The second Mexican consensus on hepatocellular carcinoma. Part I: Epidemiology and diagnosis

Cisneros-Garza, L.E.; González-Huezo, M.S.; Moctezuma‐Velázquez, Carlos; Guevara-Cetina, L. Ladrón de; Vilatobá, Mario; García‐Juárez, Ignacio; Alvarado-Reyes, R.; Álvarez-Treviño, G.A.; Allende-Pérez, Silvia; Bornstein-Quevedo, L.; Calderillo-Ruiz, G.; Carrillo-Martínez, Miguel Ángel; Castillo-Barradas, M.; Cerda-Reyes, Eira; Félix-Leyva, J.A.; Gabutti-Thomas, J.A.; Guerrero-Ixtlahuac, J.; Higuera-de-la-Tijera, Fátima; Huitzil-Melendez, D.; Kimura‐Hayama, Eric; López-Hernández, P.A.; Malé-Velázquez, R.; Méndez-Sánchez, Nahúm; Morales-Ruiz, M.A.; Ruiz-García, Érika; Sánchez-Ávila, Juan Francisco; Torrecillas-Torres, Laura

doi:10.1016/j.rgmxen.2021.10.009

Cited by 3 publications

(2 citation statements)

References 155 publications

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“…Hepatocellular carcinoma (HCC), the most common form of liver cancer [1], is the fourth leading cause of mortality and the second most lethal malignant tumor worldwide [2]. Despite the fact that the availability of diagnostic tools is limited, such as histology and radiologic tests, there is still a great demand for swift, accurate and convenient methods for diagnosing HCC [3].…”

Section: Introductionmentioning

confidence: 99%

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Chen

Huang

Ouyang

et al. 2023

IJMS

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Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

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Section: Introductionmentioning

confidence: 99%

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Chen

Huang

Ouyang

et al. 2023

IJMS

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“…Sex-stratified analyses by Acuna et al and others have revealed that increases in risk among US-born Hispanic populations appear to only occur for males, a finding that may help pinpoint drivers of differences in risk by nativity[ 23 , 24 ]. Our results also showed that disparities in HCC incidence by ethnicity exist among foreign-born adults, likely due to the relatively high rates of liver cancer in Mexico driven etiologically by alcoholic liver disease, hepatitis C virus, increasingly, non-alcoholic steatohepatitis[ 26 ]. Across each time period, Hispanic adults were also more likely to be diagnosed at a later stage compared to NHW adults, which mirrors previous research showing that Hispanic individuals are more likely to present with more advanced staging[ 7 , 27 – 29 ].…”

Section: Discussionmentioning

confidence: 92%

Disparities in hepatocellular carcinoma incidence among Hispanic and non-Hispanic adults in Arizona: Trends between 2009-2017

Morrill,

Wightman,

Cruz

et al. 2024

Annals of Epidemiology

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ATP6V1C1, associated with the tumor microenvironment and mTORC1 signaling pathway, is a potential diagnostic, prognostic, and therapeutic biomarker for hepatocellular carcinoma

Pan,

Chen,

et al. 2024

Discov Onc

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Background Hepatocellular carcinoma (HCC) is a global health challenge with high mortality. ATP6V1C1, one of the subunit genes of vacuolar adenosine triphosphatase (V-ATPase), is a potential oncogene. However, its role in HCC remains unclear. Materials and methods Differential analysis of mRNA and microRNA (miRNA), combined with machine learning, identified ATP6V1C1 as a potential biomarker for HCC. The expression and prognostic role of ATP6V1C1 in HCC were evaluated. Additionally, we explored the distribution of ATP6V1C1 in HCC tumor microenvironment (TME) at single-cell and spatial transcriptome levels. Furthermore, the association between ATP6V1C1 and malignant biological features, TME characteristics, and therapy response in HCC was investigated. Finally, in vitro experiments validated the effects of ATP6V1C1 on the malignant phenotype of HCC. Results ATP6V1C1 had higher expression in HCC tissues compared to paired normal tissues. Upregulated ATP6V1C1 was associated with poor HCC prognosis. ATP6V1C1 was primarily expressed in malignant cells and the tumor region in HCC TME. A positive correlation was observed between ATP6V1C1 expression and the activation of cancer-related pathways. The high ATP6V1C1 expression group exhibited increased pro-tumorigenic immune infiltration, inhibited anti-tumor immune activity, and high tumor proliferation rate. HCC patients of low ATP6V1C1 expression group had more clinical response to anti-tumor therapies. Knockdown of ATP6V1C1 impaired the proliferation, migration, and invasion of HCC cells by downregulating the mTORC1 signaling pathway. Conclusion ATP6V1C1 multifacetedly contributes to the oncogenesis and progression of HCC and is a promising diagnostic and prognostic biomarker with predictive value on therapy response. Supplementary Information The online version contains supplementary material available at 10.1007/s12672-024-01578-w.

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The second Mexican consensus on hepatocellular carcinoma. Part I: Epidemiology and diagnosis

Cited by 3 publications

References 155 publications

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Identification of Anoikis-Related Subgroups and Prognosis Model in Liver Hepatocellular Carcinoma

Disparities in hepatocellular carcinoma incidence among Hispanic and non-Hispanic adults in Arizona: Trends between 2009-2017

ATP6V1C1, associated with the tumor microenvironment and mTORC1 signaling pathway, is a potential diagnostic, prognostic, and therapeutic biomarker for hepatocellular carcinoma

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