CD44 on cancer stem cell is a potential immunological and prognostic pan-cancer biomarker

CD44 on cancer stem cell is a potential immunological and prognostic pan-cancer biomarker | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CD44 on cancer stem cell is a potential immunological and prognostic pan-cancer biomarker Yajuan Zhu, Zhuoyuan Zhang, Shan Shan Yang, Yang Du, Jiyan Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4921451/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Apr, 2025 Read the published version in Cancer Cell International → Version 1 posted 11 You are reading this latest preprint version Abstract Background CD44, a widespread cancer stem cell marker, displayed a vital participation in the cancer immune invasion and may related with the response to the immunotherapy. However, the role of CD44 in cancer immunology is not well defined. Therefore, we intended to explore the prognostic value and the potential immunological functions in 33 human cancer types. Methods Based on the data of patients from The Cancer Genome Atlas (TCGA)and Genotype-Tissue Expression (GTEx) databases, Sangerbox was used to analyze the correlations between CD44 expression and tumor-infiltrated immune cells, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens in human cancers. Results We found that elevated CD44 is associated with tumor stage and prognosis in different cancers. GSEA results showed that upregulated CD44 involved in cancer stem cell associated process, antigen processing and presentation, and immune response, including immune cell proliferation and activation. Furthermore, CD44 plays an essential role in the tumor microenvironment and participates in immune regulation. The correlation of CD44 gene expression and infiltration levels of most immune cells differed according to the caner types. Notably, the upregulation of CD44 expression is correlated notably positively with Treg, macrophages M1 and M2 in most analyzed cancers, especially in testicular germ cell tumor. Furthermore, we further verified the effect of CD44 on tumor growth and immune microenvironment in mouse xenografted with shRNA-CD44 MC38. Moreover, DNA methylation existed in CD44 expression and associated with dysfunctional T-cell phenotypes via different mechanisms, thus resulting in tissue-dependent prognoses. Conclusion CD44 may serve as a potential prognostic and immunological biomarker in various malignant tumors. Moreover, CD44 could be a novel target for tumor immunotherapy. CD44 infiltrated immune cells immune checkpoints cancer prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Tumor microenvironment (TME) comprises a variety of cells, among which infiltrating immune cells account for a large proportion( 1 ). Cancer is not a genetic disease but an ecological disease: a multidimensional spatiotemporal “unity of ecology and evolution” pathological ecosystem( 2 ). The interactions of TME and host immunity have become increasingly important in cancer therapy. Immunotherapy, including immune checkpoints inhibitors (ICIs), therapeutic vaccines and engineered T cells has been developed in the cancer treatment( 3 ). Especially, immune checkpoints inhibitors, such as programmed death-1/programmed cell death ligands (PD1/PD-Ls), cytotoxic T lymphocyte-associated antigen-4 (CTLA4), and anti-lymphocyte activation gene 3 (LAG3) shown promising clinical benefits in different malignancies and brought promising perspectives to patients with cancer. However, not all patients can benefit from ICIs because of the existed or acquired resistance( 4 ). In addition, there are still no effective prognostic biomarkers for the ICIs treatment. Therefore, more effective targets or biomarkers is urgently needed to be identified as anticancer drugs. The Cancer Genome Atlas (TCGA), a public database, provides a chance to perform pan-cancer gene analyses and evaluate their roles in the immune infiltration and cancer prognosis( 5 ). CD44, a cartilage link protein family member, is a receptor for hyaluronic acid (HA) and interact with various ligands, such as versican, osteopontin, fibronectin, and matrix metalloproteinases (MMPs). This transmembrane glycoprotein participates in a wide variety of cellular functions, including lymphocyte activation, recirculation, homing, and tumor metastasis( 6 , 7 ). CD44 is overexpressed as standard isoform (CD44s) or alternatively spliced variant isoforms (CD44v) in CSCs and frequently underwent alternative splicing to support cancer progression and related with poor survival( 7 ).The cluster of differentiation of CD44 has been recognized as a cancer stem cell marker and therapeutic targets in various cancers. Targeted inhibition of CD44 for therapeutic intervention, including CD44 neutralizing antibodies, pharmacological inhibitors, peptide mimetics, HA oligomers and aptamers are developed in various stages of preclinical and clinical trials( 8 ). CD44 participated in several processes associated with immune responses.CD44 expression is upregulated on naive T cells after activation via the T cell receptor (TCR).CD44 was essential for the generation of memory T helper 1 (Th1) cells and has implications in many diseases( 9 ). As for cancer, CD44 is highly expressed in gastric cancer and associated with gastric immune invasion. CD44 can be used as a prognostic biomarker of gastric cancer( 10 ). In triple-negative breast cancer (TNBC) and non–small cell lung cancer (NSCLC), CD44 positively regulated the PD-L1 expression through binding to the regulatory region of PD-L1 locus( 11 ). CD44 displayed a vital participation in the cancer immune invasion and may related with the response to the immunotherapy. However, the role of CD44 in caner immune microenvironment and cancer therapy is not well defined. In our pan-cancer analysis study, we comprehensively described the cellular location and mRNA expression of CD44 in healthy body. Then we investigated the alternations of CD44 and their prognostic values in TCGA cancer types. To explore the role of CD44 in the possible mechanism of immune invasion, we analyzed the relationship between CD44 alterations and immune cell infiltrations in tumor, immune checkpoint genes, tumor mutation burden (TMB) level, along with microsatellite instability (MSI) event. The relationship between CD44 methylation with T-cell dysfunctions and the effectiveness of ICI therapies was also calculated. 2. Materials and methods Data and software availability All original data were downloaded from The Cancer Genome Atlas (TCGA) ( https://cancergenome.nih.gov/ ) and Genotype-Tissue Expression (GTEx) (http://commonfund.nih.gov/GTEx)databases.Sangerbox( https://doi.org/10.1002/imt2.36,Version3.0 ) was used to extract CD44 (ENSG00000026508) gene expression data from these public database and convert it into a data matrix for subsequent analyses. CD44 location and expression analysis The representative immunofluorescence staining of CD44 were retrieved from the Human Protein Atlas (HPA) database ( http://www.proteinatlas.org ). Meanwhile, the colon cell lines (HT29 and HCT116) were stained with CD44 antibody to certify the expression and the subcellular locations in tumor cells. A gene network interaction analysis of CD44 was analyzed(gpsprot.org/index.php). Furthermore, the expression of CD44 were Log2 transformed and visualized by R software (Version 4.0.2; https://www.Rproject.org ) and “ggplot2” package. CD44 methylation data from cBioPortal ( www.cbioportal.org ) were used. Promoter methylation levels are displayed by beta values ranging from 0 (unmethylated) to 1 (fully methylated) for each tumor. The correlation of CD44 methylation with prognosis and dysfunctional T-cell phenotypes were conducted using the TIDE server. Multivariate Cox regression analysis and survival analysis To assess whether the high expression level of CD44 independently was the predictor of patient prognosis, including overall survival (OS), cancer-specific survival (CSS) of cancer with different cancer. The univariate Cox regression analysis and log-rank test were conducted. The “survival” package was utilized to plot the survival curves. The relationship between CD44 expression and survival outcome in pan-cancer was manifested as forest plots using the R packages “forestplot”. The biological significance of CD44 expression in tumors Gene Set Enrichment Analysis (GSEA) was conducted to investigate the biological functions of CD44 in tumors. Samples were separated into a high-CD44 group and a low-CD44 group, and the GSEA software was used to enrich the gene ontology (GO) and MSigDB database. Relationship between CD44 expression and immunity The association of between CD44 expression and maker genes of the immune response process, including the antigen presentation, immune receptor, chemokine, immune stimulator and inhibitor, and immune checkpoint was analyzed on the Sangerbox website. Then we estimated whether the mRNA expression of CD44 is associated with the immune infiltration landscapes in different tumor types. The enrichment score for each immune cell in 33 tumors were quantified in the Tumor Immune Estimation Resource 2.0 (TIMER2.0) web server, and the correlation between CD44 gene expression and these immune infiltrating cells was analyzed. Moreover, we explored the relationship between CD44 and tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens in human TCGA cancers. Immunofluorescence staining The paraffin-embedded sections of tumor tissues were heated at 50°C for 1.5 h. The deparaffinized slides were processed for antigen retrieval by microwave heating in EDTA Tris-HCl buffer (pH8.0) for 15min. To reduce background staining, the sections were treated for 1 h with 1% normal goat serum (Boster, Wuhan). The samples were incubated with the rabbit Ab against CD44 (Proteintech, Wuhan) overnight at 4°C.Next, the secondary rabbit antibody with FITC (Boster, Wuhan) were incubated for 1 h. The immunohistochemistry images were collected using a confocal microscope (Nikon, Japan). Colon cancer and adjacent tissues from COAD patients who had surgical resection at the West China Hospital in Sichuan Province, China, between 2016 and 2017 were gathered for this study. None of the patients received radiotherapy, chemotherapy, or immunotherapy before the operation. The West China Hospital’s Medical Ethics Committee gave its approval to all operations (decision No. 2024664). Cell culture and in vitro testing The mouse colon cell line MC38 was purchased from the American Type Culture Collection (Rockville, MD, USA) and cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 100 U/ml penicillin/streptomycin (Gibco, Carlsbad, CA, USA) in a humidified chamber with 5% CO 2 at 37°C. Stable MC38 cell line expressing shRNA -CD44 was using lentiviral delivery system. Then, the antibody CD44 (clone IM7) was used to detect the expression of CD44 in MC38 and MC38-shRNA CD44 via flow cytometry. The CCK8 kit (Dojindo, Japan) was used to evaluate the cell proliferation and clonogenic assays are used for testing the capability of forming colonies of two cell lines. The migrated cells were detected via Transwell chamber assay. Animal studies MC38 cells in the logarithmic growth phase (1x10 6 cells/200µl) were subcutaneously inoculated into the right flanks of female C57BL/6 mice (6 weeks old). After 15 days, the 4 mice each group were sacrificed to obtain the tumor issues. The survival time of the remaining mice were observed until 35 days after the inoculation. All animal procedures were performed according to the protocol approved by the West China Hospital Animal Care and Use Committee. Immune cell markers analysis Cells disserted from tumor tissue were stained with antibodies and analyzed by flow cytometry. The following antibodies and dye were obtained from BioLegend: CD45(clone 30-F-11), CD4 (clone RM4-5), CD8 (clone 145-2c11), CD25 (clone 3C7), Foxp3(clone MF23), CD11b (clone M1/70), F4/80 (clone T45-2342), CD86(clone GL-1), CD206(clone C068C2), CD11c(HL3), MH-II (clone M5/114.15.2), Gr1 (clone RB6-8C5), and fixable viability stain 620. Stained cells were analyzed on BDLSR Fortessa TM (BD Biosciences) and FlowJo software. Statistical Analysis Differences between two groups and multiple groups were analyzed using a Student’s t-test and one-way analysis of variance (ANOVA), respectively. Survival analysis was conducted using Kaplan–Meier method, and Pearson correlation analysis was utilized to calculate correlation coefficients. Those mentioned analyses above is conducted by R software (Version 4.0.2). A two-tailed P-value < 0.05 was defined as the threshold of significance. 3. Results CD44 localized in cytoplasm and membrane of tumor cell and significantly associated with cancer Gene and disease network interactions revealed that CD44 had 151 gene functional partners and the top 15 interacted genes were shown in Fig. 1 A. The Open Target platform showed that total 980 diseases or phenotypes were associated with CD44 expression. Among these, solid cancer, such as breast cancer, hepatocellular carcinoma, glioblastoma, urinary bladder carcinoma non-small cell lung carcinoma and chronic myelogenous leukemia displayed a relationship with CD44 expression ( Fig. 1 B ) . To evaluate the distribution and expression of CD44 in tumor cell, we retrieved the immunofluorescence results of A-431, U-2OS, and U251-MG from the HPA database. The endoplasmic reticulum (ER) and microtubules were marked with yellow and red, respectively. It was observed that CD44 overlapped with ER and microtubules but displayed no staining in the nuclei, suggesting that CD44 colocalized with these markers in the cytoplasm of tumor cell ( Fig. 1 C ) . In addition, our immunofluorescence staining results also demonstrated the location of CD44 in the colon cancer cell lines (HT29 and HCT116) ( Fig. 1 D ) . Furthermore, compared with the adjacent tissue, the number of cancer cells expressing CD44 were increased in cancer tissue of colon cancer patients ( Fig. 1 E ) . These results suggests that CD44 expression showed a relationship with various cancers and colon cancer patients had increased number of tumor cell expressing CD44 in tumor tissue. CD44 is significantly aberrantly expressed in various tumors tissues and associated with tumor stages To further clarify the association of CD44 and cancer, the CD44 expression were evaluated in all types of cancer from TCGA databased. Compared with the normal tissues, the significantly overexpressed CD44 was observed in 25 tumors. The top 5 items were glioblastoma multiforme (GBM) (T:7.59 ± 1.15, N:2.70 ± 1.59, p = 1.8e- 83), glioma (GBMLGG)(T:6.26 ± 1.59,N:2.70 ± 1.59, p = 8.4e-204),brain lower grade glioma (LGG)(T:5.86 ± 1.48,N:2.70 ± 1.59,p = 2.4e-159),breast invasive carcinoma(BRCA)(T:7.52 ± 1.18, N:7.02 ± 0.82, p = 7.7e-13), and cervical squamous cell carcinoma and endocervical adenocarcinoma(CESC) (T:7.61 ± 1.17, N:7.04 ± 0.89, p = 0.04). In contrast, we observed significant downregulation in six tumors such as uterine corpus endometrial carcinoma (UCEC) (T: 5.71 ± 1.42, N: 6.59 ± 1.19, p = 2.4e-3), lung adenocarcinoma (LUAD) (T:6.87 ± 1.05, N:7.58 ± 0.64, p = 8.6e-29), and prostate adenocarcinoma (PRAD)(T:6.10 ± 1.08, N:6.59 ± 0.69,p = 1.6e-6) ( Fig. 2 A ) .In addition, we found that CD44 expression is significantly increased from stage I to IV of PAAD(Stage I = 21,II = 147,III = 3,IV = 4,p = 0.01), and stomach and esophageal carcinoma(STES)(Stage I = 76,II = 201,III = 230,IV = 57,p = 0.02), pan-kidney cohort (KIPAN)(Stage I = 464,II = 107,III = 189,IV = 103,p = 0.01).Of note, BRCA(Stage I = 182,II = 617,III = 248,IV = 20,p = 1.4e-3) displayed a relative decrease in the stage IV ( Fig. 2 B ) .Then, we analyzed the CD44 expression in G1-G3 or G4 of pan-cancer. We found that CD44 expression had an continuous upregulation from Grade 1 to Grade4 of GBMLGG(G2 = 247,G3 = 260,p = 1.8e-5),LGG(G2 = 247,G3 = 260,p = 1.8e-5),ESCA(esophageal carcinoma)(G1 = 18,G2 = 74,G3 = 49,p = 8.8e-3),STES(G1 = 30,G2 = 222,G3 = 294,p = 0.04),KIPAN(G1 = 14,G2 = 228,G3 = 206,G4 = 74,p = 5.2e-5),STAD(stomach adenocarcinoma)(G1 = 12,G2 = 148,G3 = 245,p = 0.01), KIRC(kidney renal clear cell carcinoma)(G1 = 14,G2 = 228,G3 = 206,G4 = 74,p = 5.2e-5),PAAD(G1 = 31,G2 = 95,G3 = 48,p = 1.4e- 5).While, HNSC (head and neck squamous cell carcinoma) (G1 = 61, G2 = 304, G3 = 124, G4 = 7,p = 2.1e-3) showed the reverse change with the grade increase ( Fig. 2 C ) . These above results suggested that CD44 significantly upregulated and increased in the advanced stage of most types of tumors. CD44 may evolve with the progress and development of cancer and may affect the survival outcome of patients with cancer. CD44 is a potential prognostic marker in pan-cancer Based on TCGA RNA-seq data and clinical information, a Cox proportional hazards regression model was used to determine the association of CD44 expression levels with the prognosis of patients with various cancer. We found that total 9 types of cancer with higher CD44 expression had poorer overall survival and cancer specific survival. These TCGA cancer types were GBMLGG, LGG, KIRP, KIPAN, HNSC, PAAD, and TGCT (testicular germ cell tumor) ( Fig. 3 A ) . On the contrary, increased CD44 mRNA level uniquely related with considerable outcome in UVM. The significant Kaplan-Meier survival curves of OS and CSS were showed in Fig. 3 B and Fig. 3 C. Gene Set Enrichment Analysis Considering the correlation between CD44 expression and prognosis, Gene set enrichment analysis (GSEA) was used for the Gene Ontology (GO) and ImmuneSigDB gene sets from Molecular Signatures Database (MSigDB) analyses of high-CD44 and low-CD44 group in pan-cancer ( Fig. 4 A-B ) . We found that many CSCs related gene sets and immune associated sets were enriched in the high-risk group. GO enrichment analysis suggested that these genes were mainly concentrated in cell adhesion and migration, epithelial-mesenchymal transition (EMT), Notching signaling pathway, phosphatidylinositol phosphate biosynthesis process ( Fig. 4 A ) . GO and ImmuneSigDB enrichment analysis commonly displayed that upregulated CD44 involved in MHC II biosynthesis, cytokine, chemokine, and interleukin production, T cell and B cell proliferation, and regulations on T cell activation. CD44 expression is related with immune cell infiltration in human cancers The subtypes and amounts of infiltrating lymphocytes in tumor are important predictors of the survival of patients with cancer( 12 ).Hence, we obtained the content of 11 specific immune cells in each sample of total 44 cancer types. Then, based on TIMER database, we used the Spearman rank correlation coefficient to explore the relationship between CD44 expression and these immune cell scores. Our results indicated that CD44 expression significantly correlated with tumor purity in 43 cancer types. The heat map described the results at p < 0.005. The upregulation of CD44 expression is correlated notably positively with Treg, macrophages M1 and M2 in most types of analyzed cancers, especially in TGCT (R = 0.68, R = 0.71, respectively) ( Fig. 5 A ) . While CD44 expression showed a negative relationship with amounts of infiltrated monocytes. In addition, CD44 expression was correlated with the infiltration levels of CD4 + T cells in 17 cancer types, B cells in 17 cancer types, CD8 + T cells in 22 cancer types, neutrophils in 25 cancer types, and dendritic cells in 20 cancer types. KIPAN, GBMLGG, LGG, and TCGT displayed a strong correlation between CD44 expression and quantities of immune infiltrated cells. Correlations between CD44 expression and immune marker sets, TMB, and MSI in cancers Then, we explored whether the cancer immune response is related with the CD44 mRNA expression. We found that chemokines (41genes), immune receptors (18 genes), MHC (21genes), immunoinhibitors (24 genes), immunostimulators (46 genes) were obviously activated in the group with overexpressed CD44 ( Fig. 5 B ) . Among them, CD44 expression is positively correlated with immune chemokines, such as (chemokine C-C motif) CCL2, CCL5, CCL15, CCL20, CCL21, CXCL13, and their receptors, such as CCR1, CCR2, CCR5, CCR7, and CXCR3. These chemokines and receptors can improve the infiltration of CD8 + T cells, TH17 cells, and antigen-presenting cells. MHC associated genes that reveal the capacity of antigen presentation and processing also had a positive relationship with CD44 expression. It was also observed that ICIs (immune checkpoint inhibitors), such as PD-L1, CTLA-4, LAG-3, IDO1, and TIGIT had a positively strong correlation with CD44 expression in many types of cancer, especially in ESCA and UVM ( Fig. 5 C ) . Moreover, TMB, MSI, and neoantigen both play an essential association with the therapeutic efficacy of ICIs. Our results showed that there was a strongly positive association between CD44 expression and TMB, MSI, and neoantigen in COAD, READ, SARC, UCEC, and READ. In the contrast, LUAD (lung adenocarcinoma), LUSC (lung squamous cell carcinoma), BLCA (bladder urothelial carcinoma), CHOL (cholangiocarcinoma) showed a negative relationship with CD44 expression ( Fig. 5 D-F ) . These findings further revealed that CD44 is a potential predictor for the sensitivity of immunotherapy based on the immune checkpoint. CD44 methylation related with T-cell dysfunctions and poor prognoses of cancer cohorts We calculated the promoter methylation level of CD44 in pan-cancer. Different beta-values were hypermethylation (0.7–0.5) or hypomethylation (0.3–0.25). Many TCGA cancer types showed the hypermethylation of CD44. In LUSC, LUAD, ESCA, BRCA, the promoter methylation levels of CD44 were significantly higher than those in normal groups. While the cancer cohort had decreased CD44 methylation levels in PAAD, COAD, LIHC, TGCT ( Fig. 6 A ) . Hypomethylation of CD44 was positively associated with dysfunctional T cell phenotypes and survival outcomes in 20 cancer types ( Fig. 6 B ) . Then, Kaplan-Meier survival analyses were performed to explore the relationship between CD44 promoter methylation and patient prognosis. Brain cancer, PAAD, and HNSC cohort with higher methylation levels of CD44 had better survival prognosis. In contrast, the hypomethylation level of CD44 was positively associated with T-cell dysfunctions but was a protective factor in patients in LUAD ( Fig. 6 C ) . Together, these results indicated that epigenetic methylation of CD44 is associated with dysfunctional T-cell phenotypes via different mechanisms that ultimately result in poor prognoses of PAAD, COAD, LIHC, TGCT cohorts while prolonging the survival of LUAD cohort. CD44 promoted the tumor growth and remodeled the immune environment of mouse colon cancer To further verify the function of CD44 in cancer, we constructed stable MC38 cell line expressing shRNA -CD44 using lentiviral delivery approach. Then, the flow cytometry detected that the expression of CD44 was significantly decreased in MC38 shRNA-CD44 cell line ( Fig. 7 A ) . We found that CD44 knockdown reduced the proliferation, colony number and migration cells in MC38 ( Fig. 7 B-D ) . Furthermore, CD44 knockdown also inhibited subcutaneous xenograft tumor growth in mice ( Fig. 7 E ) . The mouse xenografted with shRNA-CD44 MC38 had a prolonged survival outcome ( Fig. 7 F ) . Importantly, the immune environment of mouse colon cancer was detected by multicolor flow cytometry. Total CD45 positive cells were higher in the group xenografted with shRNA-CD44 MC38.Of these, the group xenografted with shRNA-CD44 MC38 had obviously increased CD4 + , CD8 + T cells and MDSC (myeloid derived suppressor cell) in CD45 cells. In contrast, Treg cell in CD45 cells of the mouse xenografted with shRNA-CD44 MC38 was significantly decreased. Dendritic cells, macrophages M2 and M1 in in CD45 cells showed no significant difference among two groups. 4. Discussion A subpopulation of patients with cancer had limited response rates to ICIs ( 13 ).The tumor genomic and microenvironment characteristics were explored to find the biomarkers of responses to ICIs( 14 ). The biomarkers with good predictive value were required to evaluate the immune response and select beneficial patients with cancer.CD44, a CSCs marker, is upregulated and had association with the immune response in many tumors. CD44 may be a promising biomarker for ICIs treatment and therapeutic targets. Therefore, we comprehensively investigated the expression of CD44 and its predictive values in 33 TCGA cancer. CD44, including some of its alternatively spliced variants, one of the most common cell surface biomarkers for CSCs, maintains stem cell phenotype and innates the metastasis( 15 ). In our results, compared to normal tissue, CD44 is obviously overexpressed in a variety of tumors. The different CD44 expression were observed in stage I-IV and G1-4 of most cancer cohorts, implying that the CD44 expression associated with tumor metastasis. Of these, PAAD showed a simultaneous upregulation with the increase of stage and differentiation of cancer. A previous studies described that CD44 is required for the induction of epithelial-mesenchymal transition and confer invasive properties via MT1-MMP in pancreatic cancer( 16 ). It is worthy to note that a meta-analysis showed that CD44 overexpression was related to lymph node metastasis, but no relationship with the differentiation and distance metastasis in pancreatic cancer( 17 ). Despite of the not consistent description of CD44 in the caner metastasis, these results suggested that CD44 is potentially a therapeutic target treating metastatic cancers. In our study, we found the number of CD44 positive cells was significantly upregulated in the tumor tissue of colon cancer patients compared with the adjacent tissue. In vitro, CD44 promoted the proliferation and migration of colon cancer line, indicating CD44 exerts a promotive effect on tumor progression of colon cancer. Given the significance of CD44 in the tumor recurrence, the prognosis analysis of CD44 in pan-cancer was conducted in our study. CD44 was a risk prognostic factor for most cancer types, including GBMLGG, LGG, KIRP, KIPAN, HNSC, PAAD, and TGCT. Consistently, a previous study also revealed that CD44 overexpression was significantly associated with several types of cancer, such as pancreatic cancer, colorectal and breast cancer( 17 – 19 ). Mechanically, CD44s regulated TGF-β signaling mediated mesenchymal phenotype and increased expression of the EMT marker, vimentin and low E-cadherin expression, thus resulting in the poor prognosis of hepatocellular carcinoma( 20 ). On the contrary, patients with high CD44 expression uniquely had a better survival in UVM. Inconsistently, a bioinformatics analysis showed that CD44 was a member of ferroptosis-related seven-gene signature that had a negative association between risk score and UM prognosis ( 20 ). In metastatic UVM, CD44 mRNA level was increased, suggesting the CD44 was an oncogenic molecule of cancer progress invasion and prognostic parameter( 21 ). Our result showed that the low expression of CD44 was positively with promising survival outcome in mouse colon cancer. There were no conclusive results on prognostic significance of CD44 receptor in caner. The CD44 expression and its prognostic values varied in different types of cancers. Given these above characteristics, we explored biological signaling pathways CD44 involved in cancer. It was known that the dysregulation of several signaling pathways, such as Notching and Hippo pathways contributes to cancer, especially the development of CSCs. Our results of Go analysis displayed that Notching signaling pathway and phosphatidylinositol phosphate biosynthesis process were enhanced in the high-CD44 group. It has been proved that phosphatidylinositol phosphate biosynthesis process regulated the activity of Hippo signaling pathway as the upstream modulator( 22 ). The GO analysis displayed that cell adhesion and migration, epithelial-mesenchymal transition (EMT) processes were enriched in the group with high CD44 expression. Increased expression of EMT transcription factors, such as OCT4 and SOX2, contributes to the phenotype and functions of CSC( 23 ). The dendritic cell (DC)-based cancer vaccines targeting CSCs reduced the lung metastasis and prolonged the survival via conferring the specific cytotoxic T lymphocytes in the adjuvant setting( 24 ). Similarly, as a conserved CSCs marker in various cancers, we found that CD44 had an important role in the immune response via regulating MHC II biosynthesis, cytokines, chemokines, and interleukin production, T cell and B cell proliferation, and regulations on T cell activation. Especially, CD44 expression was correlated with the infiltration levels of macrophages M1, M2 and Treg in most types of analyzed cancers, suggesting that CD44 may have an essential role in the emergency of immunosuppressive microenvironment. We further verified the effect of CD44 on tumor microenvironment in mouse colon cancer. We found that CD4 + , CD8 + T cells and MDSC in CD45 cells was significantly increased in the mouse xenografted with shRNA-CD44 MC38. While Treg cell in CD45 cells of was significantly decreased. Interestingly, Dendritic cells, macrophages M2 and M1 in in CD45 cells showed no significant relationship between CD44 expression in mouse model. The differences in the immune microenvironments may be the reason for the heterogeneity of human and mouse tumor model. Immune checkpoints, such as PD-1 and CTLA-4, involves the tumor invasion from the immune attack and determines the immunotherapy results( 25 ). In our study, immune checkpoint inhibitors, such as PD-L1, CTLA-4, LAG-3, IDO1, and TIGIT had a positively strong correlation with CD44 expression in many types of cancer, especially in ESCA and UVM. This suggests that CD44 might coordinate the activities of these immune checkpoint genes via different signal pathways and mediate immune invasion. TMB reflects the total number of somatic mutations per coding area in the genome of tumor cells ( 26 ). TMB level is commonly regarded as a notable biomarker to predict the effectiveness of immunotherapy in many tumors( 27 ). MSI is also an important biomarker of ICI s and high-frequency MSI is an independent risk factor for the prognosis of in colorectal cancer( 28 ).Our results demonstrated that there was a strongly positive association between CD44 expression and TMB, MSI, and neoantigen in COAD, READ, SARC, UCEC, and READ. In the contrast, LUAD, LUSC, BLCA, CHOL showed a negative relationship. CD44 was both a tumor stem cell marker and an immunosuppressive molecule. The level of CD44 expression may alter the TMB, MSI, and neoantigen in cancer, thus exerting an effect on the patient response to ICIs. These findings further revealed that CD44 is a potential pan-cancer immunotherapy target and biomarker to predict the therapeutic efficacy of immunotherapy targeting immune checkpoint. In addition, we found that CD44 is hypomethylated in various cancer types. While mRNA levels of CD44 was overexpressed in those cancers. It was indicated that epigenetic methylation of CD44 could affect its transcriptome in cancer. The epigenetic marker 6mA DNA methylation affects the gene expression. 6mA DNA methylation can promote mRNA metabolism and translation, leading to the gene activation. Meanwhile, m6A can alter RNA folding and structure to promote translation and affects splicing( 29 ). The switching of standard form of CD44 (CD44s) and CD44 variant isoforms (CD44v) generated by alternative splicing of middle exons was associated with EMT and tumor metastases( 7 ). It may explain that methylation of CD44 was associated with cancer survival. Interestingly, our results showed that hypomethylation of CD44 mediated in dysfunctional T cell phenotypes and survivals in 20 cancer types. Brain cancer, PAAD, and HNSC cohort with higher methylation levels of CD44 had better survival prognosis. Inversely, the hypomethylation level of CD44 was positively mediated T-cell dysfunctions but was a protective factor of patients with LUAD via a different mechanism. The methylation level of CD44 in different cancer further supports our conclusion that CD44 displayed a tissue-dependent regulation on cancer immunity and survival prognosis. 5. Conclusion In summary, our pan-cancer analysis described the CD44 expression in normal and tumor tissues and revealed the correlation between CD44 expression and clinical stage. The high expression of CD44 was associated with unfavorable survival outcome. CD44 can be served as an independent prognostic factor for different tumors. Moreover, CD44 expression was related with immune cell infiltration, TMB, MSI, and neoantigens across various cancer types. CD44 is hypomethylated in various cancer types and associated with T-cell dysfunctions and poor prognoses of patients with cancer. The effect of CD44 expression on prognosis and cancer immunity varies with tumor types. The specific role of CD44 in each cancer needs to be investigated. Our findings elucidated the role of CD44 as onco-immunological marker, and provided a reference for the personalized immune-based therapy in the future. Abbreviations CSC cancer stem cell HPA The Human Protein Atlas TCGA The Cancer Genome Atlas TMB tumor mutational burden TME tumor microenvironment PD1/PD-Ls programmed death-1/programmed cell death ligands CTLA4 cytotoxic tlymphocyte associated protein 4 MMPs matrix metalloproteinases TCR T cell receptor TNBC triple-negative breast cancer NSCLC non–small cell lung cancer EMT epithelial-mesenchymal transition MSI microsatellite instability Declarations Competing interests The authors declare that they have no competing interests. Funding No Authors' contributions YJZ: Writing - drafting. JYL : Conceptualization, Methodology, Supervision. ZYZ and YD : Writing - review & editing. 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Biochem J. 2016;473(19):3013–30. Chen C, Zhao S, Karnad A, Freeman JW. The biology and role of CD44 in cancer progression: therapeutic implications. J Hematol Oncol. 2018;11(1):64. Matzke-Ogi A, Jannasch K, Shatirishvili M, Fuchs B, Chiblak S, Morton J, et al. Inhibition of Tumor Growth and Metastasis in Pancreatic Cancer Models by Interference With CD44v6 Signaling. Gastroenterology. 2016;150(2):513–e2510. Baaten BJ, Li CR, Deiro MF, Lin MM, Linton PJ, Bradley LM. CD44 regulates survival and memory development in Th1 cells. Immunity. 2010;32(1):104–15. Hou W, Kong L, Hou Z, Ji H. CD44 is a prognostic biomarker and correlated with immune infiltrates in gastric cancer. BMC Med Genom. 2022;15(1):225. Kong T, Ahn R, Yang K, Zhu X, Fu Z, Morin G, et al. CD44 Promotes PD-L1 Expression and Its Tumor-Intrinsic Function in Breast and Lung Cancers. Cancer Res. 2020;80(3):444–57. Ohtani H. Focus on TILs: prognostic significance of tumor infiltrating lymphocytes in human colorectal cancer. Cancer Immun. 2007;7:4. Schreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Sci (New York NY). 2011;331(6024):1565–70. Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell. 2017;168(4):707–23. Zöller M. CD44: can a cancer-initiating cell profit from an abundantly expressed molecule? Nat Rev Cancer. 2011;11(4):254–67. Jiang W, Zhang Y, Kane KT, Collins MA, Simeone DM, di Magliano MP, et al. CD44 regulates pancreatic cancer invasion through MT1-MMP. Mol cancer research: MCR. 2015;13(1):9–15. Liu Y, Wu T, Lu D, Zhen J, Zhang L. CD44 overexpression related to lymph node metastasis and poor prognosis of pancreatic cancer. Int J Biol Mark. 2018;33(3):308–13. Wang C, Xie J, Guo J, Manning HC, Gore JC, Guo N. Evaluation of CD44 and CD133 as cancer stem cell markers for colorectal cancer. Oncol Rep. 2012;28(4):1301–8. Louderbough JM, Schroeder JA. Understanding the dual nature of CD44 in breast cancer progression. Mol cancer research: MCR. 2011;9(12):1573–86. Mima K, Okabe H, Ishimoto T, Hayashi H, Nakagawa S, Kuroki H, et al. CD44s regulates the TGF-β-mediated mesenchymal phenotype and is associated with poor prognosis in patients with hepatocellular carcinoma. Cancer Res. 2012;72(13):3414–23. Krishna Y, Acha-Sagredo A, Sabat-Pośpiech D, Kipling N, Clarke K, Figueiredo CR et al. Transcriptome Profiling Reveals New Insights into the Immune Microenvironment and Upregulation of Novel Biomarkers in Metastatic Uveal Melanoma. Cancers. 2020;12(10). Li FL, Fu V, Liu G, Tang T, Konradi AW, Peng X, et al. Hippo pathway regulation by phosphatidylinositol transfer protein and phosphoinositides. Nat Chem Biol. 2022;18(10):1076–86. Corgnac S, Damei I, Gros G, Caidi A, Terry S, Chouaib S et al. Cancer stem-like cells evade CD8(+)CD103(+) tumor-resident memory T (T(RM)) lymphocytes by initiating an epithelial-to-mesenchymal transition program in a human lung tumor model. J Immunother Cancer. 2022;10(4). Hu Y, Lu L, Xia Y, Chen X, Chang AE, Hollingsworth RE, et al. Therapeutic Efficacy of Cancer Stem Cell Vaccines in the Adjuvant Setting. Cancer Res. 2016;76(16):4661–72. Topalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell. 2015;27(4):450–61. Campbell BB, Light N, Fabrizio D, Zatzman M, Fuligni F, de Borja R, et al. Comprehensive Analysis of Hypermutation in Human Cancer. Cell. 2017;171(5):1042–e5610. Samstein RM, Lee CH, Shoushtari AN, Hellmann MD, Shen R, Janjigian YY, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51(2):202–6. Gryfe R, Kim H, Hsieh ET, Aronson MD, Holowaty EJ, Bull SB, et al. Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer. N Engl J Med. 2000;342(2):69–77. Zhao BS, Roundtree IA, He C. Post-transcriptional gene regulation by mRNA modifications. Nat Rev Mol Cell Biol. 2017;18(1):31–42. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 08 Apr, 2025 Read the published version in Cancer Cell International → Version 1 posted Editorial decision: Revision requested 21 Nov, 2024 Reviews received at journal 20 Nov, 2024 Reviews received at journal 12 Nov, 2024 Reviews received at journal 06 Nov, 2024 Reviewers agreed at journal 03 Nov, 2024 Reviewers agreed at journal 29 Oct, 2024 Reviewers agreed at journal 29 Oct, 2024 Reviewers invited by journal 29 Oct, 2024 Editor assigned by journal 17 Aug, 2024 Submission checks completed at journal 17 Aug, 2024 First submitted to journal 15 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4921451","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":344765016,"identity":"e24e899f-4da8-4a40-9de9-f4d165f3f1b9","order_by":0,"name":"Yajuan Zhu","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yajuan","middleName":"","lastName":"Zhu","suffix":""},{"id":344765017,"identity":"9e1ab36f-b067-4439-bcfa-6ccb99d44fd7","order_by":1,"name":"Zhuoyuan Zhang","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Zhuoyuan","middleName":"","lastName":"Zhang","suffix":""},{"id":344765018,"identity":"11c43251-d06b-431c-973f-52bc30130d89","order_by":2,"name":"Shan Shan Yang","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Shan","middleName":"Shan","lastName":"Yang","suffix":""},{"id":344765020,"identity":"45313e08-4f60-4320-84af-607fa37c1cda","order_by":3,"name":"Yang Du","email":"","orcid":"","institution":"Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Du","suffix":""},{"id":344765025,"identity":"4acf7b0c-d2f9-4e5a-890d-934f01af0d84","order_by":4,"name":"Jiyan Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYBACPmYGBoMEIIONvf/jgw8GNnYEtbDBtPDxHDA2nFGQlkxYC4whJ5FgJs3z4RBjA0Et7DwGBQ/b7PLYJBISpG0MDjAzsB8+ugG/w3gMDBLbkovZeB4cMM4xuMPHwJOWdoMILcyJbeyJDck5Bs+YGSR4zIjRUp/YxpDMcNjC4DBjA5FaDie2caQxNjMQp4WtwCDh3PHENp4zzIw9BmnJbIT8ws9/eJvhj7LqxPntPew/fvyxseNnP3wMrxaQRQaMbMhcAspBgPkBwx8ilI2CUTAKRsHIBQB9x0MV35/+agAAAABJRU5ErkJggg==","orcid":"","institution":"Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Jiyan","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-08-15 22:23:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4921451/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4921451/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12935-025-03748-4","type":"published","date":"2025-04-08T16:04:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66561262,"identity":"6f4bb16d-80a6-4341-92df-f35ec4047282","added_by":"auto","created_at":"2024-10-14 10:16:57","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1246120,"visible":true,"origin":"","legend":"\u003cp\u003eLocalization, functional partners, and expression profile of CD44 under disease condition and colon cancer. (A) Network of functional gene partners of CD44. (B) \u0026nbsp;The CD44-associated disease network. (C) The immunofluorescence staining of the subcellular distribution of CD44 within the nucleus, endoplasmic reticulum (ER), and microtubules of A-431, U-2OS, and U251-MG from the HPA database. (D)The immunofluorescence staining of CD44 in the HT29 and HCT116 colon cells. (E) The number of CD44 positive cells per field of view in adjacent tissue and tumor tissue from colon cancer patient.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/8188316d83bc301445357670.jpg"},{"id":66560485,"identity":"8a5888d8-83f1-4fd7-85ff-92edc6325adc","added_by":"auto","created_at":"2024-10-14 10:08:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":929359,"visible":true,"origin":"","legend":"\u003cp\u003ePan-cancer CD44 expression. (A) Differential CD44 mRNA expression in tumor tissues from TCGA database and normal tissues from TCGA and GTEx database. (B) CD44 expression of tumor tissues in different stages (I-IV) of BRCA, KIPAN, STES, and PAAD. (C) CD44 expression of tumor tissues in different stages (G1-4). *p \u0026lt; 0.05; **p \u0026lt; 0.01; ***p \u0026lt; 0.001 and ****p \u0026lt; 0.0001; ns, not significant.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/d876b63e6c385c95624f1f11.jpg"},{"id":66560486,"identity":"0f635ac1-adaa-4a45-9709-bcb9a116a546","added_by":"auto","created_at":"2024-10-14 10:08:58","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1667885,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival analysis comparing the high and low expression of CD44 expression on CSS and OS of different cancers in the TCGA database. (A) Forest plot of univariate Cox regression analysis of OS. (B) Forest plot of univariate Cox regression analysis of CSS. (C) Kaplan-Meier OS diagram of GBMLGG, LGG, PAAD, and UVM. (D) Kaplan-Meier CSS diagram of GBMLGG, LGG, PAAD, and UVM.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/4d9c451b64ebb2a92669afb7.jpg"},{"id":66560487,"identity":"3757d4ac-fe9b-4bd7-a67a-281a89be389f","added_by":"auto","created_at":"2024-10-14 10:08:58","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":713195,"visible":true,"origin":"","legend":"\u003cp\u003eGo and ImmuneSigDB enrichment analysis of CD44 in indicated tumor types. Values of p \u0026lt; 0.05 and results higher than 5 were considered and displayed.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/b0c99bf26e28d64cdb736e35.jpg"},{"id":66561263,"identity":"f42191f9-6e47-4200-abdf-d71bdb5d08ba","added_by":"auto","created_at":"2024-10-14 10:16:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2176586,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrative analysis of CD44 expression in the infiltrating immune microenvironment.\u003c/p\u003e\n\u003cp\u003e(A) The correlations between immune cell infiltration and CD44 expression levels in different cancers. *p \u0026lt; 0.05, **p \u0026lt;0.01, ***p \u0026lt; 0. 001. (B) Correlation between CD44 expression and immune-related genes. (C) The heatmap represents the relationship of immune activating genes and immunosuppressive status related genes. (D) Heatmap of correlation between CD44 expression and tumor mutational burden (TMB). (E) Heatmap showing the association of CD44 expression and MSI. (F) Heatmap showing the association of CD44 expression and neoantigen.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/8ff67545081e35320260324b.jpg"},{"id":66560482,"identity":"39789522-94d2-45c0-8a2a-45c2c5af15bf","added_by":"auto","created_at":"2024-10-14 10:08:57","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":969319,"visible":true,"origin":"","legend":"\u003cp\u003eEpigenetic modification of CD44 mediates dysfunctional T-cell phenotypes and poor prognoses of cancer cohorts. (A) The CD44 methylation levels (beta values) of tumor and adjacent normal tissues from TCGA database. (B)The correlation between CD44 methylation and cytotoxic T-cell levels (CTLs), dysfunctional T-cell phenotypes, and risk factors of TCGA cancer cohorts. (C) Overall survival curves of cancer groups with high methylation levels and those with low methylation levels of CD44. Only TCGA cancers with statistically significant differences between cohorts are presented.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/caf881d6fbe57b1bcf71aa94.jpg"},{"id":66560379,"identity":"f04c201d-f737-4e9e-99e8-a3ff9c5483c2","added_by":"auto","created_at":"2024-10-14 10:08:54","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":633212,"visible":true,"origin":"","legend":"\u003cp\u003eThe effect of CD44 on tumor growth and the immune microenvironment of mouse colon cancer. (A)The flow cytometry to detect the expression of CD44 in MC38 and MC38 shRNA-CD44 cell line. (B)The CCK8 assay of two cell lines. (C) The colony assay and statistical bar chart of two cell lines. (D) The migration assay and statistical bar chart of two cell lines. (E)The subcutaneous xenograft tumor in mice xenografted with two cell lines. (F)The survival curve of two groups xenografted with two cell lines. (G)The immune environment detected by multicolor flow cytometry.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/f0aebc4ff286b54684b5334d.jpg"},{"id":80558208,"identity":"e022842c-7ca9-4eac-888d-492b95f45304","added_by":"auto","created_at":"2025-04-14 16:13:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9213893,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4921451/v1/6c401e05-ade8-4ebd-8c4f-6ced62503537.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"CD44 on cancer stem cell is a potential immunological and prognostic pan-cancer biomarker","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTumor microenvironment (TME) comprises a variety of cells, among which infiltrating immune cells account for a large proportion(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Cancer is not a genetic disease but an ecological disease: a multidimensional spatiotemporal \u0026ldquo;unity of ecology and evolution\u0026rdquo; pathological ecosystem(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The interactions of TME and host immunity have become increasingly important in cancer therapy. Immunotherapy, including immune checkpoints inhibitors (ICIs), therapeutic vaccines and engineered T cells has been developed in the cancer treatment(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Especially, immune checkpoints inhibitors, such as programmed death-1/programmed cell death ligands (PD1/PD-Ls), cytotoxic T lymphocyte-associated antigen-4 (CTLA4), and anti-lymphocyte activation gene 3 (LAG3) shown promising clinical benefits in different malignancies and brought promising perspectives to patients with cancer. However, not all patients can benefit from ICIs because of the existed or acquired resistance(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In addition, there are still no effective prognostic biomarkers for the ICIs treatment. Therefore, more effective targets or biomarkers is urgently needed to be identified as anticancer drugs. The Cancer Genome Atlas (TCGA), a public database, provides a chance to perform pan-cancer gene analyses and evaluate their roles in the immune infiltration and cancer prognosis(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCD44, a cartilage link protein family member, is a receptor for hyaluronic acid (HA) and interact with various ligands, such as versican, osteopontin, fibronectin, and matrix metalloproteinases (MMPs). This transmembrane glycoprotein participates in a wide variety of cellular functions, including lymphocyte activation, recirculation, homing, and tumor metastasis(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). CD44 is overexpressed as standard isoform (CD44s) or alternatively spliced variant isoforms (CD44v) in CSCs and frequently underwent alternative splicing to support cancer progression and related with poor survival(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).The cluster of differentiation of CD44 has been recognized as a cancer stem cell marker and therapeutic targets in various cancers. Targeted inhibition of CD44 for therapeutic intervention, including CD44 neutralizing antibodies, pharmacological inhibitors, peptide mimetics, HA oligomers and aptamers are developed in various stages of preclinical and clinical trials(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCD44 participated in several processes associated with immune responses.CD44 expression is upregulated on naive T cells after activation via the T cell receptor (TCR).CD44 was essential for the generation of memory T helper 1 (Th1) cells and has implications in many diseases(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). As for cancer, CD44 is highly expressed in gastric cancer and associated with gastric immune invasion. CD44 can be used as a prognostic biomarker of gastric cancer(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). In triple-negative breast cancer (TNBC) and non\u0026ndash;small cell lung cancer (NSCLC), CD44 positively regulated the PD-L1 expression through binding to the regulatory region of PD-L1 locus(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). CD44 displayed a vital participation in the cancer immune invasion and may related with the response to the immunotherapy. However, the role of CD44 in caner immune microenvironment and cancer therapy is not well defined.\u003c/p\u003e \u003cp\u003eIn our pan-cancer analysis study, we comprehensively described the cellular location and mRNA expression of CD44 in healthy body. Then we investigated the alternations of CD44 and their prognostic values in TCGA cancer types. To explore the role of CD44 in the possible mechanism of immune invasion, we analyzed the relationship between CD44 alterations and immune cell infiltrations in tumor, immune checkpoint genes, tumor mutation burden (TMB) level, along with microsatellite instability (MSI) event. The relationship between CD44 methylation with T-cell dysfunctions and the effectiveness of ICI therapies was also calculated.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e \u003cb\u003eData and software availability\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll original data were downloaded from The Cancer Genome Atlas (TCGA) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cancergenome.nih.gov/\u003c/span\u003e\u003cspan address=\"https://cancergenome.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Genotype-Tissue Expression (GTEx) (http://commonfund.nih.gov/GTEx)databases.Sangerbox(\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/imt2.36,Version3.0\u003c/span\u003e\u003cspan address=\"10.1002/imt2.36,Version3.0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to extract CD44 (ENSG00000026508) gene expression data from these public database and convert it into a data matrix for subsequent analyses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCD44 location and expression analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe representative immunofluorescence staining of CD44 were retrieved from the Human Protein Atlas (HPA) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.proteinatlas.org\u003c/span\u003e\u003cspan address=\"http://www.proteinatlas.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Meanwhile, the colon cell lines (HT29 and HCT116) were stained with CD44 antibody to certify the expression and the subcellular locations in tumor cells. A gene network interaction analysis of CD44 was analyzed(gpsprot.org/index.php). Furthermore, the expression of CD44 were Log2 transformed and visualized by R software (Version 4.0.2; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.Rproject.org\u003c/span\u003e\u003cspan address=\"https://www.Rproject.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and \u0026ldquo;ggplot2\u0026rdquo; package. CD44 methylation data from cBioPortal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"https://cancergenome.nih.gov/\" target=\"_blank\"\u003ewww.cbioportal.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.cbioportal.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were used. Promoter methylation levels are displayed by beta values ranging from 0 (unmethylated) to 1 (fully methylated) for each tumor. The correlation of CD44 methylation with prognosis and dysfunctional T-cell phenotypes were conducted using the TIDE server.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMultivariate Cox regression analysis and survival analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo assess whether the high expression level of CD44 independently was the predictor of patient prognosis, including overall survival (OS), cancer-specific survival (CSS) of cancer with different cancer. The univariate Cox regression analysis and log-rank test were conducted. The \u0026ldquo;survival\u0026rdquo; package was utilized to plot the survival curves. The relationship between CD44 expression and survival outcome in pan-cancer was manifested as forest plots using the R packages \u0026ldquo;forestplot\u0026rdquo;.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe biological significance of CD44 expression in tumors\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGene Set Enrichment Analysis (GSEA) was conducted to investigate the biological functions of CD44 in tumors. Samples were separated into a high-CD44 group and a low-CD44 group, and the GSEA software was used to enrich the gene ontology (GO) and MSigDB database.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRelationship between CD44 expression and immunity\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe association of between CD44 expression and maker genes of the immune response process, including the antigen presentation, immune receptor, chemokine, immune stimulator and inhibitor, and immune checkpoint was analyzed on the Sangerbox website. Then we estimated whether the mRNA expression of CD44 is associated with the immune infiltration landscapes in different tumor types. The enrichment score for each immune cell in 33 tumors were quantified in the Tumor Immune Estimation Resource 2.0 (TIMER2.0) web server, and the correlation between CD44 gene expression and these immune infiltrating cells was analyzed. Moreover, we explored the relationship between CD44 and tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens in human TCGA cancers.\u003c/p\u003e \u003cp\u003e \u003cb\u003eImmunofluorescence staining\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe paraffin-embedded sections of tumor tissues were heated at 50\u0026deg;C for 1.5 h.\u003c/p\u003e \u003cp\u003eThe deparaffinized slides were processed for antigen retrieval by microwave heating in EDTA Tris-HCl buffer (pH8.0) for 15min. To reduce background staining, the sections were treated for 1 h with 1% normal goat serum (Boster, Wuhan). The samples were incubated with the rabbit Ab against CD44 (Proteintech, Wuhan) overnight at 4\u0026deg;C.Next, the secondary rabbit antibody with FITC (Boster, Wuhan) were incubated for 1 h. The immunohistochemistry images were collected using a confocal microscope (Nikon, Japan). Colon cancer and adjacent tissues from COAD patients who had surgical resection at the West China Hospital in Sichuan Province, China, between 2016 and 2017 were gathered for this study. None of the patients received radiotherapy, chemotherapy, or immunotherapy before the operation. The West China Hospital\u0026rsquo;s Medical Ethics Committee gave its approval to all operations (decision No. 2024664).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCell culture and in vitro testing\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe mouse colon cell line MC38 was purchased from the American Type Culture Collection (Rockville, MD, USA) and cultured in DMEM supplemented with 10% fetal bovine serum (FBS) and 100 U/ml penicillin/streptomycin (Gibco, Carlsbad, CA, USA) in a humidified chamber with 5% CO\u003csub\u003e2\u003c/sub\u003e at 37\u0026deg;C. Stable MC38 cell line expressing shRNA -CD44 was using lentiviral delivery system. Then, the antibody CD44 (clone IM7) was used to detect the expression of CD44 in MC38 and MC38-shRNA CD44 via flow cytometry. The CCK8 kit (Dojindo, Japan) was used to evaluate the cell proliferation and clonogenic assays are used for testing the capability of forming colonies of two cell lines. The migrated cells were detected via Transwell chamber assay.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnimal studies\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMC38 cells in the logarithmic growth phase (1x10\u003csup\u003e6\u003c/sup\u003e cells/200\u0026micro;l) were subcutaneously inoculated into the right flanks of female C57BL/6 mice (6 weeks old). After 15 days, the 4 mice each group were sacrificed to obtain the tumor issues. The survival time of the remaining mice were observed until 35 days after the inoculation. All animal procedures were performed according to the protocol approved by the West China Hospital Animal Care and Use Committee.\u003c/p\u003e \u003cp\u003e \u003cb\u003eImmune cell markers analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCells disserted from tumor tissue were stained with antibodies and analyzed by flow cytometry. The following antibodies and dye were obtained from BioLegend: CD45(clone 30-F-11), CD4 (clone RM4-5), CD8 (clone 145-2c11), CD25 (clone 3C7), Foxp3(clone MF23), CD11b (clone M1/70), F4/80 (clone T45-2342), CD86(clone GL-1), CD206(clone C068C2), CD11c(HL3), MH-II (clone M5/114.15.2), Gr1 (clone RB6-8C5), and fixable viability stain 620. Stained cells were analyzed on BDLSR Fortessa \u003csup\u003eTM\u003c/sup\u003e (BD Biosciences) and FlowJo software.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eDifferences between two groups and multiple groups were analyzed using a Student\u0026rsquo;s t-test and one-way analysis of variance (ANOVA), respectively. Survival analysis was conducted using Kaplan\u0026ndash;Meier method, and Pearson correlation analysis was utilized to calculate correlation coefficients. Those mentioned analyses above is conducted by R software (Version 4.0.2). A two-tailed P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was defined as the threshold of significance.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cb\u003eCD44 localized in\u003c/b\u003e cytoplasm and membrane of tumor cell \u003cb\u003eand significantly associated with cancer\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGene and disease network interactions revealed that CD44 had 151 gene functional partners and the top 15 interacted genes were shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. The Open Target platform showed that total 980 diseases or phenotypes were associated with CD44 expression. Among these, solid cancer, such as breast cancer, hepatocellular carcinoma, glioblastoma, urinary bladder carcinoma non-small cell lung carcinoma and chronic myelogenous leukemia displayed a relationship with CD44 expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. To evaluate the distribution and expression of CD44 in tumor cell, we retrieved the immunofluorescence results of A-431, U-2OS, and U251-MG from the HPA database. The endoplasmic reticulum (ER) and microtubules were marked with yellow and red, respectively. It was observed that CD44 overlapped with ER and microtubules but displayed no staining in the nuclei, suggesting that CD44 colocalized with these markers in the cytoplasm of tumor cell \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. In addition, our immunofluorescence staining results also demonstrated the location of CD44 in the colon cancer cell lines (HT29 and HCT116) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cb\u003e)\u003c/b\u003e. Furthermore, compared with the adjacent tissue, the number of cancer cells expressing CD44 were increased in cancer tissue of colon cancer patients \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. These results suggests that CD44 expression showed a relationship with various cancers and colon cancer patients had increased number of tumor cell expressing CD44 in tumor tissue.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCD44 is significantly aberrantly expressed in various tumors tissues and associated with tumor stages\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further clarify the association of CD44 and cancer, the CD44 expression were evaluated in all types of cancer from TCGA databased. Compared with the normal tissues, the significantly overexpressed CD44 was observed in 25 tumors. The top 5 items were glioblastoma multiforme (GBM) (T:7.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15, N:2.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59, p\u0026thinsp;=\u0026thinsp;1.8e- 83), glioma (GBMLGG)(T:6.26\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59,N:2.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59, p\u0026thinsp;=\u0026thinsp;8.4e-204),brain lower grade glioma (LGG)(T:5.86\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48,N:2.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59,p\u0026thinsp;=\u0026thinsp;2.4e-159),breast invasive carcinoma(BRCA)(T:7.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18, N:7.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82, p\u0026thinsp;=\u0026thinsp;7.7e-13), and cervical squamous cell carcinoma and endocervical adenocarcinoma(CESC) (T:7.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17, N:7.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.89, p\u0026thinsp;=\u0026thinsp;0.04). In contrast, we observed significant downregulation in six tumors such as uterine corpus endometrial carcinoma (UCEC) (T: 5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.42, N: 6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19, p\u0026thinsp;=\u0026thinsp;2.4e-3), lung adenocarcinoma (LUAD) (T:6.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05, N:7.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64, p\u0026thinsp;=\u0026thinsp;8.6e-29), and prostate adenocarcinoma (PRAD)(T:6.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.08, N:6.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69,p\u0026thinsp;=\u0026thinsp;1.6e-6) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e.In addition, we found that CD44 expression is significantly increased from stage I to IV of PAAD(Stage I\u0026thinsp;=\u0026thinsp;21,II\u0026thinsp;=\u0026thinsp;147,III\u0026thinsp;=\u0026thinsp;3,IV\u0026thinsp;=\u0026thinsp;4,p\u0026thinsp;=\u0026thinsp;0.01), and stomach and esophageal carcinoma(STES)(Stage I\u0026thinsp;=\u0026thinsp;76,II\u0026thinsp;=\u0026thinsp;201,III\u0026thinsp;=\u0026thinsp;230,IV\u0026thinsp;=\u0026thinsp;57,p\u0026thinsp;=\u0026thinsp;0.02), pan-kidney cohort (KIPAN)(Stage I\u0026thinsp;=\u0026thinsp;464,II\u0026thinsp;=\u0026thinsp;107,III\u0026thinsp;=\u0026thinsp;189,IV\u0026thinsp;=\u0026thinsp;103,p\u0026thinsp;=\u0026thinsp;0.01).Of note, BRCA(Stage I\u0026thinsp;=\u0026thinsp;182,II\u0026thinsp;=\u0026thinsp;617,III\u0026thinsp;=\u0026thinsp;248,IV\u0026thinsp;=\u0026thinsp;20,p\u0026thinsp;=\u0026thinsp;1.4e-3) displayed a relative decrease in the stage IV\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e.Then, we analyzed the CD44 expression in G1-G3 or G4 of pan-cancer. We found that CD44 expression had an continuous upregulation from Grade 1 to Grade4 of GBMLGG(G2\u0026thinsp;=\u0026thinsp;247,G3\u0026thinsp;=\u0026thinsp;260,p\u0026thinsp;=\u0026thinsp;1.8e-5),LGG(G2\u0026thinsp;=\u0026thinsp;247,G3\u0026thinsp;=\u0026thinsp;260,p\u0026thinsp;=\u0026thinsp;1.8e-5),ESCA(esophageal carcinoma)(G1\u0026thinsp;=\u0026thinsp;18,G2\u0026thinsp;=\u0026thinsp;74,G3\u0026thinsp;=\u0026thinsp;49,p\u0026thinsp;=\u0026thinsp;8.8e-3),STES(G1\u0026thinsp;=\u0026thinsp;30,G2\u0026thinsp;=\u0026thinsp;222,G3\u0026thinsp;=\u0026thinsp;294,p\u0026thinsp;=\u0026thinsp;0.04),KIPAN(G1\u0026thinsp;=\u0026thinsp;14,G2\u0026thinsp;=\u0026thinsp;228,G3\u0026thinsp;=\u0026thinsp;206,G4\u0026thinsp;=\u0026thinsp;74,p\u0026thinsp;=\u0026thinsp;5.2e-5),STAD(stomach adenocarcinoma)(G1\u0026thinsp;=\u0026thinsp;12,G2\u0026thinsp;=\u0026thinsp;148,G3\u0026thinsp;=\u0026thinsp;245,p\u0026thinsp;=\u0026thinsp;0.01), KIRC(kidney renal clear cell carcinoma)(G1\u0026thinsp;=\u0026thinsp;14,G2\u0026thinsp;=\u0026thinsp;228,G3\u0026thinsp;=\u0026thinsp;206,G4\u0026thinsp;=\u0026thinsp;74,p\u0026thinsp;=\u0026thinsp;5.2e-5),PAAD(G1\u0026thinsp;=\u0026thinsp;31,G2\u0026thinsp;=\u0026thinsp;95,G3\u0026thinsp;=\u0026thinsp;48,p\u0026thinsp;=\u0026thinsp;1.4e- 5).While, HNSC (head and neck squamous cell carcinoma) (G1\u0026thinsp;=\u0026thinsp;61, G2\u0026thinsp;=\u0026thinsp;304, G3\u0026thinsp;=\u0026thinsp;124, G4\u0026thinsp;=\u0026thinsp;7,p\u0026thinsp;=\u0026thinsp;2.1e-3) showed the reverse change with the grade increase\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. These above results suggested that CD44 significantly upregulated and increased in the advanced stage of most types of tumors. CD44 may evolve with the progress and development of cancer and may affect the survival outcome of patients with cancer.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCD44 is a potential prognostic marker in pan-cancer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eBased on TCGA RNA-seq data and clinical information, a Cox proportional hazards regression model was used to determine the association of CD44 expression levels with the prognosis of patients with various cancer. We found that total 9 types of cancer with higher CD44 expression had poorer overall survival and cancer specific survival. These TCGA cancer types were GBMLGG, LGG, KIRP, KIPAN, HNSC, PAAD, and TGCT (testicular germ cell tumor) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. On the contrary, increased CD44 mRNA level uniquely related with considerable outcome in UVM. The significant Kaplan-Meier survival curves of OS and CSS were showed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGene Set Enrichment Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eConsidering the correlation between CD44 expression and prognosis, Gene set enrichment analysis (GSEA) was used for the Gene Ontology (GO) and ImmuneSigDB gene sets from Molecular Signatures Database (MSigDB) analyses of high-CD44 and low-CD44 group in pan-cancer \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-B\u003cb\u003e)\u003c/b\u003e. We found that many CSCs related gene sets and immune associated sets were enriched in the high-risk group. GO enrichment analysis suggested that these genes were mainly concentrated in cell adhesion and migration, epithelial-mesenchymal transition (EMT), Notching signaling pathway, phosphatidylinositol phosphate biosynthesis process \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. GO and ImmuneSigDB enrichment analysis commonly displayed that upregulated CD44 involved in MHC II biosynthesis, cytokine, chemokine, and interleukin production, T cell and B cell proliferation, and regulations on T cell activation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCD44 expression is related with immune cell infiltration in human cancers\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe subtypes and amounts of infiltrating lymphocytes in tumor are important predictors of the survival of patients with cancer(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).Hence, we obtained the content of 11 specific immune cells in each sample of total 44 cancer types. Then, based on TIMER database, we used the Spearman rank correlation coefficient to explore the relationship between CD44 expression and these immune cell scores. Our results indicated that CD44 expression significantly correlated with tumor purity in 43 cancer types. The heat map described the results at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.005. The upregulation of CD44 expression is correlated notably positively with Treg, macrophages M1 and M2 in most types of analyzed cancers, especially in TGCT (R\u0026thinsp;=\u0026thinsp;0.68, R\u0026thinsp;=\u0026thinsp;0.71, respectively) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. While CD44 expression showed a negative relationship with amounts of infiltrated monocytes. In addition, CD44 expression was correlated with the infiltration levels of CD4\u003csup\u003e+\u003c/sup\u003eT cells in 17 cancer types, B cells in 17 cancer types, CD8\u003csup\u003e+\u003c/sup\u003eT cells in 22 cancer types, neutrophils in 25 cancer types, and dendritic cells in 20 cancer types. KIPAN, GBMLGG, LGG, and TCGT displayed a strong correlation between CD44 expression and quantities of immune infiltrated cells.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCorrelations between CD44 expression and immune marker sets, TMB, and MSI in cancers\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThen, we explored whether the cancer immune response is related with the CD44 mRNA expression. We found that chemokines (41genes), immune receptors (18 genes), MHC (21genes), immunoinhibitors (24 genes), immunostimulators (46 genes) were obviously activated in the group with overexpressed CD44 \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Among them, CD44 expression is positively correlated with immune chemokines, such as (chemokine C-C motif) CCL2, CCL5, CCL15, CCL20, CCL21, CXCL13, and their receptors, such as CCR1, CCR2, CCR5, CCR7, and CXCR3. These chemokines and receptors can improve the infiltration of CD8\u0026thinsp;+\u0026thinsp;T cells, TH17 cells, and antigen-presenting cells. MHC associated genes that reveal the capacity of antigen presentation and processing also had a positive relationship with CD44 expression. It was also observed that ICIs (immune checkpoint inhibitors), such as PD-L1, CTLA-4, LAG-3, IDO1, and TIGIT had a positively strong correlation with CD44 expression in many types of cancer, especially in ESCA and UVM \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Moreover, TMB, MSI, and neoantigen both play an essential association with the therapeutic efficacy of ICIs. Our results showed that there was a strongly positive association between CD44 expression and TMB, MSI, and neoantigen in COAD, READ, SARC, UCEC, and READ. In the contrast, LUAD (lung adenocarcinoma), LUSC (lung squamous cell carcinoma), BLCA (bladder urothelial carcinoma), CHOL (cholangiocarcinoma) showed a negative relationship with CD44 expression \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD-F\u003cb\u003e)\u003c/b\u003e. These findings further revealed that CD44 is a potential predictor for the sensitivity of immunotherapy based on the immune checkpoint.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCD44 methylation related with T-cell dysfunctions and poor prognoses of cancer cohorts\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWe calculated the promoter methylation level of CD44 in pan-cancer. Different beta-values were hypermethylation (0.7\u0026ndash;0.5) or hypomethylation (0.3\u0026ndash;0.25). Many TCGA cancer types showed the hypermethylation of CD44. In LUSC, LUAD, ESCA, BRCA, the promoter methylation levels of CD44 were significantly higher than those in normal groups. While the cancer cohort had decreased CD44 methylation levels in PAAD, COAD, LIHC, TGCT \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. Hypomethylation of CD44 was positively associated with dysfunctional T cell phenotypes and survival outcomes in 20 cancer types \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB\u003cb\u003e)\u003c/b\u003e. Then, Kaplan-Meier survival analyses were performed to explore the relationship between CD44 promoter methylation and patient prognosis. Brain cancer, PAAD, and HNSC cohort with higher methylation levels of CD44 had better survival prognosis. In contrast, the hypomethylation level of CD44 was positively associated with T-cell dysfunctions but was a protective factor in patients in LUAD \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC\u003cb\u003e)\u003c/b\u003e. Together, these results indicated that epigenetic methylation of CD44 is associated with dysfunctional T-cell phenotypes via different mechanisms that ultimately result in poor prognoses of PAAD, COAD, LIHC, TGCT cohorts while prolonging the survival of LUAD cohort.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCD44 promoted the tumor growth and remodeled the immune environment of mouse colon cancer\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo further verify the function of CD44 in cancer, we constructed stable MC38 cell line expressing shRNA -CD44 using lentiviral delivery approach. Then, the flow cytometry detected that the expression of CD44 was significantly decreased in MC38 shRNA-CD44 cell line \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA\u003cb\u003e)\u003c/b\u003e. We found that CD44 knockdown reduced the proliferation, colony number and migration cells in MC38\u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB-D\u003cb\u003e)\u003c/b\u003e. Furthermore, CD44 knockdown also inhibited subcutaneous xenograft tumor growth in mice \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE\u003cb\u003e)\u003c/b\u003e. The mouse xenografted with shRNA-CD44 MC38 had a prolonged survival outcome \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF\u003cb\u003e)\u003c/b\u003e. Importantly, the immune environment of mouse colon cancer was detected by multicolor flow cytometry. Total CD45 positive cells were higher in the group xenografted with shRNA-CD44 MC38.Of these, the group xenografted with shRNA-CD44 MC38 had obviously increased CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e T cells and MDSC (myeloid derived suppressor cell) in CD45 cells. In contrast, Treg cell in CD45 cells of\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ethe mouse xenografted with shRNA-CD44 MC38 was significantly decreased. Dendritic cells, macrophages M2 and M1 in in CD45 cells showed no significant difference among two groups.\u003c/p\u003e "},{"header":"4. Discussion","content":" \u003cp\u003eA subpopulation of patients with cancer had limited response rates to ICIs (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).The tumor genomic and microenvironment characteristics were explored to find the biomarkers of responses to ICIs(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The biomarkers with good predictive value were required to evaluate the immune response and select beneficial patients with cancer.CD44, a CSCs marker, is upregulated and had association with the immune response in many tumors. CD44 may be a promising biomarker for ICIs treatment and therapeutic targets. Therefore, we comprehensively investigated the expression of CD44 and its predictive values in 33 TCGA cancer.\u003c/p\u003e \u003cp\u003eCD44, including some of its alternatively spliced variants, one of the most common cell surface biomarkers for CSCs, maintains stem cell phenotype and innates the metastasis(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). In our results, compared to normal tissue, CD44 is obviously overexpressed in a variety of tumors. The different CD44 expression were observed in stage I-IV and G1-4 of most cancer cohorts, implying that the CD44 expression associated with tumor metastasis. Of these, PAAD showed a simultaneous upregulation with the increase of stage and differentiation of cancer. A previous studies described that CD44 is required for the induction of epithelial-mesenchymal transition and confer invasive properties via MT1-MMP in pancreatic cancer(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). It is worthy to note that a meta-analysis showed that CD44 overexpression was related to lymph node metastasis, but no relationship with the differentiation and distance metastasis in pancreatic cancer(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Despite of the not consistent description of CD44 in the caner metastasis, these results suggested that CD44 is potentially a therapeutic target treating metastatic cancers. In our study, we found the number of CD44 positive cells was significantly upregulated in the tumor tissue of colon cancer patients compared with the adjacent tissue. In vitro, CD44 promoted the proliferation and migration of colon cancer line, indicating CD44 exerts a promotive effect on tumor progression of colon cancer.\u003c/p\u003e \u003cp\u003eGiven the significance of CD44 in the tumor recurrence, the prognosis analysis of CD44 in pan-cancer was conducted in our study. CD44 was a risk prognostic factor for most cancer types, including GBMLGG, LGG, KIRP, KIPAN, HNSC, PAAD, and TGCT. Consistently, a previous study also revealed that CD44 overexpression was significantly associated with several types of cancer, such as pancreatic cancer, colorectal and breast cancer(\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Mechanically, CD44s regulated TGF-β signaling mediated mesenchymal phenotype and increased expression of the EMT marker, vimentin and low E-cadherin expression, thus resulting in the poor prognosis of hepatocellular carcinoma(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). On the contrary, patients with high CD44 expression uniquely had a better survival in UVM. Inconsistently, a bioinformatics analysis showed that CD44 was a member of ferroptosis-related seven-gene signature that had a negative association between risk score and UM prognosis (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In metastatic UVM, CD44 mRNA level was increased, suggesting the CD44 was an oncogenic molecule of cancer progress invasion and prognostic parameter(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Our result showed that the low expression of CD44 was positively with promising survival outcome in mouse colon cancer. There were no conclusive results on prognostic significance of CD44 receptor in caner. The CD44 expression and its prognostic values varied in different types of cancers.\u003c/p\u003e \u003cp\u003eGiven these above characteristics, we explored biological signaling pathways CD44 involved in cancer. It was known that the dysregulation of several signaling pathways, such as Notching and Hippo pathways contributes to cancer, especially the development of CSCs. Our results of Go analysis displayed that Notching signaling pathway and phosphatidylinositol phosphate biosynthesis process were enhanced in the high-CD44 group. It has been proved that phosphatidylinositol phosphate biosynthesis process regulated the activity of Hippo signaling pathway as the upstream modulator(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The GO analysis displayed that cell adhesion and migration, epithelial-mesenchymal transition (EMT) processes were enriched in the group with high CD44 expression. Increased expression of EMT transcription factors, such as OCT4 and SOX2, contributes to the phenotype and functions of CSC(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The dendritic cell (DC)-based cancer vaccines targeting CSCs reduced the lung metastasis and prolonged the survival via conferring the specific cytotoxic T lymphocytes in the adjuvant setting(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Similarly, as a conserved CSCs marker in various cancers, we found that CD44 had an important role in the immune response via regulating MHC II biosynthesis, cytokines, chemokines, and interleukin production, T cell and B cell proliferation, and regulations on T cell activation. Especially, CD44 expression was correlated with the infiltration levels of macrophages M1, M2 and Treg in most types of analyzed cancers, suggesting that CD44 may have an essential role in the emergency of immunosuppressive microenvironment. We further verified the effect of CD44 on tumor microenvironment in mouse colon cancer. We found that CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e T cells and MDSC in CD45 cells was significantly increased in the mouse xenografted with shRNA-CD44 MC38. While Treg cell in CD45 cells of was significantly decreased. Interestingly, Dendritic cells, macrophages M2 and M1 in in CD45 cells showed no significant relationship between CD44 expression in mouse model. The differences in the immune microenvironments may be the reason for the heterogeneity of human and mouse tumor model.\u003c/p\u003e \u003cp\u003eImmune checkpoints, such as PD-1 and CTLA-4, involves the tumor invasion from the immune attack and determines the immunotherapy results(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). In our study, immune checkpoint inhibitors, such as PD-L1, CTLA-4, LAG-3, IDO1, and TIGIT had a positively strong correlation with CD44 expression in many types of cancer, especially in ESCA and UVM. This suggests that CD44 might coordinate the activities of these immune checkpoint genes via different signal pathways and mediate immune invasion. TMB reflects the total number of somatic mutations per coding area in the genome of tumor cells (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). TMB level is commonly regarded as a notable biomarker to predict the effectiveness of immunotherapy in many tumors(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). MSI is also an important biomarker of ICI s and high-frequency MSI is an independent risk factor for the prognosis of in colorectal cancer(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).Our results demonstrated that there was a strongly positive association between CD44 expression and TMB, MSI, and neoantigen in COAD, READ, SARC, UCEC, and READ. In the contrast, LUAD, LUSC, BLCA, CHOL showed a negative relationship. CD44 was both a tumor stem cell marker and an immunosuppressive molecule. The level of CD44 expression may alter the TMB, MSI, and neoantigen in cancer, thus exerting an effect on the patient response to ICIs. These findings further revealed that CD44 is a potential pan-cancer immunotherapy target and biomarker to predict the therapeutic efficacy of immunotherapy targeting immune checkpoint.\u003c/p\u003e \u003cp\u003eIn addition, we found that CD44 is hypomethylated in various cancer types. While mRNA levels of CD44 was overexpressed in those cancers. It was indicated that epigenetic methylation of CD44 could affect its transcriptome in cancer. The epigenetic marker 6mA DNA methylation affects the gene expression. 6mA DNA methylation can promote mRNA metabolism and translation, leading to the gene activation. Meanwhile, m6A can alter RNA folding and structure to promote translation and affects splicing(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The switching of standard form of CD44 (CD44s) and CD44 variant isoforms (CD44v) generated by alternative splicing of middle exons was associated with EMT and tumor metastases(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). It may explain that methylation of CD44 was associated with cancer survival. Interestingly, our results showed that hypomethylation of CD44 mediated in dysfunctional T cell phenotypes and survivals in 20 cancer types. Brain cancer, PAAD, and HNSC cohort with higher methylation levels of CD44 had better survival prognosis. Inversely, the hypomethylation level of CD44 was positively mediated T-cell dysfunctions but was a protective factor of patients with LUAD via a different mechanism. The methylation level of CD44 in different cancer further supports our conclusion that CD44 displayed a tissue-dependent regulation on cancer immunity and survival prognosis.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn summary, our pan-cancer analysis described the CD44 expression in normal and tumor tissues and revealed the correlation between CD44 expression and clinical stage. The high expression of CD44 was associated with unfavorable survival outcome. CD44 can be served as an independent prognostic factor for different tumors. Moreover, CD44 expression was related with immune cell infiltration, TMB, MSI, and neoantigens across various cancer types. CD44 is hypomethylated in various cancer types and associated with T-cell dysfunctions and poor prognoses of patients with cancer. The effect of CD44 expression on prognosis and cancer immunity varies with tumor types. The specific role of CD44 in each cancer needs to be investigated. Our findings elucidated the role of CD44 as onco-immunological marker, and provided a reference for the personalized immune-based therapy in the future.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCSC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecancer stem cell\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHPA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Human Protein Atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTCGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eThe Cancer Genome Atlas\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTMB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etumor mutational burden\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTME\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etumor microenvironment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePD1/PD-Ls\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprogrammed death-1/programmed cell death ligands\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCTLA4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecytotoxic tlymphocyte associated protein 4\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMPs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ematrix metalloproteinases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eT cell receptor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTNBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etriple-negative breast cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNSCLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon\u0026ndash;small cell lung cancer\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEMT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eepithelial-mesenchymal transition\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMSI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emicrosatellite instability\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYJZ:\u003c/strong\u003e Writing - drafting.\u003cstrong\u003e\u0026nbsp;JYL\u003c/strong\u003e: Conceptualization, Methodology, Supervision. \u003cstrong\u003eZYZ\u003c/strong\u003e and \u003cstrong\u003eYD\u003c/strong\u003e: Writing - review \u0026amp; editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBindea G, Mlecnik B, Tosolini M, Kirilovsky A, Waldner M, Obenauf AC, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013;39(4):782\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo W. Nasopharyngeal carcinoma ecology theory: cancer as multidimensional spatiotemporal unity of ecology and evolution pathological ecosystem. Theranostics. 2023;13(5):1607\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchumacher TN, Schreiber RD. Neoantigens in cancer immunotherapy. Sci (New York NY). 2015;348(6230):69\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBagchi S, Yuan R, Engleman EG. Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. Annu Rev Pathol. 2021;16:223\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlum A, Wang P, Zenklusen JC, SnapShot. TCGA-Analyzed Tumors Cell. 2018;173(2):530.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNam K, Oh S, Shin I. Ablation of CD44 induces glycolysis-to-oxidative phosphorylation transition via modulation of the c-Src-Akt-LKB1-AMPKα pathway. Biochem J. 2016;473(19):3013\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen C, Zhao S, Karnad A, Freeman JW. The biology and role of CD44 in cancer progression: therapeutic implications. J Hematol Oncol. 2018;11(1):64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatzke-Ogi A, Jannasch K, Shatirishvili M, Fuchs B, Chiblak S, Morton J, et al. Inhibition of Tumor Growth and Metastasis in Pancreatic Cancer Models by Interference With CD44v6 Signaling. Gastroenterology. 2016;150(2):513\u0026ndash;e2510.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBaaten BJ, Li CR, Deiro MF, Lin MM, Linton PJ, Bradley LM. CD44 regulates survival and memory development in Th1 cells. Immunity. 2010;32(1):104\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHou W, Kong L, Hou Z, Ji H. CD44 is a prognostic biomarker and correlated with immune infiltrates in gastric cancer. BMC Med Genom. 2022;15(1):225.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKong T, Ahn R, Yang K, Zhu X, Fu Z, Morin G, et al. CD44 Promotes PD-L1 Expression and Its Tumor-Intrinsic Function in Breast and Lung Cancers. Cancer Res. 2020;80(3):444\u0026ndash;57.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOhtani H. Focus on TILs: prognostic significance of tumor infiltrating lymphocytes in human colorectal cancer. Cancer Immun. 2007;7:4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchreiber RD, Old LJ, Smyth MJ. Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Sci (New York NY). 2011;331(6024):1565\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSharma P, Hu-Lieskovan S, Wargo JA, Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell. 2017;168(4):707\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZ\u0026ouml;ller M. CD44: can a cancer-initiating cell profit from an abundantly expressed molecule? Nat Rev Cancer. 2011;11(4):254\u0026ndash;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiang W, Zhang Y, Kane KT, Collins MA, Simeone DM, di Magliano MP, et al. CD44 regulates pancreatic cancer invasion through MT1-MMP. Mol cancer research: MCR. 2015;13(1):9\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu Y, Wu T, Lu D, Zhen J, Zhang L. CD44 overexpression related to lymph node metastasis and poor prognosis of pancreatic cancer. Int J Biol Mark. 2018;33(3):308\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang C, Xie J, Guo J, Manning HC, Gore JC, Guo N. Evaluation of CD44 and CD133 as cancer stem cell markers for colorectal cancer. Oncol Rep. 2012;28(4):1301\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLouderbough JM, Schroeder JA. Understanding the dual nature of CD44 in breast cancer progression. Mol cancer research: MCR. 2011;9(12):1573\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMima K, Okabe H, Ishimoto T, Hayashi H, Nakagawa S, Kuroki H, et al. CD44s regulates the TGF-β-mediated mesenchymal phenotype and is associated with poor prognosis in patients with hepatocellular carcinoma. Cancer Res. 2012;72(13):3414\u0026ndash;23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrishna Y, Acha-Sagredo A, Sabat-Pośpiech D, Kipling N, Clarke K, Figueiredo CR et al. Transcriptome Profiling Reveals New Insights into the Immune Microenvironment and Upregulation of Novel Biomarkers in Metastatic Uveal Melanoma. Cancers. 2020;12(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi FL, Fu V, Liu G, Tang T, Konradi AW, Peng X, et al. Hippo pathway regulation by phosphatidylinositol transfer protein and phosphoinositides. Nat Chem Biol. 2022;18(10):1076\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorgnac S, Damei I, Gros G, Caidi A, Terry S, Chouaib S et al. Cancer stem-like cells evade CD8(+)CD103(+) tumor-resident memory T (T(RM)) lymphocytes by initiating an epithelial-to-mesenchymal transition program in a human lung tumor model. J Immunother Cancer. 2022;10(4).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHu Y, Lu L, Xia Y, Chen X, Chang AE, Hollingsworth RE, et al. Therapeutic Efficacy of Cancer Stem Cell Vaccines in the Adjuvant Setting. Cancer Res. 2016;76(16):4661\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTopalian SL, Drake CG, Pardoll DM. Immune checkpoint blockade: a common denominator approach to cancer therapy. Cancer Cell. 2015;27(4):450\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCampbell BB, Light N, Fabrizio D, Zatzman M, Fuligni F, de Borja R, et al. Comprehensive Analysis of Hypermutation in Human Cancer. Cell. 2017;171(5):1042\u0026ndash;e5610.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSamstein RM, Lee CH, Shoushtari AN, Hellmann MD, Shen R, Janjigian YY, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51(2):202\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGryfe R, Kim H, Hsieh ET, Aronson MD, Holowaty EJ, Bull SB, et al. Tumor microsatellite instability and clinical outcome in young patients with colorectal cancer. N Engl J Med. 2000;342(2):69\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao BS, Roundtree IA, He C. Post-transcriptional gene regulation by mRNA modifications. Nat Rev Mol Cell Biol. 2017;18(1):31\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cancer-cell-international","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ccin","sideBox":"Learn more about [Cancer Cell International](http://cancerci.biomedcentral.com/)","snPcode":"12935","submissionUrl":"https://submission.nature.com/new-submission/12935/3","title":"Cancer Cell International","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CD44, infiltrated immune cells, immune checkpoints, cancer prognosis","lastPublishedDoi":"10.21203/rs.3.rs-4921451/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4921451/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCD44, a widespread cancer stem cell marker, displayed a vital participation in the cancer immune invasion and may related with the response to the immunotherapy. However, the role of CD44 in cancer immunology is not well defined. Therefore, we intended to explore the prognostic value and the potential immunological functions in 33 human cancer types.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBased on the data of patients from The Cancer Genome Atlas (TCGA)and Genotype-Tissue Expression (GTEx) databases, Sangerbox was used to analyze the correlations between CD44 expression and tumor-infiltrated immune cells, immune checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), and neoantigens in human cancers.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe found that elevated CD44 is associated with tumor stage and prognosis in different cancers. GSEA results showed that upregulated CD44 involved in cancer stem cell associated process, antigen processing and presentation, and immune response, including immune cell proliferation and activation. Furthermore, CD44 plays an essential role in the tumor microenvironment and participates in immune regulation. The correlation of CD44 gene expression and infiltration levels of most immune cells differed according to the caner types. Notably, the upregulation of CD44 expression is correlated notably positively with Treg, macrophages M1 and M2 in most analyzed cancers, especially in testicular germ cell tumor. Furthermore, we further verified the effect of CD44 on tumor growth and immune microenvironment in mouse xenografted with shRNA-CD44 MC38. Moreover, DNA methylation existed in CD44 expression and associated with dysfunctional T-cell phenotypes via different mechanisms, thus resulting in tissue-dependent prognoses.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCD44 may serve as a potential prognostic and immunological biomarker in various malignant tumors. Moreover, CD44 could be a novel target for tumor immunotherapy.\u003c/p\u003e","manuscriptTitle":"CD44 on cancer stem cell is a potential immunological and prognostic pan-cancer biomarker","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-14 10:08:20","doi":"10.21203/rs.3.rs-4921451/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-22T01:08:32+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-20T22:39:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-12T07:58:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-07T01:15:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"184888318664441651688101191896055213506","date":"2024-11-03T22:23:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"269046111169830998581000913738104927638","date":"2024-10-29T23:22:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"151267170161874902564465619039854434537","date":"2024-10-29T22:13:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-10-29T22:09:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-17T10:19:37+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-17T10:19:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cancer Cell International","date":"2024-08-15T22:14:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cancer-cell-international","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ccin","sideBox":"Learn more about [Cancer Cell International](http://cancerci.biomedcentral.com/)","snPcode":"12935","submissionUrl":"https://submission.nature.com/new-submission/12935/3","title":"Cancer Cell International","twitterHandle":"@OncoBioMed","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a4a73131-c014-45ab-a11e-9c3a9dfa4cb1","owner":[],"postedDate":"October 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-04-14T16:07:02+00:00","versionOfRecord":{"articleIdentity":"rs-4921451","link":"https://doi.org/10.1186/s12935-025-03748-4","journal":{"identity":"cancer-cell-international","isVorOnly":false,"title":"Cancer Cell International"},"publishedOn":"2025-04-08 16:04:53","publishedOnDateReadable":"April 8th, 2025"},"versionCreatedAt":"2024-10-14 10:08:20","video":"","vorDoi":"10.1186/s12935-025-03748-4","vorDoiUrl":"https://doi.org/10.1186/s12935-025-03748-4","workflowStages":[]},"version":"v1","identity":"rs-4921451","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4921451","identity":"rs-4921451","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}