Multivariate gene expression‐based survival predictor model in esophageal adenocarcinoma

Zhao, Maoyuan; Wang, Jingsong; Yuan, Meng; Ma, Zeliang; Bao, Yi; Hui, Zhouguang

doi:10.1111/1759-7714.13626

Cited by 9 publications

(9 citation statements)

References 63 publications

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“…ITPR1 was found downregulated in the esophageal adenocarcinoma (EAC) tissues compared with the normal [ 39 ]. Basing the TCGA database, Zhao et al found that ITPR1 could be a potential biomarker for esophageal adenocarcinoma [ 40 ]. ITPR1 may also involve in head and neck squamous cell carcinoma cancer genetics.…”

Section: Discussionmentioning

confidence: 99%

Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer

Zheng

Bai

Zhou

et al. 2022

Aging

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Inositol 1,4,5-Triphosphate Receptor Family (ITPRs) are necessary intracellular Ca2+-release channel encoders and participate in mammalian cell physiological and pathological processes. Previous studies have suggested that ITPRs participate in tumorigenesis of multiple cancers. Nevertheless, the diverse expression profiles and prognostic significance of three ITPRs in pancreatic cancer have yet to be uncovered. In this work, we examined the expression levels and survival dates of ITPRs in patients with pancreatic cancer. As a result, we identified that ITPR1 and ITPR3 expression levels are significantly elevated in cancerous specimens. Survival data revealed that over-expression of ITPR2 and ITPR3 resulted in unfavourable overall survival and pathological stage. The multivariate Cox logistic regression analysis showed that ITPR3 could be an independent risk factor for PAAD patient survival. Moreover, to investigate how ITPRs work, co-expressed genes, alterations, protein-protein interaction, immune infiltration, methylation, and functional enrichment of ITPRs were also analyzed. Then, we evaluated these findings in clinical samples. Moreover, the gain and loss of function of ITPR3 were also conducted. The electron microscope assay was employed to explore the role of ITPR3 in pancreatic cancer cell lines’ endoplasmic reticulum stress. In summary, our findings demonstrated that ITPR3 has the potential to be drug targets and biomarkers for human pancreatic cancer.

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Section: Discussionmentioning

confidence: 99%

Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer

Zheng

Bai

Zhou

et al. 2022

Aging

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“…ITPR1 (inositol 1,4,5‐trisphosphate receptor 1) is a ligand‐gated ion channel in regulating calcium release from endoplasmic reticulum and acts as a autophagy sensor 42 . ITPR1 down‐regulation is observed in esophageal adenocarcinoma and has been recognized as a potential biomarker of prognosis in esophageal adenocarcinoma 43,44 . MAP1LC3C (microtubule‐associated protein 1 light chain 3 gamma), a critical structural protein in autophagosome membrane, has been reported to be an independent prognostic biomarker in colorectal cancer 45,46 .…”

Section: Discussionmentioning

confidence: 99%

“…as a potential biomarker of prognosis in esophageal adenocarcinoma. 43,44 MAP1LC3C (microtubule-associated protein 1 light chain 3 gamma), a critical structural protein in autophagosome membrane, has been reported to be an independent prognostic biomarker in colorectal cancer. 45,46 However, there is little knowledge concerning prognostic implications of DAPK2, ITPR1, and MAP1LC3C in ESCC.…”

Section: Pca Analysis For High-risk and Low-risk Samples Based On M6a...mentioning

confidence: 99%

Prognostic score model based on six m6A‐related autophagy genes for predicting survival in esophageal squamous cell carcinoma

Chen

Gong

et al. 2022

Clinical Laboratory Analysis

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Background: Prognostic signatures based on autophagy genes have been proposedfor esophageal squamous cell carcinoma (ESCC). Autophagy genes are closely associated with m6A genes. Our purpose is to identify m6A-related autophagy genes in ESCC and develop a survival prediction model. Methods: Differential expression analyses for m6A genes and autophagy genes were performed based on TCGA and HADd databases followed by constructing a co-expression network. Uni-variable Cox regression analysis was performed for m6Arelated autophagy genes. Using the optimal combination of feature genes by LASSO Cox regression model, a prognostic score (PS) model was developed and subsequently validated in an independent dataset. Results:The differential expression of 13 m6A genes and 107 autophagy genes was observed between ESCC and normal samples. The co-expression network contained 13 m6A genes and 96 autophagy genes. Of the 12 m6A-related autophagy genes that were significantly related to survival, DAPK2, DIRAS3, EIF2AK3, ITPR1, MAP1LC3C, and TP53 were used to construct a PS model, which split the training set into two risk groups with significant different survival ratios (p = 0.015, 1-year, 3-year, and 5-year AUC = 0.873, 0.840, and 0.829). Consistent results of GSE53625 dataset confirmed predictive ability of the model (p = 0.024, 1-year, 3-year, and 5-year AUC = 0.793, 0.751, and 0.744). The six-gene PS score was an independent prognostic factor from clinical factors (HR, 2.362; 95% CI, 1.390-7.064; p-value = 0.012). Conclusion:Our study recommends 6 m6A-related autophagy genes as promising prognostic biomarkers and develops a PS model to predict survival in ESCC.

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“…Thus, recent studies have profoundly explored the wide ranges from single gene marker to multigene array for the potential mRNA [ 7 , 8 ], long noncoding RNA (lncRNA) [ 9 ], and competing endogenous RNA (ceRNA) network [ 10 ]-based prognostic biomarkers for esophageal cancer. In addition to the genes, including FAM46A , RAB15 , SLC20A1 , IL1A , and ACSL1 , which have been found to be associated with the overall survival (OS) or relapse-free survival (RFS) of EAC patients [ 11 ], several autophagy-related genes [ 12 ], as well as glycolysis-related genes [ 13 ], have also been detected as the potential prognostic biomarkers of EAC progression. Moreover, ceRNA network-derived eight-gene panel [ 10 ] and four-gene panel [ 13 ] models have been established to predict the overall survival rate of EAC patients.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to the genes, including FAM46A , RAB15 , SLC20A1 , IL1A , and ACSL1 , which have been found to be associated with the overall survival (OS) or relapse-free survival (RFS) of EAC patients [ 11 ], several autophagy-related genes [ 12 ], as well as glycolysis-related genes [ 13 ], have also been detected as the potential prognostic biomarkers of EAC progression. Moreover, ceRNA network-derived eight-gene panel [ 10 ] and four-gene panel [ 13 ] models have been established to predict the overall survival rate of EAC patients. Furthermore, several genetic panels have been developed based on the tumor microenvironment-associated oncogenes [ 14 , 15 ], flavoproteins [ 16 ], histone modifications [ 17 ], actin cytoskeletal proteins [ 18 ], and other heterogeneous pathways [ 19 – 21 ], to track the ESCC prognostic signatures.…”

Section: Introductionmentioning

confidence: 99%

Identification of a Ten-Gene Signature of DNA Damage Response Pathways with Prognostic Value in Esophageal Squamous Cell Carcinoma

Zhuang

Ben

Zhou

et al. 2021

Journal of Oncology

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Molecular prognostic signatures are critical for treatment decision-making in esophageal squamous cell cancer (ESCC), but the robustness of these signatures is limited. The aberrant DNA damage response (DDR) pathway may lead to the accumulation of mutations and thus accelerate tumor progression in ESCC. Given this, we applied the LASSO Cox regression to the transcriptomic data of DDR genes, and a prognostic DDR-related gene expression signature (DRGS) consisting of ten genes was constructed, including PARP3, POLB, XRCC5, MLH1, DMC1, GTF2H3, PER1, SMC5, TCEA1, and HERC2. The DRGS was independently associated with overall survival in both training and validation cohorts. The DRGS achieved higher accuracy than six previously reported multigene signatures for the prediction of prognosis in comparable cohorts. Furtherly, a nomogram incorporating DRGS and clinicopathological features showed improved predicting performance. Taken together, the DRGS was identified as a novel, robust, and effective prognostic indicator, which may refine the scheme of risk stratification and management in ESCC patients.

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Multivariate gene expression‐based survival predictor model in esophageal adenocarcinoma

Cited by 9 publications

References 63 publications

Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer

Transcriptional ITPR3 as potential targets and biomarkers for human pancreatic cancer

Prognostic score model based on six m6A‐related autophagy genes for predicting survival in esophageal squamous cell carcinoma

Identification of a Ten-Gene Signature of DNA Damage Response Pathways with Prognostic Value in Esophageal Squamous Cell Carcinoma

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