Reversal of cancer gene expression identifies repurposed drugs for diffuse intrinsic pontine glioma

Abstract

Diffuse intrinsic pontine glioma (DIPG) is an aggressive incurable brainstem tumor that targets young children. Complete resection is not possible, and chemotherapy and radiotherapy are currently only palliative. This study aimed to identify potential therapeutic agents using a computational pipeline to perform an in silico screen for novel drugs. We then tested the identified drugs against a panel of patient-derived DIPG cell lines. Using a systematic computational approach with publicly available databases of gene signature in DIPG patients and cancer cell lines treated with a library of clinically available drugs, we identified drug hits with the ability to reverse a DIPG gene signature to one that matches normal tissue background. The biological and molecular effects of drug treatment was analyzed by cell viability assay and RNA sequence. In vivo DIPG mouse model survival studies were also conducted. As a result, two of three identified drugs showed potency against the DIPG cell lines Triptolide and mycophenolate mofetil (MMF) demonstrated significant inhibition of cell viability in DIPG cell lines. Guanosine rescued reduced cell viability induced by MMF. In vivo, MMF treatment significantly inhibited tumor growth in subcutaneous xenograft mice models. In conclusion, we identified clinically available drugs with the ability to reverse DIPG gene signatures and anti-DIPG activity in vitro and in vivo. This novel approach can repurpose drugs and significantly decrease the cost and time normally required in drug discovery.

Trial registration: ClinicalTrials.gov NCT04477200.

Keywords: Computational approach; Diffuse intrinsic pontine glioma; Drug repurposing; Machine learning; Mycophenolate mofetil.

Fig. 1

Prediction of DIPG drug hits. A Working model. In vitro/in vivo illustrations were taken from Biorender. B DIPG samples in a tumor map comprising > 17,000 samples. The tumor map is a t-distributed stochastic neighbor embedding (t-SNE) plot of sample TPM expressions. DIPG and brain cancer samples are highlighted. C Correlation between predicted reversal gene expression scores (sRGES) and experimental drug efficacy with a half maximal activity concentration (AC50) value. A lower sRGES means a higher potency to reverse the DIPG signature genes. The drug corresponding to the dot plot are described in Additional file 1: Table S1). D Meta-disease genes and their enriched pathways. The pathways commonly changed by the predicted drugs are highlighted. E Enriched target class of CDK in the predictions. The black line on the left suggests it is ranked on the top in the prediction list. An enriched target class means the ligands of the target tend to be highly ranked in the predictions. The enrichment of other two targets (TOP, HDAC) are illustrated in Additional file 4: Fig. S1(three eample drugs are labeled in each plot). F Top candidates selected for validation. The first row shows the meta disease signature. The signatures of four top candidates and three randomly selected control compounds are visualized. The altered genes are listed in Additional file 6: Table S5

Fig. 2

Cell viability assay valuation of the predicted drugs. Triptolide (A), triamterene (B) and mycophenolate mofetil (C) in DIPG cell lines (SF8628, SU-DIPG-IV) as well as control NHA cells. Left: Graphs showing the proliferation response of normal human astrocytes (NHA) and DIPG cell lines (SU-DIPG-IV, SF8628), to increasing concentrations of each drug. Values shown are the average [mean ± standard deviation (SD)] from triplicate samples for each incubation condition. Right: Dot plot representation of IC50 values shown are the average (mean ± SD) from triplicate samples for each cell lines. Statistical analysis was performed using a two-tailed unpaired t-test: triptolide, NHA versus SU-DIPG-IV, *P < 0.05; NHA versus SF8628, *P = 0.05; triamterene, NHA versus SU-DIPG-IV, *P < 0.05; NHA versus SF8628, *P < 0.05; MMF, NHA versus SU-DIPG-IV, ***P < 0.001; NHA versus SF8628, **P < 0.01

Fig. 3

RNAseq analysis of treated samples in DIPG cells. t-SNE plot of treatment samples with vehicle control (0.1% DMSO), 1 µM of MMF, 2 nM of triptolide, and 30 µM of triamterene in SF8628 (A, left) and SU-DIPG-IV (B, left) cells. MMF reversed the DIPG disease gene expression in SF8628 (A, right) and SU-DIPG-IV (B, right) cells

Fig. 4

Comparison of the effects of mycophenolate mofetil (MMF) and mycophenolic acid (MPA) in DIPG cells. A Left: Graphs showing the proliferation response of SU-DIPG-IV, to increasing concentrations of MMF and MPA for 3 days treatment. Values shown are the average (mean ± SD) from triplicate samples for each incubation condition. Right: Dot plot representation of IC50 values shown are the average (mean ± SD) from triplicate samples for each treatment condition. B Left: Graphs showing the proliferation response of SF8628, to increasing concentrations of MMF and MPA treatment. Values shown are the average (mean ± SD) from triplicate samples for each incubation condition. Right: Dot plot representation of IC50 values shown are the average (mean ± SD) from triplicate samples for each treatment condition. Statistical analysis was performed using a two-tailed unpaired t-test. No significant differences were found among MMF and MPA

Fig. 5

Guanosine but not xanthosine rescued MMF inhibitor response of DIPG cells. Graphs showing the proliferation response of SF8628 (A) and CNMC-D-1428 (B), to increasing concentrations of MMF in the presence of Guanosine or xanthosine treatment for 6 days in SF8628 cells or 3 days in CNMC-D-1428 cells. Values shown are the average (mean ± SD) from triplicate samples for each incubation condition

Fig. 6

In vivo anti-tumor activity of MMF in patient-derived DIPG xenografted models. A Mice with SF8628 intracranial tumors were either treated with vehicle (DMSO, n = 7) or MMF (50 mg/kg for 15 days, n = 9). Left: Tumor growth curve for bioluminescence values in each treatment group. Tumor bioluminescence values show mean and upper SD. Upper left: Corresponding tumor bioluminescence intensity overlay images for representative DMSO (left) and MMF (right)-treated mice on day 11 post-tumor cell implantation. Right: Corresponding survival plots of each treatment group. B Mice with SF8628 subcutaneous (sc) tumor were either treated with vehicle (DMSO, n = 7) or MMF (100 mg/kg, n = 7) daily for 15 days for 3 weeks. Left: Growth plots for sc tumors in each treatment group. Tumor volumes were normalized against tumor volume obtained at day 6 post-tumor cell injection. Normalized tumor volume show mean and upper SD. Middle: Dot plot representation of sc tumor volume in mice at day 42 post-tumor cell injection. Unpaired t-test values for comparisons between DMSO and MMF treatment: ***P = 0.0002. Photographs of nude mice (upper) and sc tumor taken from these mice (lower) in which SF8628 cells were inoculated into the right flank. Right: Animal survival at the indicated days after inoculation. Log-rank test was used for comparisons between DMSO and MMF treatment: ***P = 0.0003. C Left: Images of representative Ki-67 and TUNEL staining for sc tumors from mice euthanized at the end of treatment. The scale bar is defined as the length of 50 µm. Right, mean and SD values representing the average number in positive cells in four-high-powered fields in each tumor. Statistical analysis was performed using the unpaired t-test. Ki-67: DMSO versus MMF, ***P = 0.0002. TUNEL: DMSO versus MMF, **P = 0.0060