Mixed lineage kinase domain-like is a key receptor interacting protein 3 downstream component of TNF-induced necrosis.

Tumor necrosis factor (TNF) is an important inflammatory cytokine and induces many cellular responses, including inflammation, cell proliferation, apoptosis, and necrosis. It is known that receptor interacting protein (RIP) kinases, RIP1 and RIP3, are key effectors of TNF-induced necrosis, but little is known about how these two RIP kinases mediate this process, although reactive oxygen species (ROS) generation and JNK activation have been suggested to be two downstream events of RIP kinases. Here we report the identification of mixed lineage kinase domain-like, MLKL, as a key RIP3 downstream component of TNF-induced necrosis. Through screening a kinase/phosphatase shRNA library in human colon adenocarcinoma HT-29 cells, we found that knockdown of MLKL blocked TNF-induced necrosis. Our data suggest that MLKL functions downstream of RIP1 and RIP3 and is recruited to the necrosome through its interaction with RIP3. Finally, we found that MLKL is required for the generation of ROS and the late-phase activation of JNK during TNF-induced necrosis. However, because these two events are not involved in TNF-induced necrosis in HT-29 cells, the target of MLKL during TNF-induced necrosis remains elusive. Taken together, our study suggests that MLKL is a key RIP3 downstream component of TNF-induced necrotic cell death.

Evolutionarily conserved protein ERH controls CENP-E mRNA splicing and is required for the survival of KRAS mutant cancer cells.

Cancers with Ras mutations represent a major therapeutic problem. Recent RNAi screens have uncovered multiple nononcogene addiction pathways that are necessary for the survival of Ras mutant cells. Here, we identify the evolutionarily conserved gene enhancer of rudimentary homolog (ERH), in which depletion causes greater toxicity in cancer cells with mutations in the small GTPase KRAS compared with KRAS WT cells. ERH interacts with the spliceosome protein SNRPD3 and is required for the mRNA splicing of the mitotic motor protein CENP-E. Loss of ERH leads to loss of CENP-E and consequently, chromosome congression defects. Gene expression profiling indicates that ERH is required for the expression of multiple cell cycle genes, and the gene expression signature resulting from ERH down-regulation inversely correlates with KRAS signatures. Clinically, tumor ERH expression is inversely associated with survival of colorectal cancer patients whose tumors harbor KRAS mutations. Together, these findings identify a role of ERH in mRNA splicing and mitosis, and they provide evidence that KRAS mutant cancer cells are dependent on ERH for their survival.

Machine learning framework for intelligent aeration control in wastewater treatment plants: Automatic feature engineering based on variation sliding layer.

Intelligent control of wastewater treatment plants (WWTPs) has the potential to reduce energy consumption and greenhouse gas emissions significantly. Machine learning (ML) provides a promising solution to handle the increasing amount and complexity of generated data. However, relationships between the features of wastewater datasets are generally inconspicuous, which hinders the application of artificial intelligence (AI) in WWTPs intelligent control. In this study, we develop an automatic framework of feature engineering based on variation sliding layer (VSL) to control the air demand precisely. Results demonstrated that using VSL in classic machine learning, deep learning, and ensemble learning could significantly improve the efficiency of aeration intelligent control in WWTPs. Bayesian regression and ensemble learning achieved the highest accuracy for predicting air demand. The developed models with VSL-ML models were also successfully implemented under the full-scale wastewater treatment plant, showing a 16.12 % reduction in demand compared to conventional aeration control of preset dissolved oxygen (DO) and feedback to the blower. The VSL-ML models showed great potential to be applied for the precision air demand prediction and control. The package as a tripartite library of Python is called wwtpai, which is freely accessible on GitHub and CSDN to remove technical barriers to the application of AI technology in WWTPs.

Oligomannurarate sulfate sensitizes cancer cells to doxorubicin by inhibiting atypical activation of NF-κB via targeting of Mre11.

Aberrant regulation of nuclear factor kappa B (NF-κB) transcription factor is involved in cancer development, progression and resistance to chemotherapy. JG3, a marine-derived oligomannurarate sulfate, was reported as a heparanase and NF-κB inhibitor to significantly block tumor growth and metastasis in various animal models. However, the detailed functional mechanism remains unclear. Here, we report that JG3 inhibits NF-κB activation by specifically antagonizing the doxorubicin-triggered Ataxia-telangiectasia-mutated kinase (ATM) and the sequential MEK/ERK/p90Rsk/IKK signaling pathway but does not interfere with TNF-α-mediated NF-κB activation. This selective inactivation of the specific NF-κB cascade is attributed to the binding capacity of JG3 for Mre11, a major sensor of DNA double-strand breaks (DSB). Based on this selective mechanism, JG3 showed synergistic effect with doxorubicin in a panel of tumor cells and did not affect immune system function as shown in the in vivo delayed-type hypersensitivity (DTH) and hemolysis assays. All these highlight the clinical potential of JG3 as a favorable sensitizer in cancer therapy. In addition, identification of Mre11 as a potential target in the development of NF-κB inhibitors provides a platform for the further development of effective anticancer agents.

Oligomannurarate sulfate blocks tumor growth by inhibiting NF-kappaB activation.

AIM: JG3, a novel marine-derived oligosaccharide, significantly inhibits angiogenesis and tumor metastasis by blocking heparanase activity. It also arrests tumor growth, an effect that is not fully explained by its anti-heparanase activity. Here we sought to identify the mechanisms underlying JG3-mediated inhibition of tumor growth. METHODS: Heparanase expression was assessed by RT-PCR and Western blotting. NF-kappaB activation status was determined using immunofluorescence, Western blotting, DNA-binding and transcription-activity assays. The effect of JG3 on upstream components of the NF-kappaB pathway and on selected transcription factors were monitored by Western blotting. The antitumor effect of JG3 and its relation to NF-kappaB activation were evaluated using four different tumor xenograft models. RESULTS: We found that JG3 effectively inhibited NF-kappaB activation independent of heparanase expression. Our results indicate that JG3 inactivated NF-kappaB by interfering with the activation of upstream components of the NF-kappaB pathway without generally affecting the nuclear translocation of transcription factors. Further, in vivo studies demonstrated that JG3 effectively arrested the growth of tumors derived from cell lines in which NF-kappaB was constitutively active (BEL-7402 liver carcinoma and MDA-MB-435s breast carcinoma), but did not affect the growth of tumors derived from NF-kappaB-negative cell lines (SGC-7901 gastric cancer and HO-8910 ovarian carcinoma). CONCLUSION: Our data indicate that NF-kappaB mediates the JG3-induced arrest of tumor growth. These results define a new mechanism of action of JG3 and highlight the potential for JG3 as a promising lead molecule in cancer therapy.

Marine-derived oligosaccharide sulfate (JG3) suppresses heparanase-driven cell adhesion events in heparanase over-expressing CHO-K1 cells.

AIM: To elucidate the detailed mechanisms underlying the appreciable effects of JG3, a novel marine-derived oligosaccharide, on cell migration using a Chinese hamster ovary (CHO) cell line stably over-expressing heparanase. METHODS: A retrovirus infection system was used to establish a CHO-K1 cell line stably transfected with heparanase. Immunocytochemistry was used to assess cell morphology. Flow cytometry was selected to analyze the activation of beta1-integrin, and Western blotting was used to analyze the downstream effects on the cell adhesion pathway. An affinity precipitation assay was used to determine activation of the small GTPases, Rac1, and RhoA. RESULTS: JG3 abolished heparanase-driven formation of focal adhesions and cell spreading. Although JG3 failed to block the heparanase-triggered activation of beta1-integrin or the phosphorylation of Src, the oligosaccharide caused a significant dephosphorylation of FAK and subsequent inactivation of Erk. Furthermore, JG3 was found to arrest the activation of Rac1. CONCLUSION: All these findings help form an alternative view to understand the mechanisms underlying the inhibitory effects of JG3 on cell motility.Acta Pharmacologica Sinica (2009) 30: 1033-1038; doi: 10.1038/aps.2009.97; published online 22 June 2009.

One-step immortalization of primary human airway epithelial cells capable of oncogenic transformation.

BACKGROUND: The ability to transform normal human cells into cancer cells with the introduction of defined genetic alterations is a valuable method for understanding the mechanisms of oncogenesis. Easy establishment of immortalized but non-transformed human cells from various tissues would facilitate these genetic analyses. RESULTS: We report here a simple, one-step immortalization method that involves retroviral vector mediated co-expression of the human telomerase protein and a shRNA targeting the CDKN2A gene locus. We demonstrate that this method could successfully immortalize human small airway epithelial cells while maintaining their chromosomal stability. We further showed that these cells retain p53 activity and can be transformed by the KRAS oncogene. CONCLUSIONS: Our method simplifies the immortalization process and is broadly applicable for establishing immortalized epithelial cell lines from primary human tissues for cancer research.

Using pooled miR30-shRNA library for cancer lethal and synthetic lethal screens.

Pooled shRNA library is a powerful, rapid, and cost-effective technology to carry out functional genomic screens in mammalian cells. This approach has been applied extensively to identify genetic dependencies in cancer cells that might be exploited for therapeutic purposes. In this chapter we provide a detailed protocol for using the Hannon-Elledge miR30-based library to conduct dropout screens in cancer cell lines. This protocol is readily adaptable to other pooled shRNA libraries and should facilitate the functional annotation of the human genome.