Pan-cancer analysis from multi-omics data reveals AAMP as an unfavourable prognostic marker

Cancer is a major cause of death affecting human health worldwide. There are an estimated 19.3 million new cancer cases and almost 10.0 million cancer deaths occurred in 2020 globally [1]. Since the occurrence and development of tumors may be accompanied by different gene alterations, it is an important problem to find biomarkers for the diagnosis of different tumors. Pan-cancer research is to analyze multiple aspects of a large number of tumors and examine the differences in genes in different tumor types, so as to have a fuller understanding of tumors and find therapeutic and diagnostic targets for a variety of tumors.

Angio-associated migratory cell protein (AAMP) was first discovered by Beckner when they screened cell surface proteins related to cell motility in melanoma cells [2]. It belonged to the immunoglobulin superfamily and had homologous domains with cell adhesion molecule proteins NCAM, LFA-2, PECAM, etc. The structural characteristics of AAMP protein suggested that it may be involved in cell adhesion and migration. Subsequently, it was found that AAMP was involved in cancer occurrence and development. For example, AAMP could accelerate the adhesion and proliferation of breast cancer cells, and high AAMP expression had a worse prognosis for breast cancer patients [3, 4]. AAMP interacted with EGFR to enhance the proliferation and drug resistance of non-small cell lung cancer cells [5]. The interaction between AAMP and CDC42 could accelerate non-small cell lung cancer cells' metastasis [6]. However, there are few studies on the AAMP gene expression pattern and latent function in pan-cancer.

To study the latency effect of AAMP in pan-cancer, we analyzed the transcription level of AAMP and its relationship with clinical pathology from multiple public databases. Then, we conducted bioinformatics analysis to investigate the biological function and prognostic significance of AAMP in pan-cancer.

AAMP is a member of the immunoglobulin superfamily and is widely distributed in various types of cells. It is essential in transcriptional activation, cell cycle regulation, protein–protein interaction, and signal transduction [19‐21]. AAMP is expressed in a variety of cell types, including endothelial cells, aortic smooth muscle cells, dermal fibroblasts, renal proximal tubular cells, glomerular mesangial cells, human breast cancer cells, human melanoma cells and prostate cancer cells [22‐24]. Recent studies have shown that AAMP mainly locates in the cytoplasm and membrane of vascular endothelial cells, affecting the angiogenesis, diffusion, migration, and cytoskeleton remodeling processes of endothelial cells [25, 26]. In addition, it has been reported that AAMP is abnormally up-regulated in metastatic CRC and boosts the occurrence of colorectal cancer by inhibiting SMURF2-mediated RhoA liquefaction and degradation [27]. Furthermore, AAMP is highly expressed in invasive gastrointestinal and breast carcinoma cells and is a marker of poor prognosis [4, 28]. In addition, AAMP plays a positive role in angiogenesis and is regulated by Astrocytes in coculture [29]. These results showed that AAMP is vital in cancer occurrence and progression.

Our study explored AAMP expression, prognostic value, gene alteration, TMB, and MSI in pan-cancer through multiple databases. AAMP had high expression in 18 kinds of tumors, while AAMP had low expression in four tumors. The highly expressed AAMP had inferior OS, DSS, and PFI in ACC and LIHC. We used cBioPortal to study AAMP gene alteration in pan-cancer. In UCEC, AAMP had the highest gene alteration frequency, including mutation 1.89%, amplification 1.32%, and deep deletion 0.19%. TMB and MSI are considered as two biomarkers of response to immunotherapy. Tumors with high TMB and high MSI are sensitive to immunotherapy response [30]. Therefore, we study the correlation between AAMP and TMB, MSI in pan-cancer. AAMP expression was positively correlated with TMB for ACC, ESCA, LUAD, STAD, LUSC, THYM, and PAAD while negatively correlated for KIRP, THCA, and UCS. Regarding MSI, AAMP had a positive relation to MSI in ESCA, STAD, KIRC, LUSC, LIHC, and UVM, and negative relation in THCA. AAMP correlated with TMB and MSI in ESCA, STAD, and LUSC. It can be speculated that in ESCA, STAD, and LUSC, tumors with high expression of AAMP have better responses to immunotherapy.

We focused on LIHC after screening and discussed the AAMP expression, prognosis, clinical features, and immunity. AAMP was over-expressed at the mRNA expression level from the TCGA database and protein expression level from CPTAC. The immunohistochemical staining in the HPA database also confirmed AAMP's high expression in LIHC. Moreover, AAMP overexpression was correlated with histological grade and pathological stage of LIHC. AAMP had higher expression in the higher histological grade and advanced pathological stage. Kaplan–Meier survival curve demonstrated that AAMP's high expression was related to unfavorable OS, DSS, and PFI. The univariate and multivariate analysis results showed that AAMP was an independent adverse prognostic factor for LIHC patients. Furthermore, ROC curve analysis demonstrated that OS of 1, 3 and 5 years was more than 0.6. We also confirmed the high expression of AAMP in LIHC in another different database. The results showed that 1, 2 and 3 year OS was 0.662, 0.737, and 0.726 by ROC curve analysis. These findings suggested that AAMP expression had an excellent prediction ability in TCGA and ICGC and could predict LIHC prognosis, supporting AAMP expression as a new predictor of survival for LIHC.

TME is essential in tumor development and is closely related to patient outcomes [31]. In recent years, increasing studies have confirmed that different TME of patients is vital in mediating late metastasis, immune escape, and immunosuppression. We used the ssGSEA algorithm to explore the association between AAMP and immune cell infiltration in LIHC. With the increase of AAMP expression, the number of DC, Cytotoxic cells, pDC, neutrophils, B cells, Th17 cells, Treg, mast cells, eosinophils, iDC, Th1 cells, Tgd, T cells, NK CD56 dim cells decreased, and the number of T helper cells, Th2 cells, and Tcm increased. Therefore, changes in AAMP expression lead to changes in Th1/Th2. The immunosuppressive state will affect the body's anti-tumor immunity and ultimately result in tumors [32]. Immune and stromal cells, as the non-tumor components of TME, have gradually attracted the attention of researchers due to their essential roles in tumor genesis, metastasis, drug resistance, and prognosis [33, 34]. We found that the stromal score and immune score of AAMP over-expression were lower than AAMP low-expression, indicating that AAMP affected the occurrence and development of LIHC through immunocyte infiltration. Recently, the treatment of advanced malignant patients has been revolutionized by the introduction of immune checkpoint inhibitors [35]. Moreover, common checkpoints included CD274, CTLA4, HAVCR2, LAG3, PDCD1, PDCD1LG2, TIGIT, and SIGLEC15. The expression of CD274, CTLA4, HAVCR2, LAG3, PDCD1, and TIGIT in the AAMP high-expression group was higher than AAMP low expression group, which showed that AAMP was the vital immunotherapeutic target in LIHC. TIDE is considered an indicator of cancer's immune intelligence response rate. The patients with higher TIDE scores have lower immune responses. In our study, the patients with increased expression of AAMP have low immune response rates and cannot benefit from immune checkpoint inhibitors. This may be because high AAMP expression induces a decrease in B and T cells, while low lymphocyte counts indicate a poor host anti-tumor immune response [36].

To further investigate the biological process of AAMP in LIHC, we analyzed GSEA in TCGA and ICGC databases. Interestingly, the highly expressed AAMP in the two databases is mainly concentrated in cell cycle, DNA replication, and mismatch repair, indicating that AAMP causes liver cancer through the above pathways.

We discussed the expression pattern and prognostic significance of AAMP in pan-cancer and LIHC from a bioinformatics perspective, providing a basis for further research on the mechanism of AAMP for LIHC. However, our study had some limitations. We studied AAMP expression in pan-cancer and LIHC only by bioinformatics. Furthermore, many experiments to explore the mechanism of AAMP for LIHC will help developing a more accurate prognosis model for patients and providing a basis for more personalized treatment.

AAMP is a better molecular marker with diagnostic and prognostic value in pan-cancer, especially in LIHC. High expression of AAMP is significantly associated with poor prognosis of LIHC and is considered an independent prognostic marker by Cox regression. This study provides a theoretical basis for more comprehensive analysis of the clinical application of this molecule in tumor therapy in the future.