Skip to main content
NCBI home page
Medicine logoLink to Medicine
. 2023 Aug 25;102(34):e34996. doi: 10.1097/MD.0000000000034996

Pan-cancer analyses reveal GTSE1 as a biomarker for the immunosuppressive tumor microenvironment

Ke Tan a, Zixuan Fang b, Lingzhen Kong c, Chen Cheng c, Sydney Hwang c, Min Xu a,d,*
PMCID: PMC10470696  PMID: 37653815

Abstract

G2 and S phase-expressed-1 (GTSE1) has been reported to be associated with poor prognosis in many cancer types. However, the knowledge of GTSE1 across 33 cancer types remains scarce, and the mechanisms by which GTSE1 promotes cancer development remain incompletely understood. R language and TIMER2.0 were used to analyze the clinical relevance of GTSE1 across > 10,000 subjects representing 33 cancer types based on the cancer genome atlas databases. The expression of GTSE1 was upregulated in almost all cancer types and hyperactivity of GTSE1 is likely to induce DNA repair response and positively correlates with the tumor mutational burden and microsatellite instability which are both promising predictive biomarkers for immunotherapy. GTSE1 was upregulated in TP53 mutation patients. Additionally, GTSE1 also positively correlates with tumor purity and tumor infiltration of immune-suppressive myeloid-derived suppressor cells. Consistently, high expression of GTSE1 is associated with poor patient survival in many cancer types. Conclusion: Our study provides new insights into the diagnostic and prognostic role of GTSE1 in cancers and suggests therapeutic approaches for GTSE1-overexpressing cancers by targeting DNA repair response, and the tumor immune microenvironment.

Keywords: DNA repair response, GTSE1, TP53, tumor immune microenvironment

1. Introduction

The tumor suppressor TP53 is an essential regulator of multiple cellular processes that contributes to suppressing tumorigenesis.[1] G2 and S phase-expressed-1 (GTSE1) can negatively regulate TP53 transactivation function, protein levels, and TP53-dependent apoptosis.[2] As a transcriptional suppressor of TP53, GTSE1 interacts with TP53 protein to transport it to the cytoplasm for degradation.[3] The TP53 gene is frequently mutated in about half of the human cancers and these defects usually confer poor prognosis and responses to therapy. As a cell cycle regulator, the hyperactivity of GTSE1 delays the transition from G2 to the M phase, causing chromosomal instability.[4]

GTSE1 has been reported to play an important role in many cancers. In myeloma cells, GTSE1 is upregulated after treatment with cisplatin, which contributes to drug-resistant.[5] In prostate cancer, GTSE1 was highly expressed and is correlated with poor prognosis. GTSE1 also activates the SP1/FOXM1 pathway, contributing to prostate cancer cell proliferation.[6] In breast cancer cells, GTSE1 promotes cell growth via the AKT pathway and enhances tumor metastasis by promoting the Epithelial-Mesenchymal transition pathway.[7] In bladder cancer, GTSE1 promotes cancer cell proliferation, migration and invasion, leading to a poor prognosis.[8] In hepatocellular carcinoma, GTSE1 activates the epithelial-mesenchymal transition pathway and high expression of GTSE1 is associated with poor prognosis.[9] Despite intensive studies, the clinical significance of GTSE1 in tumor expression, cancer survival rate, tumor mutation rate and tumor microenvironment across pan-cancer remains unclear.

To address this question, we analyzed cancer databases to investigate the impact of GTSE1 on tumor mutational burden (TMB), microsatellite instability (MSI), tumor immune microenvironment and patient survival. By analyzing the data for GTSE1 in the cancer genome atlas (TCGA) cancer database, we found that its mRNA expression was higher in tumor tissues compared to adjacent normal tissues in almost all cancer types and a high mRNA level of GTSE1 was associated with poor prognosis. As GTSE1 suppresses TP53, which is known as the guardian of the genome, we next investigated the mRNA level of GTSE1 in TP53-mutated patients and its correlation with TMB and MSI. We found GTSE1 was highly expressed in TP53 mutated patients compared to wildtype patients and was positively correlated with TMB and MSI in many cancer types. To explore the potential role of GTSE1 upregulation in the tumor immune microenvironment, we analyzed the relationship between GTSE1 and tumor purity, tumor stromal score and immune score. Upregulation of GTSE1 was positively correlated with the tumor purity and infiltration of immunosuppressive myeloid-derived suppressor cells (MDSCs) in almost all cancer types. Upregulation of GTSE1 was negatively correlated with tumor stromal score and immune score in some cancer types. Our analyses revealed clinical evidence for the role of GTSE1 in modulating DNA repair response, tumor immune microenvironment, and patient survival.

2. Materials and methods

2.1. mRNA expression and patient survival

mRNA expression data of 33 cancer types in tumor and normal samples from the TCGA pan-cancer atlas downloaded from UCSC Xena (https://xenabrowser.net.) were used for analysis. Survival data were downloaded from TCGA Pan-Cancer (PANCAN) from UCSC Xena. Differential mRNA expression of GTSE1 was analyzed in normal and tumor tissues by Wilcox test and drawn by R package “ggpubr.” The relationship between the expression level of GTSE1 and tumor stage in the pan-cancer analysis was calculated by R package “limma” and plotted by R package “ggpubr.” Survival analysis was calculated by R package“survival” and “survminer”. Tumor patients were divided into a high and low group according to medium median GTSE1 mRNA level. Kaplan–Meier analysis was performed for survival data. When P < .01, the result will be generated for figure production.

2.2. Correlation between gene expression and tumor mutational burden and microsatellite instability

mRNA data of GTSE1 in TCGA was downloaded from the UCSC Xena website. Somatic mutation data were downloaded from VarScan2 Variant Aggregation and Masking from the UCSC Xena website. TMB = (total mutation/total covered bases) × 106. MSI score for each sample was obtained from TCGA. Spearman rank correlation coefficient was used to analyze the relationship of mRNA level GTSE1 with TMB and MSI for each sample in the pan-cancer atlas. The radar map was drawn by R package “fmsb.”

2.3. Correlation between mRNA level of GTSE1 and stromal score and immune score

RNA sequence was downloaded from UCSC Xena. Immune score and stromal score were estimated by R package “estimate.”[10] Spearman rank correlation coefficient between the mRNA level of GTSE1 and stromal score or immune score was calculated. Results were plotted by R package “ggplot2,” “ggpubr” and “ggextra..” The figure was produced when P < .001.

2.4. Correlation between mRNA level of GTSE1 and tumor infiltration of MDSCs and tumor purity

Spearman rank correlation coefficient between the mRNA level of GTSE1 and tumor infiltration of MDSCs was performed by TIMER2.0 (http://timer.cistrome.org)[11–13] using the tumor immune dysfunction and exclusion algorithm.[14] Spearman rank correlation coefficient between the mRNA level of GTSE1 and tumor purity was calculated for each sample in the pan-cancer atlas at TIMER2.0.

2.5. Gene expression analysis of scRNA-seq data

GTSE1 expression in cutaneous squamous cell carcinoma (cSCC) was analyzed by the CHARTS database (https://charts.morgridge.org)[15] via the scRNA-seq data. Gene set enrichment analysis was performed using the CancerSEA method.[16] The scRNA-seq data for cSCC were obtained from GSE144236.[17]

3. Results

3.1. Upregulation of GTSE1 mRNA expression in cancers

We examined first whether the expression of GTSE1 was upregulated in cancers. By comparing the mRNA levels of GTSE1 in tumor tissues and adjacent normal tissues across pan-cancer, we found that GTSE1 was upregulated in bladder cancer (BLCA), breast cancer (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), cholangiocarcinoma, colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma, kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma, rectum adenocarcinoma, Sarcoma (SARC), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA), and uterine corpus endometrial carcinoma (UCEC) (Fig. 1A). In addition, accompanied by an increase in clinical stage, the mRNA level of GTSE1 was upregulated in adrenocortical carcinoma (ACC), KIRC, KIRP and LUAD (Fig. 1B).

Figure 1.

Figure 1.

Open in a new tab

Upregulation of GTSE1 mRNA expression across pan-cancer. (A) mRNA level of GTSE1 in 33 cancer types. Blue represents normal tissues. Red represents cancer tissues. * represents P < .05. ** represents P < .01, *** represents P < .001. (B) mRNA level of GTSE1 in different clinical stages. GTSE1 = G2 and S phase-expressed-1.

3.2. Prognostic value of GTSE1 in cancer patients

GTSE1 is highly expressed in tumor tissues compared to normal tissues. The ability of GTSE1 to suppress tumor-suppressed gene TP53 suggests that their expression levels may have prognostic value in cancer patients. Consistent with this idea, our results indicate that upregulation of GTSE1 is associated with a poorer survival rate in ACC, KIRC, KIRP, brain Lower Grade Glioma, LUAD, mesothelioma, and pancreatic adenocarcinoma based on Kaplan–Meier survival curves (Fig. 2A).

Figure 2.

Figure 2.

Open in a new tab

Upregulation of GTSE1 mRNA expression in cancer predicts poor prognosis. (A) Kaplan–Meier survival curve analysis of overall survival (OS) in the pan-cancer atlas for patients with the top 50% and bottom 50% according to mRNA expression levels of GTSE1. When P < .01, the figure is produced. GTSE1 = G2 and S phase-expressed-1.

3.3. Upregulation of GTSE1 mRNA expression in TP53 mutated patients

To further explore the relationship between GTSE1 and TP53, we analyzed the mRNA of GTSE1 in TP53 wildtype patients and mutated patients across a pan-cancer from the TIMER 2.0 database. Consistent with the hypothesis, GTSE1 was upregulated in TP53 mutated patients compared to TP53 wildtype patients, in ACC, BLCA, BRCA, GBM, ESCA, KICH, KIRC, LIHC, LUAD, and ovarian serous cystadenocarcinoma (Fig. 3A).

Figure 3.

Figure 3.

Open in a new tab

upregulation of GTSE1 in TP53 mutated patients compared to TP53 wildtype patients. (A) mRNA levels of GTSE1 in TP53 mutated patients and TP53 wildtype patients in ACC, BLCA, BRCA, GBM, ESCA, KICH, KIRC, LIHC, LUAD, and OV. ACC = adrenocortical carcinoma, BLCA = bladder urothelial carcinoma, BRCA = breast invasive carcinoma, ESCA = esophageal carcinoma, GBM = glioblastoma multiforme, GTSE1 = G2 and S phase-expressed-1, KICH = kidney chromophobe, KIRC = kidney renal clear cell carcinoma, LIHC = liver hepatocellular carcinoma, LUAD = lung adenocarcinoma.

3.4. Correlation of the expression of GTSE1 with tumor mutational burden and microsatellite instability

We observed GTSE1 was upregulated in TP53-mutated patients. TP53 is a well-known candidate gene for predicting chemotherapy response, and mutant TP53 is associated with elevated TMB.[18] TMB is an emerging biomarker for various cancers, defined as the mutation frequency per million base pairs of genomic sequence,[19,20] and is now used alongside MSI as a predictor for response to immunotherapy.[21,22] To better understand the role of GTSE1 in tumorigenesis, we analyzed the correlation of GTSE1 mRNA expression with TMB and MSI. As shown in Figure 4A, GTSE1 expression was positively correlated with TMB in multiple cancer types, including ACC, BLCA, BRCA, COAD, head and neck squamous cell carcinoma, KICH, KIRC, brain lower grade glioma, LUAD, LUSC, Mesothelioma, ovarian serous cystadenocarcinoma, pancreatic adenocarcinoma, prostate adenocarcinoma, Rectum adenocarcinoma, SARC, skin cutaneous melanoma, STAD, UCEC and uterine carcinosarcoma (P < .05). Interestingly, the expression of GTSE1 was negatively correlated with TMB in Thymoma, which has the lowest TMB compared to other cancer types. Furthermore, we found that GTSE1 was positively correlated with MSI in COAD, LUSC, SARC, STAD, UCEC, and uterine carcinosarcoma, and negatively correlated with MSI in lymphoid neoplasm diffuse large B-cell lymphoma (Fig. 4B).

Figure 4.

Figure 4.

Open in a new tab

Expression of GTSE1 positively correlates with tumor mutational burden and microsatellite instability in the majority of cancer types. (A) Spearman rank correlation coefficient between the GTSE1 mRNA expression and TMB for each cancer type. *, P < .05; **, P < .01; ***, P < .001. (B) Spearman rank correlation coefficient between the GTSE1 mRNA expression and MSI for each cancer type. *, P < .05; **, P < .01; ***, P < .001. GTSE1 = G2 and S phase-expressed-1, MSI = microsatellite instability, TMB = tumor mutational burden.

3.5. Correlation between the mRNA expression of GTSE1 and the stromal score and immune score

TMB and MSI are predictors of response to immunotherapy. We are conducting a study to determine whether the mRNA level of GTSE1 affects the tumor microenvironment. The “estimate” method was used to calculate the stromal score and immune score across pan-cancer. Interestingly, the expression of GTSE1 was negatively correlated with the stromal score in BLCA, BRCA, CESC, COAD, GBM, LIHC, LUAD, LUSC, SARC, STAD, and testicular germ cell tumors (Fig. 5A). Consistent with the TMB correlation result, THCA was the only cancer type that the expression of GTSE1 that was negatively correlated with the stromal score. We next conducted an analysis of the correlation between the expression of GTSE1 and immune score. The mRNA level of GTSE1 was negatively correlated with the immune score in BLCA, CESC, ESCA, GBM, LUSC, STAD, and positively in THCA (Fig. 5B). Consequently, GTSE1 was found to be negatively correlated with the stromal score and immune score in CESC, GBM, LUSC, and STAD, which suggested that GTSE1 may have suppressed the immune response in these cancer types.

Figure 5.

Figure 5.

Open in a new tab

Expression of GTSE1 negatively correlates with stromal score and immune score in the majority of cancer types. (A) Spearman rank correlation coefficient between the GTSE1 mRNA expression and stromal score. (B) Spearman rank correlation coefficient between the GTSE1 mRNA expression and immune score. GTSE1 = G2 and S phase-expressed-1.

3.6. Correlation between the expression of GTSE1 and the infiltration of MDSCs

Based on the results presented above, we hypothesized that GTSE1 may suppress the immune response in cancer. To test this hypothesis further in clinical samples, we analyzed the potential correlation between the expression of GTSE1 and tumor infiltration of immune cells using TIMER2 (http://timer.cistrome.org/). Interestingly, we found a strong positive correlation between GTSE1 expression and the abundance of MDSCs, which play a prominent role in immune suppression in cancers (Fig. 6). These findings, together with the TMB and MSI results, suggest that targeting the suppressive tumor immune microenvironment may be a potential immunotherapy strategy for cancer patients with elevated expression of GTSE1.

Figure 6.

Figure 6.

Open in a new tab

Expression of GTSE1 positively correlates with infiltration of MDSCs across pan-cancer. (A–C) Spearman rank correlation coefficient between GTSE1 and tumor purity or the infiltration of MDSCs in each cancer type from the TIMER2.0 database. GTSE1 = G2 and S phase-expressed-1, MDSCs = myeloid-derived suppressor cells.

3.7. GTSE1 highly expressed in cells with DNA repair pathway enrichment

To further study the consequence of GTSE1 high expression in cancer cells and the mechanism by which GTSE1 remodels the immune microenvironment, we assessed the function of GTSE1 based on scRNA-seq data from the CHARTS database. The scRNA-seq data was obtained from cSCC samples to determine whether upregulation of GTSE1 occurred in the same groups of cells enriched in the same pathway. As shown in Figure 7A–F, GTSE1 was highly expressed in cells with DNA repair pathway enrichment in the 6 cSCC samples. Our findings suggest that GTSE1 suppressed TP53, an important genome integrity protector, which may cause genomic instability and activate the DNA repair response. Genomic instability can lead to the release of cytosolic DNA, which in turn can remodel the immune microenvironment.

Figure 7.

Figure 7.

Open in a new tab

Expression of GTSE1 enriched in DNA repair response pathway in cSCC. scRNA-seq results were visualized by CHARTS. cSCC tumor sample data were obtained from Ji et al[17] (A) from the P2 sample. (B) From the P4 sample. (C) From the P6 sample. (D) From the P7 sample. (E) From the P8 sample. (F) From the P9 sample. GTSE1 = G2 and S phase-expressed-1. cSCC = cutaneous squamous cell carcinoma.

4. Discussion

Our study demonstrated that GTSE1 was overexpressed in the majority of tumors compared to adjacent normal tissues across pan-cancer (Fig. 1A). Furthermore, we found that GTSE1 was overexpressed in mutated TP53 compared to wildtype tumors (Fig. 3A). Notably, we observed a positive correlation between the upregulation of GTSE1 and TMB, and the tumor infiltration of immunosuppressive MDSCs across pan-cancer (Figs. 4A, B and 6). Moreover, our single-cell RNA sequencing results showed that GTSE1 was enriched in cells with a DNA repair response. Based on these findings, we propose that GTSE1 hyperactivity promotes cancer progression by inducing both genomic instability and an immune-suppressive tumor microenvironment.

There are 2 possibilities for the important role of GTSE1 in modulating the tumor microenvironment. One possibility is that GTSE1 overexpression causes chromosome instability in cancer, which disrupts the tumor environment. Chromosome instability often occurred in cancer cells due to hyperstable kinetochore microtubules. GTSE1 overexpression inhibits the microtubule depolymerase MCAK, which partly promotes microtubule hyperstabilization and chromosome instability.[23,24] Chromosome instability leads to the release of DNA fragments into the cytoplasm, which in turn activates the cGAS-STING signaling pathway to modulate the immune microenvironment.[25] The other possibility is that GTSE1 overexpression inhibits the function of tumor suppressor gene TP53, which plays an important role in immune surveillance. Martin et al[26] demonstrated unexpected functions of tumor suppressor genes in cancer immune surveillance. Through CRISPR/Cas9 screens in syngeneic mouse tumor models with or without an adaptive immune system, the authors found that knocking out many tumor suppressors, including Trp53, resulted in immune evasion. In addition to Trp53, the other tumor suppressor gene GNA13, when lost, results in an increase in the number of MDSCs in the tumor microenvironment, as well as an increase in their suppressive activity, creating an immunosuppressive environment that promotes tumor growth and metastasis.[26] Therefore, both chromosome instability and tumor suppressor inactivation can promote carcinogenesis by modulating the tumor immune microenvironment.

TMB and MSI have recently emerged as predictive markers for immunotherapy.[27] TMB is a crucial biomarker that predicts the likelihood of response to immune checkpoint inhibitors targeting PD-1 and PD-L1.[20] For instance, Pembrolizumab, which targets PD-1, has been approved by the FDA for treating adult and pediatric patients with microsatellite instability-high solid tumors.[28] MDSCs and their secreted factors restrict antitumor immune responses and directly promote cancer cell proliferation, invasion and metastasis.[29] Targeting the infiltration and functions of these immunosuppressive cells can be beneficial for treating cancers. Clinically available drugs that inhibit the STAT pathway, which is vital for MDSC accumulation and suppressive functions, have been reported to target MDSCs.[30] Therefore, strategies targeting the DNA repair response, TMB, MSI, and MDSCs could be effective in treating cancers with high expression of GTSE1.

Acknowledgments

This study was supported by the National Natural Science Foundation of China (82072754 and 81672402), the Project of Jiangsu Provincial Health Commission (M2020011), and Jiangsu Key R&D Program Social Development Project, China (BE2018689 and SH2018033).

Author contributions

Conceptualization: Ke Tan, Min Xu.

Data curation: Ke Tan, Zixuan Fang.

Formal analysis: Ke Tan, Zixuan Fang, Lingzhen Kong.

Funding acquisition: Min Xu.

Investigation: Ke Tan, Zixuan Fang, Lingzhen Kong, Chen Cheng, Sydney Hwang, Min Xu.

Methodology: Ke Tan, Zixuan Fang, Lingzhen Kong, Chen Cheng, Sydney Hwang, Min Xu.

Project administration: Ke Tan, Min Xu.

Resources: Ke Tan, Zixuan Fang, Lingzhen Kong, Chen Cheng.

Software: Ke Tan, Zixuan Fang, Lingzhen Kong, Chen Cheng, Sydney Hwang.

Supervision: Min Xu.

Validation: Ke Tan, Zixuan Fang.

Visualization: Ke Tan, Zixuan Fang.

Writing – original draft: Ke Tan, Zixuan Fang, Lingzhen Kong.

Writing—review & editing: Ke Tan, Lingzhen Kong, Chen Cheng, Sydney Hwang, Min Xu.

Abbreviations:

ACC
adrenocortical carcinoma
BLCA
bladder urothelial carcinoma
BRCA
breast invasive carcinoma
CESC
cervical squamous cell carcinoma and endocervical adenocarcinoma
COAD
colon adenocarcinoma
cSCC
cutaneous squamous cell carcinoma
ESCA
esophageal carcinoma
GBM
glioblastoma multiforme
GTSE1
G2 and S phase-expressed-1
KICH
kidney chromophobe
KIRC
kidney renal clear cell carcinoma
KIRP
kidney renal papillary cell carcinoma
LIHC
liver hepatocellular carcinoma
LUAD
lung adenocarcinoma
LUSC
lung squamous cell carcinoma
MDSCs
myeloid-derived suppressor cells
MSI
microsatellite instability
OV
ovarian serous cystadenocarcinoma
SARC
Sarcoma
STAD
stomach adenocarcinoma
TCGA
the cancer genome atlas
THCA
thyroid carcinoma
TMB
tumor mutational burden
UCEC
uterine corpus endometrial carcinoma

KT and ZF contributed equally to this work.

All data were obtained from public database (TCGA, CHARTS). Ethical approval was not necessary.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are publicly available.

How to cite this article: Tan K, Fang Z, Kong L, Cheng C, Hwang S, Xu M. Pan-cancer analyses reveal GTSE1 as a biomarker for the immunosuppressive tumor microenvironment. Medicine 2023;102:34(e34996).

Contributor Information

Ke Tan, Email: 452239075@qq.com.

Zixuan Fang, Email: 1274215032@qq.com.

Lingzhen Kong, Email: lingzhen@wustl.edu.

Chen Cheng, Email: cheche@wustl.edu.

Sydney Hwang, Email: h.sydney@wustl.edu.

References

  • [1].Thomas AF, Kelly GL, Strasser A. Of the many cellular responses activated by TP53, which ones are critical for tumour suppression? Cell Death Differ. 2022;29:961–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [2].Monte M, Benetti R, Buscemi G, et al. The cell cycle-regulated protein human GTSE-1 controls DNA damage-induced apoptosis by affecting p53 function. J Biol Chem. 2003;278:30356–64. [DOI] [PubMed] [Google Scholar]
  • [3].Monte M, Benetti R, Collavin L, et al. hGTSE-1 expression stimulates cytoplasmic localization of p53. J Biol Chem. 2004;279:11744–52. [DOI] [PubMed] [Google Scholar]
  • [4].Utrera R, Collavin L, Lazarević D, et al. A novel p53-inducible gene coding for a microtubule-localized protein with G2-phase-specific expression. EMBO J. 1998;17:5015–25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Subhash VV, Tan SH, Tan WL, et al. GTSE1 expression represses apoptotic signaling and confers cisplatin resistance in gastric cancer cells. BMC Cancer. 2015;15:1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [6].Lai W, Zhu W, Li X, et al. GTSE1 promotes prostate cancer cell proliferation via the SP1/FOXM1 signaling pathway. Lab Investig. 2021;101:554–63. [DOI] [PubMed] [Google Scholar]
  • [7].Lin F, Xie Y-J, Zhang X-K, et al. GTSE1 is involved in breast cancer progression in p53 mutation-dependent manner. Jour Exp Clin Cancer Res. 2019;38:1–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Liu A, Zeng S, Lu X, et al. Overexpression of G2 and S phase-expressed-1 contributes to cell proliferation, migration, and invasion via regulating p53/FoxM1/CCNB1 pathway and predicts poor prognosis in bladder cancer. Int J Biol Macromol. 2019;123:322–34. [DOI] [PubMed] [Google Scholar]
  • [9].Wu X, Wang H, Lian Y, et al. GTSE1 promotes cell migration and invasion by regulating EMT in hepatocellular carcinoma and is associated with poor prognosis. Sci Rep. 2017;7:1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [10].Yoshihara K, Shahmoradgoli M, Martínez E, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013;4:2612. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [11].Li T, Fu J, Zeng Z, et al. TIMER2. 0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020;48:W509–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].Li T, Fan J, Wang B, et al. TIMER: a web server for comprehensive analysis of tumor-infiltrating immune cells. Cancer Res. 2017;77:e108–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [13].Li B, Severson E, Pignon J-C, et al. Comprehensive analyses of tumor immunity: implications for cancer immunotherapy. Genome Biol. 2016;17:1–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [14].Jiang P, Gu S, Pan D, et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med. 2018;24:1550–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [15].Bernstein MN, Ni Z, Collins M, et al. CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets. BMC Bioinf. 2021;22:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [16].Yuan H, Yan M, Zhang G, et al. CancerSEA: a cancer single-cell state atlas. Nucleic Acids Res. 2019;47:D900–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [17].Ji AL, Rubin AJ, Thrane K, et al. Multimodal analysis of composition and spatial architecture in human squamous cell carcinoma. Cell. 2020;182:497–514.e22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].Wang L, Yan K, He X, et al. LRP1B or TP53 mutations are associated with higher tumor mutational burden and worse survival in hepatocellular carcinoma. J Cancer. 2021;12:217–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [19].Fumet J-D, Truntzer C, Yarchoan M, et al. Tumour mutational burden as a biomarker for immunotherapy: current data and emerging concepts. Eur J Cancer. 2020;131:40–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Yarchoan M, Hopkins A, Jaffee EM. Tumor mutational burden and response rate to PD-1 inhibition. N Engl J Med. 2017;377:2500–1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Rizzo A, Ricci AD, Brandi G. PD-L1, TMB, MSI, and other predictors of response to immune checkpoint inhibitors in biliary tract cancer. Cancers (Basel). 2021;13:558. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [22].Ganesh K, Stadler ZK, Cercek A, et al. Immunotherapy in colorectal cancer: rationale, challenges and potential. Nature Rev Gastroenterol Hepatol. 2019;16:361–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [23].Bakhoum SF, Genovese G, Compton DA. Deviant kinetochore microtubule dynamics underlie chromosomal instability. Curr Biol. 2009;19:1937–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [24].Bendre S, Rondelet A, Hall C, et al. GTSE1 tunes microtubule stability for chromosome alignment and segregation by inhibiting the microtubule depolymerase MCAK. J Cell Biol. 2016;215:631–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Kwon J, Bakhoum SF. The cytosolic DNA-sensing cGAS–STING pathway in cancer. Cancer Discov. 2020;10:26–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Martin TD, Patel RS, Cook DR, et al. The adaptive immune system is a major driver of selection for tumor suppressor gene inactivation. Science. 2021;373:1327–35. [DOI] [PubMed] [Google Scholar]
  • [27].Palmeri M, Mehnert J, Silk A, et al. Real-world application of tumor mutational burden-high (TMB-high) and microsatellite instability (MSI) confirms their utility as immunotherapy biomarkers. ESMO Open. 2022;7:100336. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Marcus L, Lemery SJ, Keegan P, et al. FDA approval summary: pembrolizumab for the treatment of microsatellite instability-high solid Tumors FDA approval summary: pembrolizumab for MSI-H Solid Tumors. Clin Cancer Res. 2019;25:3753–8. [DOI] [PubMed] [Google Scholar]
  • [29].Umansky V, Blattner C, Gebhardt C, et al. The role of myeloid-derived suppressor cells (MDSC) in cancer progression. Vaccines (Basel). 2016;4:36. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [30].de Haas N, de Koning C, Spilgies L, et al. Improving cancer immunotherapy by targeting the STATe of MDSCs. Oncoimmunology. 2016;5:e1196312. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Medicine are provided here courtesy of Wolters Kluwer Health

RESOURCES