Genomic analyses identify signicant genes and processes in adrenocortical carcinoma cells with overexpressed Ptch1

Adrenocortical carcinoma is a rare malignancy that mainly comes from family diseases. However, the mechanism and treatment of this cancer are still unclear today. Here, our objective is to determine the signicant genes and signaling by analyzing the RNA-seq data from the Ptch1 overexpression cancer cells. The KEGG and GO analyses showed the Calcium signaling pathway and Pathogenic Escherichia coli infection were the key signaling pathways in Ptch1-overexpressed cancer cells. Moreover, we further identied the ten interactive molecules including ALB, STAT3, FOS, NRXN1, SNAP25, SYP, FYN, SPP1, THY1, GRIN2A. Our study may provide insights into the mechanism of Ptch1 regulating adrenocortical carcinoma. signicance between benign


Introduction
Adrenal tumors are common and benign in the human population, but adrenocortical carcinoma (ACC) is a rare endocrine malignancy 1 . The surveillance database showed the incidence is approximately 0.72 per million cases per year in the USA 1 . The reason for ACC is largely caused by the TP53 mutations, which account for 50%-80% of children with ACC 2 . Thus, TP53 germline testing is recommended for patients with ACC 3 . Most ACC patients showed signs of hormone excess, and other patients indicate nonspeci c symptoms caused by the tumor growth including the abdominal pain, early satiety or unrelated medical issues 4 . Recently, there are a couple of new modes of treatment such as receptors or enzymes 5 .
Unfortunately, these medical trials do not meet the patients' needs due to various side effects.
Ptch1 was detected in various cancers such as lung cancers, colorectal cancers, and breast cancers 6 .
There were signi cant associations between Ptch1 and Gli1 expression with large tumor size 7 . Moreover, the mediation of Smo activation by Ptch1 is changed in several cancers. Ptch1 inhibits Smo substoichiometrically to control the progression of cancers 8 . Ptch1 contains a GXXXD motif that is highly conserved in the resistance-nodulation-division family, and changes in GXXXD motif are essential for the activity of oncogene PTC-3 9 . Thus, Ptch1 may be a prognostic marker for high-risk cancer patients.
In our study, we analyzed the impact of Ptch1 on ACC by using the RNA-seq data. We gured out a number of DEGs and signi cant signaling pathways. We also performed the gene enrichment and created the protein-protein interaction (PPI) network to obtain the interacting signaling map and key molecules.
These key genes and pathways in our study may provide novel insights for the treatment of ACC.

Data resources
Gene dataset GSE189424 was downloaded from the GEO database. The data was produced by the Illumina NextSeq 500 (Homo sapiens) (Functional Genomics Platform of Nice-Sophia-Antipolis, 660 route des lucioles, Valbonne -Sophia-Antipolis, France). The analyzed dataset includes three controls and three Ptch1 overexpression H295R cell lines.

Data acquisition and processing
The data were organized and conducted by the R package as previously described [10][11][12][13] . We used a classical t-test to identify DEGs with P< 0.01 and fold change ≥1.5 as being statistically signi cant.
The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) KEGG and GO analyses were conducted by the R package (ClusterPro ler) and Reactome. P<0.05 was considered statistically signi cant.

Protein-protein interaction (PPI) networks
The Molecular Complex Detection (MCODE) was used to create the PPI networks. The signi cant modules were produced from constructed PPI networks and String networks. The biological processes analyses were performed by using Reactome (https://reactome.org/), and P<0.05 was considered signi cant.

Identi cation of DEGs in ACC cells after overexpression of Ptch1
To determine the effects of Ptch1 on ACC, we analyzed the RNA-seq data from the ACC cells with the overexpression of Ptch1. A total of 1160 genes were identi ed with the threshold of P < 0.01. The top upand down-regulated genes were indicated by the heatmap and volcano plot ( Figure 1). The top ten DEGs were listed in Table 1.

PPI network analysis
To determine the relationship among the DEGs, we create the PPI network by using 867 nodes and 2328 edges (Combined score > 0.2 as a cutoff, Cytoscope software). Table 2 showed the top ten genes with the highest scores. The top two signi cant clusters were indicated in Figure 3. We further analyzed the PPI and DEGs with Reactome map ( Figure 4) and identi ed the top ten functional processes including "Response of EIF2AK1 (HRI) to heme de ciency", "Negative regulation of activity of TFAP2 (AP-2) family transcription factors", "Acyl chain remodelling of PG", "Ligand-receptor interactions", "Dissolution of Fibrin Clot", "Defective CHST3 causes SEDCJD", "Collagen degradation", "RUNX3 regulates RUNX1-mediated transcription", "CHL1 interactions", and "Acyl chain remodelling of PS" (Supplemental Table S1).

Discussion
Ptch1 is the most important Hh signaling regulator in cancers such as colorectal cancer, but the potential relationships between Ptch1 and patients' outcomes are still not clear 14 . Therefore, we herein use the data from the renal cancer cells with the overexpression of Ptch1 to assess the functions of Ptch1, thereby exploring the possible anti-cancer drugs.
By analyzing the KEGG and GO enrichment data, we found the "Calcium signaling pathway" and "Pathogenic Escherichia coli infection" were the key signaling pathways in Ptch1-overexpressed cancer cells. Yingying Hong et al found that Ptch1 siRNA decreases the SPARC levels, which affects the calcium metabolism 15 . Wu-Bo Li et al found that PTCH1 protein is a critical target for regulating the in uenza virus infection. Moreover, PTCH1 was discovered to have association with decreased morbidity during the in uenza infection 16 .
Besides the biological signaling, we also identi ed ten interacting molecules that were affected by the overexpression of Ptch1 in renal cancer cells. Sakae Konishi et al found that C-reactive protein/ALB ratio is a predictive marker for prognosis in cancer patients 17 . Keita Tamura et al also found the utility of the albumin can be considered as an objective prognostication tool to validate the metastatic cell carcinoma patients receiving second-line axitinib 18 . The activation of STAT3 can mediate multiple gene functions such as cell proliferation, differentiation, and apoptosis. Moreover, the inhibition of STAT3 was considered as an important therapy for cancer 19 . Circadian clocks regulate several downstream gene expressions through the transcriptional level to further mediate the cell functions such as proliferation, differentiation, apoptosis, cell death, and metabolism 20-31 . Zhenghui Tang et al found that STAT3 can inhibit the CRY2 expression through the CLOCK/BMAL1/P300 signaling 32 . Neil J Manimala et al found that FOS is a cellular proto-oncogene that increases the genes involved in proliferation and cancer formation 33 . Takuma Yotsumoto et al found that NRXN1 is a novel drug target for cancers such as lung cancer 34 . Qiongzhen Huang et al found that SNAP25 can inhibit the glioma progression through mediating synapse plasticity 35  In summary, our study found a strong relationship between Ptch1 and adrenocortical cancer. The Calcium signaling pathway and Pathogenic infection are the major affected processes in the Ptch1 regulated adrenocortical cancer. Based on these ndings, our study provides valuable insights for the diagnosis and treatment of adrenocortical cancer.

Funding
This work was not supported by any funding.

Declarations of interest
There is no con ict of interest to declare. reactive protein/albumin ratio is a predictive factor for prognosis in patients with metastatic renal cell carcinoma. Int J Urol 2019, 26:992-8.   The PPI network analyses of DEGs in ACC cells after overexpression of Ptch1 The cluster (A) and cluster (B) were constructed by MCODE.

Figure 4
Reactome map representation of the signi cant biological processes in ACC cells after overexpression of Ptch1 (yellow)

Supplementary Files
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