Treatment patterns and survival in advanced unresectable esophageal squamous cell cancer: A population‐based study

Pape, Marieke; Vissers, Pauline A. J.; Vos‐Geelen, Judith de; Hulshof, Maarten C.C.M.; Gisbertz, Suzanne S.; Jeene, Paul M.; Laarhoven, H.W.M. van; Verhoeven, Rob H.A.

doi:10.1111/cas.15262

Cited by 10 publications

(5 citation statements)

References 27 publications

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“…ESCC is a dangerous and aggressive disease with an unfavorable prognosis [ 26 ]. After receiving radiation and chemotherapy, patients with inoperable tumors have a survival time of only 17–54 months, and patients with surgically resected EC have a 5-year survival rate of approximately 30% [ 27 ]. Mitochondria are important organelles in eukaryotes, and their dysfunction leads to many diseases [ 28 ].…”

Section: Discussionmentioning

confidence: 99%

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

Wang,

Zhang,

Shi

et al. 2024

J. Microbiol. Biotechnol.

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Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

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Section: Discussionmentioning

confidence: 99%

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

Wang,

Zhang,

Shi

et al. 2024

J. Microbiol. Biotechnol.

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“…According to the Global Cancer Statistics 2020, esophageal cancer ranks 7th and 6th in terms of incidence and mortality ( Chen et al, 2016 ; Arnold et al, 2020 ; Sung et al, 2021 ). The 5-year survival rate for patients with resectable esophageal cancer is close to 30%, while unresectable tumors are mainly treated with radiotherapy and chemotherapy, with a median survival of only 17–54 months ( Cookson, 2000 ; Pape et al, 2022 ). Thus, it is crucial to identify novel therapeutic targets of ESCC in order to improve prognosis.…”

Section: Introductionmentioning

confidence: 99%

“…The 5-year survival rate for patients with resectable esophageal cancer is close to 30%, while unresectable tumors are mainly treated with radiotherapy and chemotherapy, with a median survival of only 17-54 months (Cookson, 2000;Pape et al, 2022). Thus, it is crucial to identify novel therapeutic targets of ESCC in order to improve prognosis.…”

Section: Introductionmentioning

confidence: 99%

A tricarboxylic acid cycle-based machine learning model to select effective drug targets for the treatment of esophageal squamous cell carcinoma

Liang

Tan

et al. 2023

Front. Pharmacol.

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Background: The tricarboxylic acid cycle (TCA cycle) is an important metabolic pathway and closely related to tumor development. However, its role in the development of esophageal squamous cell carcinoma (ESCC) has not been fully investigated.Methods: The RNA expression profiles of ESCC samples were retrieved from the TCGA database, and the GSE53624 dataset was additionally downloaded from the GEO database as the validation cohort. Furthermore, the single cell sequencing dataset GSE160269 was downloaded. TCA cycle-related genes were obtained from the MSigDB database. A risk score model for ESCC based on the key genes of the TCA cycle was built, and its predictive performance was evaluated. The association of the model with immune infiltration and chemoresistance were analyzed using the TIMER database, the R package “oncoPredict” score, TIDE score and so on. Finally, the role of the key gene CTTN was validated through gene knockdown and functional assays.Results: A total of 38 clusters of 8 cell types were identified using the single-cell sequencing data. The cells were divided into two groups according to the TCA cycle score, and 617 genes were identified that were most likely to influence the TCA cycle. By intersecting 976 key genes of the TCA cycle with the results of WGCNA, 57 genes significantly associated with the TCA cycle were further identified, of which 8 were screened through Cox regression and Lasso regression to construct the risk score model. The risk score was a good predictor of prognosis across subgroups of age, N, M classification and TNM stage. Furthermore, BI-2536, camptothecin and NU7441 were identified as possible drug candidates in the high-risk group. The high-risk score was associated with decreased immune infiltration in ESCC, and the low-risk group had better immunogenicity. In addition, we also evaluated the relationship between risk scores and immunotherapy response rates. Functional assays showed that CTTN may affect the proliferation and invasion of ESCC cells through the EMT pathway.Conclusion: We constructed a predictive model for ESCC based on TCA cycle-associated genes, which achieved good prognostic stratification. The model are likely associated with the regulation of tumor immunity in ESCC.

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“…Although the incidence of ESCC has shown a decreasing trend in certain countries (Liang et al, 2017), ESCC continues to be a pressing public health issue on account of its increased fatality rate (Abnet et al, 2018). Majority of ESCC patients present at an advanced stage during medical consultation, and conventional surgical interventions often exhibit suboptimal effectiveness or even fail to achieve a radical resection in some cases (He et al, 2022;Pape et al, 2022), with a 5-year survival rate of less than 30% (Allemani et al, 2018). As tumor molecular biology and immune escape mechanisms are more thoroughly studied, a growing number of targeted and immune drugs are being investigated as potential treatments to prolong the survival time of patients with ESCC (Kojima et al, 2020;Costoya and Arce, 2023).…”

Section: Introductionmentioning

confidence: 99%

DASES: a database of alternative splicing for esophageal squamous cell carcinoma

Chen,

Kuang,

Luan

et al. 2023

Front. Genet.

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Esophageal carcinoma ranks as the sixth leading cause of cancer-related mortality globally, with esophageal squamous cell carcinoma (ESCC) being particularly prevalent among Asian populations. Alternative splicing (AS) plays a pivotal role in ESCC development and progression by generating diverse transcript isoforms. However, the current landscape lacks a specialized database focusing on alternative splicing events (ASEs) derived from a large number of ESCC cases. Additionally, most existing AS databases overlook the contribution of long non-coding RNAs (lncRNAs) in ESCC molecular mechanisms, predominantly focusing on mRNA-based ASE identification. To address these limitations, we deployed DASES (http://www.hxdsjzx.cn/DASES). Employing a combination of publicly available and in-house ESCC RNA-seq datasets, our extensive analysis of 346 samples, with 93% being paired tumor and adjacent non-tumor tissues, led to the identification of 257 novel lncRNAs in esophageal squamous cell carcinoma. Leveraging a paired comparison of tumor and adjacent normal tissues, DASES identified 59,094 ASEs that may be associated with ESCC. DASES fills a critical gap by providing comprehensive insights into ASEs in ESCC, encompassing lncRNAs and mRNA, thus facilitating a deeper understanding of ESCC molecular mechanisms and serving as a valuable resource for ESCC research communities.

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Treatment patterns and survival in advanced unresectable esophageal squamous cell cancer: A population‐based study

Cited by 10 publications

References 27 publications

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

Construction of a Novel Mitochondria-Associated Gene Model for Assessing ESCC Immune Microenvironment and Predicting Survival

A tricarboxylic acid cycle-based machine learning model to select effective drug targets for the treatment of esophageal squamous cell carcinoma

DASES: a database of alternative splicing for esophageal squamous cell carcinoma

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