scholarly journals The human gut chemical landscape predicts microbe-mediated biotransformation of foods and drugs

eLife ◽  
2019 ◽  
Vol 8 ◽  
Author(s):  
Leah Guthrie ◽  
Sarah Wolfson ◽  
Libusha Kelly

Microbes are nature’s chemists, capable of producing and metabolizing a diverse array of compounds. In the human gut, microbial biochemistry can be beneficial, for example vitamin production and complex carbohydrate breakdown; or detrimental, such as the reactivation of an inactive drug metabolite leading to patient toxicity. Identifying clinically relevant microbiome metabolism requires linking microbial biochemistry and ecology with patient outcomes. Here we present MicrobeFDT, a resource which clusters chemically similar drug and food compounds and links these compounds to microbial enzymes and known toxicities. We demonstrate that compound structural similarity can serve as a proxy for toxicity, enzyme sharing, and coarse-grained functional similarity. MicrobeFDT allows users to flexibly interrogate microbial metabolism, compounds of interest, and toxicity profiles to generate novel hypotheses of microbe-diet-drug-phenotype interactions that influence patient outcomes. We validate one such hypothesis experimentally, using MicrobeFDT to reveal unrecognized gut microbiome metabolism of the ovarian cancer drug altretamine.

Author(s):  
Hai Wang ◽  
Pranay Agarwal ◽  
Gang Zhao ◽  
Guang Ji ◽  
Christopher M. Jewell ◽  
...  

2015 ◽  
Vol 41 (4) ◽  
pp. 585-591 ◽  
Author(s):  
J.-Y. Lee ◽  
T.H. Kim ◽  
D.H. Suh ◽  
J.W. Kim ◽  
H.S. Kim ◽  
...  

Oncotarget ◽  
2017 ◽  
Vol 8 (43) ◽  
pp. 74466-74478 ◽  
Author(s):  
Andrzej Klejewski ◽  
Karolina Sterzyńska ◽  
Karolina Wojtowicz ◽  
Monika Świerczewska ◽  
Małgorzata Partyka ◽  
...  

Author(s):  
Maria Rosaria Amoroso ◽  
Danilo Swann Matassa ◽  
Ilenia Agliarulo ◽  
Rosario Avolio ◽  
Francesca Maddalena ◽  
...  

Author(s):  
Galina Karashchuk ◽  
Nataliya Karashchuk ◽  
Signe Caksa ◽  
Tyler S. Smith ◽  
Alexander S. Brodsky

2012 ◽  
Vol 72 (2 Supplement) ◽  
pp. A30-A30
Author(s):  
Alexander S. Brodsky ◽  
Hsin-Ta Wu ◽  
Souriya Vang ◽  
Benjamin Raphael ◽  
Laurent Brard

NAR Cancer ◽  
2020 ◽  
Vol 2 (3) ◽  
Author(s):  
McKenzie K Grundy ◽  
Ronald J Buckanovich ◽  
Kara A Bernstein

Abstract Regulation of homologous recombination (HR) is central for cancer prevention. However, too little HR can increase cancer incidence, whereas too much HR can drive cancer resistance to therapy. Importantly, therapeutics targeting HR deficiency have demonstrated a profound efficacy in the clinic improving patient outcomes, particularly for breast and ovarian cancer. RAD51 is central to DNA damage repair in the HR pathway. As such, understanding the function and regulation of RAD51 is essential for cancer biology. This review will focus on the role of RAD51 in cancer and beyond and how modulation of its function can be exploited as a cancer therapeutic.


2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 5502-5502
Author(s):  
M. S. Carey ◽  
B. T. Hennessy ◽  
A. M. Gonzalez-Angulo ◽  
W. Liu ◽  
K. R. Coombes ◽  
...  

5502 Background: A number of clinicopathologic risk factors are used for survival prediction and clinical decision-making in epithelial ovarian cancer (EOC). Information from novel technologies such as gene arrays has not had an impact on patient management. We studied EOC protein signaling profiles to determine if their addition to accepted clinicopathologic factors improves their accuracy in predicting individual patient outcomes. Methods: We applied a novel functional proteomics technology, reverse phase protein array (RPPA), to quantify expression and activation of 42 steroid and kinase signaling pathway proteins in 106 high-grade EOCs from patients with stages 1–4 tumors managed with surgery and platinum-based chemotherapy. Cox regression analysis and a novel committee modeling approach were used to study the impact of functional proteomics on patient outcomes. Results: In a Cox model using only clinical variables, stage and residual disease were significantly related to overall survival. By adding the proteins to the clinical Cox model, two proteins that were significantly associated with overall survival on univariate analysis (phosphorylated-MAPK (p-MAPK; log rank p = 0.0047) and progesterone receptor (PR; log rank p = 0.027)) remained significant at the alpha=0.10 level (z-test p-values 0.074 and 0.034, respectively, when treated as binary variables according to martingale residual plots); as a result, these two proteins added to the predictive accuracy of the clinical survival model. However, using the novel committee modeling approach in test and validation EOC sets, a closest neighbor metric was applied to successfully define distinct proteins groups, each composed of nine proteins, that are predictive of specific survival times in patients with EOC. This granular approach to modeling is particularly suited to defining the molecular heterogeneity of EOC. Conclusions: EOC is a complex process with significant individual variability. Using novel approaches to functional proteomic study and statistical modeling, our striking finding is that distinct combinations of steroid and kinase signaling proteins are predictive markers of specific survival times in EOC. No significant financial relationships to disclose.


JAMA ◽  
2017 ◽  
Vol 317 (5) ◽  
pp. 466
Author(s):  
Rebecca Voelker
Keyword(s):  

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