1. Introduction
Cervical Squamous Cell Carcinoma (CESC), alongside breast, colorectal, and lung cancers, ranks among the four most prevalent malignancies in women [1]. CESC primarily manifests as two histological subtypes—squamous cell carcinoma and adenocarcinoma, with squamous cell carcinoma being more predominant, largely due to its association with human papillomavirus (HPV) infection [2]. Pathogens such as HPV [3], Helicobacter pylori, hepatitis B virus, and Epstein-Barr virus (EBV) contribute significantly to the rising morbidity and mortality of CESC. Clinical management strategies depend on tumor stage [4] and grade, with common interventions including radical hysterectomy [5] [6], brachytherapy [7], chemotherapy, immunotherapy [8], and combination therapies. Recent clinical trials have demonstrated that checkpoint inhibitors like ipilimumab and nivolumab synergistically modulate cervical tumor microenvironments, enhancing therapeutic efficacy [9]. However, due to the limited research on specific immune biomarkers for CESC and its persistently high mortality rate, identifying novel, highly sensitive, and specific tumor markers remains a critical research focus.
Tumor cells predominantly rely on glycolysis for energy supply, and excessive glycolytic activity has been established as a key driver of tumor progression [10]. Lactate dehydrogenase (LDH), a family of NAD+-dependent isoenzymes, catalyzes the interconversion of pyruvate and lactate while mediating the redox exchange between NADH and NAD+ [11]. This enzymatic activity underscores its pivotal role in the Warburg effect [12]. Notably, inhibition of lactate dehydrogenase A (LDHA) disrupts serine and aspartate biosynthesis, indirectly activating the GCN2-ATF4 signaling axis. This upregulates SLC1A5 expression and enhances glutamine/essential amino acid uptake, ultimately promoting mTORC1 activation and prolonging tumor cell survival [13]. Recently discovered LDH family members, lactate dehydrogenase A-like 6A (LDHAL6A) and 6B (LDHAL6B), are reportedly expressed exclusively in testicular tissue [14]. Additionally, antimetabolic agents have been shown to suppress CESC cell proliferation by targeting glycolysis-related proteins, such as lactate dehydrogenase B (LDHB) [15]. Lactate dehydrogenase C (LDHC), located on chromosome 7, was the first testis-specific isozyme identified in male germ cells [16]. Conversely, alterations in lactate dehydrogenase D (LDHD) expression influence lactate metabolism via glycolysis, with elevated LDHD levels observed in renal cell carcinoma [17] and esophageal squamous cell carcinoma [18] compared to normal tissues. Despite these findings, the roles of LDHC and LDHD in CESC pathogenesis remain poorly understood.
In this study, we comprehensively analyzed the expression profiles of LDH family members across human tissues and their differential expression patterns in pan-cancer. Utilizing multi-omics approaches, we investigated the LDH gene family’s involvement in CESC and evaluated its diagnostic and prognostic potential through GEO dataset validation. Receiver operating characteristic (ROC) curve analysis further confirmed the robust diagnostic efficacy of most LDH members in CESC prognosis. Kaplan-Meier (KM) survival analysis revealed significant associations between LDH family expression and patient survival, supporting their utility as prognostic biomarkers. Additionally, we conducted mutation interaction, methylation correlation, and immune infiltration analyses, complemented by cellular validation experiments focusing on LDHC. This systematic exploration elucidates the functional relevance of LDHC and other LDH members in CESC progression, diagnosis, and clinical outcomes, providing a theoretical foundation for future diagnostic and therapeutic strategies targeting the LDH family in CESC.
2. Materials and Methods
2.1. Data Source and Processing
The expression profiles, prognostic significance, and immune cell infiltration patterns of LDH gene family members were analyzed using data from the TCGA database (https://portal.gdc.cancer.gov) [19], accessed via the Xiantao Academic platform (https://www.xiantaozi.com/login). Transcripts per million (TPM) normalized expression matrices were downloaded and log2-transformed (log2[value + 1]) for downstream analyses. To externally validate the diagnostic and prognostic relevance of LDH genes in CESC, we obtained the GSE63514 and GSE44001 datasets from the GEO database (https://www.ncbi.nlm.nih.gov/geo) and plotted receiver operating characteristic (ROC) curves. The area under the ROC curve (AUC) was calculated, and the closer the value was to 1, the higher the diagnostic efficiency. In the analysis, normal controls were pathologically confirmed normal tissues (paired adjacent or healthy donor), with cases being histologically diagnosed CESC samples. The diagnostic value of these genes is significant for P < 0.05.
2.2. mRNA Expression Analysis of the LDH Family
The Human Protein Atlas (HPA) database (https://www.proteinatlas.org) [20] was employed to evaluate LDH family expression across human tissues. Using the “TISSUE” module and GTEx dataset, we queried the official gene symbols of LDH members (e.g., LDHA, LDHB) to generate tissue-specific expression profiles. Using the Xiantao Academic database, we selected three matched pairs of cervical cancer tumor tissues and adjacent normal tissues to compare LDH family gene expression profiles. The GSE63514 dataset was analyzed to confirm differential LDH expression in CESC versus normal cervical tissues. Diagnostic performance was assessed via receiver operating characteristic (ROC) curves using the “pROC” R package.
2.3. Protein Expression Levels of LDH Family Members
Immunohistochemical (IHC) staining results for LDH proteins in CESC and normal cervical tissues were retrieved from the HPA database using the “PATHOLOGY” and “TISSUE” modules. Clinical metadata for these samples were systematically curated to ensure relevance.
2.4. Prognostic Analysis of LDH Family Members
The Xiantao Academic database analyzed the association between LDH gene expression and three survival endpoints: Overall Survival (OS), Disease-Specific Survival (DSS) and Progress-Free Interval (PFI). Clinical and expression data from GSE44001 were processed via the Sangerbox platform (http://sangerbox.com/) as follows: Dataset and clinical metadata were retrieved using the “GSE44001” identifier. Probe annotation and data normalization were performed in the “Data Tabulation and Interactive Analysis” module. Survival analysis was conducted using the survival R package (v3.3.1), correlating LDH expression with CESC prognosis. Univariate and multivariate Cox regression models were applied to evaluate LDH genes as independent prognostic factors, implemented through the Xiantao Academic database.
2.5. Genetic Variation and Protein Interaction Networks of LDH
Family Members
To investigate the mutational landscape of LDH family members in CESC, we utilized the cBioPortal database (https://www.cbioportal.org/) [21]. Protein-protein interaction (PPI) networks for LDH family members were constructed using the GeneMANIA database (http://genemania.org) [22] and STRING database (https://cn.string-db.org/) [23]. Subsequently, interacting genes were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses via the “ClusterProfiler” R package, with results visualized using ggplot2.
2.6. DNA Methylation Analysis of LDH Family
DNA methylation levels of LDH family members were analyzed using the UALCAN online database (https://ualcan.path.uab.edu/) [24] [25]. The GSCALite database (http://bioinfo.life.hust.edu.cn/web/GSCALite/) [26] was employed to assess correlations between mRNA expression and DNA methylation, with results presented as scatter plots.
2.7. Correlation with Immune Cell Infiltration and Checkpoints
The Xiantao Academic Database (https://www.xiantaozi.com/login) was used to evaluate: Associations between LDH family gene expression and immune cell infiltration in CESC. Correlations between LDH members and immune checkpoint genes, including PDCD1, CD274, PDCD1LG2, CTLA4, LMTK3, LAG3, TIGIT, HAVCR2 and SIGLEC15.2.
2.8. Single-Gene Enrichment Analysis of LDHC
Using the Researcher’s Home database (https://www.home-for-researchers.com/#/), we explored LDHC-regulated signaling pathways in cervical cancer progression. CESC patients were stratified into high- and low-LDHC expression groups based on median expression values. Differentially expressed genes (DEGs) were identified using the “DESeq2” R package (|log2FC| ≥ 1.5, *p* < 0.05), followed by GO/KEGG enrichment analyses (“ClusterProfiler”) and visualization.2.
2.9. Cell Culture
HeLa cells (ATCC) were cultured in DMEM high-glucose medium (Gibco, C11995500BT) supplemented with 10% FBS (Sigma, F8318) and 1% penicillin/streptomycin (Gibco, 15140122) at 37˚C with 5% CO2. Cells in the logarithmic growth phase were harvested using trypsin (Gibco, 25200056) for experiments, with triplicate wells for all assays.
2.10. CCK-8 Assay
Cells (3,000/well) were seeded in 96-well plates (Corning, 3599) with 100 µL medium. Five plates were prepared to measure OD450 values at 0 h (post-attachment), 24 h, 48 h, 72 h, and 96 h. Before measurement, CCK-8 reagent (UElandy, C6005M) was diluted (10% medium: CCK-8 = 1:9), and 10 µL was added to each well. After 1-hour incubation, absorbance was measured using a VICTOR Nivo plate reader, and proliferation curves were plotted.
2.11. Colony Formation Assay
Log-phase cells (3,000/well) were seeded in 6-well plates (Corning, 3516) and cultured for 14 days (medium replaced every 2 - 3 days). When clusters reached 30 - 50 cells/field, cultures were terminated. Cells were: 1) Washed with PBS (Gibco, C10010500). 2) Fixed with 4% paraformaldehyde (biosharp, BL539A) for 30 min. 3) Stained with crystal violet (Solarbio, G1063) for 40 min. 4) Imaged, and colonies (>50 cells) were counted.
2.12. Wound Healing Assay
Cells were seeded in 6-well plates at a density of 2 × 105 cells/mL and incubated until reaching approximately 90% confluence. A uniform scratch was created using a sterile pipette tip perpendicular to the plate bottom. Initial wound area (0 h) was measured using an inverted microscope (Axio Vert A1, 07060200) by capturing multiple fields. After 48 h incubation, the same fields were re-imaged to measure remaining wound area. The migration rate was calculated as: Scratch healing rate (%) = [(0 h area − 48 h area)/0 h area] × 100ys.
2.13. Cell Invasion and Migration Assays
Transwell chambers (JET, TCS003024) were used for both assays. For invasion experiments, 100 μL Matrigel (Corning, 356234) was evenly coated and polymerized in the upper chamber. Cells (2 × 105 cells/mL in serum-free medium) were seeded in the upper chamber, while 10% FBS medium served as chemoattractant in the lower chamber. After 24 h incubation, non-migrated cells were removed with PBS. Migrated/invaded cells were fixed with 4% paraformaldehyde (50 min), stained with 0.1% crystal violet (50 min), and counted from four random microscope fields per chamber.
2.14. Western Blotting
Total protein was extracted using RIPA lysis buffer (Aase, PC103) supplemented with 1% PMSF (Aase, GRF101). Protein concentration was determined (Aase, ZJ102) and normalized. Samples were separated on 7.5% SDS-PAGE gels (Aase, PG211) at 80 V (40 min) then 120 V (35 min), followed by transfer to methanol-activated PVDF membranes (Millipore, IPVH00010) at 200 mA for 60 min. Membranes were blocked (Yase, PS108P, 40 min), incubated with primary antibodies (Proteintech LDHC: 19989-1-AP, 4˚C overnight) and HRP-conjugated secondary antibodies (Invitrogen 31460/31430, 2 h RT). Protein bands were visualized using ECL reagent (Accelerase, SQ201) and quantified with ImageJ.
2.15. Quantitative RT-PCR
Total RNA was extracted using TRIzol (Yingjie Life, 15596026) and reverse transcribed (Tolobio, 22107). qPCR was performed with SYBR Green (Tolobio, 22204-1) under conditions: 94˚C (3 min); 35 cycles of 94˚C (15 s), 64˚C (2 min), 72˚C (2 min); final extension at 72˚C (10 min). Relative expression was calculated via 2(−ΔΔCt) method. Primer sequences are listed in Table 1.
Table 1. Primer sequences used as target and reference genes used in qPCR reactions.
Gene name |
Primers |
Sequence |
LDHA |
forward primer |
CGGATCTCATTGCCACGC |
reverse primer |
CACCAACCCCAACAACTGTA |
LDHAL6A |
forward primer |
CTTGTCCTTGTGGATGTTGATG |
reverse primer |
TCTCCTTTTTTCTGGCGTGC |
LDHAL6B |
forward primer |
GAGTTGGACTGTGCCTGTTG |
reverse primer |
ATCTTGCTCACGGGGGT |
LDHB |
forward primer |
GACTTTGTCTTCTCCGCACGA |
reverse primer |
GCTGATAGCACACGCCATACC |
LDHC |
forward primer |
GCCATAACGACGCATACTAAAAG |
reverse primer |
GCCATAACGACGCATACTAAAAG |
LDHD |
forward primer |
CAACCTCACGGGGCTCTTCG |
reverse primer |
AACTCAATGCGGGCTACGGG |
GAPDH |
forward primer |
CCTGGGAAACCTGCCAAGTATG |
reverse primer |
GGTCCTCAGTGTAGCCCAAGATG |
2.16. Statistical Analysis
The Mann-Whitney U test was used to analyze the expression levels of unpaired samples of LDH family in pan-cancer, and the Wilcoxon singed rank test was used to process the paired samples. The prognostic survival analysis of LDH family in pan-cancer was performed by one-way and multifactorial Cox regression test as the statistical analysis of variance. Immunocorrelation analysis using Spearman correlation coefficient was used to determine the relationship between two variables. Experimental data were taken as mean ± standard deviation after three independent experiments, and paired samples were statistically analyzed using the paired t-test, with p ≤ 0.05 considered statistically significant.
3. Results
3.1. Tissue-Specific Expression of LDH Family Members
The study design is illustrated in Figure 1. Analysis of the Human Protein Atlas (HPA) database revealed distinct tissue distribution patterns for LDH family members (Figure 1). LDHA demonstrated predominant expression in retina, liver, and skeletal muscle, while LDHB showed significantly higher expression in midbrain, kidney, and cardiac muscle—tissues with high aerobic metabolic activity. Consistent with previous reports, both LDHAL6B and LDHC exhibited exclusive testicular distribution. LDHD was primarily expressed in liver, cardiac muscle, and skeletal muscle. These findings collectively demonstrate that LDH family members display tissue-specific expression patterns, with particular enrichment in organs exhibiting high oxygen consumption.
3.2. Pan-Cancer mRNA Expression Profiling
Our comprehensive analysis revealed cancer-type specific expression patterns for each LDH family member (Figure 2). LDHA was significantly upregulated in 14 cancer types including BRCA, CESC, and GBM, while being downregulated in KICH (Figure 2(A)). LDHAL6A showed elevated expression in CHOL, LIHC and STAD tumors compared to 11 other cancer types where its expression was reduced (Figure 2(B)). LDHAL6B expression was increased in GBM, HNSC, KIRC and STAD tumor tissues relative to their normal counterparts (Figure 2(C)). LDHB exhibited upregulation in 8 cancer types including CHOL and LIHC, but downregulation in 6 others (Figure 2(D)). LDHC was overexpressed in CESC, ESCA and HNSC tumors while being underexpressed in 5 cancer types (Figure 2(E)). Notably, LDHD showed tumor-specific expression limited to KICH and LUAD, despite being widely expressed in normal tissues (Figure 2(F)).
Figure 1. General flow chart of the article.
Figure 2. Expression analysis of LDH family in pan-cancer. (A) LDHA; (B) LDHAL6A; (C) LDHAL6B; (D) LDHB; (E) LDHC; (F) LDHD.
3.3. Differential Expression in Cervical Cancer
Comparative analysis between CESC and adjacent normal tissues yielded important findings (Figure 3). TCGA data revealed significant upregulation of LDHA and LDHC in tumor tissues, while LDHAL6B showed higher expression in normal tissue (Figure 3(A)-(F)). External validation using GSE63514 dataset confirmed increased expression of LDHAL6A, LDHB and LDHC in tumors, with LDHD being more highly expressed in normal cervical tissue (Figure 3(G)-(L)). PCR validation of clinical samples largely corroborated these findings, showing predominant tumor overexpression of most LDH members except for LDHAL6B and LDHD (Figure 3(A)-(F)).
Figure 3. Expression analysis of LDH gene family in cervical cancer. (A) - (F) Differential expression of LDH gene family members in the TCGA database. (G) - (L) Differential expression of LDH family members in the external validation GES63514.3.4. Some Common Mistakes.
3.4. Diagnostic Potential in CESC
ROC curve analysis demonstrated the diagnostic value of LDH family members in CESC. TCGA data revealed exceptional diagnostic performance for LDHC (AUC = 0.950, 95% CI: 0.921 - 0.980) and LDHA (AUC = 0.915, 95% CI: 0.766 - 1.000), with other members showing moderate diagnostic value (Figure 4(A)-(F)). The GSE63514 validation cohort confirmed LDHC’s strong diagnostic potential (AUC = 0.884) (Figure 4(G)-(L)). These consistent results across independent datasets highlight LDHC as the most promising diagnostic biomarker among LDH family members for cervical cancer.
Figure 4. Diagnostic efficacy of LDH gene family in cervical cancer. (A) - (F) Diagnostic efficacy of LDH gene families in the TCGA database. (G) - (L) Diagnostic efficacy of LDH gene family members in the external validation dataset GES63514.
3.5. Protein Expression Validation
Immunohistochemical analysis from the HPA database provided protein-level confirmation of our findings. LDHA, LDHB and LDHD all showed significantly higher protein expression in CESC compared to normal cervical tissues (Figure 5(A)-(F)). The remaining three LDH family members were not detectable in the database, suggesting potential tissue-specific expression limitations.
Figure 5. Protein levels of LDH family in cervical cancer. (A) - (B) Protein expression levels of LDHA in normal cervical tissues and cervical cancer tissues, respectively; (C) - (D) Protein expression of LDHB in normal cervical tissues and cervical cancer, respectively.
3.6. Prognostic Significance in CESC
Survival analysis revealed important clinical correlations (Figure 6). High expression of LDHA and LDHAL6B was associated with worse overall survival (OS), while elevated LDHB, LDHC and LDHD correlated with better outcomes (Figure 6(A)-(F)). Similar trends were observed for disease-specific survival (DSS) and progression-free interval (PFI), with LDHC-high patients showing particularly favorable prognosis (Figure 6(G)-(L), Supplementary Figure 4(A)-(F)). External validation using GSE44001 dataset confirmed the adverse prognostic association of LDHA, LDHAL6A and LDHAL6B high expression (Supplementary Figure 4(G)-(L)).
Figure 6. Effect of LDH gene family on survival of cervical cancer patients. (A) - (F) Effect of LDH gene family members in the TCGA database on overall survival (OS) of cervical cancer patients. (G) - (L) Effect of LDH gene family members in the TCGA database on disease-specific survival (DSS) in cervical cancer patients.
Cox regression analysis identified four genes (LDHA, LDHAL6B, LDHC, LDHD) as significant prognostic factors in univariate analysis. Multivariate analysis further established LDHAL6B as an independent prognostic marker for CESC patients.
3.7. Mutation and Protein Interaction Networks of LDH Family
Members
Comprehensive analysis of mutation patterns in CESC using the cBioPortal database revealed distinct mutation frequencies among LDH family members: LDHA (0.9%), LDHAL6A (0.8%), LDHAL6B (1%), LDHB (2.2%), LDHC (1.1%), and LDHD (1.5%), with gene amplification being the predominant mutation type (Figure 7(A)-(B)). Protein-protein interaction (PPI) networks constructed through GeneMANIA and STRING databases demonstrated extensive functional associations between LDH members and other proteins (Figure 7(C)-(D)). Subsequent functional enrichment analysis revealed that interacting proteins were primarily involved in critical metabolic processes including dicarboxylic acid metabolism, lactate metabolism, pyruvate metabolism, and energy production (Figure 7(E)). KEGG pathway analysis further identified significant enrichment in pyruvate metabolism, cysteine and methionine metabolism, carbon metabolism, glycolysis/gluconeogenesis, and propanoate metabolism (Figure 7(F)), highlighting the central role of LDH family members in cellular metabolic regulation.
3.8. DNA Methylation Patterns of LDH Family Members
Methylation analysis using UALCAN database demonstrated significant epigenetic differences between CESC and normal cervical tissues (Figure 8(A)-(F)). Notably, LDHB exhibited significantly higher methylation levels in tumor tissues, while LDHC showed marked hypomethylation. Correlation analysis between mRNA expression and methylation status revealed a significant negative association for LDHAL6A, LDHAL6B, LDHB, LDHC, and LDHD (Figure 8(G)-(L)), suggesting potential epigenetic regulation of these genes in cervical carcinogenesis. No significant correlation was observed between LDHA expression and methylation status.
3.9. Immune Microenvironment Associations of LDH Family
Members
Comprehensive immune correlation analysis revealed distinct patterns of association between LDH family expression and immune cell infiltration (Figure 9). LDHA expression showed positive correlation with Th2 cells and neutrophils, while demonstrating negative associations with multiple immune cell types including eosinophils, Tregs, and dendritic cells. LDHAL6A exhibited positive correlations with Thelper cells and Tcm, while LDHAL6B showed associations with Thelper cells and neutrophils. Particularly noteworthy was LDHC’s exclusive positive correlation with NK CD56bright cells and negative association with TFH cells and macrophages. Immune checkpoint analysis demonstrated significant correlations between LDH members and key checkpoint molecules (Supplementary Figure 2(A)-(F)), with LDHD showing the most extensive interaction profile, including positive correlation with LMTK3 and negative associations with multiple checkpoints (CD274, PDCD1LG2, CTLA4, LAG3, and HAVCR2).
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Figure 7. Mutational features of LDH gene family members and protein interactions network. (A) - (B) Mutational features of LDH family member genes in cervical cancer were described using the cBioPortal database; (C) construction of LDH gene family member interactions networks based on the Gene MANIA database; (D) analysis of protein interactions networks of LDH family members based on the STRING database; (E) - (F) GO and KEGG enrichment analysis.
Figure 8. Methylation analysis of LDH gene family members. (A) - (F) Analysis of methylation level differences between LDH gene family members in cervical cancer tissues and paracellular carcinomas based on the UALCAN database; (G) - (L) Correlation between gene expression and methylation levels of LDH gene family members analyzed using MethSurv database.
Figure 9. Correlation analysis of LDH gene family members with the level of immune cell infiltration in cervical cancer patients. (A) LDHA; (B) LDHAL6A; (C) LDHAL6B; (D) LDHB; (E) LDHC; (F) LDHD.
3.10. Functional Enrichment Analysis of LDHC in CESC
To elucidate LDHC’s functional role in CESC progression, we performed single-gene enrichment analysis after stratifying patients into high-(G1) and low-expression (G2) groups based on median LDHC expression. Differential expression analysis identified 264 significantly altered genes (226 upregulated, 38 downregulated) between the groups (Figure 10(A)-(B)). KEGG pathway analysis of upregulated genes revealed enrichment in tyrosine metabolism, transcriptional misregulation in cancer, and sulfur metabolism pathways (Figure 10(C)), while GO analysis highlighted involvement in developmental processes including ureteric bud development and sensory organ morphogenesis (Figure 10(D)). Downregulated genes were significantly enriched in pathways including α-linolenic acid metabolism and small cell lung cancer (Figure 10(E)), with GO terms related to immune regulation such as neutrophil migration and degranulation. These findings suggest LDHC may play multifaceted roles in both metabolic reprogramming and immune modulation during cervical cancer progression.
3.11. Validation of LDH Gene Family Expression and Functional
Characterization of LDHC in CESC
To validate the expression patterns of LDH family members in cervical cancer, we analyzed clinical CESC specimens and adjacent normal tissues. Our results demonstrated significant upregulation of LDHA, LDHAL6A, LDHB and LDHC in tumor tissues, while LDHAL6B and LDHD showed marked downregulation (Figure 3). Given LDHC’s prominent diagnostic and prognostic value in CESC revealed by our preliminary analyses, coupled with the absence of prior functional studies, we selected this gene for further investigation using the Hela cell line. Successful knockdown of LDHC was confirmed at both transcriptional (qPCR) and translational (Western blot) levels (Figure 11(A)-(C)). Functional assays revealed that LDHC depletion significantly enhanced the malignant phenotype of CESC cells. CCK-8 proliferation assays showed accelerated growth kinetics in LDHC-knockdown cells (Figure 11(D)). This pro-tumorigenic effect was further supported by colony formation assays demonstrating increased proliferative capacity (Figure 12(A)), wound healing assays revealing enhanced migratory potential (Figure 12(B)), and Transwell experiments confirming greater invasive capability (Figure 13(A)-(B)). Collectively, these findings position LDHC as a potential tumor suppressor in cervical carcinogenesis.
4. Discussion
Our study provides the first comprehensive characterization of LDH family members in CESC, addressing a critical knowledge gap in the field. Through systematic analysis of expression patterns across normal and malignant tissues, we have identified distinct tissue-specific distributions: while LDHA, LDHB and LDHD exhibit ubiquitous expression, LDHAL6B and LDHC demonstrate testis-specific localization, consistent with their classification as testicular lactate dehydrogenase isoforms [27] [28]. Notably, pan-cancer analysis revealed consistent overexpression of multiple LDH members in CESC and other malignancies, suggesting their potential as diagnostic biomarkers.
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Figure 10. Single-gene pathway enrichment analysis of LDHC. (A) Differentially expressed genes (DEGs) in the LDHC high and low expression groups demonstrated by volcano plots; (B) Expression levels of LDHC high and low groups demonstrated by heatmaps; (C) KEGG pathway enrichment analysis of up-regulated genes; (D) GO pathway enrichment analysis of up-regulated genes; (E) KEGG pathway enrichment analysis of down-regulated genes; (F) GO pathway enrichment analysis of down-regulated genes.
Figure 11. Construction of LDHC knockdown cell lines and the effect of LDHC knockdown on the proliferative ability of cervical cancer cells. (A) Verification of protein expression level differences between LDHC knockdown cell groups and wild cell lines by WB assay; (B) Quantitative analysis of protein levels after LDHC knockdown; (C) Verification of mRNA expression level changes after LDHC knockdown by RT-qPCR assay; (D) CCK8 proliferation assay of Cell.
Figure 12. Effect of LDHC knockdown on proliferation and healing ability of cervical cancer cells. (A) cell clone formation experiment; (B) cell scratch healing experiment.
Figure 13. Effect of LDH knockdown on the migration and invasion ability of cervical cancer cells. (A) cell migration assay; (B) cell invasion assay.
The prognostic significance of LDH family members in CESC appears complex. While most members (LDHA, LDHB) correlate with poor outcomes when overexpressed, potentially through mechanisms like JNK-mediated apoptosis [29] or cis-platin resistance [15], LDHC presents a striking exception. LDHC demonstrates marked tissue-specific expression, suggesting its potential involvement in cervical carcinogenesis through distinct molecular regulatory mechanisms. Our clinical da-ta associate high LDHC expression with improved survival, a finding corroborated by functional studies showing that LDHC knockdown enhances proliferation, migration and invasion in Hela cells. Furthermore, our immune infiltration analysis revealed specific correlations between LDHC and antitumor immune cells, particularly NK CD56bright cells. This tumor-suppressive role contrasts with the onco-genic functions reported for other LDH isoforms and warrants further investigation to elucidate the underlying molecular mechanisms.
These findings have important implications for understanding cervical cancer pathogenesis and developing targeted therapies. The differential effects of LDH family members suggest that therapeutic strategies may need to be isoform-specific, particularly given LDHC’s unique protective role. Future studies should explore whether LDHC’s antitumor effects involve metabolic reprogramming or interactions with specific signaling pathways in cervical epithelial cells.
Our comprehensive mutation analysis revealed that LDH family members exhibit high mutation frequencies across various cancers, with amplification being the predominant mutation type. Notably, in Group 3 medulloblastoma, LDHA expression positively correlates with MYC amplification, suggesting LDHA inhibition as a potential therapeutic strategy [30]. Similarly, LDHB overexpression associates with KRAS copy number increases and mutations in lung cancer [31]. These findings collectively indicate that amplification-driven overexpression of LDH isoforms may serve as important oncogenic drivers and potential therapeutic targets.
Protein interaction network analysis demonstrated significant functional connections among LDH family members, with GO and KEGG enrichment analyses highlighting their involvement in key metabolic processes including lactate metabolism, pyruvate metabolism, and glycolysis/gluconeogenesis. These pathways play crucial roles in tumor biology, where pyruvate metabolism fuels cellular energy demands while lactate accumulation in the tumor microenvironment promotes immune evasion and supports malignant progression [32]. Our results suggest that LDH-mediated metabolic reprogramming may significantly contribute to CESC pathogenesis.
DNA methylation analysis revealed distinct epigenetic patterns among LDH isoforms in CESC. We observed hypermethylation of LDHB contrasting with hypomethylation of LDHC, both showing significant negative correlations with their respective expression levels. This finding aligns with existing literature demonstrating that LDHA promotes HPV16 expression through H3K79 methylation [33], while LDHB promoter methylation suppresses its tumor-suppressive function in breast and liver cancers [31] [34]. Interestingly, LDHC’s demethylation pattern mirrors its testis-specific expression profile [35], supporting our hypothesis that methylation status regulates LDH isoform expression in tissue-specific manners. While direct evidence linking all LDH members to CESC remains limited, our findings strongly suggest that differential methylation contributes to tumorigenesis through metabolic pathway modulation.
Our immune correlation analysis uncovered complex relationships between LDH family members and tumor immunology. High LDHA expression correlated with poor patient survival, consistent with reports that LDHA-derived lactate accumulation impairs T cell and NK cell function in melanoma [36]. Similarly, LDH-related genes may promote CESC progression by activating M2 macrophages and inhibiting dendritic cell activation [37]. Immune checkpoint analysis revealed significant associations between LDH isoforms and key regulators including CTLA-4, PD-1, and PD-L1, which are critical targets for cancer immunotherapy [38] [39]. Notably, dual blockade of PD-L1 and LAG3 demonstrates enhanced anti-tumor efficacy [40], suggesting potential combination strategies for CESC treatment.
Single-gene enrichment analysis implicated LDHC in the IL-17 signaling pathway, which plays established roles in inflammation and tumorigenesis [41]. While glycolytic genes typically promote tumor progression through IL-17 pathway activation [42], our functional studies revealed LDHC's unexpected protective role in CESC. Knockout experiments demonstrated that LDHC depletion enhances tumor cell proliferation, migration, and invasion—a novel finding that challenges conventional understanding of LDH family functions. Although limited by the absence of in vivo validation and clinical sample constraints, these results position LDHC as a potential tumor suppressor in cervical carcinogenesis.
Our findings regarding the tumor-suppressive role of LDHC in CESC underscore the significant impact of the LDH family in the pathogenesis of gynecologic malignancies. This observation aligns with recent studies emphasizing the critical and distinct functions of LDH isoforms. For instance, LDHB has been demonstrated to contribute to immune evasion in ovarian cancer cells [37], whereas LDHA plays a contrasting role in promoting the survival and proliferation of cervical cancer cells under energy stress conditions [43]. These collective findings indicate that the functional roles of the LDH family warrant further investigation. Future work should aim to elucidate whether the protective effect of LDHC is specific to the pathogenesis of CESC or represents a broader, previously unrecognized tumor-suppressive pathway in other gynecologic malignancies.
5. Conclusion
Our study establishes LDHC as a clinically significant biomarker in CESC, with high expression correlating with favorable outcomes. Functional characterization revealed its unique tumor-suppressive properties, as evidenced by enhanced malignant phenotypes following gene knockout. These findings provide novel insights into LDH family biology and suggest LDHC as a potential therapeutic target for cervical cancer management.
Acknowledgements
We appreciate the valuable suggestions from our colleagues on manuscript revision.
Author Contributions
Professor Dong and Professor Liao are responsible for the research design and writing guidance, while SX mainly participates in the experiment. SX and XZ are mainly involved in cell culture and statistical analysis. YH participated in the initial draft drafting and bioinformatics analysis. YL and ZX provide guidance for the experiment. All authors have made significant contributions to this article and have approved its submission.
Ethics Statement
The research pertaining to human tissues underwent a thorough examination and received approval from the Institutional Research Ethics Committee of Affiliated Hospital of Youjiang Medical University for Nationalities (Ethical review number: YYFY-LL-2023-145).
Funding
Funded by the Youth Fund Program of the Guangxi Natural Science Foundation (2023JJB140064) and the Project of Baise Scientific Research and Technology Development Plan in 2024 (Grant No. 20250321, 20250315).
Data Availability Statement
The data underlying in this study are freely available from the TCGA, GEO, GTEx, GeneMANIA, STRING, Xiantao Academic, Home for Researchers, and HPA databases. All the original findings shown within the investigation are involved in the article/Supplementary Material. Regarding clinical trial number: Not applicable.