DeepGene: an advanced cancer type classifier based on deep learning and somatic point mutations

BACKGROUND: With the developments of DNA sequencing technology, large amounts of sequencing data have become available in recent years and provide unprecedented opportunities for advanced association studies between somatic point mutations and cancer types/subtypes, which may contribute to more accurate somatic point mutation based cancer classification (SMCC). However in existing SMCC methods, issues like high data sparsity, small volume of sample size, and the application of simple linear classifiers, are major obstacles in improving the classification performance. RESULTS: To address the obstacles in existing SMCC studies, we propose DeepGene, an advanced deep neural network (DNN) based classifier, that consists of three steps: firstly, the clustered gene filtering (CGF) concentrates the gene data by mutation occurrence frequency, filtering out the majority of irrelevant genes; secondly, the indexed sparsity reduction (ISR) converts the gene data into indexes of its non-zero elements, thereby significantly suppressing the impact of data sparsity; finally, the data after CGF and ISR is fed into a DNN classifier, which extracts high-level features for accurate classification. Experimental results on our curated TCGA-DeepGene dataset, which is a reformulated subset of the TCGA dataset containing 12 selected types of cancer, show that CGF, ISR and DNN all contribute in improving the overall classification performance. We further compare DeepGene with three widely adopted classifiers and demonstrate that DeepGene has at least 24% performance improvement in terms of testing accuracy. CONCLUSIONS: Based on deep learning and somatic point mutation data, we devise DeepGene, an advanced cancer type classifier, which addresses the obstacles in existing SMCC studies. Experiments indicate that DeepGene outperforms three widely adopted existing classifiers, which is mainly attributed to its deep learning module that is able to extract the high level features between combinatorial somatic point mutations and cancer types

A covalently bound inhibitor triggers EZH2 degradation through CHIP‐mediated ubiquitination

Abstract Enhancer of zeste homolog 2 (EZH2) has been characterized as a critical oncogene and a promising drug target in human malignant tumors. The current EZH2 inhibitors strongly suppress the enhanced enzymatic function of mutant EZH2 in some lymphomas. However, the recent identification of a PRC2‐ and methyltransferase‐independent role of EZH2 indicates that a complete suppression of all oncogenic functions of EZH2 is needed. Here, we report a unique EZH2‐targeting strategy by identifying a gambogenic acid (GNA) derivative as a novel agent that specifically and covalently bound to Cys668 within the EZH2‐SET domain, triggering EZH2 degradation through COOH terminus of Hsp70‐interacting protein (CHIP)‐mediated ubiquitination. This class of inhibitors significantly suppressed H3K27Me3 and effectively reactivated polycomb repressor complex 2 (PRC2)‐silenced tumor suppressor genes. Moreover, the novel inhibitors significantly suppressed tumor growth in an EZH2‐dependent manner, and tumors bearing a non‐GNA‐interacting C668S‐EZH2 mutation exhibited resistance to the inhibitors. Together, our results identify the inhibition of the signaling pathway that governs GNA‐mediated destruction of EZH2 as a promising anti‐cancer strategy

Relationships between Hematopoiesis and Hepatogenesis in the Midtrimester Fetal Liver Characterized by Dynamic Transcriptomic and Proteomic Profiles

In fetal hematopoietic organs, the switch from hematopoiesis is hypothesized to be a critical time point for organogenesis, but it is not yet evidenced. The transient coexistence of hematopoiesis will be useful to understand the development of fetal liver (FL) around this time and its relationship to hematopoiesis. Here, the temporal and the comparative transcriptomic and proteomic profiles were observed during the critical time points corresponding to the initiation (E11.5), peak (E14.5), recession (E15.5), and disappearance (3 ddp) of mouse FL hematopoiesis. We found that E11.5-E14.5 corresponds to a FL hematopoietic expansion phase with distinct molecular features, including the expression of new transcription factors, many of which are novel KRAB (Kruppel-associated box)-containing zinc finger proteins. This time period is also characterized by extensive depression of some liver functions, especially catabolism/utilization, immune and defense, classical complement cascades, and intrinsic blood coagulation. Instead, the other liver functions increased, such as xenobiotic and sterol metabolism, synthesis of carbohydrate and glycan, the alternate and lectin complement cascades and extrinsic blood coagulation, and etc. Strikingly, all of the liver functions were significantly increased at E14.5-E15.5 and thereafter, and the depression of the key pathways attributes to build the hematopoietic microenvironment. These findings signal hematopoiesis emigration is the key to open the door of liver maturation

A new gamboge derivative compound 2 inhibits cancer stem-like cells via suppressing EGFR tyrosine phosphorylation in head and neck squamous cell carcinoma

Cancer stem-like cells represent a population of tumour-initiating cells that lead to the relapse and metastasis of cancer. Conventional anti-cancer therapeutic drugs are usually ineffective in eliminating the cancer stem-like cells. Therefore, new drugs or therapeutic methods effectively targeting cancer stem-like cells are in urgent need to successfully cure cancer. Gamboge is a natural anti-cancer medicine whose pharmacological effects are different from those of conventional chemotherapeutical drugs and they can kill some kinds of cancer cells selectively. In this study, we identified a new gamboge derivative, Compound 2 (C2), which presents eminent suppression effects on cancer cells. Interestingly, when compared with cisplatin (CDDP), C2 effectively suppresses the growth of both cancer stem-like cells and non-cancer stem-like cells derived from head and neck squamous cell carcinoma (HNSCC), inhibiting the formation of tumour spheres and colony in vitro, resulting in the loss of expression of multiple cancer stem cell (CSC)-related molecules in HNSCC. Treating with C2 effectively inhibited the growth of HNSCC in BALB/C nude mice. Further investigation found that C2 notably inhibits the activation of epithelial growth factor receptor and the phosphorylation of its downstream protein kinase homo sapiens v-akt murine thymoma viral oncogene homolog (AKT) in HNSCC, resulting in down-regulation of multiple CSC-related molecules in HNSCC. Our study has demonstrated that C2 effectively inhibits the stem-like property of cancer stem-like cells in HNSCC and may be a hopeful targeting drug in cancer therapy

IRTKS Promotes Insulin Signaling Transduction through Inhibiting SHIP2 Phosphatase Activity

Insulin signaling is mediated by a highly integrated network that controls glucose metabolism, protein synthesis, cell growth, and differentiation. Our previous work indicates that the insulin receptor tyrosine kinase substrate (IRTKS), also known as BAI1-associated protein 2-like 1 (BAIAP2L1), is a novel regulator of insulin network, but the mechanism has not been fully studied. In this work we reveal that IRTKS co-localizes with Src homology (SH2) containing inositol polyphosphate 5-phosphatase-2 (SHIP2), and the SH3 domain of IRTKS directly binds to SHIP2’s catalytic domain INPP5c. IRTKS suppresses SHIP2 phosphatase to convert phosphatidylinositol 3,4,5-triphosphate (PI(3,4,5)P3, PIP3) to phosphatidylinositol (3,4) bisphosphate (PI(3,4)P2). IRTKS-knockout significantly increases PI(3,4)P2 level and decreases cellular PI(3,4,5)P3 content. Interestingly, the interaction between IRTKS and SHIP2 is dynamically regulated by insulin, which feeds back and affects the tyrosine phosphorylation of IRTKS. Furthermore, IRTKS overexpression elevates PIP3, activates the AKT–mTOR signaling pathway, and increases cell proliferation. Thereby, IRTKS not only associates with insulin receptors to activate PI3K but also interacts with SHIP2 to suppress its activity, leading to PIP3 accumulation and the activation of the AKT–mTOR signaling pathway to modulate cell proliferation