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. Author manuscript; available in PMC: 2025 Jul 1.
Published in final edited form as: Clin Transl Oncol. 2025 Jan 8;27(7):3163–3174. doi: 10.1007/s12094-024-03796-8

Expression of vesiculation-related genes is associated with a tumor-promoting microenvironment: a pan-cancer analysis

Luisa Westermann 1, Brenda Diergaarde 2,3, Simon Heidegger 4,5, Hendrik Poeck 6, Mirosław J Szczepański 7, Torsten E Reichert 1, Silvia Spoerl 8, Theresa L Whiteside 3,9,10, Steffen Spoerl 1, Nils Ludwig 3,9
PMCID: PMC12178821  NIHMSID: NIHMS2064593  PMID: 39776398

Abstract

Background.

Small extracellular vesicles (sEV) released by tumor cells (tumor-derived sEV; TEX) mediate intercellular communication between tumor and non-malignant cells and were shown to impact disease progression. This study investigates the relationship between the expression levels of the vesiculation-related genes linked to sEV production and the tumor microenvironment (TME).

Methods.

Two independent gene sets were analyzed, both previously linked to sEV production in various non-malignant or malignant cells. Expression profiles were compared among 28 tumor types listed in the Cancer Genome Atlas (TCGA). Gene expression and survival analysis (GEPIA2), immunogenomic analysis (TISIDB), and genomic analysis (GSCA) were performed.

Results.

Vesiculation-related genes were overexpressed in tissues of most tumor types compared to healthy tissues, and high expression levels were associated with worse overall survival in cervical squamous cell carcinoma, kidney chromophobe, lower grade glioma, hepatocellular carcinoma, lung squamous cell carcinoma, and pancreatic adenocarcinoma but with improved overall survival in kidney renal clear cell carcinoma. Expression of these signatures correlated with an increased abundance of infiltrating CD4(+) T cells and dendritic cells, a decreased abundance of B cells and eosinophils, and activation of tumor cell apoptosis and epithelial–mesenchymal transition pathways in all tumor types. 17-AAG was identified as a potential drug candidate to target tumors with elevated expression of vesiculation-related genes.

Conclusions.

Vesiculation-related genes were associated with distinct immunological and genomic landscapes further emphasizing the important role of TEX in cancer progression.

Keywords: extracellular vesicles, exosomes, vesiculation-related genes, tumor-infiltrating immune cells, tumor microenvironment

Introduction

Cancer is a complex and heterogenous disease with a multifaceted nature and diverse manifestations across different tissues and individuals [1]. This complexity is also observed within the tumor microenvironment (TME) which comprises a heterogenous milieu of various cell types, including cancer cells, stromal cells (such as fibroblasts and immune cells), blood vessels, extracellular matrix (ECM) components, and signaling molecules [2]. Current investigations focus on the intricate interplay within this environment and aim to decipher the communication between malignant and non-malignant cells, which can result in cellular reprogramming by the tumor and ultimately in the promotion of disease progression [3,4]. Important mediators of intercellular communication within the TME and beyond are extracellular vesicles (EVs), a heterogenous population of membranous vesicles produced by all cell types, including tumor cells [5]. The subset of small extracellular vesicles (sEV) with diameters of 30-150 nm is abundantly released by tumor cells and carries bioactive cargo components such as proteins, lipids, glycoconjugates, nucleic acids, as well as soluble factors (chemokines, cytokines, and enzymes) [6]. We and others commonly refer to sEV produced by tumor cells as tumor-derived exosomes or TEX [7,8]. TEX have been shown to induce functional changes in the TME and at sites distant from the tumor [9]. Specifically, TEX promote angiogenesis and metastasis, modulate immune cell functions, and alter composition of the ECM [10-12]. As such, TEX represent an ubiquitous subcellular system that regulates disease progression in patients with cancer [13].

The biogenesis and release of TEX involve a series of well-coordinated processes. Briefly, these processes originate from the endosomal system, where the inward budding of the plasma membrane forms early endosomes. Within these endosomes, intraluminal vesicles are created through further inward budding of the endosomal membrane, resulting in the formation of multivesicular bodies (MVBs) [5]. MVBs can either fuse with lysosomes for degradation or with the plasma membrane to release their intraluminal vesicles as TEX into the extracellular space [14]. This vesiculation process is regulated by various molecular mechanisms, and several factors have been described in the literature as influencing the quantity of TEX release including Rab11 [14], cortactin [15], or Rab27a and Rab27b [16]. Both in vitro and in vivo studies have directly linked tetraspanins, small and Rab GTPase, and factors associated with the ESCRT machinery and the SNARE complex to increased numbers of TEX in the extracellular space [17]. Hessvik and Llorente described the molecules known to be involved in TEX biogenesis and/or release in their review [17], and based upon this information, Fathi et al. created a gene signature associated with increased sEV release [18]. While most experimental evidence for this vesiculation signature was obtained from non-cancer cell lines, Hurwitz et al. applied proteomic profiling of TEX isolated from 60 cell lines from the National Cancer Institute (NCI-60) and performed a subsequent network analysis of vesicle quantity and proteomes to identify a signature associated with vesicle secretion [19].

We have previously used a bioinformatics approach to link transcriptional expression of these two signatures with the TME features in head and neck squamous cell carcinoma (HNSCC) [20]. Also, we demonstrated that these signatures are associated with beneficial response to checkpoint inhibitor treatment in melanoma patients and correlate with activation of cancer-intrinsic RIG-I signaling resulting in the release of immunostimulatory EVs [21]. In this study, we evaluate the expression levels of these two vesiculation signatures in 28 different tumor types utilizing data from the Cancer Genome Atlas (TCGA). The aims of the study are to: 1) characterize the expression levels and clinical features of the vesiculation signatures in a pan-cancer analysis; and 2) evaluate correlations of the vesiculation signatures with genomic and compositional features of the TME.

Materials and Methods

Two gene signatures

This study utilizes two vesiculation-related gene signatures that are presented in Supplementary Table 1. The two signatures overlap by only two genes (RAB7A and RALB) and are considered independent gene sets. The first signature, developed by Fathi et al. [18], includes multiple genes generally linked to EV production in predominantly non-tumor cells and is hereafter referred to as the “Common EV signature”. The second signature, established by Hurwitz et al. based on proteomic profiling of sixty cell lines from the National Cancer Institute (NCI-60), represents production of TEX and is hereafter referred to as the “TEX signature” [19]. To enhance the biological interpretation of the gene signatures and uncover potential functional relationships, actual and putative functional interactions within the Common EV and TEX signatures were analyzed using the STRING database (https://string-db.org/). The gene sets GOBP_VESICLE_BUDDING_FROM_MEMBRANE (M22483) and GOBP_EXTRACELLULAR_VESICLE_BIOGENESIS (M24918) were downloaded from Molecular signatures databases v7.5.1 (https://www.gsea-msigdb.org/gsea/msigdb/index.jsp; Supplementary Table 2).

RNA sequencing data acquisition – study cohort

Gene expression levels based on RNA-Seq data from cancer patients and clinical characteristics including outcome information were obtained from the Cancer Genome Atlas (TCGA; https://gdc.cancer.gov/) and analyzed using the tools described below. Expression profiles of the Common EV and TEX signatures were compared among a total of 28 tumor types within the TCGA patient cohort. Profiles were also compared to normal samples using matched adjacent normal tissues or GTEx data. Abbreviations for the cancer types evaluated in this study are listed in Supplementary Table 3.

GEPIA2 analysis

The 2018 version of Gene Expression Profiling Interactive Analysis2 (GEPIA2; http://gepia2.cancer-pku.cn/) [22] was utilized to assess the expression levels of genes in both the Common EV signature and the TEX signature. The mean value of the log2(TPM+1) was used as the signature score. For the comparison of gene expression levels between tumor types, matched TCGA normal and GTEx data were included as implemented in GEPIA2. A p value < 0.01 was defined as a statistically significant difference. The GEPIA2 survival analysis tool was used to analyze overall survival (OS) with Kaplan-Meier curves and to create survival maps. High-expression and low-expression cohorts were split based on median expression levels and were compared using the log-rank test with p values < 0.05 indicating statistically significant differences. The correlation analysis tool of GEPIA2 was employed to perform a Pearson correlation analysis of the expression of the Common EV and TEX signatures with indicated genes. These included immunoinhibitory genes, immunostimulatory genes, and chemokine genes. Heatmaps were generated using GraphPad Prism version 9.4.0.

TISIDB Analysis

The 2019 version of the Tumor-immune system interactions and The Drug Bank Database (TISIDB; http://cis.hku.hk/TISIDB) was utilized to determine the potential association between candidate genes and tumor-infiltrating immune cells in the indicated 28 tumor types [23]. Spearman’s correlation analysis was employed to analyze gene expression levels of immunomodulators and the Common EV and TEX signatures with data presented as Fisher z-transformed correlation coefficients. Heatmaps were generated using GraphPad Prism version 9.4.0.

GSCA Analysis

Version 2023-3-23 of Gene Set Cancer Analysis (GSCA) [24] was used to analyze the correlation between gene expression and GDSC drug sensitivity in pan-cancer. The Gene Set Variation Analysis (GSVA) and pathway activity module was used to assess the correlation between GSVA score and activity of cancer-related pathways.

Results

Vesiculation-related gene signatures are overexpressed in most tumor types in comparison to normal tissues and demonstrate prognostic value in CESC, KICH, KIRC, LGG, LIHC, LUSC, and PAAD

It is noteworthy that both the Common EV signature and the TEX signature exhibit strong interactions between their individual genes as visualized in Figure 1A and B. These strong interactions of the genes within the signatures and their similar functional background support the concept of analyzing the genes according to signature scores rather than as individual profiles. Analysis of gene expression levels of the Common EV signature revealed that increased expression in tumor versus normal tissue was prevalent in 24/28 tumors (for abbreviations see Supplementary Table 3): ACC, BLCA, BRCA, CESC, CHOL, ESCA, GMB, HNSC, KIRC, KIRP, LGG, LIHC, OV, PAAD, PCPG, PRAD, READ, SARC, STAD, TGCT, THCA, UCEC with significant differences in CHOL and PAAD (p < 0.01; Figure 2A). Conversely, decreased expression of the Common EV signature was only observed for KICH, LUSC, SKCM, and UCS (Figure 2A). The expression of the TEX signature in tumor versus normal tissue was increased in 22/28 tumor types: ACC, BLCA, BRCA, CESC, CHOL, COAD, ESCA, GBM, HNSC, KIRC, KIRP, LGG, LIHC, OV, PAAD, PCPG, READ, SARC, SKCM, STAD, TGCT, THCA, with significant differences in CHOL, GBM, and PAAD (p < 0.01; Figure 2B). Decreased expression was observed in 6/28 tumor types: KICH, LUAD, LUSC, PRAD, UCEC, UCS (Figure 2B).

Figure 1.

Figure 1.

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Actual and putative functional interactions between the Common EV signature (A) and the TEX signature (B) (marked with lines) were found by the STRING database (https://string-db.org).

Figure 2.

Figure 2.

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Analysis of gene expression levels of Common EV signature (A) and TEX signature (B) in 28 different tumor types. Comparison of tumor tissue (red) with normal tissue (grey). Asterisks mark significant differences with p < 0.01.

The survival analysis demonstrated significantly decreased OS in patients with high expression of the Common EV signature in 7/28 tumor types: CESC (p = 0.039), KICH (p = 0.015), LGG (p = 9.6e-05), LIHC (p = 0.0055), LUSC (p = 0.035), and PAAD (p = 0.0053). Only in KIRC, high expression was associated with significantly increased OS (p = 0.0069; Figure 3A). Similar results were observed in the analysis of the TEX signature. High expression of the TEX signature was associated with significantly decreased OS in five tumor types: CESC (p = 0.031), KICH (p = 0.012), LGG (p = 8.6e-07), LIHC (p = 0.0012), and PAAD (p = 0.021). In KIRC, high expression of the TEX signature was associated with significantly increased OS (p = 0.00014; Figure 3B). We also evaluated whether these alterations in OS were related to the whole signatures or to individual genes in the signatures. OS values of individual genes are presented in Figure S1A and B. The results suggest that OS is affected by a combined effect of multiple genes instead of one or two individual genes. To further elaborate on these findings, the Common EV signature and TEX signature were compared to the GOBP_VESICLE_BUDDING_FROM_MEMBRANE and GOBP_EXTRACELLULAR_VESICLE_BIOGENESIS signatures in terms of OS in patients with CESC, LGG, LIHC, and PAAD. While changes in OS were observed with the expression of these two gene ontology sets, the effects were more pronounced with the Common EV and TEX signatures (Figure S2).

Figure 3.

Figure 3.

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Kaplan–Meier overall survival curves of Common EV signature (A) and TEX signature (B) high expression versus low expression in patients diagnosed with 28 different tumor types. Red: high gene expression; blue: low gene expression

These findings indicate that both vesiculation signatures are highly expressed in most tumor types and, for some tumor types, this upregulation was associated with altered OS, demonstrating the potential clinical relevance of both vesiculation pathways.

Increased expression of vesiculation-related genes correlates with immune cell infiltration in tumors

To evaluate the impact of the two vesiculation signatures on the composition of the immune microenvironment and compare their potential immunoregulatory role among different tumor types, the relationships between the expression of vesiculation-related genes and the abundance of immune cell subsets was explored. Interestingly, the immune landscape associated with high expression levels of the vesiculation-related genes showed similar patterns across most tumor types, and the abundance of most immune cell subsets was correlated with expression levels of the Common EV and TEX signatures (Figure 4A and B). Among these positive correlations, central memory CD8(+) T cells, central memory CD4(+) T cells, activated dendritic cells, and monocytes showed relatively the strongest correlations with both EV signatures. In contrast, the abundance of B cell subsets and eosinophils was negatively correlated with the expression of the Common EV and TEX signatures (Figure 4A and B). These data indicate that the expression of vesiculation-related genes is associated with a distinct immune landscape characterized by the increased abundance of infiltrating CD8(+) and CD4(+) T cells, dendritic cells, and monocytes and the exclusion of B cells and eosinophils across all tumor types. When comparing the tumor types, some tumors were characterized by relatively stronger association of the Common EV and TEX signatures and abundance of the immune cell infiltration (especially in GBM, LGG, and THCA), while other tumor types only showed absent or negative correlation with immune cell abundance (COAD, ESCA, and PRAD; Figure 4A and B). These results suggest that the vesiculation-related genes are associated with distinct immunoregulatory landscapes depending on the tumor type. Specifically, when comparing the expression of the Common EV and TEX signatures in LGG, it appears that the abundance of infiltrating immune cells is mostly associated with the TEX signature. Thus, it can be hypothesized that TEX either play a key immunoregulatory role or the immune cell infiltration induces TEX release in this tumor type. This is in contrast to THCA, where the level of immune cell abundance is only weakly correlated with the TEX signature, suggesting a potential dominant immunoregulatory role of EVs deriving from non-malignant cells in this tumor type (Figure 4A and B).

Figure 4.

Figure 4.

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Correlation of vesiculation-related genes with immune cell infiltration and immunoinhibitory factors. (A) Heat map visualizing the correlation of the expression levels of the Common EV signature and the immune cell infiltration levels of indicated cell subsets. (B) Heat map visualizing the correlation of the expression levels of the TEX signature and the immune cell infiltration levels of indicated immune cell subsets. (C) Heat map visualizing the correlation of the expression levels of the Common EV signature and the indicated immunoinhibitory factors. (D) Heat map visualizing the correlation of the expression levels of the TEX signature and the indicated immunoinhibitory factors.

To explore which factors may be responsible for the immunoregulatory role of the vesiculation-related genes, correlations with immunoinhibitory and immunostimulatory factors as well as chemokines were analyzed. Except for CHOL, activity of the vesiculation pathways in all tumor types was positively correlated with immunosuppressive factors, predominantly with ENTPD1, IL10RB, and TGFBR1 (Figure 4C and D). The most prominent association of the Common EV and TEX signatures with immunosuppressive factors was observed in LGG, PRAD, and READ (Figure 4C and D).

The relationships between the expression of vesiculation-related genes and immunostimulatory factors are presented in Figure 5A and B. C10orf54, CD276, NT5E, PVR, and TMEM173 correlated the strongest relative to all other immunostimulatory genes and among most tumor types in both signatures. Interestingly, in CHOL only low or negative correlations of the vesiculation-related genes with both immunostimulatory and immunoinhibitory factors were observed (Figure 4C,D and 5A,B).

Figure 5.

Figure 5.

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Correlation of vesiculation-related genes with immunostimulatory factors and chemokines. (A) Heat map visualizing the correlation of the expression levels of the Common EV signature and the indicated immunostimulatory factors. (B) Heat map visualizing the correlation of the expression levels of the TEX signature and the indicated immunostimulatory factors. (C) Heat map visualizing the correlation of the expression levels of the Common EV signature and the indicated chemokines. (D) Heat map visualizing the correlation of the expression levels of the TEX signature and the indicated chemokines.

The expression of the two vesiculation signatures was associated with the upregulation of specific chemokines (Figure 5C and D). While the correlations with CXCL16 were most prominent among all tumor types, the correlations of CCL14-27 were absent or even negative. As described above for other immunoregulatory factors, CHOL was characterized by mostly negative correlations of vesiculation-related gene expression and chemokines (Figure 5C and D).

In aggregate, these data indicate that the expression of vesiculation-related genes is not only associated with a distinct immune landscape, but also with an altered composition of immunoregulatory factors in the TME.

Pathway scores of vesiculation-related genes correlate with tumor cell apoptosis and EMT across pan-cancer

To evaluate potential correlations of the vesiculation-related genes with cancer-related pathways, GSVA was used as a pathway-centric analysis method. Specifically, both EV signatures positively correlated with tumor cell apoptosis (significant in 14/28 for Common EV signature and 11/28 for TEX signature) and negatively correlated with cell cycle, DNA damage, and hormone AR in most tumor types (Figure 6A and B). While the pathway scores of the Common EV signature did not correlate with pathway activity of EMT in most tumor types (Figure 6A), we observed a significant correlation of the TEX signature scores and EMT pathway activity in 17/28 tumor types (Figure 6B), suggesting that the release of TEX is related to EMT. In some tumor types the correlation between the activity of cancer-related pathways was less pronounced with regards to the Common EV signature and was stronger with regards to the TEX signature (ACC, BLCA, KICH) indicating a relation of the TEX signature to a tumor-promoting TME. In HNSC and UCEC we observed stronger correlations of the cancer-related pathway activity with the Common EV signature, indicating a tumor-promoting role of EVs released by non-malignant cells (Figure 6A and B). Overall, the results suggest that vesiculation-related genes are associated with a distinct genomic landscape of cancer hallmark genes across all investigated tumor types.

Figure 6.

Figure 6.

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Association between GSVA score of vesiculation-related genes and activity of cancer related pathways in selected cancers. (A) Heat map visualizing the correlation of the GSVA score of the Common EV signature and the indicated cancer-related pathways. (B) Heat map visualizing the correlation of the GSVA score of the TEX signature and the indicated cancer-related pathways. *p ≤ 0.05; #: FDR ≤ 0.05

Identification of potential drug candidates for targeting tumors with increased expression of vesiculation-related genes

To identify potential drug candidates for targeting tumor cells with increased expression of vesiculation-related genes, the correlations between gene expression and GDSC drug sensitivity of 265 small molecules were investigated. A summary of the top 30 ranked drugs is presented in Figure S3, where positive correlations indicate that higher gene expression may lead to drug resistance and negative correlations indicate that higher gene expression may increase drug sensitivity. Interestingly, the antitumor antibiotic tanespimycin (17-AAG), which is a Hsp90 inhibitor, was identified as the only potential drug candidate with mostly negative correlations in the Common EV and TEX signatures (Figure S3). These results suggest that tumors with highly activated vesiculation pathways were resistant to many drugs, but may be sensitive to 17-AAG.

Discussion

Tumor cell-derived sEV also known as TEX are known to mediate intercellular communication in the TME and to functionally reprogram recipient cells towards a tumor-promoting phenotype [25]. Among the multiple mechanisms tumors utilize to reprogram their microenvironment, the production, release and delivery of TEX to recipient cells in the TME has emerged as a major contributor to tumor-driven reprogramming and tumor escape from the host immune system [26]. Our recent studies demonstrated that a strong correlation exists between the expression levels of genes responsible for release of sEV by the tumor and specific immune landscapes in HNSCC as well as in melanoma [20,21]. We have now extended our studies to analysis of vesiculation-related genes in all 28 tumor types included in the TCGA patient cohort. Here, we report that expression of vesiculation-related genes was upregulated in most tumor types (significantly in CHOL, GBM, and PAAD), correlated with decreased or improved patient survival in many different tumor types and was associated with distinct genetic and immunologic landscapes in the TME.

Interestingly, our analysis revealed distinct immunological changes associated with high expression levels of vesiculation-related genes. High expression of these genes was associated with an increased abundance of CD4(+) T cells, dendritic cells, and monocytes, while B cells and eosinophils were largely excluded from the TME. This immune landscape suggests that vesiculation-related genes may be associated with the recruitment of certain immune cell subsets while excluding others, thereby shaping the TME in a tumor-supportive manner. Furthermore, we found that the Common EV and TEX signatures were positively correlated with tumor cell apoptosis and negatively correlated with pathways such as cell cycle and DNA damage repair. These associations suggest that vesiculation-related genes might contribute to enhanced tumor cell turnover while simultaneously reducing the ability of the cells to repair DNA damage, potentially promoting genomic instability in the tumor cells.

Despite the fact that the Common EV and TEX signatures shared only two genes, our analysis unveiled strikingly similar behavior between these two vesiculation signatures in various human cancers. This consistency underscores the robustness of our findings and strongly suggests that the observed results are indicative of the key role EV-mediated processes play within the TME. These results further emphasize the importance of sEV/TEX in cancer progression and as biomarkers for prognosis and response to treatment, with high expression of vesiculation-related genes serving as a marker for high levels of TEX. Additionally, this finding raises the question of whether there is a mechanistic difference between vesiculation in healthy cells and tumor-associated vesiculation. Future studies are necessary to explore this aspect further, as potential differences might serve as therapeutic targets to block the release of TEX.

In our analysis, 17-AAG, an Hsp90 inhibitor, was identified as a potential therapeutic agent for tumors with elevated vesiculation-related gene expression. 17-AAG is known to interfere with multiple oncogenic pathways by inhibiting Hsp90, a chaperone protein critical for the stability of various oncogenic proteins [27]. Notably, our findings indicated that tumors with high vesiculation activity may be particularly susceptible to 17-AAG treatment. This relationship aligns with the observed immunological and apoptotic changes, as 17-AAG’s activity may exploit the vulnerabilities created by elevated vesiculation pathways, including reduced cell cycle progression and impaired DNA damage repair. As a result, 17-AAG could be a promising candidate for targeting tumors with upregulated vesiculation-related pathways, potentially disrupting the tumor-promoting effects of TEX within the TME.

Expression levels of vesiculation-related genes in nearly all tumors corresponded to well-established findings of highly increased TEX production by tumors [19] and of TEX dysregulated phenotype [18]. Exploring the clinical implications of vesiculation-related genes, we showed that elevated expression serves as a prognostic indicator in various tumor types, including CESC, KICH, LGG, LIHC, LUSC, PAAD, and KIRC. Thus, the vesiculation-related genes themselves are of interest as biomarkers. These genes may not only indicate elevated TEX levels but also serve as crucial markers for tumor behavior and patient prognosis. Analogous to these findings which are based on bulk RNA sequencing of tumor tissues and, therefore, indirectly assess sEV quantities, various recent studies have evaluated EVs isolated from body fluids as biomarkers of the tumor presence, progression or response to therapy [28,29]. A large-scale, comprehensive mass spectrometry-based comparative analysis of EVs from individuals with or without cancer indicated a potential utility of EVs in early cancer diagnosis [30]. That study also identified tumor-associated protein profiles in EVs in paired plasma and tumor tissues, validating the role of EVs as a novel liquid tumor biopsy approach in cancer. The prognostic role of EVs was subsequently reported by Lin et al. demonstrating that the signature of cargo components in EVs as well as their concentration are independent prognostic factors in patients with colorectal liver metastases [31]. Additionally, EV-bound CXCL7 was found as a biomarker of early response to systemic chemotherapy in these patients [31]. In another study, Han et al. demonstrated that nucleic acids in EVs isolated from plasma of PAAD patients can be utilized as prognostic biomarkers [32]. Our results further emphasize the prognostic significance of the Common EV and TEX signatures as upregulation of their activity in PAAD was associated with significantly decreased OS (p = 0.0053 and p = 0.021, respectively).

We aimed to elucidate the role of the vesiculation-related genes in a pan-cancer context, and results of our investigation highlight both their clinical and biological importance. The high expression of these genes may not only indicate elevated levels of TEX but also underscores their value as biomarkers for cancer progression and response to treatment. Given the immunomodulatory nature of TEX and their interference with cell-based cancer therapies [33], vesiculation-related genes may serve as predictors of response in this context. However, further validation in independent patient cohorts is essential to confirm our findings, as all our results are only derived from patients within the TCGA cohort.

Conclusions

This study represents a comprehensive analysis of the vesiculation-related genes across multiple tumor types, aiming at elucidating the role of TEX in orchestrating a tumor-promoting TME. Through integrated bioinformatics approaches, we systematically examined the expression patterns and functional interactions of vesiculation-related genes in diverse cancers. We demonstrated increased transcriptional expression of vesiculation-related genes in most patient cohorts and prognostic relevance in a subset of tumor types and established a correlation of expression levels of vesiculation-related genes with distinct immunological and genomic landscapes. The latter included an association of the vesiculation-related genes with an increased abundance of CD4(+) T cells and dendritic cells and a decreased abundance of tumor-infiltrating B cells and eosinophils. Also, the expression of vesiculation-related genes was linked to the activity of cancer hallmark pathways (apoptosis and EMT), indicating their involvement in shaping a tumor-promoting genomic landscape. Our findings shed light on the intricate interplay between TEX and the TME, uncovering novel insights into the molecular mechanisms driving cancer progression and metastasis.

Supplementary Material

Supllementary Material

Highlights.

  • Vesiculation-related genes were overexpressed in many tumor types, particularly in cholangiocarcinoma, pancreatic adenocarcinoma, and glioblastoma multiforme

  • Expression of vesiculation-related genes was associated with poor overall survival in cervical squamous cell carcinoma, kidney chromophobe, lower grade glioma, hepatocellular carcinoma, lung squamous cell carcinoma, pancreatic adenocarcinoma and improved overall survival in kidney renal clear cell carcinoma

  • Expression of vesiculation-related genes correlated with increased infiltration abundance of CD4(+) T cells and dendritic cells and decreased infiltration abundance of B cells and eosinophils among all tumor types

  • Expression of vesiculation-related genes was related to expression of immunomodulatory factors (ENTPD1, IL10RB, NT5E, TGFBR1) as well as activation of apoptosis and EMT pathways among all tumor types

  • Using the GDSC resource, 17-AAG was identified as a potential drug candidate to target tumors with increased expression of vesiculation-related genes

List of abbreviations

CNV

Copy number variation

ECM

Extracellular matrix

EVs

Extracellular vesicles

GEPIA2

Gene Expression Profiling Interactive Analysis2

GSCA

Gene Set Cancer Analysis

HNSCC

Head and neck squamous cell carcinoma

nm

nanometer

MVB

multivesicular body

sEV

Small extracellular vesicles

SNV

single nucleotide variation

TCGA

The Cancer Genome Atlas

TEX

Tumor-derived exosomes

TISIDB

Tumor-immune system interactions and The Drug Bank Database

TME

Tumor microenvironment

UCSC

University of California, Santa Cruz

Footnotes

Competing interests

S.H. is an employee of and holds equity interest in Roche/Genentech Inc. The other authors declare that they have no conflict of interest.

Data Availability statement

The data utilized in this study are publicly available.

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Associated Data

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Supplementary Materials

Supllementary Material
NIHMS2064593-supplement-Supllementary_Material.docx (2.6MB, docx)

Data Availability Statement

The data utilized in this study are publicly available.

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