Prediction of drug efficacy from transcriptional profiles with deep learning
Authors: Ruimao Zheng
Jiarui Liu
Jie Zhu
Mingjing Gao
Ning Zhang
Hong Zhou
Liang Wang
Jingxiang Wang
Yongpan An
Weikaixin Kong
Zurui Liu
Xinpei Sun
Xin Wang
Zhuo Huang
Zhengwei Xie
Bingbing Guo
Yanqiu Yu
Miaomiao Gao
Journal: Nature Biotechnology (2021)
Discipline: BIOLOGY & BIOCHEMISTRY
Keywords: Drug discovery; target proteins; deep learning; efficacy prediction system; gene expression profile
Affiliations: Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, China., Beijing & Qingdao Langu Pharmaceutical R&D Platform, Beijing Gigaceuticals Tech. Co. Ltd., Beijing, China., Department of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, China., Department of Anatomy, Histology and Embryology, Neuroscience Research Institute, Health Science Center, Peking University, Beijing, China., State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Health Science Center, Peking University, Beijing, China., Department of Pharmacology, School of Basic Medical Sciences, Health Science Center, Peking University, Beijing, China. ., Peking University International Cancer Institute, Health Science Center, Peking University, Beijing, China. ., Department of Anatomy, Histology and Embryology, Neuroscience Research Institute, Health Science Center, Peking University, Beijing, China. .

Abstract:  Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning-based efficacy prediction system (DLEPS) that identifies drug candidates using a change in the gene expression profile in the diseased state as input. DLEPS was trained using chemically induced changes in transcriptional profiles from the L1000 project. We found that the changes in transcriptional profiles for previously unexamined molecules were predicted with a Pearson correlation coefficient of 0.74. We examined three disorders and experimentally tested the top drug candidates in mouse disease models. Validation showed that perillen, chikusetsusaponin IV and trametinib confer disease-relevant impacts against obesity, hyperuricemia and nonalcoholic steatohepatitis, respectively. DLEPS can generate insights into pathogenic mechanisms, and we demonstrate that the MEK-ERK signaling pathway is a target for developing agents against nonalcoholic steatohepatitis. Our findings suggest that DLEPS is an effective tool for drug repurposing and discovery. 

Retracted: No

PubPeer comments:
 Figure 4B: it appears that the gel lanes have been spliced on the right end side (between the lanes IgG S and IP), which is not indicated on the figure, nor acknowledged in the legend. ![file] , 
 Interesting. There is a discontinuity, but It s not a splice, because the bands do extend beyond the line. However, they clearly narrow as they do so. The most likely explanation is that the right-most lane has undergone lightness contrast adjustment that would reduce the intensity of any staining within it. , 
 I cannot explain the apparent discontinuity, but there is no splice between the last two lanes. I have uploaded a figure that contains all the samples that were loaded on the gel. The lanes circled in red are in the final figure.![file] , 
 The discontinuity doesn t seem to be in the original supplied. A closer look at the discontinuity in the figure (CBFb lane 6 = IgG DEP; copied at the highest resolution from the pdf) appears to show an intriguing feature. There is clearly a vertical line where the left-right change occurs, and the compression blocks appear thinner there, suggesting something happened *after* the initial compression of the whole image. ![file] Separately, features from lane 7 of the original do seem to appear, if indistinctly, in the IP lane of the figure. I would say therefore that the source checks out but there may have been a rather subtle adjustment of that one lane. , 
 Thanks to the authors for providing the original blot. I agree with Eutropis Clivicola, the source checks out. Perhaps PNAS should make it a requirement to provide the uncropped blots as supplemental data, like other publishers do... , 
 #4 RE: * ...and the compression blocks appear thinner there... .* Note, those aren t compression blocks, they are pixels. Bottom line: Given the original blot info provided by the author, it seems clear that the published image accurately portrays the results and there is no basis for serious concern. Instead, for anyone curious, it seems that a weird technical glitch has occurred in the published Figure, which propagates from panel B until about half way through panel G. It caused a whole field of pixels to become shifted rightward, so that one original column of pixels has become narrowed to about half its original width. If you open page 6 of the PDF in Illustrator, and zoom in super close, you can see how this half-pixel column propagates through all of panel B and then is visible again down in panel G, going all the way through the  FL image and about 20% of the way into the  mut 2 image -- at this point, the half-width column reverts to full-width, and pixel columns on the left-hand side go out of register with those above. At the left edge of the  mut 2 image, you can see that below this point the image gets about a half pixel wider. I ve marked these features below with yellow arrows, on a close-up of the junction between the  FL and  mut 2 images in panel G (click to enlarge). To summarize, everything above this point in the  mut 2 image of panel G appears to have been right-shifted, causing an original column of pixels to be narrowed to a half-pixel width. This is a really unusual glitch but it is nothing that raises any scientific concern. Edit: Sorry, the yellow arrow on the right should have been drawn one pixel further down. ![file] , 
 Thanks everyone for all the sleuthing. Just curious - do you see the glitch here too? This is a .png file of the figure that was provided to PNAS.![file] , 
 #7 No, the glitch does not appear to be present in that image. (E.g., the left edge of the mut 2 image in panel G is perfectly straight.) However, it is likely that you also provided the journal with a vector graphics file (such as .ai, .eps, or .pdf), because in the published PDF all of the drawing elements maintain a much higher resolution than this .png file provides. (This can be appreciated by examining the cartoon fish in panel F, plus all arrows, boxes, and lettering.) So the glitch might have arisen in that vector graphics file sometime during or after being supplied to PNAS. , 
 I supplied it to PNAS as an .ai file. Unfortunately the .ai file is too large to upload on this site. Thank you for your response! ,