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Pan-cancer analysis, providing a reliable basis for IDO2 as a prognostic biomarker and target for immunotherapy

  • Bangqian Mo , Xiashuang Zhao , Yongfeng Wang , Xianglai Jiang , Deming Liu and Hui Cai ORCID logo EMAIL logo
Published/Copyright: February 20, 2023
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Oncologie
From the journal Oncologie Volume 25 Issue 1

Abstract

Objectives

Indoleamine 2,3-dioxygenase 2 (IDO2) is a homologous protein of the classical immune negative regulator Indoleamine 2,3-dioxygenase 1 (IDO1) that is indispensable in the metabolism of tryptophan and is closely related to the pathogenesis and progression of tumors. Nevertheless, the mechanism of IDO2 in malignant tumors is not fully understood warranting further research.

Methods

Data related to IDO2 in pan-cancer was obtained from The Cancer Genome Atlas (TCGA) database. Differences in IDO2 expression between pan-cancerous and corresponding normal tissues were analyzed, and survival rates were analyzed using Kaplan–Meier. The correlation between IDO2 expression and tumor-infiltrating immune cells (TIICs), tumor mutational load (TMB), microsatellite instability (MSI), mismatch repair (MMR), immune checkpoints (ICP) and DNA methyltransferase (DNMT) was investigated by Spearman correlation analysis. Functional enrichment analysis of IDO2 was performed to explore its biological and molecular roles in tumors.

Results

Our comprehensive pan-cancer analysis showed that IDO2 expression was significantly altered in most malignancies and correlated with poor prognosis. The expression of IDO2 was strongly associated with the progression of several tumors and excessive infiltration of immune cells in the tumor microenvironment (TME). The expression of IDO2 significantly correlated with TMB, MSI, MMR and ICP in different tumors. More importantly, functional enrichment analysis showed that IDO2 acts primarily through the regulation of antitumor immunological processes. RT-PCR validated IDO2 expression in multiple cancer cell lines, consistent with the bioinformatic analysis results.

Conclusions

IDO2 is closely related to tumor genesis and immunity, and can be used as an adjunct for the diagnosis and prognosis assessment of many tumors.

Keywords: IDO2; immunotherapy; pan-cancer; prognosis; TCGA; tumor microenvironment

Introduction

Indoleamine 2,3-dioxygenase 2 (IDO2) is a homolog of the tryptophan catabolic enzyme IDO1 and is located downstream of the classical IDO1 on human chromosome 8p21 [1]; it is also a heme-containing enzyme with a lower affinity for tryptophan than IDO1 and acts as a negative regulator of IDO1, primarily by competing with IDO1 for heme binding [2]. IDO2 is an immunomodulatory molecule expressed in several cancers that inhibits T-cell proliferation [3]. It has been established that tryptophan metabolism in humans regulates the immune response to cancer, and IDO2 catabolizes tryptophan to promote tumor growth [4], [5], [6]. Over time, the decrease in tryptophan levels inhibits CD8 T cell proliferation, while tryptophan levels can reportedly induce differentiation of CD4 CD25 Foxp3 Treg cells, PD-1 expression in CD8 T cells, and CD8 T cell death, which in turn promotes the immune escape of tumor cells [3, 7], [8], [9].

The past few years have witnessed significant medical progress, especially with immune checkpoint (ICP) blockade therapy which has yielded significant clinical results. Immunotherapy of IDO1 has become a research hotspot in recent years. Although IDO1 inhibitors have entered phase III clinical trials in glioma [10], melanoma [11], prostate cancer [12], breast cancer [13], head and neck cancer [14] and colorectal cancer [15], the efficacy remains unsatisfactory. There is evidence that the expression of IDO2 inhibits CD4 and CD8+T cell proliferation and limits anti-tumor immunity [16]. Current evidence suggests that IDO2 knockout enhances IFN secretion and increases the level of tumor-infiltrating immune cells [17]. Moreover, silencing IDO2 can reportedly lead to decreased nicotinamide adenine dinucleotide (NAD+) and increased reactive oxygen species (ROS) in cancer cells. A decrease in NAD+ and an increase in ROS can induce apoptosis in cancer cells [18]. In addition, silencing IDO2 promotes T-cell proliferation and inhibits tumor cell migration and growth [19]. Taken together, these findings suggest that IDO2 affects tumor immunity and tumor cell proliferation, migration and survival. Accordingly, by exploring the role of IDO2 in the tumor immune environment, it is possible to develop new drugs targeting this enzyme in the tryptophan metabolic pathway for cancer immunotherapy.

Multi-omics databases such as TCGA, cBioPortal, TIMER, TISIDB and UALCAN are widely acknowledged for collecting comprehensive multi-omics data on human cancer patients. Based on these databases, we comprehensively analyzed IDO2 gene expression, including differential expression, prognostic value and its correlation with tumor progression, TIICs, TMB, MSI, MMR, ICP and DNMT. Functional enrichment analysis of IDO2 was performed. This study sought to provide the foothold for using IDO2 as a prognostic biomarker and target during immunotherapy.

Methods

Data sources and processing

The TCGA data were downloaded from the UCSC Xena data center (https://xena.ucsc.edu/). We downloaded transcripts of IDO2 expression data for 33 cancers and compiled information on the corresponding RNA sequences, somatic mutations, clinicopathological parameters, and survival data for each cancer for subsequent analysis.

Expression analysis of IDO2

IDO2 expression data were extracted from 33 cancers and their corresponding normal tissues. IDO2 expression differences were analyzed among cancer subgroups using the “limma” R package. The TPM format RNAseq data of TCGA and GTEx was processed by UCSC XENA through the Toil process, and the RNAseq data of TPM (transcripts per million reads) format were analyzed and compared after log2 transformation, and the results were compared by the Wilcoxon rank sum test. We additionally investigated the changes in the type and frequency of genetic alterations of IDO2 genes according to the cBioPortal database (https://www.cbioportal.org/).

Survival, ROC curve and tumor progression analyses of IDO2

Pan-cancer expression data of IDO2 and survival information of pan-cancer were extracted. Univariate Cox regression analysis based on 95% confidence intervals and risk ratios (HR) was performed to assess the correlation between IDO2 expression and the survival rate of patients in pan-cancer. The results were visualized in forest plots and Kaplan–Meier curves. The RNAseq data were analyzed and visualized using the R packages “pROC” package and “ggplot2.” The predictive performance was assessed by calculating the area under the ROC curve (AUC). The relationship between IDO2 expression and tumor progression and immune cell infiltration was evaluated using data from TCGA and the Tumor Immune Estimation Resource (https://cistrome.shinyapps.io/timer/) databases.

Analysis of the TME and TIICs

Immune and stromal cell scores were calculated using the R package “ESTIMATE” to investigate the correlation between IDO2 expression and the TME. The relevance between IDO2 expression and cancer immune infiltrating cells was analyzed by the ‘Immunedeconv’ package (an R package including both TIMER and CIBERSOR algorithms), and the results were presented as heatmaps. The TISIDB website (http://cis.hku.hk/TISIDB/index.php) was used to analyze the association between IDO2 expression and the immune and molecular subtypes of different cancer types.

Analysis of IDO2 expression versus TMB, MSI, MMR, ICP, DNMT and methylation

The association between IDO2 expression and TMB and MSI of patients with pan-cancer was examined in radar plots by the “fmsb” R package. The associations between MMR, ICP, DNMT genes and IDO2 expression levels were visualized in heat maps. The methylation of IDO2 in pan-cancer was assessed using the UALCAN (http://ualcan.path.uab.edu/index.html) database.

Functional enrichment analysis

The biological and molecular functions of IDO2 in pan-cancer were explored by Gene Ontology (GO) analysis and related pathways by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

Drug sensitivity analysis

The relationship between IDO2 expression and drug sensitivity was examined by pearson correlation analysis.

Cell culture, RNA isolation and RT-PCR

MCF-7 and MDA-MB-231 breast cancer cells, HUH-7 and HepG2 liver cancer cells, AGS and MKN-45 gastric cancer cells were placed in a humidified 5% CO2 incubator at 37 °C and cultured in RPMI-1640 containing 10% fetal bovine serum (FBS) (Invitrogen), 1% double antibodies (streptomycin and penicillin) (Corning), while MCF-10 A normal mammary epithelial cells, L-O2 normal hepatocytes and GES-1 normal gastric epithelial cells were cultured in DMEM medium under the same conditions. RNA was extracted according to the instructions of the M5 Universal RNA Mini Kit, and to determine RNA concentration and purity compliance, absorbance values were measured at 260 and 280 nm. RNA was reverse transcribed to cDNA according to the instructions of the M5 Sprint qPCR RT kit with gDNA remover reverse transcription kit. 2 × M5 HiPer SYBR Premix EsTaq (with Tli RnaseH) was used as a fluorescent dye for RT-qPCR assay. IDO2 primers were designed and synthesized by Bioengineering (Shanghai) Co. The sequences used are forward, 5′-AGCCAAACCATCTCCCA-3′; reverse, 5′-CCTGACCCTCATTCTCCA-3′. GATGG-3′. RT-qPCR reaction conditions were as follows: 95 °C for 30 s; 95 °C for 5 s, 60 °C for 30 s, 40 cycles; 60 °C for 20 s, 95 °C for 20 s. IDO2 mRNA expression levels were calculated and analyzed by the 2 −ΔΔCt formula.

Statistical analysis

Statistical analyses were computed for this study using the online database described above. A p-value <0.05 was statistically significant.

Results

Differential expression of IDO2 in normal tissues and tumor samples

TCGA database analysis was conducted to compare differences in IDO2 gene expression between normal and tumor samples (Figure 1A). Except for cancers for which no normal tissue data were available, IDO2 was expressed between 24 tumors and normal tissues, among which the expression of IDO2 was significantly different in 15 cancer types. Seven cancer types, including BRCA, CESC, ESCA, HNSC, LUAD, STAD and UCEC, showed significant upregulation of IDO2 expression in tumor samples, while IDO2 was significantly downregulated in eight cancer types, including CHOL, KICH, KIRP, LIHC, LUSC, PCPG, THCA and THYM. Differential expression analysis of IDO2 in other tumors is shown in Figure 1B. Besides MESO and UVM, IDO2 was expressed in 31 cancers, with differential expression in 26 malignant tumors. The cBioPortal (TCGA, Pan-Cancer Atlas) database was used to observe the genetic alterations in IDO2 in pan-cancer samples. Figure 1C illustrates that the highest prevalence of IDO2 alteration in pan-cancer samples was associated with invasive breast carcinoma (9%), and the most frequent genetic mutation was amplification.

Figure 1: (A) Comparison of IDO2 expression in tumor and normal tissues (from TCGA database). (B) Comparison of IDO2 expression in tumor tissues and normal tissues (from TCGA and GTEx database). (C) Type and frequency of genetic alterations of IDO2 gene in pan-cancer (from cBioPortal database).
Figure 1:

(A) Comparison of IDO2 expression in tumor and normal tissues (from TCGA database). (B) Comparison of IDO2 expression in tumor tissues and normal tissues (from TCGA and GTEx database). (C) Type and frequency of genetic alterations of IDO2 gene in pan-cancer (from cBioPortal database).

Prognostic and diagnostic value of IDO2 in multiple cancer

The correlation between IDO2 and survival was analyzed using TCGA database for 33 cancer types in terms of overall survival (OS) and disease-specific survival (DSS). The forest plot in Figure 2A shows that the expression of IDO2 in numerous tumors was related to the OS of patients. KM curves (Figure 2) revealed that the overexpression of IDO2 was associated with good prognosis in patients with CESC (B), HNSC (C), LUAD (F), MESO (G), PCPG (H), SARC I) and SKCM (J), however, KIRC (D), KIRP (E), UCS (K) and UVM (L) cancers with the high expression of IDO2 had a poor prognosis. The results of univariate Cox risk regression of DSS with IDO2 expression are shown in Figure 3A. KM data showed longer DSS rates of patients with elevated levels of IDO2 expression in CESC (B), HNSC (C), LUAD (D), MESO (E), PCPG (F) and SKCM (G). In contrast, upregulation of IDO2 expression in tumor samples was associated with poor prognosis in THCA (H), UCS (I), and UVM (J). The KM curve of the relationship between IDO2 and DFI and PFI is provided in the supplementary file. Furthermore, the diagnostic value of IDO2 in various malignancies was examined by generating receiver operating characteristic (ROC) curves. As shown in Figure 4, the IDO2 had a moderate diagnostic accuracy of CESC(A), DLBL (B), KICH (C), KIRP(D), LIHC (E), LUSC (F), PAAD (G), TGCT (H), LAML(I), THCA(J), THYM (K) and UCEC (L) (AUCs were above 0.7). To summarize, survival and ROC curve analyses indicated that IDO2 has significant prognostic and diagnostic value in multiple cancers.

Figure 2: (A) Forest plot illustrating the univariate Cox risk regression of OS with IDO2 expression, (B–L) analysis of IDO2 expression and OS using Kaplan–Meier.
Figure 2:

(A) Forest plot illustrating the univariate Cox risk regression of OS with IDO2 expression, (B–L) analysis of IDO2 expression and OS using Kaplan–Meier.

Figure 3: (A) A forest plot showing the univariate Cox regression on DSS with IDO2 expression, (B–J) analysis of IDO2 expression and DSS using Kaplan–Meier methods.
Figure 3:

(A) A forest plot showing the univariate Cox regression on DSS with IDO2 expression, (B–J) analysis of IDO2 expression and DSS using Kaplan–Meier methods.

Figure 4: ROC analysis of IDO2 genes.
Figure 4:

ROC analysis of IDO2 genes.

Correlation between IDO2 expression and tumor progression

As the expression of IDO2 in different cancers is heterogeneous, the regulatory mechanism of IDO2 may likely differ in different tumor microenvironments [3]. Accordingly, we explored the relationship between IDO2 expression and different tumor stages. As shown in Figure 5, significant differences in IDO2 expression in HNSC (A), LIHC (B), LUAD (C) and STAD (D) were observed between stage I/II and stage III/IV tumors. Furthermore, TIMER database analysis showed that IDO2 expression in these cancers was correlated with CD8+T, CD4+T, dendritic cells, and macrophage cells, suggesting that IDO2 expression can affect the tumor immune environment.

Figure 5: Correlation of IDO2 expression with tumor Progression and immune infiltrating cells in several cancers. Relevance of IDO2 expression with TNM staging in (A) HNSC, (B) LIHC, (C) LUAD and (D) STAD in the TCGA database, link of IDO2 expression with tumor purity and immune cell infiltration in these cancers (from TIMER database).
Figure 5:

Correlation of IDO2 expression with tumor Progression and immune infiltrating cells in several cancers. Relevance of IDO2 expression with TNM staging in (A) HNSC, (B) LIHC, (C) LUAD and (D) STAD in the TCGA database, link of IDO2 expression with tumor purity and immune cell infiltration in these cancers (from TIMER database).

Correlation between IDO2 expression and TIICs

TIMER analysis showed that IDO2 expression was significantly associated with TIICs, such as CD4+ T cells, CD8+ T cells, neutrophils, macrophages, DCs and B cells in 22, 19, 21, 14, 22 and 28 cancers, respectively (Figure 6A). In most cancers except ACC, LIHC, MESO and OV, IDO2 expression was positively correlated with multiple infiltrating immune cells. In addition, the CIBERSORT tool was used to explore the relationship between IDO2 expression and percolation in different immune cell subtypes (Figure 6B). Among 22 immune cell subtypes, we found that IDO2 expression in most cancers was associated with Tregs, gamma delta T cell, follicular helper T cell, T cell CD8+, activated memory CD4+ T cell, M1 Macrophage and B cell memory subtypes, and immune cell subtypes such as resting NK cell, resting Mast cell, activated Mast cell, M2 Macrophage, M0 Macrophage and plasma B cell. The ESTIMATE algorithm was used to calculate the immune and stromal fractions separately. The results showed that IDO2 expression significantly correlated with immune and stromal scores of cancer patients in CESC, HNSC, KIRC, LUAD, SARC, SKCM, STAD and UVM cancers (Figure 7A, B). The correlation between IDO2 and immune and stromal scores in other cancer patients is presented in the Supplementary Material.

Figure 6: TIICs correlate with IDO2 expression. (A) IDO2 expression correlates with the level of infiltration of several immune cells in the TIMER database. (B) IDO2 expression correlates with the degree of immune cell infiltration based on CIBERSOR. Cancer types are represented by the horizontal axis, immunity scores by the vertical axis, and correlation coefficients by the colors.*p<0.05, **p<0.01, ***p<0.001.
Figure 6:

TIICs correlate with IDO2 expression. (A) IDO2 expression correlates with the level of infiltration of several immune cells in the TIMER database. (B) IDO2 expression correlates with the degree of immune cell infiltration based on CIBERSOR. Cancer types are represented by the horizontal axis, immunity scores by the vertical axis, and correlation coefficients by the colors.*p<0.05, **p<0.01, ***p<0.001.

Figure 7: Correlation of IDO2 expression with estimate scores in CESC, HNSC, KIRC, LUAD, SARC, SKCM, STAD and UVM. (A) Immune score. (B) Stromal score.
Figure 7:

Correlation of IDO2 expression with estimate scores in CESC, HNSC, KIRC, LUAD, SARC, SKCM, STAD and UVM. (A) Immune score. (B) Stromal score.

Correlation of IDO2 expression with immune and molecular subtypes

It is widely acknowledged that different immune subtypes have significant clinical value in multiple tumors [20]. Molecular subtypes can deepen our understanding of cancer and can provide insights into pathways associated with tumor subsets [21]. We next explored the effect of IDO2 expression on immune and molecular subtypes in human malignancies using the TISIDB website. As shown in Figure 8A–I, IDO2 expression was significantly associated with different immune subtypes of CESC, CHOL, LIHC, LUAD, LUSC, MESO, SARC, TGCT and UCEC, respectively. Moreover, IDO2 was differentially expressed by different immune subtypes of the same type of cancer. For example, for MESO (Figure 8F), IDO2 was upregulated in C3 and C4 types and downregulated in C1, C2 and C6 subtypes. For the different molecular cancer subtypes, there was a significant correlation with IDO2 expression in LIHC, LUSC and UCEC (Figure 8J–L, respectively).

Figure 8: Correlation of IDO2 expression with immune and molecular subtypes in pan-cancer. Correlation of IDO2 expression with immune subtypes in CESC (A), CHOL (B), LIHC (C), LUAD (D), LUSC (E), MESO (F), SARC (G), TGCT (H) and UCEC (I); the expression of IDO2 with molecular subtypes in LIHC (J), LUSC (K) and UCEC (L) significant relationship. C1: wound healing, C2: IFN-gamma dominant, C3: inflammatory, C4: Lymphocyte depleted, C5: immunologically quiet, C6: TGF-b dominant.
Figure 8:

Correlation of IDO2 expression with immune and molecular subtypes in pan-cancer. Correlation of IDO2 expression with immune subtypes in CESC (A), CHOL (B), LIHC (C), LUAD (D), LUSC (E), MESO (F), SARC (G), TGCT (H) and UCEC (I); the expression of IDO2 with molecular subtypes in LIHC (J), LUSC (K) and UCEC (L) significant relationship. C1: wound healing, C2: IFN-gamma dominant, C3: inflammatory, C4: Lymphocyte depleted, C5: immunologically quiet, C6: TGF-b dominant.

Correlation between IDO2 expression and TMB, MSI and MMR

An increasing body of evidence suggests that tumor development is associated with TMB, MSI and MMR [22], [23], [24]. In the present study, we found that the expression of IDO2 was positively correlated with TMB in LGG and negatively correlated in CHOL, HNSC, LUAD, PAAD, STAD and THCA (Figure 9A). MSI is a marker for immune checkpoint inhibitors documented in several malignancies [25]. A positive correlation was found between MSI and IDO2 in LUAD, PRAD, and UCEC and a negative correlation in ESCA, LIHC, SKCM, TCTG, and UCS (Figure 9B). In addition, the relationships between IDO2 expression and MMR gene expression were evaluated, including epithelial cell adhesion molecule (EPCAM), post-meiotic segregation increase 2 (PMS2), MutS homolog 6 (MSH6), MSH2, and MutL homolog (MLH1). IDO2 expression was significantly correlated with at least one MMR gene in most tumor types except ACC, BLCA, CESC, ESCA, KICH, KIRP, MESO, OV, THYM, UCEC and UCS (Figure 9C). Among them, EPCAM exhibited the most significant correlation in some tumors.

Figure 9: (A) Radar plot showing the overlap between IDO2 and TMB in 33 cancer types. (B) Radar plot showing the overlap between IDO2 and MSI in 33 cancer types. Blue numbers represent Spearman’s correlation coefficients. (C) Heat map illustrating the association between IDO2 expression and MMR genes. *p<0.05, **p<0.01, ***p<0.001.
Figure 9:

(A) Radar plot showing the overlap between IDO2 and TMB in 33 cancer types. (B) Radar plot showing the overlap between IDO2 and MSI in 33 cancer types. Blue numbers represent Spearman’s correlation coefficients. (C) Heat map illustrating the association between IDO2 expression and MMR genes. *p<0.05, **p<0.01, ***p<0.001.

Correlation between IDO2 expression and ICP, DNMT genes, methylation

ICP genes have been shown to impact immune cell infiltration and immunotherapy. In the present study, analysis of the correlation between IDO2 expression and ICP genes (Figure 10A) showed that IDO2 expression was associated with multiple cancer types among 46 ICP genes. The expression of IDO2 exhibited a good correlation with the expression of multiple ICP genes in most tumors, such as PDCD1 (PD-1), CTLA4, TNFRSF9, CD86, CD274, TIGIT, LAG3, ICOS, CD40LG, CD48, and CD28. Accordingly, IDO2 may be involved in the activation of immune checkpoint genes in multiple signaling pathways and play a role in tumor progression. We performed correlation analysis between IDO2 and the expression of four methyltransferases (DNMT3A, DNMT3B, DNMT1, DNMT2) in 33 tumors, including BRCA, CESC, COAD, DLBC, GBM, HNSC, KIRC, KIRP, LUAD, PAAD, PRAD, SKCM, STAD, THCA and UCS (Figure 10B). IDO2 expression was positively correlated with at least one methyltransferase gene in LIHC, SARC, TGCT and UCEC tumors. IDO2 expression was significantly negatively correlated with at least one methyltransferase gene. No correlation was found in other tumors with methyltransferase genes. As shown in Figure 11, we analyzed the methylation levels of IDO2 in pan-cancer by UALCAN database and found that BLCA (A), BRCA (B), COAD (C), HNSC (D), KIRC (E), KIRP (F), LIHC (G), LUAD (H), PCPG (K), READ (L), SARC (M), TGCT (N) and UCEC exhibited low methylation levels of IDO2, in contrast, IDO2 was highly methylated in LUSC (I) and PRAD (J).

Figure 10: (A) Combined expression of IDO2 and ICP genes in 33 cancers. (B) Correlation between IDO2 expression and methyltransferase expression genes found in 33 cancer types. *p<0.05, **p<0.01, ***p<0.001.
Figure 10:

(A) Combined expression of IDO2 and ICP genes in 33 cancers. (B) Correlation between IDO2 expression and methyltransferase expression genes found in 33 cancer types. *p<0.05, **p<0.01, ***p<0.001.

Figure 11: Methylation levels of IDO2 in pan-cancer. Methylation of IDO2 in BLCA (A), BRCA (B), COAD (C), HNSC (D), KIRC (E), KIRP (F), LIHC (G), LUAD (H), LUSC (I), PRAD (J), PCPG (K), READ (L), SARC (M), TGCT (N) and UCEC (O) levels.
Figure 11:

Methylation levels of IDO2 in pan-cancer. Methylation of IDO2 in BLCA (A), BRCA (B), COAD (C), HNSC (D), KIRC (E), KIRP (F), LIHC (G), LUAD (H), LUSC (I), PRAD (J), PCPG (K), READ (L), SARC (M), TGCT (N) and UCEC (O) levels.

GESA analysis of IDO2 expression

To explore the biological processes or signaling pathways through which IDO2 affects tumorigenesis, we performed GO functional annotation and KEGG pathway analysis of IDO2 in different cancers. GO analysis showed that IDO2 expression could affect the tryptophan metabolism process, gene silencing, cytokine secretion, ribonucleic acid binding, leukocyte migration, leukocyte proliferation, positive regulation of cell cycle G1-S phase transition, B-cell activation, migration of vascular endothelial cells and other biological processes (Figure 12). Higher expression of IDO2 in CHOL (B), COAD (C), KIRP (E), LUAD (F), THCA (G), and THYM (H) was associated with more active immune function. In contrast, lower expression of IDO2 in CESC (A) and HNSC (D) was associated witth more active immune function. These immune function activities include immune response regulation, positive regulation of cellular immune effector processes, leukocyte-mediated immune regulation, antigen receptor-mediated signaling pathways, Fc receptor signaling pathways, immune response regulation of cell surface receptor signaling pathways, adaptive immune responses based on spontaneous recombination of immune receptors with immunoglobulin superfamily structures, immunoglobulin complexes. As shown in Figure 12, KEGG pathway analysis showed that IDO2 regulates key immune cell-related pathways in CESC (I), KICH (J), LGG (K), LIHC (L), SKCM (M), STAD (N), THCA (O) and UVM (P) cancer types, including chemokine signaling pathways, cell receptor signaling pathway, fine JAK-STAT signaling pathway, regulation of autophagy, cytoplasmic DNA-sensing pathway and natural killer cell-mediated cytotoxicity.

Figure 12: GSEA results. GO annotation of IDO2 in CESC (A), CHOL (B), COAD (C), HNSC (D), KIRP (E), LUAD (F), THCA (G) and THYM (H). IDO2 in CESC (I), KICH (J), LGG (K), LIHC (L), SKCM (M), STAD (N), THCA (O) and UVM (P) KEGG pathway analysis. Cancer-related functional pathways are shown by curves of different colors. Positive peaks indicate positive regulation, while negative peaks indicate negative regulation.
Figure 12:

GSEA results. GO annotation of IDO2 in CESC (A), CHOL (B), COAD (C), HNSC (D), KIRP (E), LUAD (F), THCA (G) and THYM (H). IDO2 in CESC (I), KICH (J), LGG (K), LIHC (L), SKCM (M), STAD (N), THCA (O) and UVM (P) KEGG pathway analysis. Cancer-related functional pathways are shown by curves of different colors. Positive peaks indicate positive regulation, while negative peaks indicate negative regulation.

Drug sensitivity study

Analysis of the relationship between IDO2 expression and drug sensitivity showed that IDO2 expression was positively correlated with the IC50 value for Zoledronate, Elesclomol, Imiquimod, Megestrol acetate, and Paclitaxel (Figure 13). Higher IDO2 expression was associated with higher IC50 values and weaker ability of the drug to induce cancer cell death, suggesting that some cancer cells are more resistant to the drug. In contrast, it was negatively correlated with LOR-253, Trametinib, and Karenitecin, suggesting that IDO2 expression reduces the resistance of cancer cells to drugs.

Figure 13: Drug sensitivity analysis. Correlations between IC50 for different drugs and IDO2 expression.
Figure 13:

Drug sensitivity analysis. Correlations between IC50 for different drugs and IDO2 expression.

Validation of IDO2 expression

IDO2 expression was analyzed in MCF-7, MDA-MB-231 and MCF-10 A HUH-7, HepG2 and L-O2, AGS, MKN-45 and GES-1 cells (Figure 14). Results showed that IDO2 expression in breast cancer cells (A) and gastric cancer cells (C) were significantly higher than in normal cells. In contrast, IDO2 expression in liver cancer cells (B) was significantly lower than in normal cells (p<0.05), consistent with the findings of bioinformatics analysis. The expression of IDO2 in cell lines is shown in Table 1.

Figure 14: Results of IDO2 expression validation (A) IDO2 expression in normal human breast epithelial cell line (MCF-10 A) and human breast cancer cell lines (MCF-7 and MDA-MB-231). (B) IDO2 expression in the human normal liver cell line (L-O2) and human hepatocellular carcinoma cell lines (HUH-7 and HepG2). (C) IDO2 expression in the human normal gastric epithelial cell line (GES-1) and human gastric cancer cell lines (AGS and MKN-45). *p<0.05, **p<0.01, ***p<0.001.
Figure 14:

Results of IDO2 expression validation (A) IDO2 expression in normal human breast epithelial cell line (MCF-10 A) and human breast cancer cell lines (MCF-7 and MDA-MB-231). (B) IDO2 expression in the human normal liver cell line (L-O2) and human hepatocellular carcinoma cell lines (HUH-7 and HepG2). (C) IDO2 expression in the human normal gastric epithelial cell line (GES-1) and human gastric cancer cell lines (AGS and MKN-45). *p<0.05, **p<0.01, ***p<0.001.

Table 1:

Expression of IDO2 in cancer cells.

Normal breast epithelial cells MCF-10 A Normal
Breast cancer cells MCF-7 Upregulated
MDA-MB-231 Upregulated
Normal liver cells L-O2 Normal
Liver cancer cells HUH-7 Downregulated
HepG2 Downregulated
Normal stomach epithelial cells GES-1 Normal
Stomach cancer cells AGS Upregulated
MKN-45 Upregulated

Discussion

IDO2 is widely thought to have huge prospects as a target for immune checkpoint inhibitors based on current evidence that the blockade of IDO2 yields a remarkable antitumor effect [26]. This study refined our current understanding of the role and characteristics of IDO2 in different cancers.

Herein, we provided hitherto undocumented evidence of elevated expression of IDO2 in most tumors. It has been demonstrated that IDO2 expression is upregulated in pancreatic [27, 28], intestinal, gastric and renal tumors [29] and downregulated in cervical cancer [30]. However, in this study, IDO2 was lowly expressed in colon cancer, possibly due to the relatively small number of colon cancer and normal tissue samples in the TCGA database, which accounted for the inconsistency with previous studies. This discrepancy may also be due to the different sources of samples.

Moreover, KM survival analysis using TCGA database data showed that elevated IDO2 expression was associated with prognosis across multiple malignancies. In terms of OS, patients with KIRC, KIRP, UCS, and UVM were associated with a poorer prognosis when IDO2 expression was upregulated. In contrast, high expression of IDO2 was associated with good prognosis in patients with CESC, HNSC, LUAD, MESO, PCPG, SARC and SKCM. A study reported that IDO2 was differentially expressed in non-small cell lung cancer and associated with poor patient outcomes [31]. We also found a clear association between IDO2 expression and tumor stage in HNSC, LIHC, LUAD, and STAD. Previously, it has been reported that polymorphisms of the IDO2 gene were related to the progression of pancreatic cell carcinoma [27, 28] and multiple myeloma [32]. In melanoma, IDO2 overexpression inhibited T-cell proliferation and promoted tumorigenesis and progression [18]. The silencing of IDO2 increases the proliferation of T cells, with decreased Treg production, enhanced cytotoxic T lymphocyte activity and decreased percentage of CD4+ CD25+ Foxp3+ Tregs [19]. IDO2 knockdown can prevent T cell failure, increase CD80 in p splenic DCs and CD8+ T cell toxicity, decrease PD-1 expression, enhance anti-breast cancer therapeutic effects, relieve tumor immunosuppression and inhibit tumor growth [33]. It has also been found that IDO2 is an active target in pancreatic carcinoma, and IDO inhibitors preferentially target and suppress the expression of IDO2, reducing the level of Kynurenine in TME and restoring the anti-tumor immune response [34]. These results suggest that peak IDO2 expression correlates with TNM staging and cancer prognosis. Importantly, the development of pharmacological therapies with IDO2 inhibitors is expected to enhance antitumor efficacy and improve patient survival.

The high metabolic activity of tumor cells has a critical impact on the immune response of TME [35]. This study demonstrated that IDO2 expression strongly correlated with CD8+T, CD4+Ts, B cells, DCs and macrophages in most tumors. It has been reported that the tryptophan catabolic enzyme IDO1 promotes tumor progression and is involved in the local inhibition of antitumor T cells [36]. Moreover, tryptophan metabolism is reduced in cells that co-express IDO1 and IDO2, while the negative regulation of apoptosis is enhanced.The number of cancer types in which IDO2 is over-expressed is smaller than that of IDO1, but it is closely related to immune cells in TME. It has been reported that IDO2 is expressed in DCs and contributes to their homeostatic tolerance [37]. By mediating the cross-talk between auto-reactive T cells and B cells, IDO2 expression in B cells modulates the autoimmune response [38]. Importantly, IDO1 mediates T cell inhibition and is also involved in decreased activation of autoreactive T cells after IDO2 knockout. IDO2 acts as a pro-inflammatory mediator of the B cell response in B cells and mediates the immune response to T-independent type II antigens [39]. The above results suggest that IDO1 and IDO2 can influence each other in the immune environment and modulate the immune response to the tumor by affecting the infiltration of different immune cells.

In addition, TMB can serve as a biomarker for pan cancer [40] and a therapeutic agent for immune system disorders [41]. In non-small cell lung cancer [42] and colorectal cancer [43], targeting TMB can reportedly improve antitumor efficacy, and TMB can also predict the prognosis of cancer patients [44]. Moreover, in colorectal cancer patients, a high MSI predicts their clinical profile and prognosis [45]. This study found a significant association between IDO2 expression and TMB in seven cancer types and MSI in eight cancer types. At least one MMR gene was associated with IDO2 expression in multiple cancers. Besides, we found that IDO2 expression was correlated with multiple immune checkpoint genes in most tumors. Nonetheless, the mechanisms by which IDO2 is co-expressed with different immune checkpoints in cancer and affects tumor immunity remain to be further explored.

In the present study, KEGG pathway analysis and GO annotation showed IDO2 expression was associated with the regulation of immune-related functions and pathways, such as tryptophan metabolic pathway, immune response regulation, positive regulation of cellular immune effector processes, leukocyte-mediated immune regulation, antigen receptor-mediated signaling pathway, fine JAK-STAT signaling pathway, regulation of autophagy, and cytoplasmic DNA sensing pathway. Most importantly, tryptophan metabolism represents a potential target for cancer treatment, where tryptophan depletion and uric acid accumulation inhibit T cell proliferation, tumor immune infiltration is restricted, and antitumor immune responses are suppressed [46, 47]. There is a relationship between higher expression of IDO1 and lower expression of infiltrating CD3 T cells, CD8 T cells, CD57 NK cells and B cells, as well as enhanced IDO1 activity in the process of Trp catabolism, which suppresses the antitumor immune response [48], [49], [50], [51], [52]. Immune tolerance mediated by IDO1 may be enhanced by IDO2 [53]. It has been reported that the liver does not express IDO1 [54], and IDO1 expression and activity are suppressed in the immune compartment, whereas the immune checkpoint molecule CTLA4 stimulates the expression of IDO1 in dendritic cells (DC) through outside-in signaling of co-stimulatory molecules CD80 and CD86 [55]. This process is closely regulated by the suppressor of cytokine signaling 3 (SOCS3), which targets IDO1 for proteasomal degradation [53]. Therefore, Treg cells can act as inducers of IDO1 during tryptophan metabolism [56]. Moreover, IDO1 can be induced in antigen-presenting cells (APCs) and B cells [57], while IDO2 is expressed in the liver [58], and its expression is involved in regulation in APCs and B cells through binding to the aryl hydrocarbon receptor (AHR). Overall, these findings suggest that IDO2 may be a component of a cell-specific feed-forward loop in IDO1-induced Trp metabolism.

In conclusion, this study demonstrated a positive association between IDO2 expression and documented the IC50 values for Zoledronate, Elesclomol, Imiquimod, Megestrol acetate, and Paclitaxel. Our findings suggest that IDO2 expression enhances the tolerance of cancer cells to drugs and weakens the antitumor effect. Similarly, IDO expression and activity are correlated to poor prognosis of advanced breast cancer and a poor response to neoadjuvant treatment. It has been reported that paclitaxel-resistant breast cancer cells exhibit higher IDO expression and activity [59]. Moreover, desipramine, an antidepressant, lowers the expression of IDO1 and IDO2 in human peripheral blood mononuclear cells (PBMC) [60]. These findings provide compelling evidence that IDO2 has huge prospects as a potential predictor of chemical sensitivity.

Although a comprehensive study of IDO2 has been performed, this study still has some limitations. First, the expression of IDO2 in three cancer types and six cancer cells was only conducted using PCR due to the limited conditions. Moreover, our study findings are primarily based on microarray and sequencing data, which can lead to errors in the analysis of cellular markers. Besides, this study only conducted bioinformatics analysis of IDO2 expression and prognosis using multiple databases, while no in vivo and in vitro experiments were conducted. Furthermore, although we found that IDO2 is strongly associated with infiltrating cells in the tumor immune environment, we could not validate the specific regulatory mechanism of IDO2 in the immune microenvironment. It is believed that in the near future, more studies will demonstrate the significant value of IDO2 as a promising prognostic biomarker and a potential predictor of sensitivity to immunotherapy in various malignancies.

Corresponding author: Hui Cai, The First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou, China; General Surgery Clinical Medical Center, Gansu Provincial Hospital, Lanzhou, Gansu, China; NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China; and Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province, Gansu Provincial Hospital, Lanzhou, Gansu, China, E-mail:

Co-writing: Bangqian Mo , Xiashuang Zhao and Yongfeng Wang were the co-first authors

Funding source: Natural Science Foundation of Gansu Province

Award Identifier / Grant number: No.18JR3RA052

Funding source: The 2021 Central-Guided Local Science and Technology Development Fund

Award Identifier / Grant number: ZYYDDFFZZJ-1

Funding source: Lanzhou Talent Innovation and Entrepreneurship Project Task Contract

Award Identifier / Grant number: 2016-RC-56

Funding source: Gansu Da Vinci robot high-end diagnosis and treatment team construction project, and National Key Research and Development Program

Award Identifier / Grant number: 2018YFC1311500

  1. Research funding: This work was funded by The 2021 Central-Guided Local Science and Technology Development Fund (ZYYDDFFZZJ-1), Natural Science Foundation of Gansu Province, China (No. 18JR3RA052), Lanzhou Talent Innovation and Entrepreneurship Project Task Contract (No. 2016-RC-56), Gansu Da Vinci robot high-end diagnosis and treatment team construction project, and National Key Research and Development Program (No. 2018YFC1311500). The above project leader is Hui Cai, who contributed to this manuscript: conceptualisation, funding.

  2. Author contributions: Bangqian Mo: Writing-Original draft preparation. Xiashuang Zhao: Writing-Review and Editing. Yongfeng Wang: Visualization, Data curation. Xianglai Jiang: Validation. Deming Liu: Investigation. Hui Cai: Conceptualization, Funding acquisition. Final draft read and approved by all authors.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: Not applicable.

References

1. Prendergast, GC, Metz, R, Muller, AJ, Merlo, LM, Mandik-Nayak, L. IDO2 in immunomodulation and autoimmune disease. Front Immunol 2014;5:585. https://doi.org/10.3389/fimmu.2014.00585.Search in Google Scholar PubMed PubMed Central

2. Mondanelli, G, Mandarano, M, Belladonna, ML, Suvieri, C, Pelliccia, C, Bellezza, G, et al.. Current challenges for IDO2 as target in cancer immunotherapy. Front Immunol 2021;12:679953. https://doi.org/10.3389/fimmu.2021.679953.Search in Google Scholar PubMed PubMed Central

3. Li, P, Xu, W, Liu, F, Zhu, H, Zhang, L, Ding, Z, et al.. The emerging roles of IDO2 in cancer and its potential as a therapeutic target. Biomed Pharmacother 2021;137:111295. https://doi.org/10.1016/j.biopha.2021.111295.Search in Google Scholar PubMed

4. Ball, HJ, Sanchez-Perez, A, Weiser, S, Austin, CJ, Astelbauer, F, Miu, J, et al.. Characterization of an indoleamine 2,3-dioxygenase-like protein found in humans and mice. Gene 2007;396:203–13. https://doi.org/10.1016/j.gene.2007.04.010.Search in Google Scholar PubMed

5. Metz, R, Duhadaway, JB, Kamasani, U, Laury-Kleintop, L, Muller, AJ, Prendergast, GC. Novel tryptophan catabolic enzyme IDO2 is the preferred biochemical target of the antitumor indoleamine 2,3-dioxygenase inhibitory compound D-1-methyl-tryptophan. Cancer Res 2007;67:7082–7. https://doi.org/10.1158/0008-5472.can-07-1872.Search in Google Scholar

6. Hou, DY, Muller, AJ, Sharma, MD, DuHadaway, J, Banerjee, T, Johnson, M, et al.. Inhibition of indoleamine 2,3-dioxygenase in dendritic cells by stereoisomers of 1-methyl-tryptophan correlates with antitumor responses. Cancer Res 2007;67:792–801. https://doi.org/10.1158/0008-5472.can-06-2925.Search in Google Scholar

7. Austin, CJ, Rendina, LM. Targeting key dioxygenases in tryptophan-kynurenine metabolism for immunomodulation and cancer chemotherapy. Drug Discov Today 2015;20:609–17. https://doi.org/10.1016/j.drudis.2014.11.007.Search in Google Scholar PubMed

8. Prendergast, GC. Immune escape as a fundamental trait of cancer: focus on IDO. Oncogene 2008;27:3889–900. https://doi.org/10.1038/onc.2008.35.Search in Google Scholar PubMed

9. Fatokun, AA, Hunt, NH, Ball, HJ. Indoleamine 2,3-dioxygenase 2 (IDO2) and the kynurenine pathway: characteristics and potential roles in health and disease. Amino Acids 2013;45:1319–29. https://doi.org/10.1007/s00726-013-1602-1.Search in Google Scholar PubMed

10. Du, L, Xing, Z, Tao, B, Li, T, Yang, D, Li, W, et al.. Correction: both IDO1 and TDO contribute to the malignancy of gliomas via the Kyn-AhR-AQP4 signaling pathway. Signal Transduct Targeted Ther 2021;6:385. https://doi.org/10.1038/s41392-021-00808-9.Search in Google Scholar PubMed PubMed Central

11. Wu, RY, Kong, PF, Xia, LP, Huang, Y, Li, ZL, Tang, YY, et al.. Regorafenib promotes antitumor immunity via inhibiting PD-L1 and IDO1 expression in melanoma. Clin Cancer Res 2019;25:4530–41. https://doi.org/10.1158/1078-0432.ccr-18-2840.Search in Google Scholar

12. Zahm, CD, Johnson, LE, McNeel, DG. Increased indoleamine 2,3-dioxygenase activity and expression in prostate cancer following targeted immunotherapy. Cancer Immunol Immunother 2019;68:1661–9. https://doi.org/10.1007/s00262-019-02394-w.Search in Google Scholar PubMed PubMed Central

13. Wei, JL, Wu, SY, Yang, YS, Xiao, Y, Jin, X, Xu, XE, et al.. GCH1 induces immunosuppression through metabolic reprogramming and IDO1 upregulation in triple-negative breast cancer. J Immunother Cancer 2021;9:e002383. https://doi.org/10.1136/jitc-2021-002383.Search in Google Scholar PubMed PubMed Central

14. Sieviläinen, M, Saavalainen, J, Adnan-Awad, S, Salo, T, Al-Samadi, A. IDO1 inhibition reduces immune cell exclusion through inducing cell migration while PD-1 blockage increases IL-6 and -8 secretion from T cells in head and neck cancer. Front Immunol 2022;13:812822. https://doi.org/10.3389/fimmu.2022.812822.Search in Google Scholar PubMed PubMed Central

15. Kovaleva, OV, Rashidova, MA, Gratchev, AN, Maslennikov, VV, Boulitcheva, IV, Gershtein, ES, et al.. Immunosuppression factors PD-1, PD-L1, and IDO1 and colorectal cancer. Dokl Biochem Biophys 2021;497:66–70. https://doi.org/10.1134/s1607672921020095.Search in Google Scholar PubMed

16. Qian, F, Liao, J, Villella, J, Edwards, R, Kalinski, P, Lele, S, et al.. Effects of 1-methyltryptophan stereoisomers on IDO2 enzyme activity and IDO2-mediated arrest of human T cell proliferation. Cancer Immunol Immunother 2012;61:2013–20. https://doi.org/10.1007/s00262-012-1265-x.Search in Google Scholar PubMed

17. Yamasuge, W, Yamamoto, Y, Fujigaki, H, Hoshi, M, Nakamoto, K, Kunisawa, K, et al.. Indoleamine 2,3-dioxygenase 2 depletion suppresses tumor growth in a mouse model of Lewis lung carcinoma. Cancer Sci 2019;110:3061–7. https://doi.org/10.1111/cas.14179.Search in Google Scholar PubMed PubMed Central

18. Liu, Y, Zhang, Y, Zheng, X, Zhang, X, Wang, H, Li, Q, et al.. Gene silencing of indoleamine 2,3-dioxygenase 2 in melanoma cells induces apoptosis through the suppression of NAD+ and inhibits in vivo tumor growth. Oncotarget 2016;7:32329–40. https://doi.org/10.18632/oncotarget.8617.Search in Google Scholar PubMed PubMed Central

19. Liu, Y, Xu, P, Liu, H, Fang, C, Guo, H, Chen, X, et al.. Silencing IDO2 in dendritic cells: a novel strategy to strengthen cancer immunotherapy in a murine lung cancer model. Int J Oncol 2020;57:587–97. https://doi.org/10.3892/ijo.2020.5073.Search in Google Scholar PubMed

20. Chen, Y, Sun, Z, Chen, W, Liu, C, Chai, R, Ding, J, et al.. The immune subtypes and landscape of gastric cancer and to predict based on the whole-slide images using deep learning. Front Immunol 2021;12:685992. https://doi.org/10.3389/fimmu.2021.685992.Search in Google Scholar PubMed PubMed Central

21. Chen, F, Chandrashekar, DS, Varambally, S, Creighton, CJ. Pan-cancer molecular subtypes revealed by mass-spectrometry-based proteomic characterization of more than 500 human cancers. Nat Commun 2019;10:5679. https://doi.org/10.1038/s41467-019-13528-0.Search in Google Scholar PubMed PubMed Central

22. Hause, RJ, Pritchard, CC, Shendure, J, Salipante, SJ. Classification and characterization of microsatellite instability across 18 cancer types. Nat Med 2016;22:1342–50. https://doi.org/10.1038/nm.4191.Search in Google Scholar PubMed

23. Roudko, V, Cimen Bozkus, C, Greenbaum, B, Lucas, A, Samstein, R, Bhardwaj, N. Lynch syndrome and MSI-H cancers: from mechanisms to "Off-The-Shelf" cancer vaccines. Front Immunol 2021;12:757804. https://doi.org/10.3389/fimmu.2021.757804.Search in Google Scholar PubMed PubMed Central

24. Merino, DM, McShane, LM, Fabrizio, D, Funari, V, Chen, S-J, White, JR, et al.. Establishing guidelines to harmonize tumor mutational burden (TMB): in silico assessment of variation in TMB quantification across diagnostic platforms: phase I of the Friends of Cancer Research TMB Harmonization Project. Journal for immunotherapy of cancer 2020;8:e000147.10.1136/jitc-2019-000147Search in Google Scholar PubMed PubMed Central

25. Yamamoto, H, Imai, K. Microsatellite instability: an update. Arch Toxicol 2015;89:899–921. https://doi.org/10.1007/s00204-015-1474-0.Search in Google Scholar PubMed

26. He, X, He, G, Chu, Z, Wu, H, Wang, J, Ge, Y, et al.. Discovery of the first potent IDO1/IDO2 dual inhibitors: a promising strategy for cancer immunotherapy. J Med Chem 2021;64:17950–68. https://doi.org/10.1021/acs.jmedchem.1c01305.Search in Google Scholar PubMed

27. Nevler, A, Muller, AJ, Sutanto-Ward, E, DuHadaway, JB, Nagatomo, K, Londin, E, et al.. Host IDO2 gene status influences tumor progression and radiotherapy response in KRAS-driven sporadic pancreatic cancers. Clin Cancer Res 2019;25:724–34. https://doi.org/10.1158/1078-0432.ccr-18-0814.Search in Google Scholar

28. Witkiewicz, AK, Costantino, CL, Metz, R, Muller, AJ, Prendergast, GC, Yeo, CJ, et al.. Genotyping and expression analysis of IDO2 in human pancreatic cancer: a novel, active target. J Am Coll Surg 2009;208:781–7. Discussion 7–9. https://doi.org/10.1016/j.jamcollsurg.2008.12.018.Search in Google Scholar PubMed PubMed Central

29. Löb, S, Königsrainer, A, Zieker, D, Brücher, BL, Rammensee, HG, Opelz, G, et al.. IDO1 and IDO2 are expressed in human tumors: levo- but not dextro-1-methyl tryptophan inhibits tryptophan catabolism. Cancer Immunol Immunother 2009;58:153–7. https://doi.org/10.1007/s00262-008-0513-6.Search in Google Scholar PubMed

30. Hascitha, J, Priya, R, Jayavelu, S, Dhandapani, H, Selvaluxmy, G, Sunder Singh, S, et al.. Analysis of Kynurenine/Tryptophan ratio and expression of IDO1 and 2 mRNA in tumour tissue of cervical cancer patients. Clin Biochem 2016;49:919–24. https://doi.org/10.1016/j.clinbiochem.2016.04.008.Search in Google Scholar PubMed

31. Mandarano, M, Bellezza, G, Belladonna, ML, Vannucci, J, Gili, A, Ferri, I, et al.. Indoleamine 2,3-dioxygenase 2 immunohistochemical expression in resected human non-small cell lung cancer: a potential new prognostic tool. Front Immunol 2020;11:839. https://doi.org/10.3389/fimmu.2020.00839.Search in Google Scholar PubMed PubMed Central

32. Kasamatsu, T, Hashimoto, N, Sakaya, N, Awata-Shiraiwa, M, Ishihara, R, Murakami, Y, et al.. IDO2 rs10109853 polymorphism affects the susceptibility to multiple myeloma. Clin Exp Med 2021;21:323–9. https://doi.org/10.1007/s10238-020-00681-w.Search in Google Scholar PubMed

33. Metz, R, DuHadaway, J, Kamasani, U, Laury-Kleintop, L, Muller, A, Prendergast, G. Novel enzyme IDO2 is the preferred biochemical target of D-1MT which relieves tumor immune suppression and stimulates tumor regression. Cancer Res 2008;68:2556.Search in Google Scholar

34. Feng, X, Shen, P, Wang, Y, Li, Z, Bian, J. Synthesis and in vivo antitumor evaluation of an orally active potent phosphonamidate derivative targeting IDO1/IDO2/TDO. Biochem Pharmacol 2019;168:214–23. https://doi.org/10.1016/j.bcp.2019.07.011.Search in Google Scholar PubMed

35. Shrihari, TG. Innate and adaptive immune cells in Tumor microenvironment. Gulf J Oncolog 2021;1:77–81.Search in Google Scholar

36. Nevler, A, Muller, AJ, Sutanto-Ward, E, DuHadaway, JB, Nagatomo, K, Londin, E, et al.. Host IDO2 gene status influences tumor progression and radiotherapy response in KRAS-driven sporadic pancreatic cancers IDO2 polymorphisms affect pancreas cancer and radioresponse. Clin Cancer Res 2019;25:724–34. https://doi.org/10.1158/1078-0432.ccr-18-0814.Search in Google Scholar PubMed PubMed Central

37. Trabanelli, S, Očadlíková, D, Ciciarello, M, Salvestrini, V, Lecciso, M, Jandus, C, et al.. The SOCS3-independent expression of IDO2 supports the homeostatic generation of T regulatory cells by human dendritic cells. J Immunol 2014;192:1231–40. https://doi.org/10.4049/jimmunol.1300720.Search in Google Scholar PubMed PubMed Central

38. Merlo, LM, DuHadaway, JB, Grabler, S, Prendergast, GC, Muller, AJ, Mandik-Nayak, L. IDO2 modulates T cell–dependent autoimmune responses through a B cell–intrinsic mechanism. J Immunol 2016;196:4487–97. https://doi.org/10.4049/jimmunol.1600141.Search in Google Scholar PubMed PubMed Central

39. Merlo, LMF, DuHadaway, JB, Montgomery, JD, Peng, WD, Murray, PJ, Prendergast, GC, et al.. Differential roles of IDO1 and IDO2 in T and B cell inflammatory immune responses. Front Immunol 2020;11:1861. https://doi.org/10.3389/fimmu.2020.01861.Search in Google Scholar PubMed PubMed Central

40. Fumet, JD, Truntzer, C, Yarchoan, M, Ghiringhelli, F. Tumour mutational burden as a biomarker for immunotherapy: current data and emerging concepts. Eur J Cancer 2020;131:40–50. https://doi.org/10.1016/j.ejca.2020.02.038.Search in Google Scholar PubMed PubMed Central

41. Steuer, CE, Ramalingam, SS. Tumor mutation burden: leading immunotherapy to the era of precision medicine? J Clin Oncol 2018;36:631–2. https://doi.org/10.1200/jco.2017.76.8770.Search in Google Scholar PubMed

42. Devarakonda, S, Rotolo, F, Tsao, MS, Lanc, I, Brambilla, E, Masood, A, et al.. Tumor mutation burden as a biomarker in resected non-small-cell lung cancer. J Clin Oncol 2018;36:2995–3006. https://doi.org/10.1200/jco.2018.78.1963.Search in Google Scholar PubMed PubMed Central

43. Lee, DW, Han, SW, Bae, JM, Jang, H, Han, H, Kim, H, et al.. Tumor mutation burden and prognosis in patients with colorectal cancer treated with adjuvant fluoropyrimidine and oxaliplatin. Clin Cancer Res 2019;25:6141–7. https://doi.org/10.1158/1078-0432.ccr-19-1105.Search in Google Scholar

44. 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;51:202–6. https://doi.org/10.1038/s41588-018-0312-8.Search in Google Scholar PubMed PubMed Central

45. 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;342:69–77. https://doi.org/10.1056/nejm200001133420201.Search in Google Scholar

46. Opitz, CA, Somarribas Patterson, LF, Mohapatra, SR, Dewi, DL, Sadik, A, Platten, M, et al.. The therapeutic potential of targeting tryptophan catabolism in cancer. Br J Cancer 2020;122:30–44. https://doi.org/10.1038/s41416-019-0664-6.Search in Google Scholar PubMed PubMed Central

47. Platten, M, Wick, W, Van den Eynde, BJ. Tryptophan catabolism in cancer: beyond IDO and tryptophan depletion. Cancer Res 2012;72:5435–40. https://doi.org/10.1158/0008-5472.can-12-0569.Search in Google Scholar

48. Brandacher, G, Perathoner, A, Ladurner, R, Schneeberger, S, Obrist, P, Winkler, C, et al.. Prognostic value of indoleamine 2,3-dioxygenase expression in colorectal cancer: effect on tumor-infiltrating T cells. Clin Cancer Res 2006;12:1144–51. https://doi.org/10.1158/1078-0432.ccr-05-1966.Search in Google Scholar

49. Ben-Haj-Ayed, A, Moussa, A, Ghedira, R, Gabbouj, S, Miled, S, Bouzid, N, et al.. Prognostic value of indoleamine 2,3-dioxygenase activity and expression in nasopharyngeal carcinoma. Immunol Lett 2016;169:23–32. https://doi.org/10.1016/j.imlet.2015.11.012.Search in Google Scholar PubMed

50. Ino, K, Yamamoto, E, Shibata, K, Kajiyama, H, Yoshida, N, Terauchi, M, et al.. Inverse correlation between tumoral indoleamine 2,3-dioxygenase expression and tumor-infiltrating lymphocytes in endometrial cancer: its association with disease progression and survival. Clin Cancer Res 2008;14:2310–7. https://doi.org/10.1158/1078-0432.ccr-07-4144.Search in Google Scholar PubMed

51. Inaba, T, Ino, K, Kajiyama, H, Yamamoto, E, Shibata, K, Nawa, A, et al.. Role of the immunosuppressive enzyme indoleamine 2,3-dioxygenase in the progression of ovarian carcinoma. Gynecol Oncol 2009;115:185–92. https://doi.org/10.1016/j.ygyno.2009.07.015.Search in Google Scholar PubMed

52. Carvajal-Hausdorf, DE, Mani, N, Velcheti, V, Schalper, KA, Rimm, DL. Objective measurement and clinical significance of IDO1 protein in hormone receptor-positive breast cancer. J Immunother Cancer 2017;5:81. https://doi.org/10.1186/s40425-017-0285-7.Search in Google Scholar PubMed PubMed Central

53. Platten, M, Nollen, EAA, Röhrig, UF, Fallarino, F, Opitz, CA. Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond. Nat Rev Drug Discov 2019;18:379–401. https://doi.org/10.1038/s41573-019-0016-5.Search in Google Scholar PubMed

54. Le Floc’h, N, Otten, W, Merlot, E. Tryptophan metabolism, from nutrition to potential therapeutic applications. Amino Acids 2011;41:1195–205. https://doi.org/10.1007/s00726-010-0752-7.Search in Google Scholar PubMed

55. Grohmann, U, Orabona, C, Fallarino, F, Vacca, C, Calcinaro, F, Falorni, A, et al.. CTLA-4-Ig regulates tryptophan catabolism in vivo. Nat Immunol 2002;3:1097–101. https://doi.org/10.1038/ni846.Search in Google Scholar PubMed

56. Fallarino, F, Grohmann, U, Hwang, KW, Orabona, C, Vacca, C, Bianchi, R, et al.. Modulation of tryptophan catabolism by regulatory T cells. Nat Immunol 2003;4:1206–12. https://doi.org/10.1038/ni1003.Search in Google Scholar PubMed

57. Prendergast, GC, Malachowski, WJ, Mondal, A, Scherle, P, Muller, AJ. Indoleamine 2,3-dioxygenase and its therapeutic inhibition in cancer. Int Rev Cell Mol Biol 2018;336:175–203. https://doi.org/10.1016/bs.ircmb.2017.07.004.Search in Google Scholar PubMed PubMed Central

58. Poulain-Godefroy, O, Eury, E, Leloire, A, Hennart, B, Guillemin, GJ, Allorge, D, et al.. Induction of TDO2 and IDO2 in liver by high-fat feeding in mice: discrepancies with human obesity. Int J Tryptophan Res 2013;6:29–37. https://doi.org/10.4137/IJTR.S11717.Search in Google Scholar PubMed PubMed Central

59. Zhao, Y, Wei, L, Liu, J, Li, F. Chemoresistance was correlated with elevated expression and activity of indoleamine 2,3-dioxygenase in breast cancer. Cancer Chemother Pharmacol 2020;85:77–93. https://doi.org/10.1007/s00280-019-04009-8.Search in Google Scholar PubMed

60. Brooks, AK, Janda, TM, Lawson, MA, Rytych, JL, Smith, RA, Ocampo-Solis, C, et al.. Desipramine decreases expression of human and murine indoleamine-2, 3-dioxygenases. Brain Behav Immun 2017;62:219–29. https://doi.org/10.1016/j.bbi.2017.02.010.Search in Google Scholar PubMed PubMed Central

Received: 2022-11-03
Accepted: 2022-12-29
Published Online: 2023-02-20

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Review Article
  3. Differential expression and functions of miRNAs in bladder cancer
  4. Research Articles
  5. Pan-cancer analysis, providing a reliable basis for IDO2 as a prognostic biomarker and target for immunotherapy
  6. Knockdown of pyruvate kinase M2 suppresses bladder cancer progression
  7. Development and validation of a nomogram for predicting survival in patients with pancreatic ductal adenocarcinoma after radical pancreatoduodenectomy
  8. SET domain containing protein 8 (SET8) promotes tumour progression and indicates poor prognosis in patients with laryngeal squamous cell carcinoma
  9. Hypoxia-inducible factor 1α (HIF-1α)-activated Gli1 induces invasion and EMT by H3K4 methylation in glioma cells
  10. The inhibitory effects of lobaplatin, or in combination with gemcitabine on triple-negative breast cancer cells in vitro and in vivo
  11. Case Report
  12. Epstein–Barr virus positive gastric adenocarcinoma with systemic EBV reactivation in a patient with persistently active systemic lupus erythematosus
https://doi.org/10.1515/oncologie-2022-1026
Keywords for this article
IDO2; immunotherapy; pan-cancer; prognosis; TCGA; tumor microenvironment
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Review Article
  3. Differential expression and functions of miRNAs in bladder cancer
  4. Research Articles
  5. Pan-cancer analysis, providing a reliable basis for IDO2 as a prognostic biomarker and target for immunotherapy
  6. Knockdown of pyruvate kinase M2 suppresses bladder cancer progression
  7. Development and validation of a nomogram for predicting survival in patients with pancreatic ductal adenocarcinoma after radical pancreatoduodenectomy
  8. SET domain containing protein 8 (SET8) promotes tumour progression and indicates poor prognosis in patients with laryngeal squamous cell carcinoma
  9. Hypoxia-inducible factor 1α (HIF-1α)-activated Gli1 induces invasion and EMT by H3K4 methylation in glioma cells
  10. The inhibitory effects of lobaplatin, or in combination with gemcitabine on triple-negative breast cancer cells in vitro and in vivo
  11. Case Report
  12. Epstein–Barr virus positive gastric adenocarcinoma with systemic EBV reactivation in a patient with persistently active systemic lupus erythematosus
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