Identification of an autophagy-related prognostic signature and validation of WDR45 in colorectal cancer

Introduction

With more than 1.9 million new cases and 935,000 deaths in 2020, colorectal cancer (CRC) is the third most common cancer and the second leading cause of cancer-related death worldwide (1). Approximately 25% of CRC patients are diagnosed at a late stage, thereby missing the opportunity to undergo radical surgery, which significantly comprises their prognosis (2). Thus, efficient and specific biomarkers are urgently needed to be identified for the early diagnosis and prognostic prediction of CRC.

Autophagy is a self-protection mechanism in eukaryotic cells. Studies have shown that autophagy-related genes (ATGs) contribute to tumor progression (3,4). The aberrant expression of ATGs has been identified as a prognostic indicator in several cancers, including CRC. For example, ATG5 overexpression was shown to be correlated with survival in cervical cancer patients. Increased ATG5 expression was also shown to contribute to tumor progression and poor prognosis through the regulation of epithelial-mesenchymal transition (EMT) (5). The ATG5 protein was also observed to be highly expressed in CRC, and positively correlated with worse disease-free survival (DFS) and overall survival (OS) (6). Increased ATG10 expression was shown to be a strong predictor of prognosis in hepatocellular carcinoma (HCC), while the inhibition of ATG10 was shown to suppress tumor progression (7). Recently, ATG10 was shown to be overexpressed in several cancers, highlighting its potential as a biomarker and therapeutic target (8).

The molecular mechanisms by which autophagy regulates tumor progression have been explored. Zhang et al. identified ATIC, which promotes tumor progression by regulating autophagy through the AKT/FOXO3 pathway, as a novel prognostic biomarker in HCC (9). However, the inhibition of autophagy by Yes-associated protein (YAP) was reported to favor cell survival and promote the progression of CRC (10). Thus, further research needs to be conducted to examine the specific roles and molecular pathways through which autophagy regulates tumor progression in CRC.

Prognostic signatures based on ATGs have been proposed as potential biomarkers in various cancers. A signature comprising five ATGs (Beclin-1, LC3A/B, p62, ULK-1, and AMBRA-1) was analyzed in a cohort of Human Epidermal Growth Factor Receptor 2 (HER2) positive gastric cancer patients and was shown to serve as an independent prognostic predictor for worse outcomes (11). A prognostic signature based on 10 ATGs was established to predict DFS only in early CRC patients (12). However, research on ATG-based signatures for predicting the OS and drug sensitivity in CRC is limited. Thus, this study sought to explore the function and clinical values of ATGs in CRC. Using a series of bioinformatics and statistical analysis methods, we identified the aberrantly expressed prognostic ATGs in CRC. We then constructed a novel prognostic signature based on the identified ATGs, and showed the prognostic value of this signature in CRC. We identified WDR45 as a novel hub ATG in CRC by analyzing its expression and its correlation with patient outcomes, drug sensitivity, and immune activity. We further validated the expression and clinical value of WDR45 in local CRC specimens. We present this article in accordance with the TRIPOD and MDAR reporting checklists (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0088/rc).

Methods

Data sources

In December 2021, 608 RNA-sequencing samples from 517 colon adenocarcinoma (COAD) patients and 91 rectum adenocarcinoma (READ) patients, along with the corresponding clinical and survival information, were downloaded from The Cancer Genome Atlas (TCGA) database. Patients with incomplete survival data (survival time recorded as “0”) or incomplete clinical information were excluded from the analysis. Furthermore, external validation of the hub genes was performed using datasets from the Gene Expression Omnibus (GEO), including GSE41258 and GSE39582.

Identification of differentially expressed autophagy-related genes (DEATGs)

The candidate predictive factors in this study were ATGs. The R package “limma” was used to identify the differentially expressed genes (DEGs) between the CRC tumor and normal samples, using a threshold of |log₂fold change| >1 and an adjusted P value <0.05. The ATGs were identified by combining gene lists from the annotated gene sets of the MSigDB database (using the search term “autophagy”) and the HADb database. The DEATGs were identified by intersecting the DEGs and ATGs.

Functional enrichment analysis of DEATGs

Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the R package “ClusterProfiler”.

Construction and validation of a prognostic signature based on ATGs

The OS rate was set as the primary study endpoint. Univariate and multivariate Cox regression analyses were conducted to analyze the prognostic value of the DEATGs. The independent high-risk factors [hazard ratio (HR) >1 and P<0.05] identified in the multivariate analysis were included in the prognostic ATG risk-score model. The risk score was calculated using the following formula: risk score =∑₁ⁿ [regression coefficient of each gene * expression of gene]. For internal validation, the TCGA-CRC cohort was randomly divided into training and testing cohorts. The training group, testing group, and all CRC patients were allocated to high- and low-risk score groups based on the median value of the risk score, and Kaplan-Meier curve analyses were performed to predict patient survival. Using the RMS package in R software, a nomogram was constructed to predict the survival rates at 1, 3, and 5 years. The calibration curve was used to evaluate the consistency between the predicted survival results and the actual observed survival results. Meanwhile, the C-index was used to evaluate discrimination ability of the model. The C-index ranged from 0.5 to 1.0, with higher values indicating better discriminative ability.

Expression and genetic alterations of the hub ATG WDR45 in pan-cancer

WDR45 messenger RNA (mRNA) expression in pan-cancer was examined using the Tumor Immune Estimation Resource (TIMER) database. Genetic alterations and the DNA methylation of WDR45 were analyzed using the cBioPortal and University of Alabama at Birmingham Cancer data analysis Portal (UALCAN) databases. To assess single nucleotide variants (SNVs) in WDR45, base substitutions, insertions, and deletions were classified as variants and visualized in a waterfall plot.

Evaluation of the expression and prognostic value of WDR45 in CRC

The c-BioPortal, UALCAN, Gene Expression Profiling Interactive Analysis (GEPIA2), and Human Protein Atlas (HPA) databases were used to analyze the mRNA and protein expression of WDR45 in CRC and paired normal tissue samples. GEPIA2 and the Kaplan-Meier plotter databases were used to examine the association between WDR45 expression and the OS and recurrence-free survival (RFS) of CRC patients. A P value <0.05 was considered statistically significant.

The relationship between WDR45 expression and drug sensitivity

To evaluate the potential effects of WDR45 on the drug sensitivity of common chemotherapeutic and targeted agents, the pRRophetic R package was used to predict the half-maximal inhibitory concentration (IC₅₀) in cancer cell lines stratified by high- and low-expression of WDR45. A P value <0.05 was considered statistically significant.

Correlation analysis of WDR45 and immune infiltration

The TIMER database was used to analyze the association between WDR45 and immune cell infiltration in the tumor microenvironment (TME), as well as the immune checkpoint genes. The “SCNA” module in the TIMER database was used to assess the relationship between somatic copy number variations (CNVs) of WDR45 and tumor infiltration. In addition, the CIBERSORT algorithm was employed to estimate the immune cell proportion of each sample. The Wilcoxon rank-sum test was used to calculate the difference in 22 human immune cells between the high- and low-expression of WDR45 groups. A P value <0.05 was considered statistically significant.

Specimen collection

Forty-six pairs of tumor tissues and adjacent normal tissues were collected from CRC patients who underwent surgery at The First Affiliated Hospital of Guangxi Medical University between 2019 and 2021. Inclusion criteria were as follows: (I) diagnosed with CRC through pathological examination; (II) no history of other tumors; (III) none of them received chemotherapy, radiotherapy, targeted therapy, or immunotherapy before the surgery. The tissue specimens were placed in liquid nitrogen immediately after separation and subsequently stored at −80 °C. This study adhered to the principles of the Declaration of Helsinki and its subsequent amendments, and was approved by the ethical review committee of The First Affiliated Hospital of Guangxi Medical University (No. 2023-E526-01). Informed consent was obtained from all participants and their family.

Immunohistochemistry (IHC) staining

The IHC assay was performed as described previously (13). WDR45 antibody (19194-1-AP, 1:200) was purchased from Proteintech (Wuhan, China).

Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) assay

The following primers (designed and synthesized by Sangon Tiotech, Shanghai, China) were used in this study: WDR45 forward: 5'-GAGAAGCAACTGCTAGTGTTCC-3', reverse: 5'-GGCTGGTTTAGAGACACACAG-3'; glyceraldehyde-3-phosphate dehydrogenase (GAPDH) forward: 5'-CGGAGTCAACGGATTTGGTCGTAT-3', reverse: 5'-AGCCTTCTCCATGGTGGTGAAGAC-3'. GAPDH served as the internal control. WDR45 mRNA expression levels were quantified using the 2^−ΔΔCt method, normalized to GAPDH.

Cell culture and transfection

Five CRC cell lines (LOVO, DLD1, HCT8, LS174T, and SW480) and a normal colonic cell line (NCM460) were obtained and preserved in our laboratory. These cell lines were cultured in RPMI-1640 medium or DMEM supplemented with 10% fetal bovine serum (Procell Life Science & Technology Co., Ltd., Wuhan, China) and 1% penicillin-streptomycin (Solarbio, Beijing, China) under the condition of 5% CO₂ at 37 °C. For cell transfection, small interfering RNA targeting WDR45 (si-WDR45) and the corresponding negative control (si-NC) were synthesized by HyCyte^® (Suzhou, China), and when the density of HCT8 cells was 70–80%, transfected into HCT8 cells using Lipofectamine 3000 reagent (Invitrogen, Carlsbad, CA, USA) in accordance with the manufacturer’s instructions. After 48 h of cultivation at 37 °C, qRT-PCR was performed to verify the transfection efficiency, and cells were collected for subsequent experiments.

Western blot analysis

Total protein was isolated from cells using the radioimmunoprecipitation assay (RIPA) lysis buffer (Solarbio, Beijing, China), and a bicinchoninic acid (BCA) commercial kit (Beyotime, Shanghai, China) was used to detect the protein concentration. A total of 30 µg of protein was separated with 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and then transferred to a 0–22 µm polyvinylidene difluoride (PVDF) membrane (Millipore, Bedford, MA, USA). Subsequently, it was incubated with the corresponding primary antibody at 4 °C overnight. The primary antibodies against WDR45 (19194-1-AP, 1:1,000), LC3 (14600-1-AP, 1:5,000) and GAPDH (10494-1-AP, 1:5,000) were purchased from Proteintech (Wuhan, China). P62 (380612, 1:1,000) was purchased form Zen Bio (Chengdu, China). The membranes were washed three times with tris-buffered saline with Tween (TBST), and then incubated with the corresponding secondary antibody for 1 h at room temperature. Signals were visualized using the G:BOX Chemi XX9 system (Genesys, Cambridge, UK).

Cell Counting Kit-8 (CCK-8) assay

The CCK-8 assay was performed as described previously (13).

5-ethynyl-2'-deoxyuridine (EdU) incorporation assay

The EdU assay was performed as described previously (13).

Colony formation assay

Each well of the six-well plate was planted with 1×10³ cells and then cultured for 10 days. After removing the medium, the cells were fixed with 4% paraformaldehyde for 20 min, and then stained with 0.5% crystal violet. The culture plates were left to dry naturally and photographed to record the colony formation.

Statistical analysis

The IHC scores of WDR45 were analyzed with Graphpad Prism version 8.0 using the paired t-test. A P value <0.05 was considered statistically significant.

Results

Identification of DEATGs in CRC

In TCGA database, a total of 511 CRC patients met the study inclusion criteria. Using the R package “limma”, a total of 8,950 DEGs were identified in the CRC tissue samples compared to the non-tumor tissue samples based on the following criteria: |log₂fold change| >1 and adjusted P value <0.05. Meanwhile, 469 genes from the Molecular Signatures Database (MSigDB) and 222 genes from the Human Autophagy Database (HADb) were found to be involved in CRC autophagy, which were identified as ATGs. By intersecting these ATGs with the DEGs from TCGA database, 320 DEATGs were identified in CRC. The top 60 up- and down-regulated DEATGs are shown in Figure S1A,S1B.

Functional analysis of the DEATGs

In terms of the biological processes, the GO analysis revealed that the DEATGs were primarily involved in autophagy, autophagy-related processes, and the regulation of autophagy (Figure 1A). In terms of the cellular components, the DEATGs were closely correlated with the vacuolar membrane, endosome membrane, lysosomal membrane, and autophagosome (Figure 1A). The KEGG analysis revealed that the DEATGs were mostly involved in pathways related to the neurodegeneration of multiple diseases, the autophagy-animal pathway, and human papillomavirus (HPV) infection (Figure 1B).

Figure 1 Identification, construction, and validation of the prognostic signature. (A) Functional analysis of the DEATGs by GO terms. (B) KEGG enrichment pathway analysis of the DEATGs. The color scale represents the P value corresponding to the degree of enrichment. (C) The univariate Cox regression analysis identified 21 DEATGs associated with the prognosis of CRC patients. (D) The multivariate Cox regression analysis of the 21 DEATGs identified independent prognostic factors for CRC. (E-G) Kaplan-Meier survival curve of (E) all, (F) training, and (G) testing set depicting the OS rates of CRC patients at high and low risk. Patients were divided into high- and low-risk groups based on the median value of the risk score. (H) The distributions and (I) survival status of CRC patients with different risk scores in TCGA cohort. Each dot represents a CRC patient. (J) A nomogram integrating risk score, age, gender, and tumor stage for predicting 1-, 3-, and 5-year overall survival rates in CRC patients. (K) The calibration curves of the nomogram. (L) Analysis of C-index for risk score, age, gender and tumor stage. The forest plots of the (M) univariate and (N) multivariate Cox regression analyses in TCGA cohort. ***, P<0.05. C-index, consistency index; CI, confidence interval; CRC, colorectal cancer; DEATG, differentially expressed autophagy-related gene; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; M, metastasis; N, node; OS, overall survival; T, tumor; TCGA, The Cancer Genome Atlas.

Identification of prognostic DEATGs in CRC patients

A univariate Cox regression analysis was performed to identify the prognostic-related DEATGs in CRC patients with a threshold of P<0.05. As shown in Figure 1C, a total of 21 DEATGs were found to be significantly correlated with the OS of CRC patients. Among them, 18 DEATGs were identified as risk factors for COAD patients (HR >1) and 3 DEATGs were identified as protective factors (HR <1, P<0.05, Figure 1C). To further assess the prognostic values of the DEATGs in CRC, a multivariate Cox regression analysis was performed, which revealed that three DEATGs (WDR45, EGFR, and MTM1) were independent prognostic factors for CRC (P<0.05, Figure 1D).

Construction and validation of a novel prognostic signature with ATGs

Based on the independent prognostic factors identified from the multivariate Cox regression analysis, two risk factors (WDR45 and EGFR) were selected to establish a novel risk model for CRC patients. The risk score for each CRC patient was calculated based on the expression levels of WDR45 and EGFR, and their corresponding coefficients. Based on the median risk score value, the CRC patients were allocated to high- and low-risk groups. The Kaplan-Meier survival curves showed that the CRC patients in the high-risk group had a worse prognosis than those in the low-risk group, with 3-year survival rates of 66.1% and 86.6%, and 5-year survival rates of 52.6% and 78.9%, respectively (P<0.01, Figure 1E). Further validation was performed in the TCGA data through training and testing sets, and the Kaplan-Meier survival curves consistently confirmed the predictive value of our signature (P≤0.05, respectively, Figure 1F,1G). The CRC patients with higher risk scores exhibited higher mortality, reflecting a worse prognosis (Figure 1H). The survival status of each patient reflected the risk score distribution, indicating that higher risk scores were associated with shorter survival times (Figure 1I). We combined the risk score with age, gender and stage to construct a nomogram (Figure 1J). The calibration curve demonstrated a high degree of consistency between the actual values and the predicted values (Figure 1K). Furthermore, the consistency index (C-index) of the risk score was close to 0.7, indicating that this risk model has a significant advantage in predicting OS (Figure 1L).

A univariate Cox regression analysis was performed to determine whether the risk score of our established model and other clinical parameters [including age, gender, stage, tumor (T) stage, nodule metastasis, and distant metastasis] contributed to OS. As shown in Figure 1M, we found that age, stage, T stage, nodule metastasis, and distant metastasis were significantly correlated with the prognosis of the CRC patients (P<0.05, Figure 1M). The multivariate analysis further revealed that only age [P<0.001, HR =1.045, 95% confidence interval (CI): 1.022–1.068] and risk score (P<0.001, HR =1.586, 95% CI: 1.308–1.924) were independent prognostic risk factors for CRC patients (Figure 1N).

Pan-cancer analysis of hub ATG WDR45

The two identified DEATGs (WDR45 and EGFR) contributed significantly to the prognosis of CRC patients. The role of EGFR in CRC has been extensively studied and widely reported. Thus, we selected WDR45 for further investigation and validation. The pan-cancer analysis revealed that WDR45 was significantly overexpressed in 17 cancer tissues, including COAD and READ, compared with adjacent normal tissues (P<0.05, Figure S1C), suggesting that it plays an oncogenic role in these human cancers. Head and neck squamous cell carcinoma patients with HPV-positive tumors also showed higher WDR45 expression levels than those with HPV-negative tumors. Similarly, metastasized skin cutaneous melanoma (SKCM) showed higher WDR45 expression compared with non-metastasized SKCM (P<0.05, Figure S1C). Genetic alterations, including mutations and copy number alterations (CNAs), in WDR45 were commonly observed in various cancers (Figure S1D-S1F).

Analysis of the expression and clinical significance of WDR45 in CRC

As shown in Figure S2A, WDR45 was found to be aberrantly and highly expressed in CRC tumor tissues compared with normal tissues in GSE21510 (P=1.6e−10), GSE71187 (P=0.04), and GSE87211 (P=4.6e−14), although a contrasting result was observed in GSE25071 (P=8.7e−06). An analysis of TCGA datasets via UALCAN verified the overexpression of WDR45 in COAD and READ (Figure S2B,S2C). The correlation between WDR45 expression and clinicopathological parameters was examined using the UALCAN portal. The expression level of WDR45 differed across the histological subtypes of COAD, such that it was most highly expressed in mucinous adenocarcinoma followed by adenocarcinoma, and most lowly expressed in normal tissues (Figure S2D). In READ, WDR45 expression was the highest in the adenocarcinoma subtype, followed by mucinous adenocarcinoma, and the lowest in normal tissues (Figure S2E). A significant relationship was found between WDR45 expression and the advanced nodal stage in both COAD and READ (Figure S2F,S2G). WDR45 was overexpressed across advanced pathological stages, including stage 1 to stage 4, in both COAD and READ relative to normal tissues (Figure S2H,S2I). In addition, the expression of WDR45 in CRC was found to be positively correlated with the mutant status of TP53. WDR45 expression was highest in the TP53 mutant tumor group, followed by the TP53 non-mutant tumor group, and lowest in the normal tissue group (Figure S2J,S2K). Unexpectedly, WDR45 promoter methylation was higher in the COAD tumor tissues than the normal tissues, but the opposite trend was observed in relation to READ (Figure S2L,S2M).

Prognostic value of WDR45 in CRC

The prognostic value of WDR45 in CRC was assessed using the Kaplan-Meier plotter and GEPIA online tools based on data from GEO and TCGA databases, respectively. The OS analysis revealed that patients with high WDR45 expression had significantly worse OS in the GSE41258 dataset (P=0.02, n=185, Figure 2A) and TCGA-COAD dataset (P=0.02, n=270, Figure 2B). However, no such significant difference in OS was observed in TCGA-READ dataset (P=0.44, n=92, Figure S3A). Meanwhile, the Kaplan-Meier plotter database revealed that high WDR45 expression was significantly correlated with shorter RFS in CRC patients (RFS: 22 vs. 79.46 months, P=3.9e−08, HR =1.78, 95% CI: 1.44–2.19, n=1,342; Figure 2C), especially in the GSE41258, GSE39582, GSE37892, GSE17538, GSE33114, and GSE14333 datasets (P<0.05, Figure 2D-2I), suggesting that CRC patients with high WDR45 expression have poor survival.

Figure 2 The prognostic value of WDR45 in CRC patients based on OS and RFS analyses. (A,B) The OS of CRC patients with high and low WDR45 expression in the (A) GSE41258 CRC dataset and (B) TCGA-COAD cohort. (C-I) The RFS of CRC patients with high and low WDR45 expression in the (C) entire CRC, (D) GSE41258, (E) GSE39582, (F) GSE37892, (G) GSE17538, (H) GSE33114, and (I) GSE14333 datasets. (J) OncoPrint visual summary of the type and frequency of WDR45 alterations in CRC patients. (K) The PPI network of WDR45. (L,M) The differential TMB in COAD and READ patients with high and low WDR45 expression. COAD, colon adenocarcinoma; CRC, colorectal cancer; HR, hazard ratio; OS, overall survival; PPI, protein-protein interaction; READ, rectum adenocarcinoma; RFS, recurrence-free survival; TCGA, The Cancer Genome Atlas; TMB, tumor mutational burden.

Genetic mutations, interacting proteins, and tumor mutational burden (TMB) analysis of WDR45 in CRC

The cBioPortal results revealed that WDR45 mutations only occurred in 2.9% of the CRC patients (Figure 2J). A protein-protein interaction (PPI) network of WDR45 was constructed to reveal its potential molecular mechanisms. The PPI network showed that WDR45 interacted with ATG2A, ATG2B, CPSF4, SLC25A11, PRKAB1, PRKAA1, PRKAA2, and PRKAG1 l. Notably, ATG2A and ATG2B showed the most interactions with WDR45 (Figure 2K). The TMB (an important indicator of immunity response in some cancers) was then analyzed in relation to WDR45 expression. We found that the TMB was significantly lower in the COAD patients with high WDR45 expression than those with low WDR45 expression (P=0.02, Figure 2L). However, no significant differences were observed in the TMB in READ between the high- and low-WDR45 expression groups (P=0.68, Figure 2M). A waterfall plot revealed the top 15 mutated genes in COAD and READ (Figure 3A,3B). In both COAD and READ, patients with high WDR45 expression exhibited higher mutation frequencies in the driver genes APC and TP53 compared to those with low WDR45 expression, suggesting more serious malignancy behaviors in the high-WDR45 expression groups.

Figure 3 Pharmaceutical screening by WDR45. (A,B) Waterfall plots showing the top 15 mutated genes for COAD and READ patients with high and low WDR45 expression. (C-N) The differential IC₅₀ values of common anti-cancer drugs in CRC patients with high and low WDR45 expression. COAD, colon adenocarcinoma; CRC, colorectal cancer; IC₅₀, half-maximal inhibitory concentration; READ, rectum adenocarcinoma.

Pharmaceutical screening by WDR45 in CRC

To enhance the clinical applicability of WDR45 in guiding systemic therapy for CRC, we estimated the IC₅₀ values to predict the sensitivity of commonly used anti-cancer drugs in high- and low-WDR45 expression groups. Based on the algorithm applied in the CRC cell line database, we found that high WDR45 expression in COAD patients was associated with increased IC₅₀ values in 74 anti-cancer agents. These anti-cancer agents included important chemotherapy and targeted therapy drugs applied extensively in CRC such as 5-fluorouracil (5-Fu), AZD7762, camptothecin, MK-2206, SN-38, and veliparib in COAD (P<0.05, Figure 3C-3H). In READ, high WDR45 expression was associated with increased IC₅₀ values in 35 anti-cancer drugs, including AKT inhibitor VIII, embelin, CDK inhibitor AT-7519, XAV939, masitinib, and rTRAIL (P<0.05, Figure 3I-3N). These results suggest that CRC patients with high WDR45 expression may be less sensitive to anti-cancer drugs, indicating its potential role in predicting drug resistance and guiding personalized systemic therapy for CRC.

Analysis of immune cell infiltration and the TME in relation to WDR45

The CIBERSORT algorithm was used to estimate the infiltration proportion of 22 human immune cells in high- and low-WDR45 expression groups. Elevated WDR45 expression was positively associated with a higher infiltration of regulatory T cells (Tregs) in both COAD and READ, but was correlated with a lower infiltration of CD4 memory resting T cells in COAD (P<0.05, Figure 4A,4B).

Figure 4 The relationship between WDR45 expression and the TME. (A,B) The infiltration proportion of 22 human immune cells in COAD and READ patients with high- and low-expression of WDR45, analyzed by CIBERSORT algorithms. (C,D) The ESTIMATE, stromal, and immune scores of the (C) COAD and (D) READ patients with high- and low-expression of WDR45, compared by the ESTIMATE algorithm. (E,F) The correlation between WDR45 expression and immune cell infiltration levels in (E) COAD and (F) READ, analyzed by the TIMER database. (G,H) Relationship between immune cell infiltration and the types of WDR45 CNVs in (G) COAD and (H) READ. *, P<0.05; **, P<0.01; ***, P<0.001. COAD, colon adenocarcinoma; CNV, copy number variation; CRC, colorectal cancer; READ, rectum adenocarcinoma; TIMER, Tumor Immune Estimation Resource; TME, tumor microenvironment; TPM, transcripts per million.

Stromal and immune cell infiltration in each tumor sample was assessed using the ESTIMATE algorithm based on gene expression. Three scores (the immune score, stromal score, and ESTIMATE score) were calculated to evaluate the proportion of stromal and immune components in the TME of CRC. The results showed that WDR45 expression was positively correlated with the stromal, immune, and ESTIMATE scores (Figure 4C,4D), but the results were not statistically significant.

Moreover, the association between WDR45 expression and immune cell infiltration was analyzed using the TIMER database. As shown in Figure 4E, in the COAD samples, WDR45 expression was negatively correlated with tumor purity, B cells, and CD8⁺ T cells, but positively correlated with CD4⁺ T cells, neutrophils, macrophages, and dendritic cells (Figure 4E). In the READ samples, WDR45 expression was negatively correlated with tumor purity, CD8⁺ T cells, and neutrophils, but positively correlated with CD4⁺ T cells, macrophages, and dendritic cells (Figure 4F).

We also examined the relationship between WDR45 CNAs and immune infiltration, and found that the arm-level gains of WDR45 significantly affected the infiltration levels of B cells, CD8⁺ T cells, macrophages, neutrophils, and dendritic cells in COAD (P<0.05, Figure 4G). The arm-level gains also significantly affected the infiltration levels of B cells and dendritic cells in READ (P<0.05, Figure 4H).

Using the TIMER database, we also examined the relationship between WDR45 and immune checkpoint inhibitors (ICIs) in CRC, and found a weak positive association between WDR45 and ICIs, including PDCD1 (PD-1), CTLA4, LAG3, and HAVCR2, in both COAD and READ (Figure S3B). These results suggest that WDR45 exerts critical regulatory effects on immune cells and the TME in CRC.

The expression characteristics of WDR45 and its impact on autophagy

The protein expression of WDR45 in CRC was obtained from the HPA database (proteinatlas.org). IHC staining showed that WDR45 positivity was mainly localized to the nuclei of the CRC tumor cells (Figure S3C). IHC staining was then performed on 46 local CRC specimens. The results showed that WDR45 was mainly localized to the nuclei, and WDR45 expression was significantly higher in the CRC tissues than the adjacent normal tissues (P<0.001, Figure 5A,5B). WDR45 expression in CRC cells was also evaluated. Both the qRT-PCR and western blot analyses showed that WDR45 was aberrantly upregulated in the CRC cell line compared with the normal colon mucosa cell line (NCM460) (Figure 5C,5D), confirming its upregulation in CRC.

Figure 5 Validation of the expression and function of WDR45 in CRC. (A) Representative images of WDR45 staining by IHC in 46 CRC tumor tissues and adjacent normal tissues of local clinical specimens (200× and 400×). (B) Comparison of IHC scores in the tumor tissues and adjacent normal tissues of 46 CRC patients. (C,D) The mRNA and protein expression of WDR45 in five CRC cell lines and the normal colon mucosa cell line (NCM460) detected by qRT-PCR and western blot. (E) Validation of the efficiency of the siRNA downregulation of WDR45 at the mRNA level. (F) CCK-8 assay showed a significant decrease in cell proliferation activity after the knockdown of WDR45. (G) EdU incorporation assay showed that the downregulation of WDR45 led to the decreased proliferation of CRC cells. The blue fluorescence is Dapi staining, which marks the location of all cell nuclei. The green fluorescence is from the Edu staining, which marks the proliferating cells. Scale bar: 100 μm. (H,I) Colony formation assay showed that the downregulation of WDR45 led to a decrease in the ability of CRC cells to form clones. (J) Western blot showed WDR45 may have a promoting effect on autophagy. ***, P<0.001. CCK-8, Cell Counting Kit-8; CRC, colorectal cancer; DAPI, diamidino-2-phenylindole; EdU, 5-ethynyl-2'-deoxyuridine; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; IHC, immunohistochemistry; OD, optical density; qRT-PCR, quantitative real-time reverse transcription polymerase chain reaction; si-NC, small interfering negative control.

After confirming the expression pattern of WDR45 in CRC, we investigated its function in CRC cells. Among the tested cell lines, HCT8 exhibited relatively high WDR45 expression and was thus selected for further functional experiments. The efficiency of WDR45 knockdown in HCT8 was confirmed by qRT-PCR (Figure 5E). As shown in Figure 5F, the knockdown of WDR45 significantly suppressed cell viability as detected by CCK-8 assay (P<0.001). Meanwhile, the EdU-positive cells were obviously reduced in the si-WDR45 group (Figure 5G). In addition, colony formation assays revealed a significant decrease in colony numbers after the knockdown of WDR45 in the HCT8 cells (P<0.001, Figure 5H,5I). Taken together, the results suggest that WDR45 knockdown inhibits the proliferation of CRC cells.

In order to explore the effect of WDR45 on autophagy in CRC, we applied western blot to detect the expression of autophagy-related proteins. The results showed that in the si-WDR45 group, the expression of P62 increased and LC3 decreased (Figure 5J). This suggests that in CRC, knockdown of WDR45 could inhibit autophagic progress.

Discussion

Despite significant advances in the diagnosis and treatment of CRC, many patients are diagnosed at late stages, and the high risk of metastasis, recurrence, and post-surgical drug resistance remains a major concern, contributing to the poor prognosis of CRC patients. Genetic alterations have been shown to contribute to the progression of CRC; thus, novel effective and sensitive biomarkers are urgently needed to be identified.

Autophagy has been shown to modulate the degradation of damaged organelles and proteins, thereby maintaining cellular homeostasis. Recent studies have shown that autophagy plays a dual role in tumor progression with its effects changing dynamically according to the cancer type and developmental stage. The aberrant expression of ATGs has been shown to either activate or block autophagy, and serves as a prognostic biomarker in various human malignancies, including CRC. For example, the PHLDA2 gene was reported to be overexpressed in CRC tumor tissues and its knockdown was reported to activate autophagy and inhibit EMT, suppressing malignant behaviors via the PI3K/AKT signaling pathway (14). However, evidence on the precise roles of ATGs in predicting the prognosis and drug sensitivity of CRC patients is limited.

In this study, we identified the prognostic DEATGs in CRC and established a prognostic signature based on these DEATGs. The univariate Cox regression analysis identified 21 DEATGs related to the prognosis of CRC, some of which have been reported to play crucial roles in the progression of CRC. Notably, ULK3 has been reported to be a high-risk factor in CRC, and TUBB2B has been reported to be an independent prognostic factor and associated with lymph node metastasis in CRC (15). Our results indicated that EGFR, ULK3, and TUBB2B are high-risk genes in CRC with HRs >1.

Moreover, FEZ1 has been reported to act as a tumor suppressor in CRC, and has been shown to be downregulated in CRC tumor tissues and correlated with survival (16). Similarly, we found that FEZ1 was a protective factor for CRC prognosis (HR <1). Some studies have reported that DAPK1 acts as an anti-metastatic gene, and that the knockdown of DAPK1 enhances chemoresistance and metastasis in CRC (17). However, our results indicated that DAPK1 was a risk factor for CRC prognosis (HR >1). Given that the previous studies did not investigate the effect of DAPK1 on CRC prognosis, the precise and specific prognostic value of DAPK1 still needs to be determined.

Our multivariate Cox regression analysis identified three DEATGs (WDR45, EGFR, and MTM1) as independent prognostic factors for CRC. Among them, MTM1 was identified as a protective factor; we then chose two risk factors (EGFR and WDR45) to construct our prognostic signature, which was shown to predict the prognosis of CRC patients accurately. Moreover, the clinical applicability of our signature was verified by internal validation. This study was constrained by using a single database (TCGA), underscoring the need for external validation. The therapeutic predictions of our signature await rigorous preclinical testing, as well as validation in larger and multi-center cohorts. Research has indicated that EGFR is highly expressed in tumor tissues and facilitates the progression of CRC, and thus can serve as a target for the perioperative clearance of circulating CRC cells (18).

WDR45 mutations have been implicated in neurodegenerative diseases and neurodevelopmental disorders through mechanisms involving endoplasmic reticulum stress and neuronal apoptosis (19). While the role of WDR45 has been investigated in some cancers, it has not been investigated in CRC. In prostate cancer, WDR45 was found to interact with RKIP to modulate EMT and autophagy (20). In cervical cancer, the expression level of WDR45 was affected by deubiquitinase OTUD5, which has been reported to exert crucial effects on DNA repair and immunity (21). A study revealed that WDR45 is a frequently altered ATG in patients with uterine corpus endometrial carcinoma (22). Consistent with findings in other cancers, our study firstly identified WDR45 as an independent risk factor for the prognosis of CRC patients. Its upregulation and its tumor promoter effect in CRC support its potential as a novel biomarker for CRC.

WDR45, a member of the WD-repeat protein Interacting with PhosphoInositides (WIPI) family (23), regulates autophagy through its interaction with ATG2 (24). WDR45 β-propeller domains serve as scaffolds for AMPK-related kinase signaling, thereby controlling autophagy (25). Moreover, ATG2A promotes autophagosome formation by transferring lipids between cell membranes to expand the phagophore (26). The ATG2A-WDR45/WIPI4-ATG9A complex is a mediator of lipid transfer and balance during autophagosome formation (27). In WDR45/45b-depleted cells, autophagosomes were found to be decreased, but were rescued by the overexpression of ATG2A (28). In addition, WDR45/WIPI4 was found to have a stronger binding capacity with ATG2A or ATG2B than other WIPIs (29). Our experimental results initially suggest that WDR45 may promote autophagic progress in CRC cells. And our PPI network showed that WDR45 interacted with ATG2A and ATG2B preferentially, providing a possible direction for future research on WDR45.

Somatic mutations are important contributors to tumor progression and are closely associated with a poor prognosis in cancer patients. Our pan-cancer analysis showed that WDR45 was overexpressed in most human cancers, suggesting that WDR45 plays an oncogenic role. Genomic alterations in WDR45 are common in several cancers. Although the mutation frequency of WDR45 was only 2.9% in CRC, the expression of WDR45 was positively related with genomic alterations in APC and TP53, which are the most common variations of tumor suppressors contributing to the poor prognosis of CRC (30).

As anticipated, the OS and RFS of the CRC patients was positively related to the expression of WDR45. DNA methylation is considered a crucial mechanism for regulating gene expression and tumor development, influencing both prognosis and treatment response (31). A high level of promoter methylation can lead to gene downregulation by inhibiting transcriptional initiation, thereby reducing mRNA synthesis. Our results showed a positive relationship between promoter methylation and WDR45 expression in COAD but a negative correlation in READ, suggesting that the overexpression of WDR45 in COAD may be driven by factors other than promoter methylation. Large-scale studies, including subgroup analyses and in-depth investigations of molecular mechanisms, need to be conducted in the future to better understand the genetic diversity of CRC.

Chemotherapy and targeted therapy have significantly improved the outcomes of CRC patients. The FOLFOX regimen is widely used as a standard chemotherapy for CRC patients in clinical settings. 5-Fu is a component of the FOLFOX regimen. In CRC, autophagy-mediated 5-Fu resistance is reversed by HMBOX1 through its promotion of HACE1-mediated ATG5 ubiquitination and degradation (32). However, we found that that the IC₅₀ of 5-Fu increased in the high-WDR45 expression groups, suggesting that WDR45 may serve as a predictive marker in the treatment of CRC patients. We also found that WDR45 was positively correlated with the IC₅₀ values of 74 anti-cancer drugs, which have previously been reported to exert anti-cancer effects in CRC. These results provide basic evidence for the clinical application of WDR45 in the future.

The TME comprises complex components, including immune infiltrating cells, stromal cells, such as fibroblasts, the extracellular matrix, chemokines, and cytokines, and plays a crucial role in tumor progression and the immune response of cancer cells. Autophagy drives immune resistance by reshaping the tumor immune microenvironment, inhibiting the infiltration and function of cytotoxic T cells, and promoting the recruitment of immunosuppressive cells such as Tregs (33). Tregs are an important subset of T cells, and targeting Tregs could improve the prognosis of many cancers. There is direct evidence that Tregs are enriched in CRC and contribute to the progression of CRC (34). The proliferation of Tregs promotes tumor growth and oxaliplatin resistance in CRC via the induction of tumor immune evasion (35). Our CIBERSORT analysis showed a higher infiltration of Tregs in CRC samples with high WDR45 expression, indicating that WDR45 may contribute to the poor prognosis of CRC patients through Treg regulation.

Moreover, the TIMER analysis showed that WDR45 expression was positively correlated with the infiltration of macrophages and CD4⁺ T cells. It is well known that macrophages exert immunosuppressive effects by inhibiting the immune microenvironment, recruiting and activating T cells and natural killer cells (36). CD4⁺ T cells are a major subset of T lymphocytes and have been reported to kill tumor cells mainly by regulating and coordinating the activity of other immune cells. However, there is controversial evidence that CD4⁺ T cells are increased in CRC tumor tissues and the circulation of advanced CRC patients, and thus could serve as predictive biomarkers for CRC (37).

The TMB is considered an important indicator of immune response. Notably, we found inconsistent correlations between TMB status and WDR45 expression in COAD and READ. Overall, our findings suggest that WDR45 may contribute to poor CRC prognosis by promoting immunosuppression through Tregs and macrophages. However, the precise effects and molecular mechanisms by which WDR45 regulates immune infiltration and immune response remain to be elucidated. Furthermore, the potential of immunotherapy in CRC, including novel and specific ICIs, warrants further exploration.

Conclusions

Our study established an accurate prognostic signature based on the identified ATGs and provided evidence of the overexpression and tumor promoter role of WDR45 in CRC. WDR45 is a promising biomarker for CRC. Targeting WDR45 may improve chemotherapy and immunotherapy in CRC.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD and MDAR reporting checklists. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0088/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0088/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0088/prf

Funding: This work was supported by the National Nature Science Foundation of China (No. 82460489), the Guangxi Natural Science Foundation (No. 2024GXNSFAA010065), and the 2025 Guangxi University Students’ Innovation and Entrepreneurship Training Program Project (No. S202510598186).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2026-1-0088/coif). All authors report that this work was supported by the National Nature Science Foundation of China (No. 82460489), the Guangxi Natural Science Foundation (No. 2024GXNSFAA010065), and the 2025 Guangxi University Students’ Innovation and Entrepreneurship Training Program Project (No. S202510598186). The authors have other no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was reviewed and approved by the Ethics Committee of The First Affiliated Hospital of Guangxi Medical University (No. 2023-E526-01). Informed consent was obtained from all participants and their family.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: L. Huleatt)