pharmacogenomics viewpoint has provided unprecedented insights into the oncogenic features modulating drug response. A recent screening of ~1,000 cancer cell lines to a collection of anti-cancer drugs illuminated the link between genotypes and vulnerability. However, due to essential differences between cell lines and tumors, the translation into predicting drug response in tumors remains challenging. Here we proposed a DNN model to predict drug response based on mutation and expression profiles of a cancer cell or a tumor. The model contains a mutation and an expression encoders pre-trained using a large pan-cancer dataset to abstract core representations of high-dimension data, followed by a drug response predictor network. Given a pair of mutation and expression profiles, the model predicts IC50 values of 265 drugs. We trained and tested the model on a dataset of 622 cancer cell lines and achieved an overall prediction performance of mean squared error at 1.96 (log-scale IC50 values). The performance was superior in prediction error or stability than two classical methods and four analog DNNs of our model. We then applied the model to predict drug response of 9,059 tumors of 33 cancer types. The model predicted both known, including EGFR inhibitors in non-small cell lung cancer and tamoxifen in ER+ breast cancer, and novel drug targets. The comprehensive analysis further revealed the molecular mechanisms underlying the resistance to a chemotherapeutic drug docetaxel in a pan-cancer setting and the anti-cancer potential of a novel agent, CX-5461, in treating gliomas and hematopoietic malignancies. Overall, our model and findings improve the prediction of drug response and the identification of novel therapeutic options.Comment: Accepted for presentation in the International Conference on Intelligent Biology and Medicine (ICIBM 2018) at Los Angeles, CA, USA. Currently under consideration for publication in a Supplement Issue of BMC Genomic

Adverse Events of Extracorporeal Ultrasound-Guided High Intensity Focused Ultrasound Therapy

High-intensity focused ultrasound (HIFU) is considered to be an alternative to surgery. Extracorporeal ultrasound-guided HIFU (USgFU) has been clinically used to treat solid tumors. Preliminary trials in a small sample of a Western population suggested that this modality was safe. Most trials are performed in China thereby providing comprehensive data for understanding the safety profile. The aim of this study was to evaluate adverse events of USgFU therapy.Clinical data were searched in 2 Chinese databases. Adverse events of USgFU were summarized and compared with those of magnetic resonance-guided HIFU (MRgFU; for uterine, bone or breast tumor) and transrectal ultrasound-guided HIFU (for prostate cancer or benign prostate hyperplasia). USgFU treatment was performed using 7 types of device. Side effects were evaluated in 13262 cases. There were fewer adverse events in benign lesions than in malignant lesions (11.81% vs. 21.65%, p<0.0001). Rates of adverse events greatly varied between the disease types (0-280%, p<0.0001) and between the applied HIFU devices in both malignant (10.58-44.38%, p<0.0001) and benign lesions (1.67-17.57%, p<0.0001). Chronological analysis did not demonstrate a decrease in the rate of adverse events. Based upon evaluable adverse events, incidences in USgFU were consistent with those in MRgFU or transrectal HIFU. Some side effects frequently occurred following transrectal HIFU were not reported in USgFU. Several events including intrahepatic metastasis, intraoperative high fever, and occlusions of the superior mesenteric artery should be of particular concern because they have not been previously noted. The types of adverse events suggested that they were ultrasonic lesions.The frequency of adverse events depended on the location of the lesion and the type of HIFU device; however, side effects of USgFU were not yet understood. USgFU did not decrease the incidence of adverse events compared with MRgFU

Nanosecond Electric Pulses Induce Early and Late Phases of DNA Damage and Cell Death in Cisplatin-Resistant Human Ovarian Cancer Cells

Chemoresistance is a challenge for management of ovarian cancer, and therefore the response of resistant cells to nanosecond electric pulses (nsEP) was explored. Human ovarian cancer cell line COC1 and the cisplatin-resistant subline COC1/DDP were subjected to nsEP (32 ns, 10 kV/cm, 10 Hz pulse repletion frequency, and 10 min exposure duration), and then the cellular responses were followed. The percentages of dead cells and of comet-formed cells in the alkaline assay displayed two peak levels (i.e., 2 and 8 h after nsEP exposure), with the highest value noted at 8 h; the percentage of comet-formed cells in the neutral assay was increased at 8 h; the apoptotic percentage was increased at 8 h, with collapse of the mitochondrial membrane potential and the activation of caspase-3 and caspase-9. The comet assay demonstrated DNA single-strand break at 2 h and double-strand break at 8 h. nsEP resulted in lower cytotoxicity in COC1/DDP cells compared with COC1 cells. These findings indicated that nsEP induced early and late phases of DNA damage and cell death, and these two types of cell death may have distinct applications to treatments of chemoresistant ovarian cancers

Extracorporeal Ultrasound-Guided High Intensity Focused Ultrasound: Implications from the Present Clinical Trials

Extracorporeal ultrasound-guided high intensity focused ultrasound (HIFU) has been clinically used for 15 years, and over 36000 cases have been reported. However, there yet lacked a consensus in the clinical values, suggesting the necessity of checking clinical findings. Clinical trials were searched and data reevaluated. HIFU was hardly performed alone; almost all present anticancer means have been applied during an HIFU treatment, and a specific regimen varied between trials; there were heterogeneity and disagreement between trials. The complexity made it difficult to distinguish the effect of HIFU. Based upon evaluable data, the efficacy of HIFU was similar to that of radio frequency, chemoembolization, chemotherapy, radiotherapy, or hormone therapy; a combined therapy did not improve the efficacy. The survival rate of HIFU plus radiotherapy was lower than that of radical surgery in liver cancers. Adverse events had no downtrend in the past years. HIFU was not a standardized procedure where the intensity and insonation mode were modified constantly throughout a treatment, limiting an evaluation from the perspective of ultrasonics. These implied that HIFU should be applied as an alternative at most occasions. The present clinical trials had defects making against the understating of HIFU

An Advanced Orthotopic Ovarian Cancer Model in Mice for Therapeutic Trials

A nude mouse received subcutaneous injection of human ovarian cancer cells HO-8910PM to form a tumor, and then the tumor fragment was surgically transplanted to the ovary of a recipient mouse to establish an orthotopic cancer model. Tumors occurred in 100% of animals. A mouse displayed an ovarian mass, ascites, intraperitoneal spread, and lung metastasis at natural death. The mean survival time was 34.1±17.2 days, with median survival time of 28.5 days. The findings indicated that the present mouse model can reflect the biological behavior of advanced human ovarian cancers. This in vivo model can be used to explore therapeutic means against chemoresistance and metastasis, and an effective treatment would prolong the survival time

Pharmacokinetic profiles of cancer sonochemotherapy

<p><b>Introduction:</b> Sonochemotherapy is a promising strategy for the treatment of cancer, however, there is limited understanding of its pharmacokinetics (PK).</p> <p><b>Area covered:</b> The PK profile of sonochemotherapy is evaluated based on released data. Preclinical investigations suggest that the blood PK of sonochemotherapy is similar to chemotherapy when using free anticancer drugs. When using encapsulated drugs, a lower plasma level usually occurs; however, the ultrasonic release of drugs within a tumor may lead to drugs leaking into circulation, causing a rebound in the plasma drug level; a higher drug level is detected in certain healthy organs, however this depends mostly on the pharmaceutical formulation. Sonochemotherapy increases both the level and retention time of drugs in a tumor. Clinical trials of combined chemotherapy and high intensity focused ultrasound (HIFU) are evaluated from the perspective of preclinical PK: the intratumoral PK and drug interactions under insonation, and a protocol to set the interval between drug administration and insonation are lacking.</p> <p><b>Expert opinion:</b> Insonation can alter the PK properties of chemotherapeutics, which may exacerbate the system and/or organ toxicity of anticancer drugs. Directly employing the PK parameters validated in conventional chemotherapy plays an important role in unsatisfactory clinical outcomes of chemotherapy combined with HIFU.</p