CAST as A Potential Oncogene from Machine Searching in Gastric Cancer Infiltrated with Macrophage and Associated with Lgr5

Affiliations: 1Divisiono f Gastroenterology and Hepatology, Department of Internal Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan 2Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan 3Department of Medical Education and Research, Kaohsiung Veterans General Hospital, Taiwan 4Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan 5Department of Emergency Medicine, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan 6Institute of Biotechnology and Chemical Engineering, I-Shou University, Kaohsiung, Taiwan 7Department of Recreation and Sports Management, Tajen University, Pingtung, Taiwan Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 20 August 2021 doi:10.20944/preprints202108.0418.v1


INTRODUCTION
Gastric cancer (GC) is one of the most important diseases worldwide. There are estimated to be more than 1 million newly diagnosed GC patients worldwide each year. GC is the fourth most common cancer and the second most common cause of death worldwide [1]. Globally, one in 33 men and one in 78 women will develop GC in their lifetime [2,3]. Since the diagnosis of GC is often advanced, the mortality rate is high. In 2018, 784,000 people died of GC worldwide, twice as many men as women, with East Asia, Eastern Europe, and South America being the regions of GC incidence and death [4].
Clinically, we can expect to see more cases of GC in the future due to the aging of the population. In recent years, we have even observed an increase in the incidence of GC in young people [5].
In GC genomics, approximately 10% of GC patients have familial genetic clusters, and about 1-3% of them have mutations [6]. Familial GC includes at least three major classifications: hereditary diffuse GC (HDGC), gastric adenocarcinoma and proximal gastric polyps and disease, and familial gastrointestinal cancers [7][8][9]. To explore the frontier of gastric carcinogenesis mechanism, recent studies had thought Lgr5 as an activator on the pathway of WNT signaling toward gastric adenocarcinoma cell proliferation. An overexpression of signature mark Lgr5 from the stem cell is derived from stomach, kidney, colon, hair follicle, and mammary gland [10]. Wu et al. found Lgr5 expression in the bottom of the normal gastric gland units, and revealed a differential expression in GC with varying differentiation.
Furthermore, Lgr5 and Bmi1 were identified as the same stem cell population.
CD133, CD26, CD44, and ALDH1 associated with Lgr5 may be functionally toward the GCs growth [11]. 6 Calpastatin (CAST) is usually discovered at the plasma membrane and surrounding the nucleus [12]. CAST inhibits the calpains, which can translocate into the nucleus, and further regulate the pathway of WNT/βcatenin pathway [13]. The single CAST gene can manufacture eight or more CAST polypeptides, weighing from 17 to 85 kDa, with the function of binding to calpain molecules and Ca2+ dependent. The CAST/calpain system regulates a variety of cellular processes, involving remodeling of cytoskeletal/membrane attachments, multi-signal transduction pathways, and cell apoptosis. CAST/calpain system also participated in numerous membrane fusion events, such as neural vesicle exocytosis and platelet aggregation [14]. Previously, CAST had been reported as a possible novel marker in GC development. Liu's study results revealed that calpastatin level decreased in GCs. Furthermore, the ratio of (CAPN1 x CAPN2)/(calpastatin x CaM) was thought as a potential index for GC diagnosis [15].
In recent years, tumor-associated macrophage (TAM) is associated with the tumor microenvironment, acting as a tumor-promoting and a tumorsuppressing character [16]. TAM is categorized into the anti-tumor M1 phenotype (classically activated state) and the pro-tumor M2 phenotype (alternatively activated state), reflecting the Th1-Th2 polarization of T cells [17]. TAM works in innate host defense and kills tumor cells. Meanwhile, TAM also has a critical regulatory role in epithelial mesenchymal transition, angiogenesis, immunosuppression, and hampering the efficacy of chemotherapy [18,19].
However, the characteristics of CAST associated with immunological response of macrophage and relevance to Lgr5 were still unaddressed. We aimed to explore the possible interaction of the above-mentioned characters.

MATERIALS AND METHODS
The Cancer Genome Atlas (TCGA) Program Analysis by Using Machine

Searching
The expression level of the CAST gene in various types of cancers was identified in the The Human Protein Atlas (THPA) database (https://www.proteinatlas.org/). We used the Python Selenium (Version 3.8) to automatically search the TCGA Database by entering different gene candidates, and we recorded all the candidate genes associated with the overall survival (OS) rate of GC. Then the most relevant genes were precisely selected, including CAST and WNT (P-value < 0.001).

Protein-Protein Interaction (PPI) Network from STRING
The STRING database (version 11.5) [20] is applied for searching for PPI scientists had interested in and worthy of investigation. Proteins relevant to the same topic could be linked by direct and indirect relationships and mapped to a weight network in STRING, containing 14094 organisms, 67.6 mio proteins, and > 20 bln interactions. Proteins are spotted as nodes and every two proteins is given as an edge and highlighted with a confidence score. Analogous functions among proteins will exhibit more if the confidence score is higher [21]. 8

Analysis 2 (GEPIA2) Datasets
We examined the mRNA level of CAST by comparing tumor and matched normal samples using the GEPIA2 database, which can provide cancer genomics data on the basis of TCGA, and the GTEx [22].

Human Protein Atlas (HPA) Appliances for Further Validation of CAST in Different Human Tissues
We used HPA, which is one of the most robust and comprehensive databases of protein and RNA in tissues and cells. HPA's goal of the Cell Atlas is to map the subcellular distribution of all human proteins over the course of a cell cycle in a canonical human cell. HPA includes over 85% of all human proteincoding genes data. Furthermore, both immunohistochemistry (IHC) scoring parameters and sub-cellular localization classifications will be purified to increase more cells types, organelles, and supply clinicians with bioinformatics about intra-organellar locations. HPA can help contribute to a deeper investigation for both basic and clinical research [23]. We used the transcriptomics and proteomics expressions to represent the character of CAST in different tumor tissues.

Survival Analysis from Kaplan-Meier (KM) Plotter
The cancer-survival information and CAST bioinformatics of the GC patients GSE15459 (http://kmplot.com/analysis/index.php?p=service&cancer=gastric) [24]. We also acquired KM survival plots, in which the number of cancer patients for a specific period is compared between subgroups with different gene expression statuses. We determined the hazard ratio (HR) and 95% confidence intervals (CI) and log-rank P-values. A P-value < 0.05 was considered statistically significant. macrophage, T cell, B cell, and NK cell. TIMER 2.0 can also analyze specific oncogene mutation groups, and genes were input for analysis of well-known oncogenic mutation in specific tumors [25][26][27]. The correlation between Lgr family, CAST, WNT family, and macrophage were surveyed, the data of which were adopted from the TCGA database. The results of surveyance were downloaded to show the outcome. The relationship between CAST gene and well-known immune infiltration in tumor were also analyzed through TIMER 2.0 for confirmation. A P-value < 0.05 was considered statistically significant.

Gene and Protein Networks Analysis
GeneMANIA (http://genemania.org/; accessed August 15, 2021, version 3.6.0) is a real-time multiple association network integration algorithms for predicting gene function [28]. The data could be extracted for gene-gene interactions (GGI) in our study. Regarding previous studies concerning the WNT family related to gastric cancer development, we surveyed the

Statistical Analysis
The results of the KM plotter and TIMER 2.0 are shown with hazard ratio (HR) and Cox P-values from a log-rank test. We evaluated the correlation of gene expression using Spearman's correlation and statistical significance.
Rho-value in determination of positive or negative correlation in protein/RNA expressions were applied.

CAST Expression in Different Tissues
We extracted the CAST RNA-sequencing expression level from the GEPIA2 database.  Table 1.

Validation of CAST expression in GC
To make more robust confidence in the association between CAST and GC.
We further mine the HPA revealing the cancer types are color-coded according to which type of normal organ the cancer originates from, including HPA036881, HPA036882, and CAB009491 from Figure 3A, Figure   3B, and Figure 3C

CAST-WNT2/WNT2B-Lgr5 Linkages toward Gastric Carcinogenesis
We input CAST, WNT2, WNT2B, and Lgr5, using GeneMANIA and found that CAST was linked to WNT family and Lgr family as shown in Figure 9.   Our research revealed CAST as a potential oncogene toward GC formation.
Previous studies seldom focused on this novel issue. Liu et al. [15] appointed that except for CAST, CAPN1, CAPN2, and CaM might also contribute to GC formation, which is partially compatible with our results. The Calpain system was also associated with colorectal adenocarcinoma and prostate cancer, which suggested that calpains might be an important character in tumorigenesis tumor progression [29,30]. Calpain system is relevant to human epidernal growth factor receptor 2 and E-cadherin in breast cancer [31,32].
Meanwhile, calpain-2 was proved to contribute to the promoter methylation of CRMP4 to repress the transcription, heading to the metastasis of prostate cancer by enhancing vascular endothelial growth factor C expression [33].
The mechanism of CAST resulting GC was still unclear. We tried to find the relevant gene expression or possible pathways. After databases mining, Lgr5 and CAST might regulate the GC formation via the same pathway-WNT family, especially WNT 2 and WNT 2B, as our novel findings in the GC formation signature. WNT/β-catenin pathway in gastric cancer showed an important feature in regulating proliferation, stem cell maintenance, and homeostasis in gastric mucosa [34,35]. More than 30% of GC in which activated WNT/β-catenin signaling can be found. The fundamental role of WNT/β-catenin signaling in the self-renewal of GC stem cells has been demonstrated [36][37][38]. WNT/β-catenin signaling paradox was also an issue recently, discussing WNT signaling hyperactivation by mutations in βcatenin destruction complex components or β-catenin itself contributes to tumorigenesis [39]. β-catenin can be further activated by additional layers of regulation, which represented as the complicated role of WNT signaling deregulation in cancer [40][41][42]. The double-sided function (tumorigenesis or tumor suppression) of WNT/β-catenin system was disclosed in our clinicopathological datasets survival follow-up.
Recently, TAM was discovered to be associated with WNT signaling in tumor microenvironment. Wu et al. [43] demonstrated that macrophages play a protumorigenic role in GC patients. The possible mechanism might be originated from tumor microenvironment related inflammation, matrix remodeling, angiogenesis, seeding at distant sites, intravasation, and tumor cell invasion [44]. The current studies also give scientists a clue that macrophages may play a helpful or harmful role in GC microenvironment.
Huang et al. also demonstrated that the heterogeneity of macrophages within the tumor is present at both macro-and micro-levels due to the gradient change of different markers [45]. In our study, the role macrophage infiltration in GC associated with CAST revealed the unsure character in GC formation and survival. We hypothesize that macrophage infiltration could manipulate the exact signaling pathway of GC carcinogenesis process. Maybe further in vitro researches should be launched to unblind the mechanism.
We had confidence in database mining for genes and macrophage relevant to GC on the basis of some characteristics such as high reproducibility, high convenience, and no need of inform and consent from patients. The analytic methodology of our article is very suitable to establish a precise/personalized evaluation of a molecular investigation of GC. Though we found a novel marker and immune infiltration correlated with GC, we had acknowledged some limitations in our study. First, though databases contained a lot of bioinformatics online, we still need to explore further experiments for external validation for the results. Second, the detailed mechanism of how these genes (CAST, WNT, and Lgr5) cause the carcinogenesis of GC was still a question mark. However, we could use databases to make preliminary reports of these genes, to facilitate the confidence of future novel GC carcinogenetic models.
Third, we need tissue sample confirmation due to the possible potential tumor purification error.

CONCLUSION
Our study explored that CAST was a signature oncogene in GCs. Moreover, the CAST gene in gastric carcinogenesis was regulated by macrophage in our OS analyses. The detailed mechanism of CAST gene related GCs formation was still investigated, probably associated with Lgr5-related pathways and WNT/β catenin cellular signaling.

Funding
There was no external funding.