Pan-cancer analysis reveals IGFL2 as a potential target for cancer prognosis and immunotherapy

Insulin-like growth factor like family member 2 (IGFL2) is a gene in the IGFL family, located on chromosome 19, whose role in cancer is unclear, and the aim of this study was to investigate

the relevance of IGFL2 expression, prognosis, immunity, and mutation in pan-cancer. Obtaining information from The Cancer Genome Atlas and The Genotype-Tissue Expression Project (GTEx)

databases for expression analysis and combining with The Gene Expression Profile Interaction Analysis database for prognostic aspects. Analysis of immune cell infiltration by TIMER and

CIBERSORT algorithms. Calculation of correlation of immune-related genes with IGFL2 expression and tumor mutational burden and microsatellite instability. Mutations and DNA methylation were

analyzed using the cBioPortal database and the UALCAN database, and functional enrichment was performed using Gene set enrichment analysis (GSEA). IGFL2 expression is significantly elevated

in tumor tissue and high expression has a worse prognosis in most cancers. In immune correlation analysis, it was associated with most immune cells and immune-related genes. In most cancers,

IGFL2 methylation is lower and the group with mutations in IGFL2 has a worse prognosis than the normal group. The GSEA analysis showed that IGFL2 was significantly enriched in signaling and

metabolism. IGFL2 may be involved in the development of many types of cancer, influencing the course of cancer with different biological functions. It may also be a biomarker for tumor

immunotherapy.

Cancer remains a disease with very high morbidity and mortality in epidemiological studies. In 2020, there will be 19.3 million cancer patients and more than 10 million deaths worldwide,

with breast cancer being the most common cancer and lung cancer having the highest mortality rate at 18 percent. 28.4 million people will have cancer by 20401. Tumor immunotherapy has been

shown to be effective in cancer treatment by using immune cells to eliminate tumor cells2.Therefore, predicting biomarkers and identifying tumor treatment targets are crucial in cancer

treatment. The human IGFL gene encodes a protein of approximately 100 amino acids and contains 11 conserved cysteine residues, including two CC motifs. This family consists of four genes and

two pseudogenes, IGFL1-IGFL4, IGFL1P1 and IGFL1P2, all clustered on chromosome 19 at 35 kb intervals, which have structural homology with the insulin-like growth factor (IGF) family3. The

IGF family of genes is a systemic growth factor and a major regulator of cell proliferation, differentiation and apoptosis 4. Its dysfunction or dysregulation may destabilize tissues and act

on target organs in an autocrine, paracrine and endocrine manner, while activating various intracellular signaling pathways to promote cell proliferation, transformation and inhibit

apoptosis, leading to the development of malignant tumors 5. IGF family members have been shown to play an important role in a variety of tumorigenesis, such as gastric cancer6, colorectal

cancer7, and lung cancer8.Among the relevant studies on the IGFL family, IGFL2 is particularly well represented and deserves analysis.Studies on IGFL2 have found that its expression is

upregulated in many cancers, and as a homolog of the IGF family, this pattern may be consistent with IGF family members. However, the mechanism of IGFL2 in various carcinogenesis is unclear

and there is a lack of correlation analysis of IGFL2. Herein, we have comprehensively analyzed the expression, prognosis, immunological and biological roles of IGFL2 in cancer based on TCGA

database data to explore the multifaceted relationship between IGFL2 and cancer.

The expression, clinical correlation, and mutation data for a total of 10,534 cases of 33 cancers from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database9, 10 were

obtained from the UCSC browser (http://xena.ucsc.edu/) for basic processing of raw data; and the normal tissue information was supplemented with gene data from The Genotype-Tissue Expression

Project (GTEx) (http://gtexportal.org) database11 for normal tissues. 33 cancer types were included: Adrenocortical carcinoma (ACC), Bladder Urothelial Carcinoma (BLCA), Breast invasive

carcinoma (BRCA), Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), Cholangiocarcinoma (CHOL), Colon adenocarcinoma (COAD), Lymphoid Neoplasm Diffuse Large B-cell

Lymphoma (DLBC), Esophageal carcinoma (ESCA), Glioblastoma multiforme (GBM), Head and Neck squamous cell carcinoma (HNSC), Kidney Chromophobe (KICH), Kidney renal clear cell carcinoma

(KIRC), Kidney renal papillary cell carcinoma (KIRP), Acute Myeloid Leukemia (LAML), Brain Lower Grade Glioma (LGG), Liver hepatocellular carcinoma (LIHC), Lung adenocarcinoma (LUAD), Lung

squamous cell carcinoma (LUSC), Mesothelioma (MESO), Ovarian serous cystadenocarcinoma (OV), Pancreatic adenocarcinoma (PAAD), Pheochromocytoma and Paraganglioma (PCPG), Prostate

adenocarcinoma (PRAD), Rectum adenocarcinoma (READ), Sarcoma (SARC), Skin Cutaneous Melanoma (SKCM), Stomach adenocarcinoma (STAD), Testicular Germ Cell Tumors (TGCT), Thyroid carcinoma

(THCA), Thymoma (THYM), Uterine Corpus Endometrial Carcinoma (UCEC), Uterine Carcinosarcoma (UCS), and Uveal Melanoma (UVM).

The expression of IGFL2 in pan-cancer was analyzed using the Timer2.0 (http://timer.cistrome.org/) online tool12 Since there is too little normal tissue in some cancers, the transcriptome

RNA-seq data of TCGA and GETx and normal tissue data were log2 transformed simultaneously to match the differential expression information between tumor and normal tissue. It was also

plotted with R software to determine the changes in IGFL2 expression in different cancer types. p