The potential effect of the angiotensin-converting enzyme 2 (ACE2) receptor of 2019-nCoV on lung adenocarcinoma patients


 BackgroundThe 2019-nCoV epidemic is the public health emergency that has had the greatest impact on the world. Our study aimed to better understand the underlying mechanisms and function of angiotensin-converting enzyme 2 (ACE2) receptor of 2019-nCoV on lung adenocarcinoma patients (LUAD), and provide a theoretical basis for early diagnosis, prognosis and targeted therapy of 2019-nCoV. MethodsThis study focuses on the expression level, functions, mutation rate, and copy number variations (CNVs) of ACE2 in LUAD using an extensive bioinformatics data mining process. The interaction between ACE2 expression and clinical-pathological parameters of patients with LUAD was investigated using UALCAN. Also, the essential biological features, single nucleotide variations (SNVs), CNVs, and pathway activities of genes interacting with ACE2 in these cancers were further analyzed. ResultsWe found that ACE2 expression in LUAD patients increased with age, but it was not related to cancer status, patient’s race, patient’s gender, or patient’s smoking habits. Moreover, our results showed that compared to that in normal tissues, ACE2 was highly expressed in colon adenocarcinoma (COAD), kidney renal papillary cell carcinoma (KIRP), pancreatic adenocarcinoma (PAAD), rectum adenocarcinoma (READ), and stomach adenocarcinoma (STAD). However, there is no significant difference in the expression of ACE2 in patients of different ages. ConclusionsThese findings demonstrate the importance of ACE2 in LUAD, and provide insights into the regulatory mechanisms and function of ACE2.

Background 89 During the Spring Festival of 2020, the outbreak of pneumococcal infection caused by the 90 and pathway activities of the genes interacting with ACE2 in these cancers. The findings of this 133 study will help enhance the understanding of the potentially positive role of ACE2 in LUAD and 134 provide a theoretical basis for the early diagnosis, prognosis, and targeted therapy of 2019-nCoV. 135 136

137
Analysis of the mutation rate and CNVs distribution of ACE2 analysis in LUAD 138 DriverDBv3 (http://driverdb.tms.cmu.edu.tw/) is a cancer database that incorporates somatic 139 mutation, methylation, copy number variation, and clinical data in addition to annotation bases. 140 This database can help researchers visualize the relationships between cancers and driver genes 141 [11]. The mutation squares indicate the number of mutation tools that identify this gene as a 142 mutation driver. As the number of tools goes from low to high, the blue color goes from light to 143 deep. The CNVs squares indicate the CNVs gain or loss of a gene. Red represents gain (1) and the 144 green represents a loss (-1). In this study, we used the DriverDBv3 tool to determine the mutation 145 rate and CNVs distribution of ACE2 and their correlations with LUAD. 146 147

Analysis of the protein network of ACE2 148
To better understand the function of related proteins and understand their regulatory 149 mechanisms more clearly. We predicted the protein-protein interactions of ACE2 vie the STRING 150 database (https://string-db.org/), which is a system that searches for known and predicted 151 protein-protein interactions [12]. The interactions include both direct physical interactions 152 between proteins and indirect functional correlations between proteins. Besides, we analyzed 153 the GO enrichment (biological process, molecular function, and cellular component) and KEGG 154 pathways of the genes interacting with ACE2 with the Enrichr online database [13]. 155 156

ACE2 expression and clinical-pathological parameter analysis in LUAD 157
We investigated the interaction between ACE2 expression and the clinicopathological 158 parameters of patients with LUAD using UALCAN (http://ualcan.path.uab.edu/index.html), which 159 is a comprehensive, user-friendly, and interactive web resource for analyzing gene expression 160 data using The Cancer Genome Atlas (TCGA) level 3 RNA-seq data and clinical data from 31 161 cancer types [14]. It provides gene expression and clinicopathological parameter information. In 162 the study, we entered the target gene ACE2 on the homepage of the website, selected LUAD, and 163 obtained the differential expression of ACE2 in pathological parameters (individual cancer status, 164 patient's race, patient's gender, patient's age, patient's smoking habits, node metastasis status, 165 and histological subtypes).

Immunohistochemical staining 168
This study was performed on archived tissues from 20 diagnosed cases of lung 169 adenocarcinoma patients who underwent surgery in Shenzhen Second People's Hospital. All the 170 patients signed the informed consent form. This study was approved by the Ethics Committee of 171 Shenzhen Second People' s Hospital in accordance with the principles of the Declarationof 172 Helsinki. The tissue samples were fixed in 4% paraformaldehyde and embedded in paraffin. Anti-ACE2 (1: 200, Affinity Biosciences) were used as primary antibodies. MXB was used to detect 174 secondary antibodies. The expression density of TACC3 in lung adenocarcinoma tissue was 175 quantitated by scoring staining intensity, including negative (-) and weak (+) staining, moderate (++) and strong (+++) staining, respectively [15,16]. 177 178

ACE2 expression in other cancers 179
We analyzed the expression of ACE2 in other cancers, including COAD, KIRP, PAAD, READ, and 180 STAD compared to normal tissues using Gene Expression Profiling Interactive Analysis (GEPIA) 181 database (http://gepia.cancer-pku.cn/), an interactive web application based on the gene 182 expression analysis of 9,736 tumors and 8,587 healthy tissue samples from the TCGA and 183 Genotype-Tissue Expression (GTEx) databases [17]. The correlation between ACE2 expression and 184 patient's age was further analyzed using the UALCAN database. in LUAD (Fig. 1B). We found the CNVs distribution mainly included gain, loss, none, and normal, 205 and was positively correlated with ACE2 expression in LUAD (cor = 0.149, p = 0.00075). Among 206 them, ACE2 expression was higher in copy number loss than in copy number gain. 207 208

ACE2 protein network analyses 209
Data from STRING were applied to determine the proteins interacting with ACE2 and the 210 results are shown in Fig. 2. The following ten proteins were found to interact with ACE2:

The enrichment analyses of ACE2 218
To further explore the regulators of ACE2 in LUAD, we next statistically analyzed the significant 219 GO enrichment terms and KEGG pathway of the identified genes via the Enrichr online database 220 Table S2). The biological processes of these proteins were mainly involved in the 221 regulation of systemic arterial blood pressure by renin-angiotensin (GO: 0003081), angiotensin 222 maturation (GO: 0002003), and regulation of angiotensin levels in the blood (GO: 0002002). 223 Regarding molecular functions, these proteins were mainly involved in the dipeptidyl-peptidase 224 activity (GO: 0008239), aminopeptidase activity (GO: 0004177), and exopeptidase activity (GO: 225 0008238). The cell component analysis of these proteins showed that they were significantly 226 enriched in invadopodium (GO: 0071437), azurophil granule membrane (GO: 0035577), and 227 ficolin-1-rich granule membrane (GO: 0101003). Moreover, KEGG pathway analysis showed 228 enrichment in the renin-angiotensin system, protein digestion and absorption, and renin 229 secretion.

LUAD 233
The goal of our study was to gain insights into the interaction between ACE2 expression and 234 the clinical-pathological parameters of patients with LUAD (Table S1). To accomplish this, we first 235 investigated ACE2 expression based on sample types, As shown in Fig. 4 A, the expression of 236 ACE2 in primary samples was significantly higher than that in normal tissues (p = 2.16E-8). 237 An analysis of individual cancer status showed that stage 1, stage 2, and stage 3 cancer tissues 238 had significantly higher expression than that in normal tissues (normal-vs-stage 1: p = 1.81E-10; 239 normal-vs-stage 2: p = 1.26E-03; normal-vs-stage 3: p = 2.48E-03), However, there was no 240 significant difference between stage 4 and normal tissues (p > 0.05) (Fig. 4 B). 241 In comparing the patient's race (Fig. 4 C), we found that Caucasians and Asians with cancer had 242 significantly higher ACE2 expression than normal control individuals (normal-vs-Caucasian: p = 243 1.55E-05; normal-vs-Asian: p = 4.57E-02). However, there was no significant difference in the 244 expression of ACE2 among Caucasians, Asians, and African Americans (p > 0.05). 245 In addition, we analyzed the relationship between ACE2 expression and patient's age (Fig. 4 D). 246 Notably, we found that the expression of ACE2 in patients aged 61-80 years was significantly 247 higher than that in patients aged 21-40 years (p = 7.23E-04), the expression of ACE2 in patients 248 aged 81-100 years was significantly higher than that in patients aged 21-40 years (p = 3.68E-02), 249 and the expression of ACE2 in patients aged 61-80 years was significantly higher than that in 250 patients aged 41-60 years (p = 1.60E-03). The results help explain why older people are more 251 susceptible to SARS-CoV2. 252 Next, we investigated whether there was a difference between the expression of ACE2 and the 253 patients' gender. As shown in Fig. 4 E, ACE2 expression was higher in both male and female 254 cancer patients than that in the normal group (normal-vs-male: p = 6.17E-04; normal-vs-female: 255 p = 1.45E-09), but no significant difference was found between ACE2 expression and sexes 256 (male-vs-female: p > 0.05). 257 Smoking is the most important risk factor for lung cancer [20]. The relationship between the 258 expression of ACE2 and smoking in LUAD remains to be studied. Here, we focused on ACE2 259 expression according to patient's smoking habits (Fig. 4 F), including non-smoker, smoker, 260 reformed smoker 1 (< 15 years), and reformed smoker 1 (> 15 years). Regarding the smoking 261 habits of LUAD patients, the expression levels of ACE2 in patients with all conditions were higher 262 than those in normal controls, but we found that there were no significant differences between 263 patients' smoking habits and the expression of ACE2 (p > 0.01). Therefore, we speculate that the 264 expression of ACE2 may not be related to the smoking habits of patients. 265 Subsequently, it is worth noting the relationship between ACE2 expression and node 266 metastasis status (N0: no regional lymph node metastasis; N1: metastases in 1 to 3 axillary lymph 267 nodes; N2: metastases in 4 to 9 axillary lymph nodes; and N3: metastases in 10 or more axillary 268 lymph nodes). As shown in Fig. 4 G, we found that there was no significant difference between 269 ACE2 expression and node metastasis status (p > 0.05). 270 Based on histological subtypes, the data showed that ACE2 expression was highest in lung 271 clear cell adenocarcinoma (Clear Cell), but there was no significant difference compared with the 272 normal group (p > 0.05). We found high ACE2 expression in the lung adenocarcinoma-not 273 otherwise specified (NOS) and lung adenocarcinoma mixed subtype compared to normal controls 274 in this cancer, with greater statistically significant (normal-vs-NOS: p = 4.38E-10; normal-vs-mixed: 275 p = 2.46E-03) (Fig. 4 H). We also found that the expression of ACE2 was higher in lung mucinous 276 adenocarcinoma compared to NOS in LUAD tumors (p = 7.67E-09).

ACE2 expression in other cancers 286
To study the expression of ACE2 in other cancers and whether it is related to the patient' s age. 287 We examined the difference in ACE2 expression between tumor and adjacent normal tissues by 288 using GEPIA (Fig. 6 A). We found that ACE2 was also highly expressed in COAD, KIRP, PAAD, READ, 289 and STAD compared to normal tissues. These results suggested that the transcription level of 290 ACE2 was cancer type-specific (p < 0.05). However, there was no significant difference in the 291 expression of ACE2 among patients aged 21-40 years, 41-60 years, 61-80 years, and 81-100 years 292 ( Fig. 6 B). 293 294

SNVs, CNVs, and pathway activity of hub proteins in LUAD 295
To further understand the SNVs, CNV, and pathway activity of these proteins, we performed 296 the analysis with GSCALite (Fig. 7 A-C). The SNVs module presented the SNVs frequency and 297 variant types of these genes in LUAD. We found that the SNVs frequencies of MME, XPNPEP2, 298 DPP4, AGTR1, and ACE2 were in the top five, and are 19 %, 16 %, 14 %, 12 %, and 11 %, 299 respectively. Among them, the variant types of ACE2 were missense mutations. In the CNVs 300 module, the main copy number variants of ACE2 include heterozygous amplification and 301 heterozygous deletion. 302 We then determined the pathway activity of these genes (Fig. 7 D-F). The pathways involved 303 are apoptosis, cell cycle, DNA damage response, EMT, hormone AR, hormone ER, PI3K/AKT, 304 RAS/MAPK, RTK (receptor tyrosine kinase), and TSC/mTOR. The results showed that RTK was 305 activated by DPP4 and ACE2. The EMT pathway was mainly activated by AGTR1, DPP4, MME, and 306 XPNPEP2. However, the cell cycle was mainly inhibited by AGTR1, DPP4, and PRCP. Besides, we 307 found that the Hormone AR pathway was mainly inhibited by DPP4, AGTR1, XPNPEP2, MME, MEP1A, and ACE2. 309 310 311

Discussion 312
At present, the 2019-nCoV epidemic is the public health emergency that has had the greatest 313 impact on the world and has received great attention from the international community. Facing 314 the "encounter" of the epidemic, China responded positively, acted quickly, and took effective 315 measures to resolutely curb the spread of the epidemic, which was highly appraised by the 316 international community. Given that 2019-nCoV pneumonia has become a new infectious disease 317 transmitted from person to person, while working hard to comply with national instructions, we 318 must work harder to understand the 2019-nCoV virus, and we should have a deeper 319 understanding of how viruses invade the human body. A recent study showed that the ACE2 320 protein had a strong binding affinity with the spike protein of SARS-CoV-2 [21]. However, whether 321 the expression of ACE2 is higher in patients with LUAD and whether it is related to the clinical and 322 pathological parameters of patients is yet to be confirmed. In this study, we described the 323 correlation between ACE2 expression and pathological parameters in LUAD and determined the 324 proteins interacting with ACE2. Next, we analyzed SNVs, CNVs, and pathway activities of the hub 325 genes in other cancers. 326 We statistically analyzed the proteins interacting with ACE2 and performed GO enrichment and 327 KEGG pathway analysis. Among the ACE2 binging proteins, we found that AGT, REN, and MME KEGG pathway analysis showed enrichment in the renin-angiotensin system, protein digestion 336 and absorption, and renin secretion. These data analysis results show that ACE2 is related to the 337 regulation of systemic arterial blood pressure, providing a direction for further research. 338 Based on sample types, we found that the expression of ACE2 in primary samples was 339 significantly higher than that in normal tissues. Notably, there was no significant difference 340 between ACE2 expression and patient's smoking habits. Therefore, we speculate that the 341 expression of ACE2 may not be related to the smoking habits of patients. In addition, our data 342 showed that ACE2 expression was not related to the cancer stage or the patient's gender, node 343 metastasis status, or histological subtypes. However, ACE2 expression in the lung increased with 344 age, but there was no significant difference in the expression of ACE2 among Caucasians, Asians, 345 and African Americans. This finding is consistent with the report from [10]. Furthermore, the 346 representative immunohistochemical staining patterns for ACE2 were further verification, and 347 high ACE2 expression was found in patients with advanced LUAD. The results help explain why 348 older people are more susceptible to 2019-nCoV. 349 Further studies are required to investigate ACE2 expression in other cancers (COAD, KIRP, 350 PAAD, READ, and STAD). Jia X et al. revealed that the expression of ACE2 in cervical squamous cell 351 carcinoma and endometrial adenocarcinoma, kidney renal clear cell carcinoma, KIRP, and PAAD was higher than that in surrounding tissues [25]. The present study not only provided evidence of 353 high ACE2 expression in KIRP and PAAD but also discovered markedly increased levels of ACE2 in 354 COAD, READ, and STAD. Therefore, we suspect that patients with these cancers may be more 355 susceptible to 2019-nCoV, and they are the key protection targets in epidemic prevention work. 356 However, there was no significant difference in the expression of ACE2 among patients aged 357 21-40 years, 41-60 years, 61-80 years, and 81-100 years. Further large-scale studies are needed 358 to verify these findings. Special attention should be given to cancer patients clinically, noting that 359 they may have a longer course of the illness or a higher risk of severe illness. 360 Subsequently, the RTK pathway was activated by ACE2. RTKs can be expressed in many cell 361 types, including cells in the tumor microenvironment [26]. As a key regulator of cancer 362 development, the RTK pathway plays an important role in the proliferation, invasion, 363 angiogenesis, and metastasis of cancer [27]. These results suggest that ACE2 plays an important 364 role in tumorigenesis and development. In addition, we found that PI3K/AKT and RAS/MAPK 365 pathways activated by ACE2. Besides, we found that the EMT pathway was inhibited by ACE2, but 366 was activated by AGT, AGTR1, DPP4, MME, PRCP, and XPNPEP2. The deregulation of the cell cycle 367 is a fundamental process that underlies cancer proliferation [28]. We found that some genes 368 were mainly inhibited in the cell cycle, especially ACE2, AGTR1, and DPP4. Although we identified 369 a potential correlation between ACE2 expression and these pathways, whether they are involved 370 in regulating ACE2 expression is worthy of future study. 371 372

Conclusion 373
Our study aimed to better understand the underlying mechanisms and function of ACE2 with 374 the utilization of extensive databases. Our results demonstrate the importance of ACE2 in LUAD 375 and provide insights into the regulatory mechanisms and functions of ACE2. We hope that these 376 findings provide useful information on the treatment and prevention of 2019-nCoV.   Table S1. Relationship between ACE2 expression and clinicopathological parameters of patients 583 with LUAD 584 585 Table S2. The GO functional enrichment and KEGG pathway analyses of ACE2 586