A new type of signaling network element, called cancer signaling bridges (CSB), has been shown to have the potential for systematic and fast-tracked drug repositioning. On the basis of CSBs, we ...developed a computational model to derive specific downstream signaling pathways that reveal previously unknown target-disease connections and new mechanisms for specific cancer subtypes. The model enables us to reposition drugs based on available patient gene expression data. We applied this model to repurpose known or shelved drugs for brain, lung, and bone metastases of breast cancer with the hypothesis that cancer subtypes have their own specific signaling mechanisms. To test the hypothesis, we addressed specific CSBs for each metastasis that satisfy (i) CSB proteins are activated by the maximal number of enriched signaling pathways specific to a given metastasis, and (ii) CSB proteins are involved in the most differential expressed coding genes specific to each breast cancer metastasis. The identified signaling networks for the three types of breast cancer metastases contain 31, 15, and 18 proteins and are used to reposition 15, 9, and 2 drug candidates for the brain, lung, and bone metastases. We conducted both in vitro and in vivo preclinical experiments as well as analysis on patient tumor specimens to evaluate the targets and repositioned drugs. Of special note, we found that the Food and Drug Administration-approved drugs, sunitinib and dasatinib, prohibit brain metastases derived from breast cancer, addressing one particularly challenging aspect of this disease.
Regulatory T cells (Tregs) play a neuroprotective role by suppressing microglia and macrophage-mediated inflammation and modulating adaptive immune reactions. We previously documented that Treg ...immunomodulatory mechanisms are compromised in Alzheimer's disease (AD). Ex vivo expansion of Tregs restores and amplifies their immunosuppressive functions in vitro. A key question is whether adoptive transfer of ex vivo expanded human Tregs can suppress neuroinflammation and amyloid pathology in a preclinical mouse model.
An immunodeficient mouse model of AD was generated by backcrossing the 5xFAD onto Rag2 knockout mice (5xFAD-Rag2KO). Human Tregs were expanded ex vivo for 24 days and administered to 5xFAD-Rag2KO. Changes in amyloid burden, microglia characteristics and reactive astrocytes were evaluated using ELISA and confocal microscopy. NanoString Mouse AD multiplex gene expression analysis was applied to explore the impact of ex vivo expanded Tregs on the neuroinflammation transcriptome.
Elimination of mature B and T lymphocytes and natural killer cells in 5xFAD-Rag2KO mice was associated with upregulation of 95 inflammation genes and amplified number of reactive microglia within the dentate gyrus. Administration of ex vivo expanded Tregs reduced amyloid burden and reactive glial cells in the dentate gyrus and frontal cortex of 5xFAD-Rag2KO mice. Interrogation of inflammation gene expression documented down-regulation of pro-inflammatory cytokines (IL1A&B, IL6), complement cascade (C1qa, C1qb, C1qc, C4a/b), toll-like receptors (Tlr3, Tlr4 and Tlr7) and microglial activations markers (CD14, Tyrobp,Trem2) following Treg administration.
Ex vivo expanded Tregs with amplified immunomodulatory function, suppressed neuroinflammation and alleviated AD pathology in vivo. Our results provide preclinical evidences for Treg cell therapy as a potential treatment strategy in AD.
Motivation: Automated identification of cell cycle phases captured via fluorescent microscopy is very important for understanding cell cycle and for drug discovery. In this article, we propose a ...novel cell detection method that utilizes both the intensity and shape information of the cell for better segmentation quality. In contrast to conventional off-line learning algorithms, an Online Support Vector Classifier (OSVC) is thus proposed, which removes support vectors from the old model and assigns new training examples weighted according to their importance to accommodate the ever-changing experimental conditions. Results: We image three cell lines using fluorescent microscopy under different experiment conditions, including one treated with taxol. Then, we segment and classify the cell types into interphase, prophase, metaphase and anaphase. Experimental results show the effectiveness of the proposed system in image segmentation and cell phase identification. Availability: The software and test datasets are available from the authors. Contact: zhou@crystal.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Motivation: Prediction of synergistic effects of drug combinations has traditionally been relied on phenotypic response data. However, such methods cannot be used to identify molecular signaling ...mechanisms of synergistic drug combinations. In this article, we propose an enhanced Petri-Net (EPN) model to recognize the synergistic effects of drug combinations from the molecular response profiles, i.e. drug-treated microarray data.
Methods: We addressed the downstream signaling network of the targets for the two individual drugs used in the pairwise combinations and applied EPN to the identified targeted signaling network. In EPN, drugs and signaling molecules are assigned to different types of places, while drug doses and molecular expressions are denoted by color tokens. The changes of molecular expressions caused by treatments of drugs are simulated by two actions of EPN: firing and blasting. Firing is to transit the drug and molecule tokens from one node or place to another, and blasting is to reduce the number of molecule tokens by drug tokens in a molecule node. The goal of EPN is to mediate the state characterized by control condition without any treatment to that of treatment and to depict the drug effects on molecules by the drug tokens.
Results: We applied EPN to our generated pairwise drug combination microarray data. The synergistic predictions using EPN are consistent with those predicted using phenotypic response data. The molecules responsible for the synergistic effects with their associated feedback loops display the mechanisms of synergism.
Availability: The software implemented in Python 2.7 programming language is available from request.
Contact:
stwong@tmhs.org
Triple negative breast cancer (TNBC) is known to contain a high percentage of CD44(+) /CD24(-/low) cancer stem cells (CSCs), corresponding with a poor prognosis despite systemic chemotherapy. ...Chloroquine (CQ), an antimalarial drug, is a lysotropic reagent which inhibits autophagy. CQ was identified as a potential CSC inhibitor through in silico gene expression signature analysis of the CD44(+) /CD24(-/low) CSC population. Autophagy plays a critical role in adaptation to stress conditions in cancer cells, and is related with drug resistance and CSC maintenance. Thus, the objectives of this study were to examine the potential enhanced efficacy arising from addition of CQ to standard chemotherapy (paclitaxel) in TNBC and to identify the mechanism by which CQ eliminates CSCs in TNBCs. Herein, we report that CQ sensitizes TNBC cells to paclitaxel through inhibition of autophagy and reduces the CD44(+) /CD24(-/low) CSC population in both preclinical and clinical settings. Also, we are the first to report a mechanism by which CQ regulates the CSCs in TNBC through inhibition of the Janus-activated kinase 2 (Jak2)-signal transducer and activator of transcription 3 signaling pathway by reducing the expression of Jak2 and DNA methyltransferase 1.
Components of the adipose tissue (AT) extracellular matrix (ECM) are recently discovered contributors to obesity-related cardiometabolic disease. We identified increased adipocyte expression of ...ECM-related clusterin (apolipoprotein J) in obese versus lean women by microarray. Our objective was to determine
) whether subcutaneous AT adipocyte (SAd) clusterin and serum clusterin are associated with insulin resistance (IR) and known markers of cardiometabolic risk and
) how clusterin may contribute to increased risk.
We validated increased clusterin expression in adipocytes from a separate group of 18 lean and 54 obese individuals. The relationship of clusterin gene expression and plasma clusterin with IR, cardiovascular biomarkers, and risk of cardiovascular disease (CVD) was then determined. Further investigations in human cultured cells and in aged LDLR
mice prone to development of obesity-associated complications were performed.
SAd clusterin correlated with IR, multiple CVD biomarkers, and CVD risk, independent of traditional risk factors. Circulating human clusterin exhibited similar associations. In human adipocytes, palmitate enhanced clusterin secretion, and in human hepatocytes, clusterin attenuated insulin signaling and APOA1 expression and stimulated hepatic gluconeogenesis. LRP2 (megalin), a clusterin receptor, highly expressed in liver, mediated these effects, which were inhibited by LRP2 siRNA. In response to Western diet feeding, an increase in adipocyte clusterin expression was associated with a progressive increase in liver fat, steatohepatitis, and fibrosis in aged LDLR
mice.
Adipocyte-derived clusterin is a novel ECM-related protein linking cardiometabolic disease and obesity through its actions in the liver.
We previously described a gene signature for breast cancer stem cells (BCSCs) derived from patient biopsies. Selective shRNA knockdown identified ribosomal protein L39 (RPL39) and myeloid leukemia ...factor 2 (MLF2) as the top candidates that affect BCSC self-renewal. Knockdown of RPL39 and MLF2 by specific siRNA nanoparticles in patient-derived and human cancer xenografts reduced tumor volume and lung metastases with a concomitant decrease in BCSCs. RNA deep sequencing identified damaging mutations in both genes. These mutations were confirmed in patient lung metastases (n = 53) and were statistically associated with shorter median time to pulmonary metastasis. Both genes affect the nitric oxide synthase pathway and are altered by hypoxia. These findings support that extensive tumor heterogeneity exists within primary cancers; distinct subpopulations associated with stem-like properties have increased metastatic potential.
Cancer patients often show heterogeneous drug responses such that only a small subset of patients is sensitive to a given anticancer drug. With the availability of large-scale genomic profiling via ...next-generation sequencing, it is now economically feasible to profile the whole transcriptome and genome of individual patients in order to identify their unique genetic mutations and differentially expressed genes, which are believed to be responsible for heterogeneous drug responses. Although subtyping analysis has identified patient subgroups sharing common biomarkers, there is no effective method to predict the drug response of individual patients precisely and reliably. Herein, we propose a novel computational algorithm to predict the drug response of individual patients based on personal genomic profiles, as well as pharmacogenomic and drug sensitivity data. Specifically, more than 600 cancer cell lines (viewed as individual patients) across over 50 types of cancers and their responses to 75 drugs were obtained from the genomics of drug sensitivity in cancer database. The drug-specific sensitivity signatures were determined from the changes in genomic profiles of individual cell lines in response to a specific drug. The optimal drugs for individual cell lines were predicted by integrating the votes from other cell lines. The experimental results show that the proposed drug prediction algorithm can be used to improve greatly the reliability of finding optimal drugs for individual patients and will, thus, form a key component in the precision medicine infrastructure for oncology care.
The role of epithelial-to-mesenchymal transition (EMT) in metastasis is a longstanding source of debate, largely owing to an inability to monitor transient and reversible EMT phenotypes in vivo. Here ...we establish an EMT lineage-tracing system to monitor this process in mice, using a mesenchymal-specific Cre-mediated fluorescent marker switch system in spontaneous breast-to-lung metastasis models. We show that within a predominantly epithelial primary tumour, a small proportion of tumour cells undergo EMT. Notably, lung metastases mainly consist of non-EMT tumour cells that maintain their epithelial phenotype. Inhibiting EMT by overexpressing the microRNA miR-200 does not affect lung metastasis development. However, EMT cells significantly contribute to recurrent lung metastasis formation after chemotherapy. These cells survived cyclophosphamide treatment owing to reduced proliferation, apoptotic tolerance and increased expression of chemoresistance-related genes. Overexpression of miR-200 abrogated this resistance. This study suggests the potential of an EMT-targeting strategy, in conjunction with conventional chemotherapies, for breast cancer treatment.
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