Comprehensive pan-cancer analysis identifies FHL2 associated with poor prognosis in lung adenocarcinoma

Abstract

Background: The FHL family (four-and-a-half-LIM-only protein family) contains five multifunctional proteins (FHL1-5) that are involved in cell survival, transcriptional regulation, and signal transduction. Among these proteins, FHL2 is one of the most reported members in tumors, which is differentially expressed in numerous tumors. However, no systematic pan-cancer analysis of FHL2 has been performed so far.

Methods: We obtained The Cancer Genome Atlas (TCGA) expression profiles and clinical data from Xena database and the Tumor Immune Estimation Resource (TIMER) database. Gene expression, prognosis, mRNA modification, and immune infiltration of FHL2 in pan-cancer were analyzed. Functional analysis validated the potential mechanism of FHL2 in lung adenocarcinoma (LUAD).

Results: FHL2 is differentially expressed in a wide range of tumors and has prognostic value. Digging into the immune landscape of FHL2, we found that FHL2 is significantly associated with tumor-associated fibroblasts. Furthermore, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) suggested that FHL2 may be involved in epithelial-mesenchymal transition (EMT)-associated pathways such as NF-KB and TGF-β in LUAD.

Conclusions: Our comprehensive bioinformatics analysis identified mRNA level expression of FHL2 correlates with prognosis in different cancers. This study may help to more fully explore the role of FHL2 in tumor progression and metastasis.

Keywords: FHL2; biomarker; immune infiltration; pan-cancer; prognosis.

Figure 1

Expression landscape of FHL2 in a wide range of cancers. (A) Results from the TIMER2.0 database show differences in FHL2 expression between normal and tumor tissues in a variety of cancers. (B) Paired test of FHL2 expression in normal and tumor tissues in multiple cancers. (C) Mean expression of FHL2 in normal tissues of 24 cancers and tumor tissues of 33 cancers. *, P<0.05; **, P<0.01, ***, P<0.001. TCGA, The Cancer Genome Atlas; TPM, transcripts per kilobase of exon model per million mapped reads; ns, no sense.

Figure 2

Molecular subtypes of fourteen types of human tumors based on FHL2 expression(log2CPM). All molecular subtypes are based on the TISIDB database (http://cis.hku.hk/TISIDB/). The types of human tumors including ACC, BRCA, COAD, ESCA, GBM, HNSC, LGG, LIHC, LUSC, OV, PCPG, READ, STAD and UCEC. ACC, adrenocortical carcinoma; BRCA, breast invasive carcinoma; COAD, colon adenocarcinoma; ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; HNSC, head and neck squamous cell carcinoma; LGG, Brain Lower Grade Glioma; LIHC, liver hepatocellular carcinoma; LUSC, lung squamous cell carcinoma; OV, ovarian serous cystadenocarcinoma; PCPG, pheochromocytoma and paraganglioma; READ, rectum adenocarcinoma; STAD, stomach adenocarcinoma; UCEC, uterine corpus endometrial carcinoma; CPM, counts per million.

Figure 3

Correlation between FHL2 expression and overall survival of cancer patients. (A) Analysis of Hazard Ratios of FHL2 in different cancers based on GEPIA2 database and Kaplan-Meier survival curves of overall survival of patients with different expression groups according to FHL2 in ACC, CESC, HNSC, LAML, LGG, LUAD and THCA. (B) Kaplan-Meier survival curves of overall survival in patients with different expression groups according to FHL2 in CESC, HNSC, KIRC, LUAD, and THCA were analyzed based on the Kaplan-Meier Plotter database. ACC, adrenocortical carcinoma; CESC, cervical squamous cell carcinoma and endocervical adenocarcinoma; HNSC, head and neck squamous cell carcinoma; LAML, Acute Myeloid Leukemia; LGG, Brain Lower Grade Glioma; LUAD, lung adenocarcinoma; THCA, thyroid carcinoma; BLCA, Bladder Urothelial Carcinoma; BRCA, breast invasive carcinoma; COAD, colon adenocarcinoma; DLBC, lymphoma diffuse large b-cell lymphoma; ESCA, esophageal carcinoma; GBM, glioblastoma multiforme; KICH, Kidney Chromophobe; KIRC, kidney renal clear cell carcinoma; KIRP, kidney renal papillary cell carcinoma; LIHC, liver hepatocellular carcinoma; LUSC, lung squamous cell carcinoma; MESO, mesothelioma; OV, ovarian serous cystadenocarcinoma; PAAD, pancreatic adenocarcinoma; PCPG, pheochromocytoma and paraganglioma; PRAD, prostate adenocarcinoma; READ, rectum adenocarcinoma; SARC, sarcoma; SKCM, Skin Cutaneous Melanoma; STAD, stomach adenocarcinoma; TGCT, Testicular Germ Cell Tumors; THYM, thymoma; UCEC, Uterine Corpus Endometrial Carcinoma; UCS, Uterine Carcinosarcoma; UVM, Uveal Melanoma.

Figure 4

Univariate analysis of FHL2 in 33 cancers using TCGA database. In the forest plot of the hazard ratio. *, P<0.05; **, P<0.01. TCGA, The Cancer Genome Atlas; LUAD, lung adenocarcinoma.

Figure 5

Association of FHL2 expression with the tumor microenvironment. (A) Distinguishing different immune subtypes of pan-cancer according to the correlation between FHL2 expression and immune function. C1 (wound healing); C2 (IFN-gamma dominant); C3 (inflammatory); C4 (lymphocyte depleted); C5 (immunologically quiet); C6 (TGF-β dominant) (B) Correlation between the expression of FHL2 and the cells in the tumor microenvironment analyzed based on EPIC algorithm. *, P<0.05; **, P<0.01; ***, P<0.001.****, P<0.0001. In the red box, we found a strong correlation between FHL2 expression and infiltration of CAFs. CPM, counts per million; TCGA, The Cancer Genome Atlas; BRCA, breast invasive carcinoma; HNSC, head and Neck squamous cell carcinoma; KICH, Kidney Chromophobe; KIRC, kidney renal clear cell carcinoma; LGG, Brain Lower Grade Glioma; LIHC, liver hepatocellular carcinoma; LUAD, lung adenocarcinoma; CAFs, cancer associated fibroblasts; NK, natural killer cell.

Figure 6

Association between FHL2 expression and fibroblast infiltration. (A) Significant correlation between FHL2 expression and fibroblast infiltration in a variety of cancers based on EPIC, MCPCounter, and TIDE algorithms, P<0.05. (B) Scatter plot showing the correlation between FHL2 expression and fibroblasts in 18 cancers calculated by TIDE algorithm. TPM, transcripts per million.

Figure 7

Expression pattern and clinical relevance of FHL2 in LUAD. Volcano plot showing high expression of FHL2 in lung adenocarcinoma tumor tissues in (A) TCGA (B) GSE31210, and (C) GSE10072 datasets, log2FC >1, P.adjust <0.05 by multiple hypothesis tests. Relevance of FHL2 expression in normal and tumor tissues in (D) TCGA, (E) GSE31210 and (F) GSE10072 datasets. ***, P<0.001. Relevance of FHL2 expression to (G) Gender, (H) Age, (I) Pathological stage, (J) Tumor [T] stage, (K) Node [N] stage, (L) Metastasis [M] stage in LUAD. TPM, transcripts per kilobase of exon model per million mapped reads; LUAD, lung adenocarcinoma; TCGA, The Cancer Genome Atlas;

Figure 8

Immunohistochemical staining of FHL2 in normal and lung adenocarcinoma tumor tissues based on the HPA database. High protein levels of FHL2 in lung adenocarcinoma tumor tissues as revealed. Left, normal tissues; Right, Tumor tissues. Image available from https://www.proteinatlas.org/ENSG00000115641-FHL2/tissue/lung. Where version: 22.0 indicates the desired version of the atlas. Y/O, years old; NOS, non-specific; HPA, Human Protein Atlas.

Figure 9

Somatic mutations of FHL2 and the relationship with mutations in lung adenocarcinoma. (A) Somatic mutation loci of FHL2. (B) Mutation landscape of FHL2. *, alter/profiled =15/1,943. (C) Frequency of alteration of different types of mutations of FHL2 in lung adenocarcinoma. The effect of FHL2 mutation status on (D) overall survival, and (E) disease-free survival of lung cancer patients was examined using the cBioPortal database. (F) Gene mutation differences among different FHL2 expression levels in lung adenocarcinoma. MSKCC, Memorial Sloan Kettering Cancer Center; TCGA, The Cancer Genome Atlas; CPTAC, Clinical Proteomic Tumor Analysis Consortium; TSP, Tech Science Press; NPJ, Nature Press Journal; oncoSG, Genome Institute of Singapore.

Figure 10

Enrichment analysis based on differentially expressed genes among different expression levels of FHL2. (A) GO biological processes, (B) GO cellular components, (C) GO molecular functions; (D) KEGG functional enrichment analysis; (E) HALLMARK gene set, and (F) KEGG gene set was used for GSEA enrichment analysis of FHL2. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; GSEA, Gene Set Enrichment Analysis; NES, Normalized Enrichment Score.

Figure 11

Association of FHL2 with the EMT pathway. (A) Correlation of FHL2 expression with the expression of the genes in the EMT pathway. CDH2 (Cadherin 2), MMP2,3,9,11 (Matrix Metallopeptidase2,3,9,11), SNAI1 (Snail Family Transcriptional Repressor 1), SNAI2 (Snail Family Transcriptional Repressor 2), TWIST1 (Twist Family BHLH Transcription Factor 1), TWIST2 (Twist Family BHLH Transcription Factor 2), VIM (Vimentin), ZEB1 (Zinc Finger E-Box Binding Homeobox 1), the above genes encode proteins that are common EMT pathway protein markers. (B) Single-cell sequencing-based analysis of the correlation between FHL2 and tumor progression-related pathways in the CancerSEA database. *, P<0.05; **, P<0.01; ***, P<0.001. TPM, transcripts per kilobase of exon model per million mapped reads; EMT, epithelial-mesenchymal transition.