Subtyping sub-Saharan esophageal squamous cell carcinoma by comprehensive molecular analysis

Liu, Wenjin; Snell, Jeff M.; Jeck, William R.; Hoadley, Katherine A.; Wilkerson, Matthew D.; Parker, Joel S.; Patel, Nirali M.; Mlombe, Yohannie; Mulima, Gift; Liomba, N. George; Wolf, Lindsey L.; Shores, Carol G.; Gopal, Satish; Sharpless, Norman E.

doi:10.1172/jci.insight.98457

Cited by 15 publications

(24 citation statements)

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“…However, the mere presence of HPV DNA in ESCC tissues cannot confirm its etiological role in tumorigenesis; thus, a large international study (interSCOPE) was designed to determine whether there were anti-L1 or anti-E6/E7 antibodies in the serum of ESCC patients, with only 4 samples found positive for HPV-16 E6 and E7 (27). Further evidence demonstrated no detectable level of HPV DNA integration in ESCC samples (28,29), and the status of HPV infection did not affect the prognosis of ESCC (30). These results indicate that HPV may play a less important role in the development of ESCC, but a hit-and-run mechanism may be utilized by HPV to induce ESCC.…”

Section: Hpv-associated Diseasesmentioning

confidence: 99%

Current strategies against persistent human papillomavirus infection (Review)

Liu

et al. 2019

Int J Oncol

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Human papillomavirus (HPV) is the most common sexually transmitted infection, exhibiting a tropism for the epidermis and mucosae. The link between persistent HPV infection and malignancies involving the anogenital tract as well as the head and neck has been well-established, and it is estimated that HPV-related cancers involving various anatomical sites account for 4.5% of all human cancers. Current prophylactic vaccines against HPV have enabled the prevention of associated malignancies. However, the sizeable population base of current infection in whom prophylactic vaccines are not applicable, certain high-risk HPV types not included in vaccines, and the vast susceptible population in developing countries who do not have access to the costly prophylactic vaccines, put forward an imperative need for effective therapies targeting persistent infection. In this article, the life cycle of HPV, the mechanisms facilitating HPV evasion of recognition and clearance by the host immune system, and the promising therapeutic strategies currently under investigation, particularly antiviral drugs and therapeutic vaccines, are reviewed.

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Section: Hpv-associated Diseasesmentioning

confidence: 99%

Current strategies against persistent human papillomavirus infection (Review)

Liu

et al. 2019

Int J Oncol

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“…Recently, three subtypes were identified based on the mRNA expression data from 59 ESCC individuals in Malawi, of which classification could be distinguished by their expression of cell cycle and neutral transcripts [ 8 ]. Besides they also observed related genomic alterations in the specific subtypes, in addition to the previous studies, Yang et al, re-analyzed previously published mRNA and lncRNA data from 119 ESCC patients in China, and identified two subtypes with significantly different prognosis, and also demonstrated key nodes on mRNA-lncRNA networks in subtype-specific ESCC [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

An esophageal squamous cell carcinoma classification system that reveals potential targets for therapy

et al. 2017

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ESCC (Esophageal squamous cell carcinoma) is a heterogeneous cancer with diverse prognosis. Here, to explore the biological diversity of ESCC, we employed gene expression profiles from 360 ESCC tumors from East Asians to establish a comprehensive molecular classification and characterization of ESCC. Using the specific 185-gene signature generated by unsupervised consensus clustering of gene expression data, we defined four subtypes associated with distinct clinical metrics: tumors with high metastasis associated with EMT (epithelial to mesenchymal transition) and active MAP4K4/JNK signaling pathway; tumors with high chromosomal instability with up regulated MYC targes; well differentiated tumors with less aggressive and moderated tumors. The clinical relevance of these subtypes was stated by significant differences in prognosis. Importantly, 24% of all ESCCs (n = 360) were classified into the high metastasis subtype associated with poorly differentiation and unfavorable prognosis. We provided evidence that this subtype relates to tumor microenvironment. Collectively, these results might contribute to more precise personalized therapeutic strategies for each subtype of ESCC patients in the near future.

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“…Through comprehensive but analysis based on iCluster, three molecular subtypes of ESCC displaying a geographical trend were obtained, but the survival difference was not studied (33). Liu et al reported the identification of 3 subtypes possessing different clinical features, genomic complexity, p53 mutational status, and RNA expression; however they did not focus on survival comparison of the different subtypes (34). In contrast to these studies on the molecular subtypes of ESCC, the results of the present study may aid in improving the prognosis of patients with ESCC.…”

Section: Discussionmentioning

confidence: 76%

A model for predicting prognosis in patients with esophageal squamous cell carcinoma based on joint representation learning

Zhang

et al. 2020

Oncol Lett

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Esophageal squamous cell carcinoma (ESCC) is one of the deadliest cancer types with a poor prognosis due to the lack of symptoms in the early stages and a delayed diagnosis. The present study aimed to identify the risk factors significantly associated with prognosis and to search for novel effective diagnostic modalities for patients with early-stage ESCC. mRNA and methylation data of patients with ESCC and the corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) database, and the representation features were screened using deep learning autoencoder. The univariate Cox regression model was used to select the prognosis-related features from the representation features. K-means clustering was used to cluster the TCGA samples. Support vector machine classifier was constructed based on the top 75 features mostly associated with the risk subgroups obtained from K-means clustering. Two ArrayExpress datasets were used to verify the reliability of the obtained risk subgroups. The differentially expressed genes and methylation genes (DEGs and DMGs) between the risk subgroups were analyzed, and pathway enrichment analysis was performed. A total of 500 representation features were produced. Using K-means clustering, the TCGA samples were clustered into two risk subgroups with significantly different overall survival rates. Joint multimodal representation strategy, which showed a good model fitness (C-index=0.760), outperformed early-fusion autoencoder strategy. The joint representation learning-based classification model had good robustness. A total of 1,107 DEGs and 199 DMGs were screened out between the two risk subgroups. The DEGs were involved in 70 pathways, the majority of which were correlated with metastasis and proliferation of various cancer types, including cytokine-cytokine receptor interaction, cell adhesion molecules PPAR signaling pathway, pathways in cancer, transcriptional misregulation in cancer and ECM-receptor interaction pathways. The two survival subgroups obtained via the joint representation learning-based model had good robustness, and had prognostic significance for patients with ESCC.

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Subtyping sub-Saharan esophageal squamous cell carcinoma by comprehensive molecular analysis

Cited by 15 publications

References 0 publications

Current strategies against persistent human papillomavirus infection (Review)

Current strategies against persistent human papillomavirus infection (Review)

An esophageal squamous cell carcinoma classification system that reveals potential targets for therapy

A model for predicting prognosis in patients with esophageal squamous cell carcinoma based on joint representation learning

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