https://orcid.org/0009-0006-4941-3879
Figures
Abstract
Background
Expression levels of transmembrane protein 41A (TMEM41A) are related to the progression of malignant tumors. However, the association between TMEM41A expression and endometrial carcinoma (EC) remains unclear. This study aims to identify the roles of TMEM41A expression in the prognosis of patients with EC and its correlation with EC progression.
Methods
The TMEM41A expression and its correlation with the survival of patients with EC were assessed. Cox regression analysis was used to identify the prognostic factors, while nomograms were used to examine the association between the prognostic factors and the survival of patients with EC. Finally, the link between TMEM41A level and immune microenvironment and RNA modifications was investigated in EC.
Results
TMEM41A was overexpressed in EC. TMEM41A overexpression could diagnose the EC and evaluate the poor prognosis of patients. Overexpression of TMEM41A was associated with clinical stage, age, weight, histological subtype, tumor grade, and survival status of patients with EC. Clinical stage, age, tumor grade, radiotherapy, and TMEM41A overexpression were factors of poor prognosis in patients with EC. The nomograms revealed the correlation between the TMEM41A level and survival time of patients with EC at 1, 3, and 5 years. Furthermore, TMEM41A overexpression was significantly correlated with the level of the stromal score, immune score, estimate score, NK CD56 bright cells, iDC, NK cells, eosinophils, pDC, T cells, TReg, cytotoxic cells, mast cells, Th17 cells, neutrophils, aDC, NK CD56 dim cells, TFH, Th2 cells, CD8 T cells, macrophages, immune cell markers, and RNA modifications.
Citation: Shi K, Liu X-L, Guo Q, Zhang Y-Q, Fan S-T, Dai L, et al. (2023) TMEM41A overexpression correlates with poor prognosis and immune alterations in patients with endometrial carcinoma. PLoS ONE 18(7): e0285817. https://doi.org/10.1371/journal.pone.0285817
Editor: Andrea Giannini, Sapienza University of Rome: Universita degli Studi di Roma La Sapienza, ITALY
Received: March 22, 2023; Accepted: April 28, 2023; Published: July 21, 2023
Copyright: © 2023 Shi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The research results were available from the databases of TCGA (https://cistrome.shinyapps.io/timer) and TIMER (https://cistrome.shinyapps.io/timer).
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Endometrial carcinoma (EC) is a common type of malignant epithelial tumor in women, with 10%-15% of patients with EC being diagnosed at an advanced stage, leading to unfavorable prognosis [1, 2]. While surgery and adjuvant treatment can improve the survival time of early patients with EC, there is no effective treatment for those with advanced cancer [1]. Over the years, several genes with crucial biological functions have emerged as research hotspots [3–5]. For instance, the combination of PARP inhibitor and PD-1/PD-L1 checkpoint inhibitor could improve the survival time of patients with cancer [3]. Therefore, identifying novel therapeutic targets and early diagnostic markers is critical in cancer.
Recent studies have shown the association between transmembrane protein 41A (TMEM41A) and the occurrences and developments of gastrointestinal tumors [6, 7], with significantly higher expression levels of SREBF pathway regulator in golgi 1 (SPRING1) in colorectal cancer than in adjacent normal tissues. In vitro and in vivo studies found that SPRING1 could enhance the growth of colorectal cancer cells, which was related to the increased expression of TMEM41A [6]. TMEM41A was strongly expressed in gastric cancer and linked to lymph node metastasis, distant metastasis, late stage, and poor prognosis. Inhibition of TMEM41A expression could reduce gastric cancer cell migration and metastasis by inhibiting the epithelial-mesenchymal transformation (EMT) process and autophagy [7]. Collectively, these preliminary findings indicate that TMEM41A is crucial in promoting cell growth and migration as an oncogene.
The Cancer Genome Atlas (TCGA) database provides transcriptome data of normal and cancer tissues of patients with cancer [8–10], which has been extensively analyzed in various studies [11–13]. For example, the down-regulation of B cell translocation gene 1 (BTG1) expression was related to poor prognosis, degree of invasion, and FIGO stage in patients with EC. Overexpression of BTG1 inhibits proliferation, migration, and invasion as well as promotes apoptosis of EC cells, which was related to the EMT process [13]. The correlation between TMEM41A expression and EC remains unclear. Therefore, this study aims to comprehensively analyze the roles and possible mechanisms of TMEM41A in EC and to identify potential candidate molecules for cancer treatment.
2. Materials and methods
2.1. Data acquisition and identification of TMEM41A expression
The transcriptome data of patients with cancer were obtained from the TCGA (https://portal.gdc.cancer.gov/repository) database in the FPKM file format. Among them, 35 cases were normal tissue, and 554 were cancer tissue samples. Additionally, 23 normal tissue and 23 cancer tissue samples were paired. The expression levels of TMEM41A in EC were analyzed by expression analysis.
2.2. Diagnostic evaluation and prognostic analysis of TMEM41A
Receiver operating characteristic (ROC) analysis on TCGA FPKM data to determine the area under the curve (AUC) and identify its diagnostic value in normal and EC tissues. The data of TMEM41A expression was combined with the prognosis data, and the missing data were excluded. After classifying the samples according to the median expression of TMEM41A, the association between changes in TMEM41A expression and the poor prognosis of patients with EC was identified using survival analysis.
2.3. Clinical characteristics analysis
The clinical characteristics of patients with EC were obtained from the TCGA database. These data included the clinical stage, age, weight, histological subtype, tumor grade, and survival status, which were used to group the samples, and TMEM41A expression in these groups was analyzed. Moreover, the median expression of TMEM41A was used to divide the samples into high- and low- expression groups to explore the correlation between TMEM41A levels and clinical characteristics of patients with EC.
2.4. Survival analysis in subgroups of patients with cancer
The clinical stage (I, II, III, and IV), weight, height, BMI, and tumor grade of patients with EC were analyzed. The patients were divided into high- and low-expression groups to explore the link between TMEM41A levels and overall survival (OS), disease-specific survival (DSS), and disease progression in patients with EC.
2.5. Establishment of TMEM41A-related nomograms based on the Cox method
The clinical data of patients with EC patients and TMEM41A expression in cancer tissues from the TCGA database were matched. The risk indicators of poor prognosis were filtered using the univariate Cox regression analysis with P < 0.05 as the screening criteria. Subsequently, multivariate Cox regression analysis was performed, and its results were used to construct the TMEM41A-related nomograms.
2.6. Analysis of immune microenvironment
Single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithms were used to evaluate the levels of immune microenvironment components in EC tissues. Correlation analysis was used to investigate the association between TMEM41A levels and stromal score, dendritic cell (DC), Tcm, immune score, Tgd, B cells, estimate score, Th1 cells, T helper cells, Tem, CD8 T cells, NK CD56dim cells, TFH, Th2 cells, macrophages, cytotoxic cells, Th17 cells, neutrophils, aDC, T cells, TReg, mast cells, eosinophils, pDC, NK cells, iDC, and NK CD56bright cells.
2.7. Correlation between TMEM41A expression and immune cell markers
The expression data of immune cell markers and TMEM41A in 554 EC tissues were obtained, and their correlation was investigated using the Spearman correlation analysis.
2.8. TIMER database
The TIMER (https://cistrome.shinyapps.io/timer) database was a cancer immune-related database. The relationship between TMEM41A expression and cancer immune cells was analyzed in the gene module of the TIMER database, and the link between TMEM41A expression and cancer immune cell copy number was analyzed in the somatic copy number alteration (SCNA) module of the TIMER database.
2.9. Association between the expression levels of TMEM41A and RNA modification
The TMEM41A was input into the RM2Target online database to obtain the TMEM41A-related RNA modification genes, which were restricted according to the artificial filtering standard of species. The expression data of RNA modification genes and TMEM41A in 554 EC tissues were obtained, and their association was investigated using Spearman correlation analysis.
2.10. Statistical analysis
Wilcoxon rank sum test and chi-square test were used to detect the expression levels of TMEM41A in EC. The ROC and survival analyses examined the link between TMEM41A expression and EC diagnosis and patient survival time. Spearman correlation analysis assessed the correlation between TMEM41A expression and immune microenvironment and RNA modification genes. A P-value < 0.05 was considered statistically significant.
3. Results
3.1. Increased expression of TMEM41A is valuable in the diagnosis and prediction of poor prognosis in patients with EC
The expression analysis based on the TCGA data revealed that TMEM41A was overexpressed both in non-paired (Fig 1A) and paired EC tissues (Fig 1B). Furthermore, ROC analysis demonstrated that the area under the curve of TMEM41A was 0.667, indicating that TMEM41A had a diagnostic value for EC (Fig 1C). Finally, survival analysis showed that enhanced TMEM41A expression was associated with shorter OS, DSS, and progression-free interval (PFI) among patients with EC (Fig 1D–1F).
(A) TMEM41A expression in unpaired tissues. (B) TMEM41A expression in paired tissues. (C) The area under the curve of TMEM41A in EC. (D-F) TMEM41A overexpression correlates to the poor prognosis in EC. EC, endometrial cancer.
3.2. TMEM41A level correlates with clinicopathological features of patients with EC
Our results highlighted a significant correlation between TMEM41A expression and various clinicopathological features in patients with EC (Fig 2). Specifically, TMEM41A was strongly expressed in cancer tissues from patients with clinical stage II, III, and IV EC compared with those of clinical stage I (Fig 2A–2C). Furthermore, TMEM41A was strongly expressed in cancer tissues of patients above 60 (Fig 2D) and those with a weight greater than 80 kg (Fig 2E). Moreover, TMEM41A was strongly expressed in mixed and serous subtype patients, compared with endometrioid subtype. In addition, TMEM41A was strongly expressed in serous patient carcinoma tissues compared to patients with mixed subtypes (Fig 2F–2H). TMEM41A was strongly expressed in cancer tissues of patients with G2 and G3 stages compared with those of G1 stage and in cancer tissues of G3 patients compared with the G2 patients (Fig 2I–2K). Notably, TMEM41A expression levels were significantly enhanced in cancer tissues from deceased patients compared to those from living patients (Fig 2L–2N). Statistical analyses revealed that high- and low-TMEM41A expression was associated with clinical stage, PFI, race, age, DSS, weight, OS, histologic type, histologic grade, and menopausal status in patients with EC (Table 1).
(A-N) Correlation analysis between TMEM41A expression and clinical stage (A-C), age (D), weight (E); histological type (F-H), histologic grade (I-K), OS event (L), DSS event (M), and PFI event (N). EC, endometrial cancer; OS, overall survival; DSS, disease-specific survival; PFI, progression-free interval.
3.3. TMEM41A overexpression associates with the poor prognosis of patients with EC in subgroup analysis
The overexpression of TMEM41A was significantly associated with poor survival and progression in patients with EC grouped by clinical stage, age, weight, and others (Figs 3–5). Specifically, TMEM41A overexpression was associated with shorter OS (Fig 3) in patients with EC with stages I, I-II, I-III, and III, body weight ≤ 80kg, or > 80kg, height, BMI, G2-3 grade, endometrioid, tumor invasion, age ≥ 60 years, hormone therapy (no), radiotherapy (no), diabetes (yes or no). Similarly, TMEM41A overexpression was associated with shorter DSS in patients with EC with stages I, I-II, I-III, II-III, II-IV, and III, weight ≤ 80 or > 80kg, height, BMI, G2-3 grade, endometrioid, tumor invasion, age > 60 years, hormone therapy (no), radiotherapy (no), diabetes (yes or no) (Fig 4). Furthermore, TMEM41A overexpression was associated with shorter PFI in EC patients with stages I, I-II, I-III, II-III, II-IV, III, and III-IV, weight > 80kg, height > 160cm, BMI, G2-3 grade, G3 grade, endometrioid, tumor invasion, age > 60 years, hormone therapy (no), radiotherapy (no), and diabetes (yes or no) (Fig 5).
EC, endometrial cancer; OS, overall survival.
EC, endometrial cancer; DSS, disease-specific survival.
EC, endometrial cancer; PFI, progression-free interval.
3.4. Construction of TMEM41A-related nomograms
Univariate Cox regression analysis revealed that clinical stage, age, histological grade, radiotherapy, and TMEM41A overexpression were risk factors for shorter OS in patients with EC (Table 2). Similarly, clinical stage and TMEM41A overexpression were risk factors for shorter DSS in patients with EC (Table 3). Moreover, clinical stage, histologic grade, and TMEM41A overexpression were risk factors for shorter PFI in patients with EC (Table 4). We further showed the association between adverse factors in patients with EC and patient prognosis to predict patient survival time via nomogram (Figs 6–8).
EC, endometrial cancer; OS, overall survival.
EC, endometrial cancer; DSS, disease-specific survival.
EC, endometrial cancer; PFI, progression-free interval.
3.5. TMEM41A overexpression associates with the EC immune microenvironment
TMEM41A overexpression was associated with stromal, immune, and estimate scores of cancer samples (Fig 9A–9C). Furthermore, stromal, immune, and estimate scores significantly differed between the high- and low-TMEM41A expression groups (Fig 9D–9F). In EC tissues of the TCGA database, TMEM41A overexpression correlated with the levels of macrophages, CD8+ T cells, TFH, Th2 cells, aDC, cytotoxic cells, eosinophils, iDC, mast cells, neutrophils, NK CD56bright cells, NK CD56dim cells, NK cells, pDC, T cells, Th17 cells, and TReg (Fig 10 and Table 5). The expression levels of 24 immune cell types in the high- and low-TMEM41A expression groups are presented in Fig 11. Additionally, we found that TMEM41A overexpression correlated with tumor purity, CD8+ T cells, macrophage, and neutrophil levels (S1 Fig), and with the copy numbers of CD8+ T cell, neutrophil, and DC in the TIMER database (S2 Fig). Finally, TMEM41A overexpression was also significantly associated with the levels of immune cell markers, including CD8A, CD3D, CD3E, CD2, CSF1R, IL10, IRF5, ITGAM, and CCR7 (Fig 12).
(A-C) Correlation analysis. (D-F) Expression analysis. EC, endometrial cancer.
(A-F) Correlation analysis of TMEM41A expression with various immune cell types, including NK CD56 bright cells (A), iDC (B), NK cells (C), pDC (D), T cells (E), and Eosinophils (F). EC, endometrial cancer.
3.6. TMEM41A expression correlates with the RNA modification
In the RM2Target database, ALKBH3, ALKBH5, ALYREF, ELAVL1, FMR1, FTO, HNRNPC, HNRNPA2B1, IGF2BP1, IGF2BP3, METTL1, METTL14, METTL16, METTL3, METTL5, PCIF1, RBMX, VIRMA, WDR4, WTAP, YBX1, YTHDC1, YTHDF1, YTHDF2, and YTHDF3 were found to be involved in regulating TMEM41A. Additionally, we found a significant correlation between the expression levels of TMEM41A and ALKBH3, ALYREF, FMR1, FTO, HNRNPC, IGF2BP1, IGF2BP3, METTL1, METTL5, PCIF1, RBMX, VIRMA, WTAP, YBX1, YTHDF1, YTHDF2, YTHDF3, YTHDC1, ALKBH5, HNRNPA2B1, and others using Spearman analysis (Table 6).
4. Discussion
In recent years, there has been growing interest in identifying new biomarkers for EC. Several studies have focused on identifying and characterizing the roles of novel oncogenes in EC progression and prognosis [14–17]. For instance, OTU deubiquitinase, ubiquitin aldehyde binding 2 (OTUB2) expression was significantly enhanced in EC, which was associated with poor prognosis of cancer patients. Overexpression of OTUB2 could promote glycolysis and induce proliferation, migration, and invasion of EC cells, while inhibition of the PKM2/PI3K/AKT signaling pathway significantly reversed the oncogenic effects of OTUB2 overexpression on EC cells [15]. Similarly, ubiquitin-specific peptidase 5 (USP5) was significantly upregulated in EC tissues, whereas its inhibition could reduce the migration and proliferation ability of EC cells and induce cell cycle arrest and apoptosis. These effects of USP5 overexpression were associated with excessive activation of the mTOR/4EBP1 signaling pathway [16]. These results suggested that targeting these biomarkers could offer potential therapeutic benefits for patients with EC. TMEM41A is a newly discovered oncogene [6, 7]. Studies have shown that the SPRING1 could enhance colorectal cancer cell growth by promoting TMEM41A expression [6]. TMEM41A is also associated with lymph node metastasis, distant metastasis, and poor prognosis in patients with gastric cancer. Inhibition of TMEM41A expression could delay gastric cancer cell metastasis by regulating EMT and autophagy [7]. In this study, we found that TMEM41A was overexpressed in EC and was a potential diagnostic and prognostic marker for the disease. Our comprehensive analysis revealed that TMEM41A overexpression was associated with shorter OS, clinical stage, age, DSS, weight, histological subtype, PFI, tumor grade, race, and menopausal status in patients with EC. Our preliminary findings indicated that TMEM41A played an oncogenic role in EC, which is consistent with previous reports, and indicates that TMEM41A could be a valuable biomarker for predicting EC prognosis and guiding personalized treatment strategies.
Nomograms have emerged as an increasingly popular method for predicting the prognosis of patients with cancer [18–20]. For example, Wang et al. constructed a nomogram consisting of histological subtype, tumor grade, depth of invasion, cervical involvement, parametrial involvement, and HGB level to accurately predict the risk of lymph node metastasis in patients with EC [19]. Similarly, Li and Yue identified age, race, marital status, FIGO stage, grade, and metastasis as important prognostic factors using univariate Cox regression analysis. The risk factor-related nomogram had predictive power and was associated with the prognosis of patients with EC [20]. In this study, we identified clinical stage, age, histological grade, radiotherapy, and TMEM41A overexpression as risk factors for shorter OS in patients with EC. Moreover, clinical stage and TMEM41A overexpression were risk factors for poor DSS in patients with EC, while clinical stage, histological grade, and TMEM41A overexpression were risk factors for shorter PFI in patients with EC. The risk factors-related prognostic nomograms predicted the survival time of patients with EC, providing novel tools for evaluating the prognosis of patients with endometrial cancer.
Immunotherapy has emerged as a promising strategy to improve the prognosis of cancer patients [21–23]. For example, patients with esophageal squamous cell carcinoma treated with an anti-programmed death 1 (PD-1) inhibitor plus chemotherapy reported a median OS of 15.3 months and a median progression-free survival (PFS) of 6.9 months, compared with 12.0 months and 5.6 months in the chemotherapy group. This study demonstrated that adding anti-PD-1 therapy to chemotherapy significantly improves survival in patients with advanced or metastatic esophageal squamous cell carcinoma [22]. Therefore, we explored the association between TMEM41A expression and components of the immune microenvironment in EC. We found that TMEM41A overexpression was correlated with EC stromal, immune, and estimate scores and was linked with tumor purity, immune cells (such as the macrophages, CD8 T cells, and TFH), and immune cell markers (such as the CD8A, CD3D, and CD3E). In addition, TMEM41A expression was significantly correlated with the levels of several RNA modification genes, including ALKBH3, ALYREF, FMR1, FTO, HNRNPC, IGF2BP1, IGF2BP3, METTL1, METTL5, PCIF1, RBMX, VIRMA, WTAP, YBX1, YTHDF1, YTHDF2, YTHDF3, YTHDC1, ALKBH5, and HNRNPA2B1. RNA modification genes play important regulatory roles in cancer [24–27]. For instance, FTO, the m6A modification gene, was highly expressed in metastatic EC tissues, and promoted EC metastasis and invasion by activating the Wnt signaling pathway through the demethylation of HOXB13 mRNA, which eliminated recognition of m6A modification via the YTHDF2 protein [27]. Additionally, the expression level of lncRNA FENDRR was decreased in endometrioid endometrial carcinoma (EEC), while the FENDRR m6A methylation level was significantly increased. YTHDF2 mediated the degradation of FENDRR and promoted cancer cell proliferation by increasing SOX4 expression in EEC [23]. Our findings demonstrated that TMEM41A was associated with immune microenvironment and RNA modification, further suggesting that TMEM41A may play a critical role in EC.
Traditionally, local invasion and histological characteristics have been used as risk factors for the prognosis of patients with EC. However, in recent years, molecular and genomic maps have emerged as promising tools to predict the prognosis of patients with EC, helping in identifying those with low, medium, and high recurrence risks [17, 28–30]. Our results revealed that TMEM41A was upregulated in EC and that its increased expression was related to poor prognosis, immune status, and RNA modification in patients with EC. This study provides new biomarkers for evaluating the prognosis of patients with EC and has the following advantages and disadvantages. We analyzed a large number of tissue samples and prognostic data, ensuring the reliability of our findings. In addition, this study is the first to report the association between TMEM41A expression and EC progression, providing new directions for future research. However, this study lacked basic research to confirm the current results. Our future studies would focus on collecting cancer tissues and normal adjacent tissues from patients with EC to verify the expression of TMEM41A and explore its impact on the prognosis of patients with EC. Moreover, the effects of inhibiting TMEM41A on the growth and migration of EC cells should be investigated. Additionally, radiomic features are crucial in the screening, diagnosis, and prognosis of patients with EC [30]. Therefore, future studies should combine TMEM41A expression and radiomic features to evaluate the prognosis of patients with EC.
5. Conclusions
In conclusion, our study demonstrates that TMEM41A exhibits strong expression in EC tissues. TMEM41A could serve as a diagnostic marker and evaluate the poor prognosis of patients with EC. Moreover, the overexpression of TMEM41A is associated with poor prognosis, stromal score, immune score, estimate score, immune cells, cell markers, and RNA modifications. These findings suggest that TMEM41A may serve as a potential biomarker for EC treatment.
Supporting information
S1 Fig. TMEM41A expression correlates with EC immunity.
EC, endometrial cancer.
https://doi.org/10.1371/journal.pone.0285817.s001
(JPG)
S2 Fig. TMEM41A expression correlates with the immune cell copy number in EC.
EC, endometrial cancer.
https://doi.org/10.1371/journal.pone.0285817.s002
(JPG)
References
- 1. Wang C, Yin Y, Sun Z, Wang Y, Li F, Wang Y, et al. ATAD2 Upregulation Promotes Tumor Growth and Angiogenesis in Endometrial Cancer and Is Associated with Its Immune Infiltration. Dis Markers. 2022; 2022: 2334338. pmid:36479043.
- 2. Song Y, Zhou G, Song E, Zhan L, Wang Q, Song H, et al. TRIM44 Promotes Endometrial Carcinoma Progression by Activating the FRS2 Signalling Pathway. Evid Based Complement Alternat Med. 2022; 2022: 6235771. pmid:36387361.
- 3. Post CCB, Westermann AM, Bosse T, Creutzberg CL, Kroep JR. PARP and PD-1/PD-L1 checkpoint inhibition in recurrent or metastatic endometrial cancer. Crit Rev Oncol Hematol. 2020; 152: 102973. pmid:32497971.
- 4. Li D, Li K, Zhang W, Yang KW, Mu DA, Jiang GJ, et al. The m6A/m5C/m1A Regulated Gene Signature Predicts the Prognosis and Correlates With the Immune Status of Hepatocellular Carcinoma. Front Immunol. 2022; 13: 918140. pmid:35833147.
- 5. Peng M, Fan S, Li J, Zhou X, Liao Q, Tang F, et al. Programmed death-ligand 1 signaling and expression are reversible by lycopene via PI3K/AKT and Raf/MEK/ERK pathways in tongue squamous cell carcinoma. Genes Nutr. 2022; 17(1): 3. pmid:35164673.
- 6. Tao Y, Luo J, Zhu H, Chu Y, Pei L. Chromosome 12 Open Reading Frame 49 Promotes Tumor Growth and Predicts Poor Prognosis in Colorectal Cancer. Dig Dis Sci. 2022; undefined: undefined. pmid:36348128.
- 7. Lin B, Xue Y, Qi C, Chen X, Mao W. Expression of transmembrane protein 41A is associated with metastasis via the modulation of E‑cadherin in radically resected gastric cancer. Mol Med Rep. 2018; 18(3): 2963–2972. pmid:30015937.
- 8. Guo Q, Liu XL, Liu HS, Luo XY, Yuan Y, Ji YM, et al. The Risk Model Based on the Three Oxidative Stress-Related Genes Evaluates the Prognosis of LAC Patients. Oxid Med Cell Longev. 2022; 2022: 4022896. pmid:35783192; PMCID.
- 9. Lin Z, Huang L, Li S, Gu J, Cui X, Zhou Y. Pan-cancer analysis of genomic properties and clinical outcome associated with tumor tertiary lymphoid structure. Sci Rep. 2020; 10(1): 21530. pmid:33299035.
- 10. Zhao YY, Xiang QM, Chen JL, Zhang L, Zheng WL, et al. SLC25A25-AS1 over-expression could be predicted the dismal prognosis and was related to the immune microenvironment in prostate cancer. Front Oncol. 2022; 12: 990247. pmid:36338724.
- 11. Xu Q, Ge Q, Zhou Y, Yang B, Yang Q, Jiang S, et al. MELK promotes Endometrial carcinoma progression via activating mTOR signaling pathway. EBioMedicine. 2020; 51: 102609. Epub 2020 Jan 6. pmid:31915116.
- 12. Guo Q, Wu CY, Jiang N, Tong S, Wan JH, Xiao XY, et al. Downregulation of T-cell cytotoxic marker IL18R1 promotes cancer proliferation and migration and is associated with dismal prognosis and immunity in lung squamous cell carcinoma. Front Immunol. 2022; 13: 986447. pmid:36544782.
- 13. Li Y, Huo J, He J, Zhang Y, Ma X. BTG1 inhibits malignancy as a novel prognosis signature in endometrial carcinoma. Cancer Cell Int. 2020; 20: 490. pmid:33041670.
- 14. Hu A, Wang Y, Tian J, Chen Z, Chen R, Han X, et al. Pan-cancer analysis reveals DDX21 as a potential biomarker for the prognosis of multiple tumor types. Front Oncol. 2022; 12: 947054. pmid:36505822.
- 15. Zhang Q, Zhang J, Yao A, Tian X, Han Z, Yuan Y, et al. OTUB2 promotes the progression of endometrial cancer by regulating the PKM2-mediated PI3K/AKT signaling pathway. Cell Biol Int. 2023; 47(2):428–438. pmid:36316812.
- 16. Li Y, Zhou J. USP5 Promotes Uterine Corpus Endometrial Carcinoma Cell Growth and Migration via mTOR/4EBP1 Activation. Cancer Manag Res. 2021; 13: 3913–3924. pmid:34012297.
- 17. Di Donato V, Giannini A, Bogani G. Recent Advances in Endometrial Cancer Management. J Clin Med. 2023;12(6): 2241. pmid:36983243.
- 18. Wu J, Zhang H, Li L, Hu M, Chen L, Xu B, et al. A nomogram for predicting overall survival in patients with low-grade endometrial stromal sarcoma: A population-based analysis. Cancer Commun (Lond). 2020; 40(7): 301–312. pmid:32558385.
- 19. Wang Z, Zhang S, Ma Y, Li W, Tian J, Liu T. A nomogram prediction model for lymph node metastasis in endometrial cancer patients. BMC Cancer. 2021; 21(1): 748. pmid:34187416.
- 20. Li R, Yue Q. A nomogram for predicting overall survival in patients with endometrial carcinoma: A SEER-based study. Int J Gynaecol Obstet. 2022; undefined: undefined. pmid:36394432.
- 21. Doroshow DB, Bhalla S, Beasley MB, Sholl LM, Kerr KM, Gnjatic S, et al. PD-L1 as a biomarker of response to immune-checkpoint inhibitors. Nat Rev Clin Oncol. 2021; 18(6): 345–362. pmid:33580222.
- 22. Luo H, Lu J, Bai Y, Mao T, Wang J, Fan Q, et al. Effect of Camrelizumab vs Placebo Added to Chemotherapy on Survival and Progression-Free Survival in Patients With Advanced or Metastatic Esophageal Squamous Cell Carcinoma: The ESCORT-1st Randomized Clinical Trial. JAMA. 2021; 326(10): 916–925. pmid:34519801.
- 23. Tawbi HA, Schadendorf D, Lipson EJ, Ascierto PA, Matamala L, Castillo Gutiérrez E, et al. Relatlimab and Nivolumab versus Nivolumab in Untreated Advanced Melanoma. N Engl J Med. 2022; 386(1): 24–34. pmid:34986285.
- 24. Shen J, Feng XP, Hu RB, Wang H, Wang YL, Qian JH, et al. N-methyladenosine reader YTHDF2-mediated long noncoding RNA FENDRR degradation promotes cell proliferation in endometrioid endometrial carcinoma. Lab Invest. 2021; 101(6): 775–784. pmid:33692441.
- 25. Li Q, Wang C, Dong W, Su Y, Ma Z. WTAP facilitates progression of endometrial cancer via CAV-1/NF-κB axis. Cell Biol Int. 2021; 45(6): 1269–1277. pmid:33559954.
- 26. Zhang L, Wan Y, Zhang Z, Jiang Y, Gu Z, Ma X, et al. IGF2BP1 overexpression stabilizes PEG10 mRNA in an m6A-dependent manner and promotes endometrial cancer progression. Theranostics. 2021; 11(3): 1100–1114. pmid:33391523.
- 27. Zhang L, Wan Y, Zhang Z, Jiang Y, Lang J, Cheng W, et al. FTO demethylates m6A modifications in HOXB13 mRNA and promotes endometrial cancer metastasis by activating the WNT signalling pathway. RNA Biol. 2021; 18(9): 1265–1278. pmid:33103587.
- 28. Cuccu I, D’Oria O, Sgamba L, De Angelis E, Golia D’Augè T, Turetta C, et al. Role of Genomic and Molecular Biology in the Modulation of the Treatment of Endometrial Cancer: Narrative Review and Perspectives. Healthcare (Basel). 2023; 11(4): 571. pmid:36833105.
- 29. Golia D’Augè T, Cuccu I, Santangelo G, Muzii L, Giannini A, Bogani G, et al. Novel Insights into Molecular Mechanisms of Endometrial Diseases. Biomolecules. 2023; 13(3): 499. pmid:36979434.
- 30. Bogani G, Chiappa V, Lopez S, Salvatore C, Interlenghi M, D’Oria O, et al. Radiomics and Molecular Classification in Endometrial Cancer (The ROME Study): A Step Forward to a Simplified Precision Medicine. Healthcare (Basel). 2022; 10(12): 2464. pmid:36553988.