Data of two public pan-cancer cohort (TCGA Pan-Cancer and TCGA TARGET GTEx) were downloaded from UCSC platform (12–14). Specifically, data were selected by removing samples with an expression level of 0 and cancers with less than 3 samples in a single cancer type. A Log₂ (x+1) transformation was performed on the transcriptome expression values. The GSE14520 dataset was downloaded from GEO. The data of external cohort were collected from a local hospital, which is approved by the First Affiliated Hospital of Wenzhou Medical University (KY2023-198).

Samples with incomplete survival information and clinical information were excluded. Four types of clinical outcomes (overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI)) were used to assess the prognostic value of ANKRD27 in different cancer types (15). The `coxph` function from the R package ‘survival’ was used in Cox regression analysis (16). The Kaplan-Meier survival curve was utilized to analyze the prognostic differences between HCC patients with high- and low- ANKRD27 expression. The Log-rank test was utilized for statistical assessment to attain significance in prognosis.

Firstly, ANKRD27, a set of 60 genes associated with the immune checkpoint pathway (17), 150 genes related to immune pathways (18), and 44 marker genes for RNA modifications (19) were gathered from a dataset of pan-cancer (20). Then, the stromal scores and the relationship between genes and immune infiltration scores in individual tumors were calculated via “ESTIMATE” and “psych” R packages, respectively (21–23). TIMER 2.0 database provides public immune cell infiltration data for cancers and the infiltration scores of B cell, T cell CD4, T cell CD8, Neutrophil, Macrophage, and DC were measured using the R package”IOBR” (24, 25). The relation between ANKRD27 expression and genes related to immunostimulators, immunoinhibitors, chemokines, chemokine receptors, and MHC was analyzed using the Spearman correlation analysis in R software.

According to the median value of ANKRD27 expression, the patients with HCC were divided into two groups (high- and low-ANKRD27 expression groups). The prognostic differences between the two groups were analyzed via R package “survival”, and the significance of the prognostic differences between the two groups was assessed using the Log-rank test. The R package ‘pROC’ was used to conduct Receiver Operating Characteristic (ROC) analysis (26).

Differentially expressed genes (DEGs) between high- and low-ANKRD27 expression groups were identified by R package “limma” (27) following the criteria: p < 0.05 and |log2-fold change (FC)| > 1.5. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were conducted via R package “clusterProfiler” (28). GSEA analysis was performed with GSEA software (29).

Predicted the chemotherapeutic response for each sample based on the largest publicly available pharmacogenomics database (the Genomics of Drug Sensitivity in Cancer, GDSC) (30). The prediction was implemented by R package “oncoPredict” (31).

HCC cell lines (Huh-7 and Hep-G2) and normal hepatic cell line (LO2) were cultured with mediums in 5% CO₂ at 37°C. The cell lines were obtained from the Servicebio company. Total mRNA was extracted with Trizol reagent, followed by reverse transcription into cDNA with Revert Aid First Strand cDNA Synthesis Kit. SYBR Green Master Mix was applied to conduct qRT-PCR, and the relative mRNA levels were commutated via the 2^-ΔΔCT method with GAPDH as an internal reference. The primer sequences of ANKRD27 and GAPDH are shown in Supplementary Table S1 .

The cells were washed in PBS and lysed with RIPA buffer supplemented with a protease inhibitor cocktail. The BCA protein assay kit quantified the protein concentration. Proteins were separated using SDS-PAGE gels and subsequently transferred to PVDF membranes. These membranes were subsequently blocked and subjected to overnight incubation with primary antibodies at 4°C. Following incubation with secondary antibodies, the protein bands were observed and measured using the chemiluminescence detection system and ImageJ software, respectively, with GAPDH serving as the reference standard.

ANKRD27-targeted specific small interfering RNA (si-ANKRD27) was synthesized by Genepharma (Suzhou, China). Briefly, cells (6 × 10⁴ cells/well) were added into 6-well plates, incubating at 37°C under 5% CO₂ conditions. Then, Huh-7 cells were transfected with si-ANKRD27 to knock down ANKRD27 expression following the manufacturer’s protocol. The sequences of si-ANKRD27 are listed in Supplementary Table S2 .

ANKRD27-knockdown Huh-7 cells were seeded in 96-well culture plates (2 × 10³ cells per well). The absorbance at 450 nm was measured daily for three consecutive days using the CCK-8 kit. Transwell chambers were placed into a 24-well plate to detect the invasion ability of the Huh-7 cells with or without si-ANKRD27 transfection. For the wound healing assay, 5 × 10⁴ cells were seeded onto 6-well plates at 48 h after RNA transfection. After reaching 90% - 95% cell fusion, the layer was scratched with a 1000 μl pipette tip. Images were captured using microscopy at 0h and 24h after wounding. All assays were conducted independently in triplicate.

The Kruskal-Wallis test was used to assess the gene expression in different tumor tissues. The Wilcoxon rank-sum test was used to compare gene expression between normal and tumor tissues. For comparison analysis, we employed unpaired Student’s t-test and a one-way analysis. Discrepancies in genes mutation frequency across samples was analyzed by the chi-square test. R software or GraphPad Prism was applied in the process of statistical analyses, with significance set at p <0.05.

To elucidate the expression of ANKRD27 from a pan-cancer perspective, pan-cancer data were collected, encompassing the data derived from the TCGA and GTEx databases. According to the data from TCGA, it was demonstrated that ANKRD27 expression was increased in twelve different cancer types, including LIHC, COAD, ESCA, and others, while significantly lower in nine cancer types, encompassing GBM, LUAD, KIRC, and others ( Figure 1A ). Further, the GTEx database has been introduced to expand the number of normal samples. As shown in Figure 1B , ANKRD27 was aberrantly expressed in most cancers (eighteen cancer types), including LIHC, LAML, STAD, and others.

To gain insight into the prognostic value of ANKRD27, four types of clinical outcomes (OS, DSS, DFI, and PFI) were analyzed. As shown in Figure 2A , heightened ANKRD27 expression emerged as a prognostic risk factor among patients afflicted with LGG, LAML, LIHC, BRCA, MESO, and ACC. Further, a prognostic analysis of DSS substantiated a significant correlation between ANKRD27 expression and five distinct tumor types, namely LGG, LUSC, MESO, LIHC, and ACC ( Figure 2B ). Regarding DFI, it was found that heightened ANKRD27 expression may exert a risk factor among patients diagnosed with CESC, LUSC, and LIHC ( Figure 2C ). Additionally, PFI prognostic analysis indicated that high expression of ANKRD27 was suggestive of a worse outcome for patients afflicted with LGG, LIHC, LUSC, ACC, CESC, and SKCM ( Figure 2D ).

In order to gain an in-depth understanding of the impact of ANKRD27 on the tumor microenvironment (TME), we conducted an investigation to examine the correlation between ANKRD27 and the extent of immune traits such as immune cell infiltration, immune checkpoints, immune modulation, and stromal score across diverse cancer types. ANKRD27 exhibited a significant negative correlation with the extent of immune cell infiltration in malignancies such as SARC, LUSC, ESCA, and UCSC, which implied that ANKRD27 might be involved in developing an immunosuppressive microenvironment in cancers ( Figure 3 ). Additionally, it was illustrated that ANKRD27 expression showed a positive correlation with the level of inhibitory immune checkpoints, such as CD274, PDCD1, CTLA4, and HAVCR2, across various types of cancer ( Figure 4 ). According to the analysis of stromal scores, ANKRD27 expression in GBM, SARC, LUSC, SKCM-P, BRCA, and others was significantly negatively correlated with immune scores ( Supplementary Figure S1 ). Additionally, ANKRD27 expression was significantly linked to the levels of various genes related to immunostimulators, immunoinhibitors, chemokines, chemokine receptors, and MHC in a wide range of cancer types ( Supplementary Figure S2 ).

Gene expression may be impacted by epigenetics, thus, the correlation between RNA modification and ANKRD27 were explored. Herein, three modification patterns were analyzed, including m1A, m5C, and m6A. Supplementary Figure S3 showed a strong positive correlation between ANKRD27 and the expressions of different RNA modification-related genes in pan-cancer.

To assess the role of ANKRD27 in HCC development, we first estimated the expression levels of ANKRD27. In the TCGA and GSE14520 cohorts, there was a high expression of ANKRD27 in TCGA and GSE14520 cohorts ( Figures 5A, B ). Further, the hepatic carcinoma cell lines, Huh-7 and Hep-G2, were utilized to assess the expression levels of ANKRD27, with the LO2 (normal hepatic cell line) serving as a control. The upregulated expression of ANKRD27 was found in Hun-7 and Hep-G2 cell lines compared to LO2 ( Figure 5C ). The results of ROC curve (AUC value = 0.927) suggested the favorable predictive accuracy of ANKRD27 in HCC ( Figure 5D ). Notably, patients exhibiting heightened expression of ANKRD27 demonstrated a significantly diminished OS in comparison to those with lower ANKRD27 expression levels ( Figure 5E ). Additionally, in external cohort and GSE14520 cohort, patients with high ANKRD27 expression showed poorer survival probability as well ( Supplementary Figures S4A, C ). In external cohort, the time-dependent ROC analysis exhibited AUC values of 0.794, 0.614, and 0.636 at 1, 2, and 3 years, respectively ( Supplementary Figure S4B ). In GSE14520 cohort, the AUC values of 1, 2, and 3 years were 0.664, 0.664, and 0.672, respectively ( Supplementary Figure S4D ). The above findings suggested the favorable predictive accuracy of ANKRD27.

Next, to evaluate the potential of ANKRD27 in clinical application, we analyzed the correlation between ANKRD27 and different clinicopathological features (age, sex, TNM stage, histological grade, and pathological stage). The research findings demonstrated that HCC patients with high expression of ANKRD27 exhibited elevated pathological stage, histological grade, and TNM stage compared to the control group ( Figures 6A, B ; Supplementary Figure S5 ). Univariate Cox regression analysis unveiled that ANKRD27 was a prognostic indicator for HCC ( Figure 6C ). Moreover, for patients with HCC, ANKRD27 was identified as an independent risk factor by multivariate Cox regression analysis ( Figure 6D ). These findings underscored the potential of ANKRD27 as a prognostic factor for patients with HCC.

Analysis of somatic mutations showed that high expression of ANKRD27 may induce high-frequency mutations in genes such as TP53, PREX2, and RPS6KA3 ( Figure 7A ). The DEGs were used for GO and KEGG functional enrichment analyses. Remarkably, HCC patients with high ANKRD27 expression exhibited a significant enrichment of cancer-related gene sets. GO enrichment analysis revealed that high expression of ANKRD27 enriched in chromosome segregation, spindle, and protein serine/threonine kinase activity ( Figure 7B ). For KEGG analysis, the endocytosis and cell cycle pathways were enriched ( Figure 7C ). The GSEA analysis was further performed. Within the Hallmark gene set, the Wnt/β-Catenin pathway and the G2M_checkpoint pathway was significantly enriched in high-ANKRD27 expression groups ( Figure 7D ). In the KEGG gene set, the homologous recombination and the DNA replication pathway were significantly enriched ( Figure 7E ).

Immunotherapy targeting immune checkpoints plays a vital role in the treatment of cancer (32). Thus, we investigated the correlation between ANKRD27 and immune checkpoint molecules. It was found that CD274, CTLA4, HAVCR2, PDCD1 and TIGIT was significantly increased in the high-ANKRD27 expression group ( Figure 8A ). There were positive correlations between ANKRD27 and CD274, CTLA4, HAVCR2, PDCD1 as well as TIGIT in TCGA-HCC cohort and external cohort ( Figure 8B ; Supplementary Figure S6A ). Furthermore, it was found that the knockdown of ANKRD27 in HCC cells led to a decrease in the expression levels of multiple immune checkpoints ( Supplementary Figure S6B ). These findings suggested that increased ANKRD27 expression may enhance immune escape in HCC.

Rapamycin (33), Cisplatin (34), Doxorubicin (35), Sorafenib (36), Roscovitine (37), and Mitomycin (38) are common chemotherapeutic drugs for patients with HCC. As shown in Figures 8C-F , compared to the patients with low ANKRD27 expression, individuals within the high ANKRD27 expression exhibited lower IC50 concentrations of Rapamycin, Cisplatin, Doxorubicin, and Sorafenib. It indicated that patients with elevated ANKRD27 expression may exhibit heightened sensitivity to a range of therapeutic agents, including Rapamycin, Cisplatin, Doxorubicin, and Sorafenib. By contrast, HCC patients with high ANKRD27 expression presented drug resistance on Roscovitine treatment ( Figure 8G ). No notable disparity in drug sensitivity to Mitomycin was observed between the groups characterized by high and low expression of ANKRD27 ( Figure 8H ).

Furthermore, the capabilities of HCC cells in proliferation, migration, invasion were assessed after ANKRD27 knockdown. Two types of si-RNA targeting ANKRD27 (si-ANKRD27#1 and si-ANKRD27#2) were synthesised. Based on the efficiency of knockdown, si-ANKRD27#2 was selected ( Figure 9A ). ANKRD27 knockdown exerted an inhibitory effect on the proliferative capacity of HCC cells, as evidenced by the CCK-8 assay ( Figure 9B ). Wound healing assay demonstrated that ANKRD27 knockdown attenuated the migratory ability of HCC cells ( Figure 9C ). Additionally, the transwell assay demonstrated that ANKRD27 knockdown significantly reduced the number of cells passing through the wells, suggesting that ANKRD27 knockdown impairs the invasive ability of HCC cells ( Figure 9D ). Thus, the negative effect of ANKRD27 knockdown on HCC cell proliferation, migration, and invasion was confirmed in vitro.