Abstract
Background: Coronavirus disease (COVID-19) is an infectious disease
discovered in 2019 and currently in outbreak across the world. Lung
injury with severe respiratory failure is the leading cause of death in
COVID-19, caused by severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2). However, there still lacks efficient treatment for
COVID-19 induced lung injury and acute respiratory failure.
Methods: Inhibition of angiotensin-converting enzyme 2 (ACE2) caused by
the spike protein of SARS-CoV-2 is the most plausible mechanism of lung
injury in COVID-19. We performed drug repositioning analysis to
identify drug candidates that reverse gene expression pattern in L1000
lung cell line HCC515 treated with ACE2 inhibitor. We confirmed these
drug candidates by similar bioinformatics analysis using lung tissues
from patients deceased from COVID-19. We further investigated
deregulated genes and pathways related to lung injury, as well as the
gene-pathway-drug candidate relationships.
Results: We propose two candidate drugs, COL-3 (a chemically modified
tetracycline) and CGP-60474 (a cyclin-dependent kinase inhibitor), for
treating lung injuries in COVID-19. Further bioinformatics analysis
shows that 12 significantly enriched pathways (P-value <0.05) overlap
between HCC515 cells treated with ACE2 inhibitor and human COVID-19
patient lung tissues. These include signaling pathways known to be
associated with lung injury such as TNF signaling, MAPK signaling and
chemokine signaling pathways. All 12 pathways are targeted in COL-3
treated HCC515 cells, in which genes such as RHOA, RAC2, FAS, CDC42
have reduced expression. CGP-60474 shares 11 of 12 pathways with COL-3
and common target genes such as RHOA. It also uniquely targets other
genes related to lung injury, such as CALR and MMP14.
Conclusions: This study shows that ACE2 inhibition is likely part of
the mechanisms leading to lung injury in COVID-19, and that compounds
such as COL-3 and CGP-60474 have potential as repurposed drugs for its
treatment.
Keywords: COVID-19, SARS-CoV-2, lung injury, ACE2, COL-3, CGP-60474
Abbreviations
COVID-19: coronavirus disease 2019, SARS-CoV-2: severe acute
respiratory syndrome coronavirus 2, ACE2: angiotensin-converting enzyme
2, AGER: advanced glycosylation end-product specific receptor, LBP:
lipopolysaccharide binding protein, SCGB1A1: secretoglobin family 1A
member, SFTPD: surfactant protein D, RAS: renin–angiotensin system, Ang
II: angiotensin II, Ang-(1-7): angiotensin (1-7), ARDS: acute
respiratory distress syndrome, ACE2i: inhibition of ACE2, NS: not
significant, NA: not available.
Introduction
Coronavirus disease 2019 (COVID-19) is an infectious disease discovered
in 2019 and currently in outbreak across the world, resulting in more
than 4.3 million infections and over 291,354 deaths as of 12 ^th May,
2020. It is causing tens of thousands of new infections and thousands
of mortalities every day. Patients with COVID-19 present with
respiratory symptoms. Severe viral pneumonia related lung injury with
acute respiratory failure is the main reason for COVID-19 related death
^[27]1. However, there still lacks efficient treatment for COVID-19
induced lung injury and acute respiratory failure.
Coronaviruses (CoVs), are a large family of enveloped, positive-sense,
single-stranded RNA viruses, which can be found in many vertebrates,
such as birds, pigs and humans, and cause various diseases. A novel
CoV, termed severe acute respiratory syndrome (SARS)-CoV-2, is the
cause of COVID-19. Lung injury with acute respiratory failure was also
the main reason for death in patients with SARS ^[28]2. The spike
protein of SARS-CoV-2 shares 79.5% sequence identity with the SARS-CoV
virus ^[29]3– [30]5, which caused the SARS pandemic in 2002, resulting
in 774 deaths in 8096 confirmed patients in 29 countries ^[31]6.
SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) as the entry
receptor and cellular serine protease TMPRSS2 for S protein priming to
allow fusion of viral and cellular membranes ^[32]7, similar to
SARS-CoV ^[33]8, [34]9. Since in SARS-CoV infection, the spike protein
of SARS-CoV inhibits ACE2 to cause severe lung injury and acute
respiratory failure ^[35]10, [36]11, it is highly likely that
SARS-CoV-2 uses the same mechanism. Inhibition of ACE2 may be part of
the pathogenic mechanism in SARS-CoV-2 induced lung injury and acute
respiratory failure. Therefore, a drug repurposing pipeline aiming to
reverse the gene expression pattern due to ACE2 inhibition may be a
candidate for treating lung injury in COVID-19.
Towards this goal, we performed drug repositioning analysis to identify
drugs and compounds for treating SARS-CoV-2 induced lung injury. To
explore the mechanisms of proposed drug treatment, we further
investigated deregulated genes and pathways in both human lung cells
treated with ACE2 inhibitor and human lung tissues from patients
deceased from COVID-19. Our results revealed that lung injury related
molecular mechanisms are shared between ACE2 inhibition and SARS-CoV-2
infection. Moreover, our proposed drugs can target key genes in these
mechanisms, and therefore may prevent lung injury in COVID-19.
Methods
Data preparation
RNA-Seq data from human lung tissues from two COVID-19 deceased
patients and age-matched healthy lung tissues, as well as human lung
A549 cells with or without H1N1 infection, were downloaded from Gene
Expression Omnibus (GEO) database (accession number: [37]GSE147507), as
reported by Melo et al. ^[38]12. Level 5 LINCS L1000 data, a collection
of gene expression profiles for thousands of perturbagens at a variety
of time points, doses, and cell lines, were downloaded from the GEO
database (accession numbers: [39]GSE70138 and [40]GSE92742). Gene
expression profiles in lung cells were extracted from the downloaded
L1000 dataset using R scripts (code is available on [41]GitHub)
^[42]13. The extracted data include 37,366 treatments of 12,706 drugs
in 13 lung cell lines at different time points and doses. Two lung cell
lines, A549 and HCC515, were treated with 10 µM moexipril, a homologue
of ACE2 that inhibits ACE2 and ACE. Gene expression profiles were
collected from A549 and HCC515 cells at six and 24 hours after
treatment. Upon moexipril treatment, ACE2 level decreased with time in
HCC515 as expected; however, levels increased in A549. This prompted us
to focus the analysis on the HCC515 line, which showed the inhibition
effect of moexipril. Differential expression of genes was measured by
z-score ^[43]14.
Gene and pathway analysis
The RNA-Seq data were analyzed using DESeq2 ^[44]15 (version: 1.26.0).
Differential gene expressions were identified by comparing cases and
controls (e.g. COVID-19 lung tissue vs. the healthy lung tissue, or
cells with H1N1 infection vs. those without H1N1 infection). The top
1000 differential expressed genes were selected by the absolute z-score
value. These genes were then used for pathway enrichment analysis using
Database for Annotation, Visualization and Integrated Discovery (DAVID)
v6.8 ^[45]16. Significant pathways (P-value <0.05) were compared
between HCC515 cells with ACE2 inhibitor inhibition and lung tissues
from COVID-19 deceased patients. A gene is called “consistent”, if it
shows changes in the same direction (increase or decrease) with ACE2
inhibitor treatment and SARS-CoV-2 infection. There are 5390 genes
deregulated in the same direction in both ACE2 inhibition-treated
HCC515 cell line and COVID-19 patient lung tissue. Among them, 797
genes are in top 1000 differentially expressed genes in either ACE2
inhibition-treated HCC515 cell line or COVID-19 patient lung tissue,
and 119 genes are in significantly enriched pathways. The importance of
pathways was ranked using the following score:
[MATH:
ScorePathway=−logPvalu<
/mi>eACE2i
+PvalueCOVI<
mi>D192nconsi<
/mi>stent :MATH]
Pvalue [ACE2i] is the P-value from pathway enrichment analysis for the
top 1000 differentially expressed genes in HCC515 cells treated with
ACE2 inhibitor. Pvalue [COVID19] is the P-value from pathway enrichment
analysis for the top 1000 differentially expressed genes in human lung
tissue infected by SARS-CoV-2. n [consistent] is the number of
consistent genes in that pathway among top 1000 differential expressed
genes for both HCC515 cells with ACE2 inhibitor treatment and lung
tissues of deceased COVID-19 patients.
The importance of genes was ranked by the following score:
[MATH:
ScoreGene=ZscoreACE2i2+ZscoreCOVID1922 :MATH]
Zscore [ACE2i] is the z-score of the gene in HCC515 cells treated with
ACE2 inhibitor. Zscore [COVID19] is the z-score of the gene in human
lung tissue infected by SARS-CoV-2.
Drug repositioning analysis
The differential gene expression list was transformed into a gene rank
list. An effective drug treatment is one that reverts the aberrant gene
expression in disease back to the normal level in health. DrInsight
Package ^[46]17 (version: 0.1.1) was used for this purpose, and the
outlier-sum (OS) statistic was retrieved, which models the overall
disease-drug connectivity by aggregating disease transcriptome changes
with drug perturbation. The Kolmogorov–Smirnov (K-S) test was then
applied to the OS statistic, to show the significance level of one drug
treatment relative to the background of all other drugs and compounds
in the reference drug dataset. The reference drug dataset contains gene
rank lists from 12,706 drug treatments in the LINCS L1000 data, as
mentioned above. The Benjamini-Hochberg (BH) false discovery rate (FDR)
was used to adjust P-values from the K-S test to avoid false
significance due to multiple comparisons. FDR<0.05 was used as the
threshold to select significant drug candidates for the disease.
Figure preparation
[47]Figure 1 and [48]Figure 5 were generated in Microsoft PowerPoint
2016. [49]Figure 2 and [50]Figure 3 were generated in R (version:
3.6.3) with ggplot2 package (version: 3.3.0) ^[51]18. [52]Figure 4 was
generated in Cystoscope (version: 3.7.2) ^[53]19.
Figure 1. Workflow of repurposing drugs for treating lung injury in COVID-19.
[54]Figure 1.
[55]Open in a new tab
Input data include gene expression in A549 cells with H1N1 infection,
HCC515 cells with ACE2 inhibitor (ACE2i), human lung tissues of
deceased COVID-19 patients and cells with drug treatment. Reversing
analysis is conducted to search for drugs that can reverse the gene
expression changes upon treatment. The candidate drug to is compared to
all other drugs and compounds, in order to estimate its significance
level at treating the disease. Candidate drugs for H1N1 are used for
validation of the computational pipeline. Candidate drugs identified in
both HCC515 cells treated with ACE2 inhibitor and in human lung tissues
of deceased COVID-19 patients are used for downstream mechanism
analysis.
Figure 2. COL-3 and CGP-60474 can reverse the expression of marker genes of
lung injury.
[56]Figure 2.
[57]Open in a new tab
Z-score: z score of differential expression of genes in the sample;
ACE2i: HCC515 cells with ACE2 inhibitor inhibition; SARS-CoV-2: human
lung tissues from COVID-19 patients deceased from SARS-CoV-2 induced
lung complications; COL-3: HCC515 cells treated with COL-3; CGP-60474:
HCC515 cells treated with CGP-60474.
Figure 3. The bubble plot of significantly enriched pathways in HCC515 cells
with ACE2 inhibitor inhibition and human COVID-19 patient lung tissues.
[58]Figure 3.
[59]Open in a new tab
X-axis and Y-axis show -log10 transformed P-values in human COVID-19
patient lung tissues (SARS-CoV-2) and HCC515 cells with ACE2 inhibitor
inhibition (ACE2i), respectively. Size of the bubble shows the average
value of -log10 transformed P-value in SARS-CoV-2 and ACE2i.
Figure 4. Target genes and pathways of COL-3 and CGP-60474 in treating lung
injury in COVID-19.
[60]Figure 4.
[61]Open in a new tab
All pathways were significant enriched in both human COVID-19 patient
lung tissues and HCC515 cells with ACE2 inhibitor inhibition. The
abnormal gene expression patterns in these pathways were reversed by
COL-3 and/or CGP-60474. Blue diamond: down-regulated gene in disease;
orange diamond: up-regulated gene in disease; hexagon: pathway; blue
line: drug decreases gene expression; orange line: drug increases gene
expression; blue/orange line width corresponds to the ability to change
gene expression; dark green line: interaction between gene and pathway;
diamond size: importance of gene in the disease; hexagon size:
importance of pathway in the disease.
Figure 5. Proposed mechanisms of lung injury in COVID-19 through ACE2 and the
therapeutic effects of COL-3 and CGP-60474.
[62]Figure 5.
[63]Open in a new tab
Results
Feasibility test of the drug repositioning pipeline using influenza A (H1N1)
infection data
Our drug repositioning is based on the assumption that if a drug can
reverse the abnormality of gene expression pattern in the disease, the
drug should be able to treat the disease ^[64]20, [65]21. Towards this
we have implemented the computational framework as shown in [66]Figure
1. We collected differential gene expression patterns in the disease
and in cells with drug treatment. Then we searched reversible genes
whose expression changes in drug treatment are opposite to those in
disease to estimate the effect of a drug for the disease. We further
compared effect of every drug to all other candidates to estimate the
significance of a drug for treating the disease.
As COVID-19 is an emerging disease with much unknown, we first
demonstrate the feasibility of the drug repositioning pipeline using
H1N1 virus infection, where much more research has been done and
multiple drugs are approved by the United States Food and Drug
Administration. We computed the differentially expressed genes from
RNA-Seq data of A549 lung cells with or without H1N1 virus infection.
We then identified the best candidates that could reverse the
expression pattern of these differentially expressed genes, by
analyzing 12,706 drugs and compounds from LINCS L1000 pharmacogenomics
data ^[67]14. The results show that CGP-60474 (FDR= 2.514×10 ^-4),
sirolimus (FDR= 3.040×10 ^-4), COL-3 (FDR= 9.452×10 ^-4), PIK-75 (FDR=
0.002), geldanamycin (FDR= 0.001), and wortmannin (FDR= 0.046) could
significantly (FDR<0.05) reverse the gene expression in H1N1 infection
in A549 lung cells ( [68]Table 1). Sirolimus, the second-best candidate
by FDR, also known as rapamycin, is a potent immunosuppressant that
acts by selectively blocking the transcriptional activation of
cytokines, thereby inhibiting cytokine production. It was previously
shown clinically effective in H1N1 infected patients with severe
pneumonia and acute respiratory failure ^[69]22 as adjuvant treatment
with steroids. PIK-75, a PI3K inhibitor, exhibits potent antiviral
activity against H1N1 virus ^[70]23. Geldanamycin is a Hsp90 inhibitor,
while wortmannin is an inhibitor of actinin-4. Both geldanamycin and
wortmannin can inhibit H1N1 virus replication ^[71]24, [72]25. In
summary, our drug repositioning pipeline has shown promise through the
example of H1N1 infection.
Table 1. Significant candidate drugs for treating infection of H1N1,
inhibition of ACE2 and infection of SARS-CoV-2, respectively.
Drug FDR value
H1N1 infection ACE2i SARS-CoV-2 infection
A549 cell HCC515 cell HCC515 cell Human lung tissue
9h 6h 24h NA
Sirolimus 3.040×10 ^-4 NS NS 0.003
COL-3 9.452×10 ^-4 NS 0.002 0.003
Geldanamycin 0.001 0.006 NS NS
CGP-60474 2.514×10 ^-4 NS 1.337×10 ^-7 0.003
Staurosporine NS NS NS 0.003
Mitoxantrone NS NS NS 0.003
Trichostatin-a NS NS 0.004 NS
Panobinostat NS NS 2.443×10 ^-5 NS
Narciclasine NS 0.006 NS NS
PIK-75 0.002 NS NS NS
Wortmannin 0.046 NS NS NS
[73]Open in a new tab
NS, not significant; NA, not available; ACE2i, inhibition of ACE2; FDR,
false discovery rate.
Repurposed drugs for treating lung injury in COVID-19
To repurpose drugs for inhibition of ACE2, we conducted differential
gene expression analysis in HCC515 and A549 lung cells with the
inhibition of ACE2 by moexipril, from the LINCS L1000 project ^[74]14
using a similar approach as for H1N1 infection described above. Upon
examination of ACE2 expression at different time points (six and 24
hours), we opted to focus on HCC515 cells, which have reduced ACE2
expression upon treatment with moexipril, an ACE2 inhibitor. At six
hours after treatment with moexipril, narciclasine (FDR=0.006) and
geldanamycin (FDR=0.006) could significantly reverse the gene
expression changes due to the ACE2 inhibitor ( [75]Table 1). At 24
hours post treatment of moexipril, the effect of CGP-60474
(FDR=1.337×10 ^-7), panobinostat (FDR=2.443×10 ^-05), trichostatin-a
(FDR=3.546×10 ^-03) and COL-3 (FDR= 0.002) became significant (
[76]Table 1). Among these predicted drugs, narciclasine and
geldanamycin are significant in HCC515 cells at 6h after treatment but
no longer significant in cells at 24h after treatment. Both
narciclasine and geldanamycin have anti-inflammatory effects and can
reduce lung injury caused by other diseases in animal model ^[77]26,
[78]27. On the other hand, in HCC515 cells treated with moexipril, the
ACE2 level at 24h is lower than that at 6h, suggesting that ACE2
inhibition is enhanced over time. Thus drugs such as narciclasine and
geldanamycin that are effective in early treatment may not be suitable
for sustained administration.
To further confirm if these effects shown in cell lines are
physiologically relevant for human lung injury due to COVID-19, we
analyzed the RNA-Seq data of human lung tissues from two COVID-19
deceased patients with age-matched normal lung tissues, as reported by
Melo et al. ^[79]12 Gene expression of individual markers for lung
injury, advanced glycosylation end-product specific receptor (AGER),
lipopolysaccharide binding protein (LBP) and secretoglobin family 1A
member (SCGB1A1) ^[80]28 is up-regulated in the HCC515 cell line
treated with ACE2 inhibitor and human COVID-19 patient lung tissue (
[81]Figure 2), whereas expression of surfactant protein D (SFTPD), a
gene encoding a protein involved in the innate immune response to
protect the lungs against inhaled microorganisms and chemicals, is
decreased. This indicates the similarity between ACE2 inhibition by
moexipril in the cell line and lung injury from COVID-19. Next we
extracted the differentially expressed genes in COVID-19 lung tissues
vs. normal lungs and used them as target genes to be reversed by the
same drugs and compounds in the drug repositioning framework as shown
in [82]Figure 1. The results show that sirolimus (FDR=0.003), COL-3
(FDR=0.003), CGP-60474 (FDR=0.003), staurosporine (FDR=0.003) and
mitoxantrone (FDR=0.003) are significant in reversing the target genes’
expression in the human lung tissues due to COVID-19 mentioned earlier
( [83]Table 1). Thus, together COL-3 and CGP-60474 show consistent
effects for reversing gene expression changes in both the HCC515 cell
line treated with ACE2 inhibitor and human COVID-19 patient lung tissue
( [84]Table 1). Moreover, COL-3 and CGP-60474 both can reversely
decrease the expression of marker genes for lung injury, AGER, LBP,
SCGB1A1, and reversely increase SFTPD expression in HCC515 cell line
pre-treated with ACE2 inhibitor moexipril. CGP-60474 (0.12 µM) appears
to be more potent than COL-3 (2.5 µM). In conclusion, COL-3 and
CGP-60474 show promise as potential purposeful drugs to treat lung
injury in COVID-19.
Pathway comparison between inhibition of ACE2 and infection of SARS-CoV-2
We performed pathway enrichment analysis with the top 1000 deregulated
genes in HCC515 cells with ACE2 inhibitor inhibition and human COVID-19
patient lung tissues. It was found that 12 significantly enriched
pathways (P-value <0.05) overlap between HCC515 cells with ACE2
inhibitor inhibition and human COVID-19 patient lung tissues (
[85]Figure 3, [86]Table 2). As expected, multiple pathways involved in
virus infection are enriched. Various signaling pathways, such as the
TNF signaling pathway, MAPK signaling pathway and chemokine signaling
pathway, with well-known associations with lung injury, are also
enriched ^[87]29– [88]31. Moreover, other pathways related to cancers
(e.g. ‘viral carcinogenesis’ and ‘proteoglycans in cancer’), or
cardiovascular diseases (e.g. ‘viral myocarditis’) also show up
significantly enriched in the results ( [89]Figure 3, [90]Table 2). A
total of 66 genes in these overlapped pathways show consistent changes
between the ACE2 inhibited lung cell line and SARS-CoV-2 lung tissues (
[91]Table 2).
Table 2. Pathway comparison between HCC515 cells with ACE2 inhibitor
inhibition and human COVID-19 patient lung tissues.
Pathway name P-value Consistent genes
SARS-CoV-2 ACE2i
Human lung
tissue HCC515
cell
Viral carcinogenesis 8.610×10 ^-06 6.744×10 ^-03 YWHAZ, PXN, CDC42,
HIST1H2BK, RHOA, CHD4, TP53, HLA-A, HLA-C,
HLA-B, CDK4, YWHAE, GTF2B, JUN
Endocytosis 4.068×10 ^-05 3.902×10 ^-02 RAB7A, CHMP5, SNX2, HSPA1A,
ARPC5, CAPZB, CDC42, RHOA, IL2RG,
HSPA8, EHD4, RAB8A, VPS45, HLA-A, HLA-C, HLA-B, WAS, ARPC5L, ARF3
Hepatitis B 3.354×10 ^-04 1.227×10 ^-02 YWHAZ, TP53, RAF1, CDK4, STAT6,
FOS, JUN, FAS
Chemokine signaling
pathway 3.797×10 ^-04 8.760×10 ^-04 CCL2, ADCY7, GNG11, PXN, CDC42,
RAC2, RHOA, RAF1, WAS, GSK3A,
GNB1
MAPK signaling pathway 5.283×10 ^-04 1.257×10 ^-02 HSPA1A, FOS, CDC42,
RAC2, PAK2, FAS, MAP2K6, HSPA8, TP53, NR4A1,
RAF1, FLNA, RPS6KA2, JUN, GADD45B, GADD45A, MAP3K13
Regulation of actin
cytoskeleton 4.760×10 ^-03 2.189×10 ^-03 ARPC5, PXN, IQGAP1, CDC42,
PFN1, RAC2, PAK2, RHOA, ACTB,
ARHGEF7, RAF1, MYL12B, WAS, ARPC5L, CFL1
Leukocyte
transendothelial
migration 5.122×10 ^-03 3.452×10 ^-02 ACTB, MYL12B, PXN, VASP, CDC42,
RAC2, RHOA
Bacterial invasion of
epithelial cells 1.697×10 ^-02 1.130×10 ^-02 ACTB, CDC42, ARPC5L, RHOA,
ARPC5, WAS, PXN
Proteoglycans in cancer 1.870×10 ^-02 9.963×10 ^-03 ACTB, PTPN6, TP53,
RAF1, IQGAP1, PXN, FLNA, CDC42, RHOA, FAS
TNF signaling pathway 3.117×10 ^-02 2.039×10 ^-02 CFLAR, CCL2, MMP14,
MMP3, FOS, JUN, BCL3, FAS, MAP2K6
Viral myocarditis 3.976×10 ^-02 2.943×10 ^-02 ACTB, EIF4G1, RAC2,
HLA-A, HLA-C, HLA-B
HTLV-I infection 4.296×10 ^-02 7.225×10 ^-03 IL1R2, ADCY7, BCL2L1,
CALR, FOS, IL2RG, BUB3, EGR1, TP53, HLA-A,
HLA-C, HLA-B, CDK4, ETS1, JUN
[92]Open in a new tab
ACE2i, inhibition of ACE2. Consitent genes, whose expression showed
same direction (increase or decrease) changes in HCC515 cells with ACE2
inhibitor treatment and lung tissues with SARS-CoV-2 infection.
We further analyzed the genes and pathways associated with the two
drugs COL-3 and CGP-60474, which show coherent effects in reversing the
gene expression patterns in HCC515 cells with ACE2 inhibitor inhibition
and human COVID-19 patient lung tissues ( [93]Figure 4). For COL-3,
from the molecular point of view, it leads to decreased expression of
many genes including RHOA, RAC2, FAS and CDC42 in lung cells, as part
of the mechanisms to protect lung from injury ( [94]Figure 4). These
genes are important players in pathways such as the chemokine signaling
pathway (for CCL2, ADCY7, GNG11, PXN, CDC42, RAC2, RHOA, WAS), TNF
signaling pathway (for CCL2, MMP3, JUN, BCL3, FAS, MAP2K6) and MAPK
signaling pathway (for HSPA1A, CDC42, RAC2, PAK2, FAS, MAP2K6, JUN,
GADD45B, GADD45A). All 12 significantly enriched pathways in [95]Figure
3 are also observed in COL-3 treatment. CGP-60474 shares 13 gene
targets with COL-3, including RHOA, WAS, HSPA1A, SNX2, RAB8A, IL2RG,
MMP3, BCL2L1, JUN, HIST1H2BK, GNG11, IQGAP1 and MYL12B. It also has a
unique set of target genes related to lung injury, such as CALR and
MMP14 ( [96]Figure 4). It decreases the expression of CALR, a
multifunctional protein that acts as a major Ca(2+)-binding (storage)
protein in the lumen of the endoplasmic reticulum ^[97]32. It also
increases the expression of MMP14, a member of the matrix
metalloproteinase (MMP) family with anti-inflammatory properties.
CGP-60474 treatment affects 11 out of 12 significantly enriched
pathways in COL-3, but not the viral myocarditis pathway. More details
on the molecular mechanisms of the target genes and pathways of these
two drug candidates are discussed below.
Discussion
The inhibition of ACE2 promotes lung injury via the renin–angiotensin
system (RAS) ^[98]33. In pulmonary RAS, ACE2 converts angiotensin II
(Ang II), an octapeptide hormone, to Ang-(1-7), an heptapeptide hormone
( [99]Figure 5). Ang II triggers pulmonary inflammation and activates
the TNF signaling pathway and MAPK signaling pathway to promote lung
injury ^[100]34, [101]35. On the other hand, Ang-(1–7) inhibits
inflammation and protects lungs from injury ^[102]36 by inhibiting the
MAPK signaling pathway ^[103]37, lowering cytokine release ^[104]38 and
downregulating the RHOA/ROCK pathway ^[105]39. Thus, inhibition of ACE2
will increase Ang II levels, decrease Ang-(1–7), and deregulate various
downstream pathways, such as TNF and MAPK signaling pathways to promote
lung injury ( [106]Figure 5). Our pathway analysis on the HCC515 lung
cell line confirmed that inhibition of ACE2 by moexipril can deregulate
TNF signaling, MAPK signaling and cytokine signaling pathways. We
further showed that these pathways are also deregulated in human lung
tissues of deceased COVID-19 patients ( [107]Table 2). Moreover,
inhibition of ACE2 induced similar expression patterns of lung injury
markers to that in human lung tissues of deceased COVID-19 patients (
[108]Figure 2). This evidence suggests that inhibition of ACE2 may
indeed be part of the molecular mechanisms of lung injury in COVID-19.
Moreover, other pathways related to cancers (e.g. ‘viral
carcinogenesis’ and ‘proteoglycans in cancer’), or cardiovascular
diseases (e.g. viral myocarditis) also show up significantly enriched
in the results ( [109]Table 2). These results may help to explain the
increased risks of fatality among COVID-19 patients with underlying
conditions (cancers, heart diseases) ^[110]40, [111]41. Additionally,
myocarditis has been clinically observed in a patient with COVID-19
^[112]42, showing a direct link between the two conditions.
Our drug repositioning analysis suggested five possible drugs based on
RNA-Seq data from patients deceased from COVID-19. Among them, clinical
trial has started for treating patients with COVID-19 pneumonia with
sirolimus ( [113]NCT04341675). Two other drugs (or compounds), COL-3
and CGP-60474, also have additional evidence of effectiveness from the
L1000 data of the lung HCC515 cell line treated with ACE2 inhibitor
moexipril. Moreover, both COL-3 and CGP-60474 could reverse the
expression patterns of lung injury markers in HCC515 cells with ACE2
inhibitor inhibition and human COVID-19 patient lung tissues (
[114]Figure 2). This phenotypic evidence suggests that COL-3 and
CGP-60474 may be effective in treating lung injury in COVID-19 (
[115]Figure 5). Therefore, we further analyzed the target genes and
pathways of these two drugs in treating lung injury in COVID-19.
COL-3, also known as incyclinide or CMT-3, is a chemically modified
tetracycline. It reversed the expression patterns of many lung injury
related genes and pathways, such as RHOA, RAC2 and FAS in the chemokine
signaling pathway, TNF signaling pathway and MAPK signaling pathway (
[116]Figure 4). RHOA, also known as ras homolog family member A, is a
member of the Rho family of small GTPases. The activation of RHOA is
crucial for lung injury ^[117]43. Inhibition of RHOA is a promising
approach to acute lung injury treatment ^[118]44. RAC2, also known as
Ras-related C3 botulinum toxin substrate 2, is a member of the Ras
superfamily of small guanosine triphosphate (GTP)-metabolizing
proteins. Rac2 plays an important role in inflammation-mediated lung
injury ^[119]45, [120]46. FAS, also known as Fas cell surface death
receptor, is a member of the TNF-receptor superfamily. FAS activation
is essential in inducing acute lung injury ^[121]47. Small interfering
RNA targeting Fas reduced lung injury in mice ^[122]48. Previous
results from many pre-clinical animal models have supported the role of
COL-3 in reducing lung injury and improves survival of experimented
animals. For example, COL-3 prevented lung injury and acute respiratory
distress syndrome (ARDS) in a clinically applicable porcine model
^[123]49– [124]55. It also improved acute respiratory distress syndrome
(ARDS) survival in an ovine model ^[125]56. Given all the evidence,
COL-3 may be an attractive candidate for a clinical trial treating
severe viral pneumonia related lung injury with respiratory failure in
COVID-19 ( [126]Figure 5).
CGP-60474, on the other hand, is an inhibitor of cyclin-dependent
kinase ( [127]Figure 5). CGP-60474 not only shared target genes with
COL-3, such as RHOA, WAS, HSPA1A, SNX2, RAB8A, IL2RG, MMP3, BCL2L1,
JUN, HIST1H2BK, GNG11, IQGAP1 and MYL12B, but also has unique target
genes that related to lung injury, like CALR and MMP14 ( [128]Figure
4). Blocking CALR activity attenuated murine acute lung injury by
inducing polarization of M2 subtype macrophages, which are
anti-inflammatory ^[129]57. MMP14 was shown to trigger the
anti-inflammatory proteolytic cascade to prevent lung injury in mice
^[130]58. Interestingly, so far only a few studies have reported some
biological functions of CGP-60474 ^[131]59– [132]61. One drug
reposition study using L1000 data also pointed to CGP-60474 as the most
potent drug based on anti-inflammatory effects ^[133]61. The authors
then experimentally showed that CGP-60474 alleviated tumor necrosis
factor-α (TNF-α) and interleukin-6 (IL-6) levels in activated
macrophages, downregulated the NF-κB activity, and reduced the
mortality rate in lipopolysaccharide induced endotoxemia mice. Another
in silico drug prediction study suggested that CGP-60474 could target
multiple cancers, though no experiments were conducted ^[134]59.
Although cyclin-dependent kinase inhibition by another drug,
seliciclib, reduced lung damage in a mouse model of ventilator-induced
lung injury ^[135]60, further in vivo investigation of CGP-60474 is
needed to test its role in treating lung injury.
In summary, we propose two candidate drugs, COL-3 and CGP-60474, which
can reverse the gene expression patterns in COVID-19 lung injury and a
lung cell line with ACE2 being inhibited. We further analyzed potential
molecular and biological mechanisms of lung injury in COVID-19. The
work will hopefully gain the interest of the biomedical and clinical
community for further validations in vivo for both candidate drugs, and
even possibly clinical trials on COL-3 to save lives from severe
respiratory failure in COVID-19.
Data availability
Source data
RNA-Seq data from Gene Expression Omnibus, Accession number
[136]GSE147507: [137]https://identifiers.org/geo:GSE147507
Phase I LINCS L1000 data from Gene Expression Omnibus, Accession number
[138]GSE92742: [139]https://identifiers.org/geo:GSE92742
Phase II LINCS L1000 data from Gene Expression Omnibus, Accession
number [140]GSE70138: [141]https://identifiers.org/geo:GSE70138
Underlying data
Zenodo: lanagarmire/COVID19-Drugs-LungInjury: Prediction of repurposed
drugs for treating lung injury in COVID-19.
[142]https://doi.org/10.5281/zenodo.3823277 ^[143]62
This project contains the following underlying data:
* -
HCC515_6_data_for_drug.csv (Differential expression of genes in
HCC515 cell at 6 h after treatment of ACE2 inhibitor)
* -
HCC515_24_data_for_drug.csv (Differential expression of genes in
HCC515 cell at 24 h after treatment of ACE2 inhibitor)
* -
COVID19-Lung_data_for_drug.csv (Differential expression of genes in
lung tissues with COVID-19)
* -
HCC515_6_drug.csv (Drugs for HCC515 cell at 6 h after transfection
of ACE2 inhibitor)
* -
HCC515_24_drug.csv (Drugs for HCC515 cell at 24 h after
transfection of ACE2 inhibitor)
* -
COVID19-Lung_drug.csv (Drugs for lung tissuse from COVID-19
patients)
* -
COL-3_single_treatment_response_data.csv (Differential expression
of genes in HCC515 cell at 24h after treatment of COL-3)
* -
CGP-60474_single_treatment_response_data.csv (Differential
expression of genes in HCC515 cell at 24h after treatment of
CGP-60474)
Data are available under the terms of the [144]Creative Commons
Attribution 4.0 International license (CC-BY 4.0).
Code availability
Source code available from:
[145]https://github.com/lanagarmire/COVID19-Drugs-LungInjury
Archived source code at time of publication:
[146]https://doi.org/10.5281/zenodo.3822923 ^[147]13
License: [148]GNU General Public License v3.0
Funding Statement
This research was supported by the National Institute of Environmental
Health Sciences through funds provided by the trans-NIH Big Data to
Knowledge (BD2K) initiative [K01ES025434]; the US National Library of
Medicine [R01 LM012373, R01 LM12907]; and the National Institute of
Child Health and Human Development [R01 HD084633; to L.X. Garmire].
[version 2; peer review: 2 approved]
References