Thirteen tumor necrosis factor receptor superfamily gene expression in malignancies and their clinical relevance to immunotherapy: a pan-cancer analysis

doi:10.21203/rs.3.rs-1598645/v1

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Thirteen tumor necrosis factor receptor superfamily gene expression in malignancies and their clinical relevance to immunotherapy: a pan-cancer analysis

https://doi.org/10.21203/rs.3.rs-1598645/v1

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Background: Although the expression of the tumor necrosis factor receptor superfamily (TNFRSF) genes and their anticancer functions in immune cells have been well described, little is known about the regulatory mechanisms and the clinical relevance of TNFRSF family gene expression in cancer cells. Recent studies indicate that the expression of CD40 (also known as TNFRSF5) is upregulated by RAS/RAF/PI3K pathway inhibition in melanoma cells, and it has the potential to be a predictive biomarker for immune checkpoint blockade (ICB) therapy responses in multiple cancer types. Therefore, we hypothesized that 13 TNFRSF genes with structural similarities to CD40 would be associated with the RAS-mediated oncogenic signaling pathways in melanoma cells and could benefit the prediction of immunotherapy responses in a range of cancers. Furthermore, there is a paucity of comparative gene expression analyses across cancer types (pan-cancer analysis) to reveal different types of cancer that share similar and distinct expression patterns of these TNFRSF genes.

Methods: We performed a pan-cancer analysis of the 13 TNFRSF genes in 18,299 samples from 23 cancer types to elucidate their expression alterations in tumorigenesis and their associations with signatures of immune cell infiltration and type I anti-tumor response, as well as the expression of oncogenes and ICB-related genes. In addition, single-cell (n = 169) and bulk (n = 37) RNA-seq data in melanoma samples with different NRAS (neuroblastoma RAS viral oncogene homolog) mutational statuses were used separately to examine the regulation of these TNFRSF genes by NRAS. Ultimately, the evaluation of these TNFRSF genes as biomarkers of immunotherapy responses in seven cancer types (n = 1,257) was performed using the Tumor Immune Dysfunction and Exclusion web platform.

Results and conclusions: Our findings demonstrate a comprehensive landscape of expression alterations in the 13 TNFRSF genes across a wide range of malignancies, with an emphasis on the association of these genes with type I anti-tumor T-cell responses and oncogene expression. In melanoma, oncogenic NRAS mutations downregulate the expression of multiple TNFRSF genes at bulk and single-cell levels. Moreover, our study suggests that the expression of the 13 TNFRSF genes could be used as potential biomarkers for predicting response to ICB therapy in certain cancer types with a partially complementary role. These findings will help us better understand the role of these TNFRSF genes in cancer development and treatment, and they may lead to the identification of candidate biomarkers for future clinical research and implications.

The tumor necrosis factor receptor superfamily (TNFRSF) contains 29 members that are co-stimulatory cell surface receptors. Members of the TNFRSF family play a crucial role in various signaling pathways that can lead to cell proliferation, differentiation, and death [1]. These TNFRSF receptors on the surface of T and B cells are targeted by agonist antibodies to regulate T-cell activation and affect immune responses against cancer [2]. Although the expression of TNFRSF genes and their anticancer functions in immune cells have been well described, little is known about the regulatory mechanisms and the clinical relevance of TNFRSF family gene expression in cancer cells. In melanoma cells, CD40 (also known as TNFRSF5) overexpression produced by RAS/RAF/PI3K pathway inhibition is associated with immunogenic cell death and an improved response to immune checkpoint blockade (ICB), including programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) blockade [3]. Subsequently, a pan-cancer study suggests that CD40 expression varies in tumorigenesis and is downregulated by the NRAS mutation in melanoma [4]. More importantly, CD40 is reported to have the potential to be a predictive biomarker for ICB therapy responses in melanoma, gastric cancer, and glioblastoma tumors. Similar to CD40, TNFRSF1B, LTBR (TNFRSF3), CD27 (TNFRSF7), TNFRSF8, TNFRSF9, TNFRSF11A, TNFRSF12A, TNFRSF13B, TNFRSF13C, TNFRSF14, TNFRSF17, TNFRSF18, and RELT (TNFRSF19L) are TNFRSF receptors that lack truncated cysteine-rich domains and functionally interact with TNFR-associated factors (TRAFs) [5]. However, little is known about whether the 13 TNFRSF genes are linked to the RAS-mediated oncogenic signaling pathways in tumors and whether these genes aid in the prediction of immunotherapy responses. Furthermore, there is a paucity of comparative gene expression analyses across cancer types (pan-cancer analysis) to reveal different types of cancer that share similar and distinct expression patterns of these TNFRSF genes. To address these gaps, we extended this pan-cancer analysis to the 13 TNFRSF genes to comprehensively analyze their expression and clinical importance, using an approach similar to that used in the pan-cancer study of CD40 [4].

Complicated associations of the 13 TNFRSF genes with the type I anti-tumor response, oncogenes, and ICB-related genes

Using the TCGA/TARGET/GTEx RNA-seq datasets that include 18,299 samples across 23 cancer types and corresponding normal tissues, we investigated the expression of the 13 TNFRSF genes and their associations with markers of major histocompatibility complex class II (HLA-DRA), dendritic cells (BATF3), B cells (PAX5), macrophages (CD68), granulocytes (mainly neutrophils, CD177), T-cells (CD4 and CD8A), type-I anti-tumor responses (IFNG and GZMB), cell proliferation (MKI67), cell death (BAX), cell survival (BCL2), type-II pro-tumor responses (IL5), several known oncogenes (ERBB2, HRAS, KRAS, NRAS, MYC, SRC, TERT, and EGFR), and ICB-related genes (PDCD1 (also known as PD-1), CD274 (also known as PD-L1), CTLA4, and CD86) in a pan-cancer analysis (Fig. 1a).

Using a threshold of false discovery rate (FDR) < 0.05 and |r| ≥ 0.3, the expression of 11 TNFRSF genes was positively correlated with at least one immune cell maker (BATF3, PAX5, CD68, CD177, CD4, and CD8A) in both normal (n = 8,163) and tumor tissues (n = 10,136) (Fig. 1b). Notably, their correlations differed between normal tissues and tumors. For example, in normal tissues, LTBR showed a positive correlation with the macrophage marker (CD68), but not with the neutrophil marker (CD177), whereas the opposite was true in tumors. Another example is TNFRSF11A, which was found to be positively correlated with the neutrophil maker (CD117) in tumors but not in normal tissues. These differences in correlation status may be partly explained by the significant role of these TNFRSF genes in immune cell turnover and immune homeostasis in normal tissues, as evidenced by the observation in normal tissues that cell proliferation (MKI67) and proapoptotic makers (BAX) were tightly linked and both were positively correlated with nine TNFRSF genes. Furthermore, eight TNFRSF genes were positively correlated with IFNG, GZMB, HLA-DRA, CD4, or CD8A, implying that their associations with type-I T-cell and APC responses in the tumor microenvironment. In tumors, CD8A, IFNG, and GZMB were determined to be positively correlated with the APC markers HLA-DRA (MHC class II molecule), BATF3 (dendritic cells), PAX5 (B cells), and CD68 (macrophages). These findings indicate that these TNFRSF genes are linked to cytotoxic T-cell responses (CD8A, IFNG, and GZMB), although they may be provided by APCs in a context-dependent way. In both normal and malignant tissues, there was no significant correlation between the 13 TNFRSF genes and type-II responses (IL5).

In addition, LTBR, TNFRSF9, TNFRSF12A, TNFRSF13C, and RELT were substantially correlated with at least one oncogene in tumors, suggesting the possible associations of these genes with oncogenic pathways. We also discovered that 12 TNFRSF genes were positively correlated with at least one ICB-related gene in tumors. Collectively, our results demonstrate that the 13 TNFRSF genes have complex associations with cytotoxic T-cell responses, oncogenic signaling pathways, and ICB therapy.

Potential prognostic value of the 13 TNFRSF genes in cancers

To evaluate whether the 13 TNFRSF genes can be utilized to improve clinical outcomes, we investigated the relationship between the expression of these TNFRSF genes and cancer patient overall survival (OS) using a pan-cancer analysis (n = 9,346). High levels of TNFRSF14, CD27, and TNFRSF13B expression in tumors were found to be associated with improved OS (all FDR < 0.05; Fig. 1c). This could be due to beneficial cytotoxic T-cell responses (CD8A, IFNG, and GZMB). By contrast, high expression patterns of TNFRSF1B, TNFRSF9, TNFRSF11A, TNFRSF8, TNFRSF13C, TNFRSF12A, LTBR, and RELT, which included five TNFRSF genes that were positively correlated with oncogenes in tumors, were associated with poorer OS (all FDR < 0.05; Fig. 1c and d). Interestingly, although TNFRSF9 and RELT were positively linked to cytotoxic T-cell responses, patients nevertheless had a poorer prognosis, which may be underlined by their positive correlation with the oncogene NRAS. This suggests that a subset of TNFRSF genes influencing cancer patient OS is not only dependent on T-cell-mediated cytotoxicity but may also be associated with oncogenic signaling pathways. As such, the development of prognostic biomarkers based on these TNFRSF genes should take this complexity into account.

Cancer-type-specific regulation of the 13 TNFRSF genes in tumorigenesis

Next, expression alterations between tumors and normal tissues in 23 cancer types were investigated separately to establish the role of the 13 TNFRSF genes in the tumorigenesis of each cancer type. These genes showed differential expression patterns between tumors and normal tissues in multiple cancers with an FDR threshold of 0.05 (Fig. 2a). Notably, these genes exhibited cancer-type-specific expression changes in tumors when compared to normal tissues. RELT, for example, exhibited higher expression levels in tumors of the bile duct, bladder, brain, breast, cervix, colon, endometrium, esophagus, head and neck, kidney, ovary, pancreas, rectum, stomach, and uterine compared to corresponding normal tissues, whereas it had lower expression levels in malignancies of the adrenal, blood, liver, lung, prostate, testis, and thyroid. Furthermore, except for pancreatic cancer, the direction of expression changes for these genes was inconsistent when comparing tumors and normal tissues for each cancer type, suggesting that these TNFRSF genes are more likely to play distinct roles in the tumorigenesis of each cancer type.

Given that melanocytes make up only 10% of the normal skin population [6], a comparison of normal skin and melanoma tissues may be biased due to the predominance of keratinocytes in the epidermal basal layer. Therefore, we validated the expression of these TNFRSF genes in nevus samples and compared them to expression in melanoma tissues using the RNA-seq dataset collected from GSE112509. TNFRSF9, TNFRSF17, and RELT showed higher expression levels in NRAS^wt melanoma (n = 18) than in NRAS^wt nevi (n = 3) (all FDR < 0.05; Fig. 2b). This matches well with our above results in the TCGA-melanoma dataset, where TNFRSF9 and TNFRSF17 expression levels were higher in melanoma tissues (n = 102) than in normal skin tissues (n = 557).

The NRAS mutation correlates with reduced expression of the 13 TNFRSF genes in melanoma

Through a pan-cancer analysis, our study establishes significant associations between the expression of a subset of the 13 TNFRSF genes and the expression of oncogenes, including NRAS. To better understand the functional relationships between them, the expression of these genes in melanoma tissues was explored under NRAS mutations, which are observed in 10–25% of melanomas [7]. These TNFRSF genes were demonstrated to be commonly downregulated by the NRAS mutation. With an FDR threshold of 0.05, the expression of TNFRSF1B, TNFRSF8, TNFRSF11A, TNFRSF12A, TNFRSF13B, TNFRSF18, and RELT in NRAS^mut melanoma tissues (n = 19) was significantly lower than in NRAS^wt melanoma tissues (n = 18) (Fig. 2b). Four additional genes, CD27, TNFRSF9, TNFRSF13C, and TNFRSF17, were identified when the FDR cutoff was set to 0.1.

Because bulk tumor samples contain a wide range of cell types, cellular heterogeneity among samples may be a substantial confounding factor in the analysis. Therefore, we used the single-cell RNA-seq dataset retrieved from GSE81383 to further investigate the expression of the 13 TNFRSF genes under NRAS mutations in melanoma cells. Eight of them (LTBR, TNFRSF9, TNFRSF11A, TNFRSF12A, TNFRSF13C, TNFRSF14, TNFRSF17, and RELT) were available to be tested in this dataset. TNFRSF9, TNFRSF14, and RELT expression were significantly downregulated in NRAS^mut/BRAF^wt melanoma cells (n = 77) compared to NRAS^wt/BRAF^wt melanoma cells (n = 92) with an FDR threshold of 0.05 (Supplementary Fig. 1). In addition, reduced expression levels of the three genes were detected when comparing NRAS^wt/BRAF^mut melanoma cells (n = 54) to NRAS^wt/BRAF^wt melanoma cells. Mutations in the oncogenes BRAF and NRAS have previously been shown to trigger constitutive activation of the mitogen-activated protein kinase (MAPK) pathway, which promotes tumor development and illness progression [8]. It is plausible that at least a subset of TNFRSF genes is linked to RAS-mediated oncogenic signaling pathways.

To test this, pathway enrichment analysis was performed on the 13 TNFRSF genes, and it was discovered that they were significantly enriched in RAS downstream signaling pathways, such as the nuclear factor kappa B (NF-κB) signaling pathway, regulation of the extracellular signal-regulated kinase 1 (ERK1) and ERK2 cascade, and regulation of the stress-activated MAPK cascade (all FDR < 0.05) (Supplementary Table 1). This link between these TNFRSF genes and RAS-mediated oncogenic signaling pathways is also supported by the functional interaction of these TNFRSF receptors and their intracellular binding partners, TRAFs, which are adaptor molecules regulating various RAS downstream signaling pathways such as the NF-κB, MAPK, and the phosphatidylinositol 3‑kinase (PI3K)/protein kinase B (AKT) [9–11]. Furthermore, it has been proposed that CD40 expression and the RAS/RAF/PI3K pathway have a compensatory role in activating RAS-downstream signaling activity [3, 4]. The proposed mechanism may also function for the 13 TNFRSF genes, as it does for CD40. Further biological experiments in cancer cells are required to corroborate the proposed mechanism.

The expression of the 13 TNFRSF genes has the potential to be exploited as biomarkers for immunotherapy

Our above results elucidate the importance of these TNFRSF genes in tumorigenesis and determine the association between them and ICB-related genes in cancers. As a result, we assessed the potential predictive value of these TNFRSF genes in first-line ICB therapy, such as PD-1/PD-ligand 1 (PD-L1) and CTLA-4 blockade. To accomplish this, we used the Tumor Immune Dysfunction and Exclusion (TIDE) web platform (tide.dfci.harvard.edu), which is a computational tool developed to evaluate the potential for tumor immune escape using gene expression profiles from cancer samples [12]. The area under the receiver operating characteristic curve (AUC) for the 13 TNFRSF genes was measured and compared to four existing immunotherapy biomarkers: CD40, tumor mutational burden (TMB), CD274, and CD8 [4, 13]. Using an AUC threshold of 0.7, we discovered that these TNFRSF genes performed well in at least one cancer type. Compared to four existing biomarkers, these TNFRSF genes were outperformed in at least one ICB cohort, highlighting the potential benefit of using them to predict ICB response (Fig. 2c). Notably, these TNFRSF genes were identified to exhibit cancer-type-specific predictive performance. For instance, among the 13 TNFRSF genes and four existing biomarkers, LTBR is the only biomarker that predicts ICB response in kidney cancer with an AUC ≥ 0.7. Furthermore, in contrast to the four existing biomarkers that only perform effectively in post-treatment tumors, TNFRSF8, TNFRSF9, TNFRSF12A, TNFRSF13C, and TNFRSF18 displayed good predictive power in both post-treatment and pre-treatment/treatment-naïve cancers. This suggests the predictive ability of the five TNFRSF genes not only relies on treatment-induced responses but also on immune escape mechanisms in pre-treatment or treatment-naïve biopsies. Moreover, although most of the 13 TNFRSF genes performed well in predicting the response to both anti-CTLA-4 and anti-PD-1 immunotherapy, TNFRSF8, TNFRSF13C, and TNFRSF17 had proper prediction ability only for anti-PD-1 immunotherapy. This suggests that these three TNFRSF genes may be more predictive of PD-1 blockade-related signals since PD-1 and CTLA-4 blockade show distinct impacts on the melanoma-reactive CD8 + T cell response [14]. Overall, these findings reveal that the 13 TNFRSF genes have context-dependent predictive potential in immunotherapy responses. Supplementary Fig. 2 illustrates their context-dependence in a systematic manner.

The next question is how well a custom biomarker that integrates expression patterns of the 13 TNFRSF genes can predict response outcomes. Although the context-dependent predictive potential of these genes in immunotherapy response has been proven above, we employed the average expression level of these genes to simplify our study. The custom biomarker provided an AUC greater than or equal to 0.7 in a greater number of ICB cohorts (n = 8) than individual TNFRSF genes (n ranging from 1 to 7) (Fig. 2c). Furthermore, we discovered that this custom biomarker outperformed individual genes in two cohorts: the Ruppin study in non-small cell lung cancer treated with PD-1 (AUC = 0.87) and the Nathanson study in melanoma treated with CTLA-4 (AUC = 0.82). These findings imply that these TNFRSF genes, at least to some extent, play a complementary role in prediction and that integrating their expression could facilitate the development of a robust immunotherapy predictive biomarker. Moreover, this custom biomarker was associated with prolonging OS in four cohorts of melanoma patients treated with anti-PD-1 or anti-CTLA4 antibodies (all P < 0.05; Supplementary Fig. 3). This is in line with previous observations that anti-PD-1 and/or anti-CTLA-4 therapy combined with the engagement of TNFRSF members improves cancer immunotherapy success rates [15]. Altogether, our findings show that these TNFRSF genes have the potential to be exploited as immunotherapy biomarkers. Based on purpose, choosing a single gene or effective integration of these genes will help boost prediction power. It is noteworthy that our results are based on analyses of publicly available datasets. Further biological and clinical research is needed to confirm the predictive abilities of these TNFRSF genes before they are used in clinical practice.

Our data depicts a comprehensive landscape of expression alterations in the 13 TNFRSF genes across a wide range of malignancies, with an emphasis on the association of these genes with type I anti-tumor T-cell responses and oncogene expression. In melanoma, oncogenic NRAS mutations downregulate the expression of multiple TNFRSF genes at bulk and single-cell levels. Moreover, our study suggests that the expression of the 13 TNFRSF genes could be used as potential biomarkers for predicting response to ICB therapy in certain cancer types with a partially complementary role. These findings will help us better understand the role of these TNFRSF genes in cancer development and treatment, and they may lead to the identification of candidate biomarkers for future clinical research and implications.

TNFRSF: Tumor necrosis factor receptor superfamily

NRAS: Neuroblastoma RAS viral oncogene homolog

PD-1: Programmed cell death protein 1

CTLA-4: Cytotoxic T-lymphocyte-associated protein 4

ICB: Immune checkpoint blockade

TRAF: TNFR-associated factor

TCGA: The cancer genome atlas

TARGET: Therapeutically applicable research to generate effective treatments

GTEx: Genotype-tissue expression

FDR: False discovery rate

MAPK: Mitogen-activated protein kinase

ERK: Extracellular signal-regulated kinase

NF-κB: Nuclear factor kappa B

PI3K: Phosphatidylinositol 3‑kinase

AKT: Protein kinase B

PD-L1: PD-ligand 1

TIDE: Tumor immune dysfunction and exclusion

AUC: Area under the receiver operating characteristic curve

TMB: Tumor mutational burden

PFS: Progression-free survival

OS: Overall survival

Ethics approval and consent to participate

The patient data we used was acquired from publicly available datasets that were collected with patients’ informed consent.

Consent for publication

Not applicable.

Availability of data and materials

All datasets used in this study are available in the NCBI Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/), The Cancer Genome Atlas (TCGA; https://tcga‐data.nci.nih.gov), the TARGET Data Matrix (https://ocg.cancer.gov/programs/target/data-matrix), and the Genotype-Tissue Expression (GTEx) databases (https://gtexportal.org/home/).

Competing interests

The authors declare that they have no competing interests.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Authors’ contributions

ZD conceived and designed the experiments. ZD performed the experiments and analyzed the data. ZD and HY wrote and revisited the paper. All authors have read and approved the final manuscript.

Acknowledgments

We would like to thank the computational support provided by Southern Methodist University’s Center. We would also like to thank the researchers who provided the expression profiles in the public repository.

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No competing interests reported.

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Thirteen tumor necrosis factor receptor superfamily gene expression in malignancies and their clinical relevance to immunotherapy: a pan-cancer analysis

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Abstract

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Introduction

Results And Discussion

Potential prognostic value of the 13 TNFRSF genes in cancers

Cancer-type-specific regulation of the 13 TNFRSF genes in tumorigenesis

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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