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The EGFR tyrosine kinase inhibitor gefitinib is commonly used for lung cancer patients. However, some patients eventually become resistant to gefitinib and develop progressive disease. Here, we indicate that ecto-ATP synthase, which ectopically translocated from mitochondrial inner membrane to plasma membrane, is considered as a potential therapeutic target for drug-resistant cells. Quantitative multi-omics profiling reveals that ecto-ATP synthase inhibitor mediates CK2-dependent phosphorylation of DNA topoisomerase IIα (topo IIα) at serine 1106 and subsequently increases the expression of long noncoding RNA, GAS5. Additionally, we also determine that downstream of GAS5, p53 pathway, is activated by ecto-ATP synthase inhibitor for regulation of programed cell death. Interestingly, GAS5-proteins interactomic profiling elucidates that GAS5 associates with topo IIα and subsequently enhancing the phosphorylation level of topo IIα. Taken together, our findings suggest that ecto-ATP synthase blockade is an effective therapeutic strategy via regulation of CK2/phospho-topo IIα/GAS5 network in gefitinib-resistant lung cancer cells.

Summary Cancer is a complex disease that relies on both oncogenic mutations and non-mutated genes for survival, and therefore coined as oncogene and non-oncogene addictions. The need for more effective combination therapies to overcome drug resistance in oncology has been increasingly recognized, but the identification of potentially synergistic drugs at scale remains challenging. Here we propose a gene-expression-based approach, which uses the recurrent perturbation-transcript regulatory relationships inferred from a large compendium of chemical and genetic perturbation experiments across multiple cell lines, to engender a testable hypothesis for combination therapies. These transcript-level recurrences were distinct from known compound-protein target counterparts, were reproducible in external datasets, and correlated with small-molecule sensitivity. We applied these recurrent relationships to predict synergistic drug pairs for cancer and experimentally confirmed two unexpected drug combinations in vitro. Our results corroborate a gene-expression-based strategy for combinatorial drug screening as a way to target non-mutated genes in complex diseases., Graphical Abstract, Highlights • Compound signatures targeting non-oncogene addiction for combinatorial drug discovery • These signatures are reproducible and linked to cancer hallmarks and drug sensitivity • Two synergistic drug combinations are experimentally confirmed in vitro, Bioinformatics; Cancer Systems Biology; Pharmacoinformatics

Alternative polyadenylation (APA) affects the length of the 3' untranslated region (3'-UTR) and the regulation of microRNAs. Previous studies have shown that cancer cells tend to have shorter 3'-UTRs than normal cells. A plausible explanation for this is that it enables cancer cells to escape the regulation of microRNAs. Here, we extend this concept to an opposing context: changes in 3'-UTR length in the development of the human preimplantation embryo. Unlike cancer cells, during early development 3'-UTRs tended to become longer, and gene expression was negatively correlated with 3'-UTR length. Moreover, our functional enrichment results showed that length changes are part of the development mechanism. We also investigated the analogy of 3'-UTR length variation with respect to lncRNAs and found that, similarly, lncRNA length tended to increase during embryo development.

Summary Strengthening the gut epithelial barrier is a potential strategy for management of gut microbiota-associated illnesses. Here, we demonstrate that dual-specificity phosphatase 6 (Dusp6) knockout enhances baseline colon barrier integrity and ameliorates dextran sulfate sodium (DSS)-induced colonic injury. DUSP6 mutation in Caco-2 cells enhances the epithelial feature and increases mitochondrial oxygen consumption, accompanied by altered glucose metabolism and decreased glycolysis. We find that Dusp6-knockout mice are more resistant to DSS-induced dysbiosis, and the cohousing and fecal microbiota transplantation experiments show that the gut/fecal microbiota derived from Dusp6-knockout mice also confers protection against colitis. Further culturomics and mono-colonialization experiments show that one gut microbiota member in the genus Duncaniella confers host protection from DSS-induced injury. We identify Dusp6 deficiency as beneficial for shaping the gut microbiota eubiosis necessary to protect against gut barrier-related diseases.

MutT Homolog 1 (MTH1) has been proven to hydrolyze oxidized nucleotide triphosphates during DNA repair. It can prevent the incorporation of wrong nucleotides during DNA replication and mitigate cell apoptosis. In a cancer cell, abundant reactive oxygen species can lead to substantial DNA damage and DNA mutations by base-pairing mismatch. MTH1 could eliminate oxidized dNTP and prevent cancer cells from entering cell death. Therefore, inhibition of MTH1 activity is considered to be an anti-cancer therapeutic target. In this study, high-throughput screening techniques were combined with a fragment-based library containing 2,313 compounds, which were used to screen for lead compounds with MTH1 inhibitor activity. Four compounds with MTH1 inhibitor ability were selected, and compound MI0639 was found to have the highest effective inhibition. To discover the selectivity and specificity of this action, several derivatives based on the MTH1 and MI0639 complex structure were synthesized. We compared 14 complex structures of MTH1 and the various compounds in combination with enzymatic inhibition and thermodynamic analysis. Nanomolar-range IC50 inhibition abilities by enzyme kinetics and Kd values by thermodynamic analysis were obtained for two compounds, named MI1020 and MI1024. Based on structural information and compound optimization, we aim to provide a strategy for the development of MTH1 inhibitors with high selectivity and specificity.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a causative agent for the outbreak of coronavirus disease 2019 (COVID-19). This global pandemic is now calling for efforts to develop more effective COVID-19 therapies. Here we use a host-directed approach, which focuses on cellular responses to diverse small-molecule treatments, to identify potentially effective drugs for COVID-19. This framework looks at the ability of compounds to elicit a similar transcriptional response to IFN-β, a type I interferon that fails to be induced at notable levels in response to SARS-CoV-2 infection. By correlating the perturbation profiles of ~3,000 small molecules with a high-quality signature of IFN-β-responsive genes in primary normal human bronchial epithelial cells, our analysis revealed four candidate COVID-19 compounds, namely homoharringtonine, narciclasine, anisomycin, and emetine. We experimentally confirmed that the predicted compounds significantly inhibited SARS-CoV-2 replication in Vero E6 cells at nanomolar, relatively non-toxic concentrations, with half-maximal inhibitory concentrations of 165.7 nM, 16.5 nM, and 31.4 nM for homoharringtonine, narciclasine, and anisomycin, respectively. Together, our results corroborate a host-centric strategy to inform protective antiviral therapies for COVID-19., Systems biology; COVID-19; Host-directed therapy; Type I interferon; Drug repurposing; Bioinformatics; Infectious disease; Transcriptomics; Pharmaceutical science

Cancer is a complex disease that relies on both oncogenic mutations and non-mutated genes for survival, thereafter coined as oncogene and non-oncogene addictions. The need for more effective combination therapies to overcome drug resistance in oncology has been increasingly recognized, but the identification of potentially synergistic drugs at scale remains challenging. Here we propose a geneexpression- based approach, which uses the recurrent perturbation–transcript regulatory relationships inferred from a large compendium of chemical and genetic perturbation experiments across multiple cell lines, to engender a testable hypothesis for combination therapies. These transcript-level recurrences were distinct from known compound–protein target counterparts, reproducible in external datasets, and correlated with small-molecule sensitivity. Using this new approach, we predicted synergistic drug pairs for cancer, including most frequently the combinations of a topoisomerase inhibitor and an mTOR or PI3K inhibitor. We also experimentally confirmed the synergistic effects of one combination of CD-437 (a retinoid) and sirolimus (an mTOR inhibitor) and the other combination of narciclasine (a protein synthesis inhibitor) and purvalanol A (a CDK inhibitor) in two breast and two lung cancer cell lines. Our results corroborate a gene-expression-based strategy for combinatorial drug screening as a way to target non-mutated genes in complex diseases.

Gastrointestinal cancers are asymptomatic in early tumor development, leading to high mortality rates. Peri- or postoperative chemotherapy is a common strategy used to prolong the life expectancy of patients with these diseases. Understanding the molecular mechanisms by which anticancer drugs exert their effect is crucial to the development of anticancer therapies, especially when drug resistance occurs and an alternative drug is needed. By integrating high-throughput techniques and computational modeling to explore biological systems at different levels, from gene expressions to networks, systems biology approaches have been successfully applied in various fields of cancer research. In this review, we highlight chemotherapy studies that reveal potential signatures using microarray analysis, next-generation sequencing (NGS), proteomic and metabolomic approaches for the treatment of gastrointestinal cancers.

Fluorescent liposomal nanovesicles (liposomes) are commonly used for lipid research and/or signal enhancement. However, the problem of self-quenching with conventional fluorescent liposomes limits their applications because these liposomes must be lysed to detect the fluorescent signals. Here, we developed a nonquenched fluorescent (NQF)1 liposome by optimizing the proportion of sulforhodamine B (SRB) encapsulant and lissamine rhodamine B-dipalmitoyl phosphatidylethanol (LRB-DPPE) on a liposomal surface for signal amplification. Our study showed that 0.3% of LRB-DPPE with 200 μm of SRB provided the maximal fluorescent signal without the need to lyse the liposomes. We also observed that the NQF liposomes largely eliminated self-quenching effects and produced greatly enhanced signals than SRB-only liposomes by 5.3-fold. To show their application in proteomics research, we constructed NQF liposomes that contained phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2) and profiled its protein interactome using a yeast proteome microarray. Our profiling led to the identification of 162 PI(3,5)P2-specific binding proteins (PI(3,5)P2-BPs). We not only recovered many proteins that possessed known PI(3,5)P2-binding domains, but we also found two unknown Pfam domains (Pfam-B_8509 and Pfam-B_10446) that were enriched in our dataset. The validation of many newly discovered PI(3,5)P2-BPs was performed using a bead-based affinity assay. Further bioinformatics analyses revealed that the functional roles of 22 PI(3,5)P2-BPs were similar to those associated with PI(3,5)P2, including vesicle-mediated transport, GTPase, cytoskeleton, and kinase. Among the 162 PI(3,5)P2-BPs, we found a novel motif, HRDIKP[ES]NJLL that showed statistical significance. A docking simulation showed that PI(3,5)P2 interacted primarily with lysine or arginine side chains of the newly identified PI(3,5)P2-binding kinases. Our study showed that this new tool would greatly benefit profiling lipid-protein interactions in high-throughput studies.