Evaluating HSP90AA1 as a predictive biomarker for prognosis in lung adenocarcinoma

Introduction

Lung cancer remains the leading cause of morbidity and mortality worldwide (1,2). It is primarily classified into two main types based on pathological characteristics: small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC), with NSCLC accounting for approximately 85% of all lung cancer cases (3,4). Among the subtypes of NSCLC, lung adenocarcinoma (LUAD) is the most prevalent. In its early stages, it often presents with nonspecific clinical symptoms, and progression to local infiltration or metastasis typically occurs in intermediate to advanced stages, significantly affecting clinical prognosis and survival outcomes. The 5-year overall survival (OS) rate for LUAD is usually below 20% (5-7).

Heat shock protein 90 (HSP90) is a structurally conserved chaperone protein, typically comprising at 1–2% of cellular proteins in normal cells, which can increase to 4–6% under stress conditions under stress conditions (8,9). HSP90 interacts with a wide array of receptors, including heat shock factor 1 (HSF1) and various oncogenic derivatives, playing a pivotal role in regulating cell survival, growth, and the cell cycle by facilitating the maturation of over 200 client proteins. These client proteins include transmembrane tyrosine kinases such as the epidermal growth factor receptor (EGFR), signaling proteins such as AKT, mutant proteins like p53, chimeric proteins such as fusion kinases, and cell cycle-dependent kinases such as Cyclin-dependent kinase 4 (CDK4) and CDK6, alongside steroid receptors for androgen, estrogen, and progesterone, all of which are significantly implicated in tumor growth (10-12). The role of HSP90 in lung cancer and its molecular mechanisms have been widely reported (13-15), several HSP90 inhibitors have also been identified and evaluated for potential clinical use (16,17). In humans, HSP90 isoforms comprise cytoplasmic HSP90α and HSP90β, the endoplasmic reticulum isoform (glucose-regulated protein 94, Grp94), and the mitochondrial isoform (tumor necrosis factor-associated protein 1, TRAP1). HSP90α, encoded by the HSP90AA1 gene, is the heat stress-inducible isoform of this molecular chaperone (15). However, the clinical implications of HSP90 isoforms and the pathways they regulate in lung cancer remain inadequately defined.

HSP90AA1 is a stress-inducible member of the HSP90 family, regulates a series of proto-oncogene products (such as c-Myc) and crucial signal transduction pathways (18,19). Recent studies have shown that HSP90AA1 promotes tumour progression, invasion and chemotherapy resistance (20,21). In addition, HSP90AA1 has been identified as a secreted extracellular factor involved in the inflammatory response, which tumor cells exploit to enhance their malignant phenotype (12). A study found that HSP90AA1 deficiency was associated with improved prognosis in 206 gastric cancer patients post-surgery (22). These findings suggest that HSP90AA1 is closely associated with cancer development and progression, making it a potential target for cancer therapy. In this study, we analyzed the relationship between HSP90AA1 expression and clinical stage as well as prognosis in LUAD. We also predicted the biological function of HSP90AA1 in LUAD and its relationship with immunity. Additionally, we conducted cellular molecular biology experiments to elucidate the role of HSP90AA1 in LUAD, thereby providing a foundation for further investigation into its function. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2155/rc).

Methods

Expression profile and prognostic value of the HSP90AA1 gene

We used TIMER2.0 (http://timer.cistrome.org/) to investigate the differential expression of HSP90AA1 between tumors and adjacent normal tissues (23). The Ualcan database (https://ualcan.path.uab.edu/) was employed to analyze the differential expression of HSP90AA1 in LUAD compared to normal tissues, as well as across various clinicopathological stages (24). Expression levels of the HSP90AA1 gene in LUAD at different clinicopathological stages and adjacent normal tissues were obtained from the GEPIA database (http://gepia.cancer-pku.cn/) (25). Immunohistochemical (IHC) results for HSP90AA1 expression in LUAD were sourced from the Human Protein Atlas (HPA) database (https://www.proteinatlas.org). The correlation between HSP90AA1 gene expression and protein levels was analyzed using the cProSite database (https://cprosite.ccr.cancer.gov/). The prognostic value of HSP90AA1 at the pan-cancer level was assessed through the GEPIA2.0 database (http://timer.comp-genomics.org/) (26). The correlation between HSP90AA1 expression and the clinicopathological characteristics of LUAD patients was analyzed by ANOVA or Wilcoxon test and visualised by “ggplot2” software package. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Survival prognosis analysis

The data of LUAD Patients were divided into high and low HSP90AA1 expression groups based on the median expression level. Correlations among survival time, clinical prognostic indicators and HSP90AA1 expression were examined via univariate and multivariate Cox regression analyses with Survival software. Nomograms were constructed with RMS software based on independent factors identified in the Cox multivariate analysis from the TCGA database. The consistency index (C-index) and calibration were evaluated to effectively measure the performance of the constructed nomograms. The Survival ROC software package was utilized to generate receiver operating characteristic (ROC) curves to assess predictive performance.

Analysis of differentially expressed genes (DEGs)

DEGs between the HSP90AA1 high and low expression groups were investigated and analyzed utilizing the Wilcoxon rank-sum test in the R programming language with the DESeq2 software (version 1.26.0) (27). Significance was defined as differences with |log₂ fold change| >2 and adjusted P values <0.05.

Gene set enrichment analysis (GSEA)

Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted using the “ClusterProfiler” package (28). Subsequently, the “ggplot2” package was used to visualise the results. We used the GSEA software and ClusterProfiler package to analyse the signalling of HSP90AA1 in LUAD (28-30).

Immune infiltration analysis

To assess the correlation between HSP90AA1 and immune cell infiltration in LUAD, we used the “CIBERSORT” to calculate the proportion of tumor-infiltrating immune cells, including the expression characteristics of 22 immune cell subtypes (https://cibersortx.stanford.edu/) (31). Based on the single sample gene set enrichment analysis (ssGSEA) algorithm provided in the R package “GSVA” (1.46.0), which facilitating the relative immune cell quantification of these datasets (32). The R package “ESTIMATE” was applied to calculate the ImmuneScore (correlated with the degree of immune cell infiltration), the StromalScore (correlated with the degree of mesenchymal cells) and the ESTIMATEScore (negatively correlated with tumour purity) (33). In order to evaluate the variability of the Tumour Immune Dysfunction and Rejection (TIDE) score, we uploaded the normalised gene expression matrix to the TIDE website (http://tide.dfci.harvard.edu), and then compared the estimates of the different HSP90AA1 expression groups using the Wilcoxon test.

Cell culture and siRNA

H1299 cells (Beyotime Biotechnology, Cat#C6274, Beyotime Biotechnology, China) were cultured in 1640 medium supplemented with 10% fetal bovine serum (FBS) (cellmax, China), 100 U/mL penicillin, and 100 mg/mL streptomycin (Beyotime Biotechnology Co., Shanghai, China). The siRNA targeting HSP90AA1 transcript and non-specific control siRNA (5'-GCU GAG UUG ACC UCU AUC GTT-3') were purchased from Suzhou GenePharma. The siRNA target sequences of HSP90AA1 are 5'-TAT GGC ATG ACA ACT ACT TTA-3' and 5'-CCC GAG AAC AAC CCT AAG TTT-3'. Specific siRNA or negative control was transfected into LUAD cells using siRNA-mate plus Transfection Kit (GenePharma, Suzhou, China) according to the manufacturer’s instructions.

Appropriate amount of H1299 cells were seeded into six-well plates, so that the cell density could reach 60% the next day. To prepare siRNA premix, 42.5 µL Buffer was added to the sterile enzyme-free EP tube, then 75 pmol siRNA was added and mixed well. Then, 15 µL transfection reagent plus was added to the siRNA premix solution, mixed by pipetting to prepare siRNA/plus complex. Before transfection, 2 mL fresh culture medium was replaced for each well, and then the siRNA/plus complex was added to the six-well plate. Cells were incubated at 37 ℃, 5% CO₂ for 24 hours before proceeding with subsequent experiments.

Western blotting

The protein samples were harvested and their concentrations were detected by BCA protein assay kit (Beyotime Biotechnology, Shanghai, China). The membrane was immersed in 5% skimmed milk for 1 hour at room temperature, then diluted primary antibody was added and incubated overnight at 4 ℃. After washing the membrane, horseradish peroxidase-conjugated secondary antibody was added, and the protein expression level was detected using Enhanced Chemiluminescence Detection Kit (Beyotime Biotechnology, Shanghai, China) and Image Lab software (Bio-Rad, USA). Primary antibodies against HSP-90, CyclinD1, CyclinB1, Caspase-3, Smac, BCL-2, and BAX were purchased from Beyotime Biotechnology (Shanghai, China). Antibodies against Hsp90 alpha Antibody and BCL-XL were purchased from Affinity Biosciences (Jiangsu, China). The beta-actin antibody was purchased from Abmart (Shanghai, China).

PI staining

The digested cell samples were washed with pre-cooled 1×PBS and treated with 70% anhydrous ethanol in a refrigerator at −20 ℃. Cells were incubated with PI/RNase staining buffer for 15 min at room temperature, and the cell cycle of each group was analyzed by the FongCyte^TM flow cytometry (Cenglang Biotechnology Co., Ltd., Beijing, China).

Annexin V-FITC/PI assay

H1299 cells were digested with trypsin in the absence of EDTA and subsequently resuspended in PBS. The cell suspensions were centrifuged, and the supernatant was discarded. Next, 195 µL of Binding Solution, 5 µL of Annexin V-FITC, and 10 µL of PI Staining Solution were added sequentially, mixed gently, and incubated in the dark for 15 minutes. This preparation was then used to evaluate the degree of apoptosis via flow cytometry. The experiment was conducted in triplicate, and the results were expressed as mean ± SD.

Statistical analyses

Data analyses were conducted using R software (version 4.0.3). The significance of gene expression levels across different tissue types was evaluated using either the LSD-t-test or the Wilcoxon test, depending on the data distribution. Gene correlation analyses were performed utilizing the R² platform, while survival data were analyzed using the Kaplan-Meier method to estimate survival curves. Statistical significance was defined at a threshold of P<0.05. All experimental results were replicated a minimum of three times, and data were presented as mean ± standard deviation (x¯±s). Statistical differences were further evaluated through either a two-tailed LSD-t-test or one-way analysis of variance (ANOVA), with a P value <0.05 considered statistically significant.

Results

HSP90AA1 is high expressed in various types of cancer

The TIMER database was employed to analyze the expression of HSP90AA1 across various cancerous and normal tissues. The results indicated a significant up-regulation of HSP90AA1 expression in 12 different cancer types, including BRCA, CESC, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, READ, STAD, and UCEC (Figure 1A). HSP90AA1 is expressed at low levels in the following five types of cancer: GBM, KIRC, KIRP, PRAD, and THCA. In contrast, HSP90AA1 expression is significantly higher in SKCM metastases compared to primary tumor groups. Further analysis of data from TCGA and CPTAC databases revealed markedly higher levels of HSP90AA1 protein and RNA in lung tissues of LUAD patients compared to normal lung tissues (Figure 1B,1C). Immunohistochemical staining demonstrated enhanced expression of HSP90AA1 in LUAD tissues relative to normal lung tissues (Figure 1D). Additionally, a strong correlation was observed between the abundance of HSP90AA1 protein and its gene expression level (R=0.6798), effectively distinguishing LUAD from paraneoplastic tissues (Figure 1E).

Figure 1 HSP90AA1 is significantly overexpressed in LUAD. (A) The expression levels of HSP90AA1 across various tumors and specific cancer subtypes are illustrated by TIMER2.0. Blue dots and blue boxes represent “normal”; red dots and red boxes represent “tumour tissue”. CESC: P=0.009; HNSC-HPV: P=0.03; KIRP: P=0.007; PRAD: P=0.001; READ: P=0.02; THCA: P=0.02; UCEC: P=0.001; BRCA, CHOL, COAD, ESCA, GBM, HNSC, KIRC, LIHC, LUAD, LUSC, SKCM, STAD: P<0.001. (B,C) The differences in RNA and protein expression levels of HSP90AA1 between tumor tissues and their corresponding normal tissues are presented by UALCAN, with statistical significance denoted as ***P<0.001. (D) In HPA database, immunohistochemical analysis reveals the expression of HSP90AA1 in normal lung tissues compared to lung adenocarcinoma tissues. Scale bar: 200 µm. (E) In cProSite database, a correlation analysis demonstrates the relationship between mRNA levels and protein abundance of HSP90AA1. *, P<0.05; **, P<0.01; ***, P<0.001. TPM, transcripts per million; TCGA, The Cancer Genome Atlas; LUAD, lung adenocarcinoma.

Prognostic value of HSP90AA1 expression in LUAD

The relationship between clinical stage and HSP90AA1 gene expression in patients with LUAD is illustrated in Figure 2A,2B. In patients with stage I, II and III LUAD, HSP90AA1 expression levels exhibited a gradual increase correlating with the clinicopathological stage. Notably, a significant elevation in expression was observed in stage IV compared to earlier stages, which aligns with the findings from the GEPIA database analysis [F-value =2.71, Pr(>F) =0.0444]. This suggests that HSP90AA1 expression levels could serve as a biomarker for identifying patients with stage IV LUAD. The area under the curve (AUC) of the HSP90AA1 expression group was found to be 0.584 at 1 year, 0.554 at 3 years, and 0.584 at 5 years, as depicted in Figure 2C. The analysis of survival was conducted utilising the Cox regression statistical method. The findings indicated that the OS and disease-specific survival (DSS) outcomes were notably higher in the cohort exhibiting low HSP90AA1 expression in comparison to the cohort demonstrating high HSP90AA1 expression (Figure 2D, P=0.004; Figure 2E, P=0.03). Furthermore, there was no statistically significant difference in progression-free interval (PFI) between the low and high expression groups (Figure 2F).

Figure 2 HSP90AA1 is a diagnostic and prognostic biomarker of LUAD. (A,B) The UALCAN and GEPIA databases are used to analyse the expression of HSP90AA1 in the different clinicopathological stages of LUAD. (C) Time-dependent ROC in LUAD patients with the HSP90AA1 gene. (D-F) Overall survival curves, disease specific survival curves, and progression-free intervals in patients with high (red line) versus low (blue line) HSP90AA1 expression in LUAD. ***, P<0.001. TCGA, The Cancer Genome Atlas; TPR, true positive rate; FPR, false positive rate; AUC, area under the curve; HR, hazard ratio; LUAD, lung adenocarcinoma; ROC, receiver operating characteristics.

The functional Role of HSP90AA1 in LUAD cells

To gain a deeper understanding of the role of the HSP90AA1 gene in cancer cells, we utilized CancerSEA to conduct a functional correlation analysis. Our findings revealed that the HSP90AA1 gene is involved in various cellular functions, including the stimulation of the cell cycle, DNA damage response, DNA repair, invasion, and proliferation of LUAD cells. Additionally, it plays an inhibitory role in processes such as angiogenesis, apoptosis, and hypoxia (Figure 3A). Further analysis indicated that in LUAD cells, HSP90AA1 exhibited a positive correlation with the cell cycle, displaying the highest correlation among the tested functions (Figure 3B).

Figure 3 Functional analysis of HSP90AA1 in LUAD. (A) In CancerSEA, the HSP90AA1 gene exhibits both promotional and repressive effects on various states within the same type of cancer, as well as across different cancers in similar states. This highlights the correlation between cell states and various cancers. (B) In CancerSEA, the correlation between HSP90AA1 gene expression and functional status is shown in LUAD. ***, P≤0.001. EMT, epithelial-mesenchymal transition; AML, acute myeloid leukemia; ALL, acute lymphoblastic leukemia; CML, chronic myelogenous leukemia; GBM, glioblastoma; AST, astrocytoma; HCG, high-grade glioma; ODG, oligodendroglioma; LUAD, lung adenocarcinoma; NSCLC, non-small cell lung cancer; Exp, expression.

Identification of HSP90AA1-related genes, pathways and cellular functions in LUAD

To investigate the potential role of HSP90AA1 in LUAD, we performed a comprehensive analysis of the signaling pathways and biological functions of genes co-expressed with HSP90AA1. Top 60 most upregulated and downregulated genes were shown in Figure 4A. GO analysis revealed that genes highly expressed alongside HSP90AA1 were significantly involved in the positive regulation of DNA metabolic processes, protein folding, and overall regulation of DNA metabolism. Additionally, the cell component analysis indicated enrichment in the chaperone complex, while the molecular functions were notably enriched in unfolded protein binding and ATP hydrolysis activity (Figure 4B). Figure 4C illustrates the interactions between HSP90AA1 and 11 genes closely associated with it. Furthermore, GSEA highlighted significant differences in KEGG pathways related to the cell cycle and proteasome between samples with high and low expression levels of HSP90AA1. Moreover, the groups with high and low expression of HSP90AA1 exhibited substantial variations in biological processes, including Central Nervous System Development and Embryo Development (Figure 4D,4E).

Figure 4 Identification of HSP90AA1-related genes, pathways and cellular functions. (A) Heatmap showing the differentially expressed top 60 genes associated with HSP90AA1. (B) The GO and KEGG analysis of co-expressed gene with HSP90AA1. (C) Circos plots were generated to visualize the co-expression network of HSP90AA1 with 11 genes in LUAD samples. Each segment of the circle represents a gene, with the width indicating the total amount of co-expression with other genes. The width of the links between genes represents the total expression correlation. (D,E) GSEA was performed to identify KEGG pathway enrichment and GO function enrichment analysis differences between samples with high and low HSP90AA1 expression. BP, biological process; CC, cellular component; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function; GO, Gene Ontology; LUAD, lung adenocarcinoma; GSEA, gene set enrichment analysis.

Relationship between HSPA90AA1 and immune cell infiltration in LUAD

CIBERSORT-based analysis was performed to assess immune cell infiltration levels in groups with high and low HSP90AA1 expression. Significant correlations were identified between HSP90AA1 and tumor-infiltrating immune cells. Specifically, the infiltration levels of activated memory Th2 cells, T helper cells, Tgd, and other activated immune cells were positively associated with HSP90AA1 expression. In contrast, the infiltration levels of CD8 T cells, plasmacytoid dendritic cells (pDC), B cells, Th17 cells, T follicular helper (TFH) cells, mast cells, immature dendritic cells (iDC), dendritic cells (DCs), and overall T cell population showed negative correlations with HSP90AA1 (Figure 5A,5B). Patients exhibiting high HSP90AA1 expression demonstrated lower mesenchymal scores, immune scores, and estimation scores compared to those with low expression levels, which correlated with the higher tumor purity observed in the high HSP90AA1 group (P<0.001; Figure 5C,5D). Furthermore, an analysis of the correlation between HSP90AA1 expression and immunotherapy efficacy revealed significant differences in tumor immune dysfunction and exclusion (TIDE) score among the different HSP90AA1 expression groups (Figure 5E). Notably, patients with high HSP90AA1 expression presented a significantly higher T-cell exclusion rate (Figure 5F), while the T-cell dysfunction score was lower in this group (Figure 5G).

Figure 5 The correlation between HSP90AA1 and immune infiltration in LUAD. (A) Enrichment scores for high and low HSP90AA1 expression groups. Cytotoxic cells: P=0.02; T cells: P=0.01; T helper cells: P=0.001; TFH: P=0.001; Tgd: P=0.02; Th1 cells: P=0.02; Th17 cells: P=0.008; ***, P<0.001. (B) Lollipop plots illustrating the correlation between immune infiltration and HSP90AA1 expression. Tgd: P=0.002; Neutrophils: P=0.07; aDC: P=0.13; NK CD56dim cells: P=0.13; Tcm: P=0.32; macrophages: P=0.13; eosinophils: P=0.54; NK cells: P=0.44; Tem: P=0.35; NK CD56bright cells: P=0.30; TReg: P=0.17; Th1 cells: P=0.06; cytotoxic cells: P=0.02; Mast cells: P=0.01; iDC: P=0.01; DC: P=0.01; T cells: P=0.01; Th17 cells: P=0.003; TFH: P=0.001. (C,D) Differences in stromal scores, immune scores, estimated scores, and tumor purity between high and low HSP90AA1 expression groups. Stromal scores: P<0.05; immune scores, estimated scores, tumor purity: P<0.001. (E-G) Immunotherapeutic response biomarkers, including tumor immune dysfunction and exclusion (TIDE) score (E), T-cell rejection scores (F), and T-cell dysfunction scores (G) between HSP90AA1 low and high expression groups. *, P<0.05; **, P<0.01; ***, P<0.001. DC, dendritic cell; aDC, activated DC; NK, natural killer; pDC, plasmacytoid DC; TFH, T follicular helper; iDC, immature DC; LUAD, lung adenocarcinoma.

Knockdown of HSP90AA1 inhibits cell proliferation through blocking the cell cycle

RNA interference is a commonly used experimental method for altering protein expression levels (34). We used two different siRNA sequences to specifically knock down the expression of HSP90AA1 protein while monitoring the proliferation of H1299 (Figure 6A,6B). The knockdown of HSP90AA1 was found to effectively inhibit the proliferation of H1299 cells compared with the control group (Figure 6C). To confirm the cause of inhibition of cell proliferation, a PI staining assay was employed for cell cycle detection in H1299 cells. The results revealed an increase in the number of cells in the G1 phase, while the number of cells in the S and G2/M phases decreased in the HSP90AA1 knockdown group compared to the control group (Figure 6D-6G). This indicates that the deletion of HSP90AA1 leads to a blockade of H1299 cells in the G1 phase. Additionally, protein immunoblotting experiments substantiated that the knockdown of HSP90AA1 effectively down-regulated the expression of cell cycle-related proteins CCNB1 and CCND1 (Figure 6H,6I). These findings suggest that HSP90AA1 may regulate the cell cycle through regulating these specific proteins.

Figure 6 HSP90AA1 is crucial for the proliferation of LUAD cells. (A,B) Western blotting assay demonstrated that the interfering siRNA effectively reduced the protein expression of HSP90AA1. H1299 vs. Si-2: P=0.007, NC vs. Si-1: P=0.007, NC vs. Si-1: P=0.02. (C) The deletion of HSP90AA1 significantly inhibited the proliferation of H1299 cells. A PI staining was conducted to assess the cell cycle changes in the H1299 (D), NC (E), and Si-1 groups (F), with the statistical results presented in (G). (H,I) Knockdown of HSP90AA1 resulted in the downregulation of CCNB1 and CCND1 protein expression. NC vs. Si-1: P=0.007, H1299 vs. Si-2: P=0.008, NC vs. Si-1: P=0.01. *, P<0.05; **, P<0.01; ***, P<0.001. NC, negative control; Si-1, HSP90AA1 siRNA1; Si-2, HSP90AA1 siRNA2; OD, optical density; PI, propidium iodide; LUAD, lung adenocarcinoma.

Knockdown of HSP90AA1 induces apoptosis via the mitochondrial pathway

To clarify the effect of HSP90AA1 knockdown on apoptosis in LUAD cells, an Annexin V-FITC/PI assay was conducted to assess apoptosis in both control and siRNA interference groups. The results indicated that cells in the HSP90AA1 knockdown group exhibited a significantly higher early apoptosis rate (Figure 7A-7D). We selected HSP90AA1-siRNA1 to specifically knock down the expression of HSP90AA1 protein and verified it (Figure 7E,7F). Further experiments demonstrated that the down-regulation of HSP90AA1 protein levels led to a decrease in the expression of classical apoptotic mitochondrial pathway proteins, including Bcl-2, Bcl-xL and XIAP, while simultaneously increasing the expression of Bax, Samc and caspase-3 proteins (Figure 7G-7L). These findings suggest that HSP90AA1 knockdown induces apoptosis in H1299 cells through mitochondrial pathways.

Figure 7 Knockdown of HSP90AA1 induces apoptosis of H1299 cells via the mitochondrial pathway. (A-C) The Annexin V-FITC/PI staining assay was performed to evaluate changes in cell apoptosis among the H1299 (A), NC (B), and Si-1 groups (C), with the statistical results illustrated in (D). *, P=0.02. (E-L) The knockdown of HSP90AA1 (H1299 vs. Si-1: P=0.004, NC vs. Si-1: P=0.006) led to a downregulation of Bcl-2 (H1299 vs. Si-1: P=0.01, NC vs. Si-1: P=0.02), Bcl-xL (**, P=0.002), and XIAP (H1299 vs. Si-1: P=0.003, NC vs. Si-1: P=0.004), as well as an upregulation of Bax (NC vs. Si-1: P=0.01, ***, P<0.001), Samc (H1299 vs. Si-1: P=0.009, NC vs. Ssi-1: P=0.11), and caspase-3 (H1299 vs. Si-1: P=0.006, NC vs. Si-1: P=0.009) protein expression. NC, negative control, si-1, HSP90AA1 siRNA1; FITC, fluorescein isothiocyanate; PI, propidium iodide.

Discussion

LUAD is a prevalent form of lung cancer associated with significant clinical morbidity and mortality, posing a serious threat to human health (35,36). Early diagnosis and personalized treatment are recognized as effective strategies for managing lung cancer (37,38). Consequently, identifying biomarkers for the diagnosis and treatment of lung cancer is of paramount importance. Clinical data derived from The Cancer Genome Atlas (TCGA) database facilitates this process, making it more accessible and feasible.

HSP90AA1, also known as HSP90α, is an isoform of the HSP90 protein primarily localized in the cytoplasm (39). It plays a critical role in cellular biosynthesis and is involved in numerous important signal transduction pathways. HSP90AA1 contributes to the stability of associated proteins, regulates hormonal responses, and helps cells cope with stress (40). In cancer cells, HSP90AA1 enhances cell viability by promoting the stability of tumor-associated proteins, such as HER2 and AKT, thereby positioning it as a potential target for cancer therapy (41,42). Additionally, HSP90AA1 interacts with multiple hormone receptors to regulate hormone signaling, influencing various cellular physiological functions (41,43). Under stressful conditions, the expression of HSP90AA1 is upregulated, assisting cells in resisting damage and restoring normal function (44). Although the function of HSP90AA1 has been recognised, there have been few reports on the association of HSP90AA1 with NSCLC and its functional role.

In this paper, we compared the expression levels of HSP90AA1 in cancer tissues and normal tissues, revealing that HSP90AA1 is associated with the clinical stage and prognosis of LUAD. Additionally, we analyzed and evaluated the biological functions of HSP90AA1 in LUAD, as well as its interactions within the molecular network. Our findings indicate that HSP90AA1 is closely related to critical cellular functions, including the cell cycle, DNA repair, and immune cell infiltration. Employing cellular molecular biology techniques, we demonstrated that HSP90AA1 deficiency not only leads to cell cycle arrest in LUAD cells but also induces apoptosis in H1299 cells via the mitochondrial pathway.

While the functional role of HSP90AA1 in LUAD has been established, its specific molecular mechanism of action remains elusive. Further clinical data and results from cellular molecular biology experiments are necessary to elucidate this mechanism. This study serves as a foundational step in the investigation of HSP90AA1 in LUAD and offers a pathway for future, more in-depth research.

Conclusions

In this paper, we identified that HSP90AA1 played an important role in the development of LUAD. It suggested that HSP90AA1 may be a predictive biomarker for prognosis in LUAD. Targeting HSP90AA1 could be a powerful treatment strategy for LUAD.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2155/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2155/prf

Funding: This work was supported by the National Natural Science Foundation of China (Nos. 81860492 and 81660491); Jiangxi University of Chinese Medicine Research Fund (No. 2020BSZR001); and Top Discipline of Jiangxi Province, Discipline of Chinese and Western Integrative Medicine, Jiangxi University of Chinese Medicine (No. zxyylxk20220103).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-24-2155/coif). The authors have 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.

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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