Genomic and transcriptomic profiling of hepatoid adenocarcinoma of the stomach

Liu, Ziyang; Wang, Anqiang; Pu, Yonglin; Li, Zhongwu; Xue, Ruidong; Zhang, Chong; Xiang, Xiao; Jian‐Yu, E; Bu, Zhaode; Bai, Fan; Ji, Jiafu

doi:10.1038/s41388-021-01976-2

Cited by 26 publications

(33 citation statements)

References 70 publications

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“…We also established a nomogram according to the RS and GC stage and followed the nomogram was verified to have a well performance in predicting patients' OS. Reviewing the 12 NFMGs, GUCY1A2 has been reported to be an independent prognostic marker for GC [ 63 ]; single-cell RNA sequencing on gastric hepatoid adenocarcinoma indicated that AHCY may be potential targets for its treatment [ 64 ]; MTHFD2 -encoded key enzyme in folate metabolism and methyl donor SAM production and its knockdown significantly suppressed GC cell proliferation [ 65 ]; ADCY3 -encoded protein may exert its tumor-promoting effects via the cAMP/PKA/CREB pathway [ 66 ]; POLR1A has also been identified to be associated with prognosis in GC [ 62 ]; NRP1 -encoded protein could accelerate cell proliferation, invasion, and migration in GC [ 67 , 68 ]. The rest involved genes, including POLR3K , POLR3A , ITPA , POLA1 , CHDH , and SRM , have not been reported in GC, providing multiple research objectives for exploring the underlying mechanisms of NF- κ B-mediated metabolism.…”

Section: Discussionmentioning

confidence: 99%

NF-κB-Related Metabolic Gene Signature Predicts the Prognosis and Immunotherapy Response in Gastric Cancer

Chen

et al. 2022

BioMed Research International

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Background. Sufficient evidence indicated the crucial role of NF-κB family played in gastric cancer (GC). The novel discovery that NF-κB could regulate cancer metabolism and immune evasion greatly increased its attraction in cancer research. However, the correlation among NF-κB, metabolism, and cancer immunity in GC still requires further improvement. Methods. TCGA, hTFtarget, and MSigDB databases were employed to identify NF-κB-related metabolic genes (NFMGs). Based on NFMGs, we used consensus clustering to divide GC patients into two subtypes. GSVA was employed to analyze the enriched pathway. ESTIMATE, CIBERSORT, ssGSEA, and MCPcounter algorithms were applied to evaluate immune infiltration in GC. The tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict patients’ response to immunotherapy. We also established a NFMG-related risk score by using the LASSO regression model and assessed its efficacy in TCGA and GSE62254 datasets. Results. We used 27 NFMGs to conduct an unsupervised clustering on GC samples and classified them into two clusters. Cluster 1 was characterized by high active metabolism, tumor mutant burden, and microsatellite instability, while cluster 2 was featured with high immune infiltration. Compared to cluster 2, cluster 1 had a better prognosis and higher response to immunotherapy. In addition, we constructed a 12-NFMG (ADCY3, AHCY, CHDH, GUCY1A2, ITPA, MTHFD2, NRP1, POLA1, POLR1A, POLR3A, POLR3K, and SRM) risk score. Followed analysis indicated that this risk score acted as an effectively prognostic factor in GC. Conclusion. Our data suggested that GC subtypes classified by NFMGs may effectively guide prognosis and immunotherapy. Further study of these NFMGs will deepen our understanding of NF-κB-mediated cancer metabolism and immunity.

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Section: Discussionmentioning

confidence: 99%

NF-κB-Related Metabolic Gene Signature Predicts the Prognosis and Immunotherapy Response in Gastric Cancer

Chen

et al. 2022

BioMed Research International

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“…Studies show that NKT cells are abundant in gastric cancer tissue with matured tertiary lymphoid structures, whereas CTLs are abundant in tumor tissue lacking lymphoid structures, suggesting that CTLs may be the earlier effectors, but NKTs may have a greater role later in orchestrating antitumor immune cells. A study that examined the CTLs within a rare type of gastric cancer, hepatoid adenocarcinoma of the stomach, found the CTLs with an exhausted phenotype; therefore, NKT cells may be more capable of long-standing cytotoxic effector function (25). There was also an enrichment in exhausted CTLs in patients with metastatic compared to non-metastatic gastric cancer correlating with worse survival outcomes (34).…”

Section: T Cellsmentioning

confidence: 99%

“…The program inferCNV, available through the Broad Institute, has been used by several groups to identify copy number alterations of malignant cells within scRNAseq data (18,21,22,44,45,124,137). Many other programs are also useful to estimate chromosomal alterations within cancer scRNAseq datasets, viz., LIAYSON, 10X supported VarTrix, GISTIC2, CopyKAT, and Mutect2 (23,25,44,55,(125)(126)(127). ABSOLUTE can be used to infer intratumoral heterogeneity (28,128,138).…”

Section: Tools For Analyzing Gastric Cancer Scrnaseq Datamentioning

confidence: 99%

“…As well, the TIMER tool is a comprehensive resource designed to analyze immune cell infiltrates across diverse cancer subtypes (139). The TCGA has a publicly available human stomach adenocarcinoma (STAD) dataset containing clinical annotations along with molecular profiles that were utilized as a reference or primary dataset in several studies (25,28,36,37,41,45,133). FirebrowseR, also generated by the Broad Institute, is a database which provides access to the PanCanAtlas, containing conserved cancer gene expression data (134).…”

Section: Tools For Analyzing Gastric Cancer Scrnaseq Datamentioning

confidence: 99%

“…Among the published scRNAseq gastric cancer works, it is apparent that they have undertaken various approaches to their studies. Most groups obtained primary gastric cancer tissues from patients to generate scRNAseq data (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35). Some utilized previously published primary tumor datasets for further analysis (36)(37)(38)(39)(40)(41)(42)(43).…”

Section: Introductionmentioning

confidence: 99%

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Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing

Hoft

Pherson²,

DiPaolo³

2022

Front. Immunol.

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Single-cell RNA sequencing (scRNAseq) technology is still relatively new in the field of gastric cancer immunology but gaining significant traction. This technology now provides unprecedented insights into the intratumoral and intertumoral heterogeneities at the immunological, cellular, and molecular levels. Within the last few years, a volume of publications reported the usefulness of scRNAseq technology in identifying thus far elusive immunological mechanisms that may promote and impede gastric cancer development. These studies analyzed datasets generated from primary human gastric cancer tissues, metastatic ascites fluid from gastric cancer patients, and laboratory-generated data from in vitro and in vivo models of gastric diseases. In this review, we overview the exciting findings from scRNAseq datasets that uncovered the role of critical immune cells, including T cells, B cells, myeloid cells, mast cells, ILC2s, and other inflammatory stromal cells, like fibroblasts and endothelial cells. In addition, we also provide a synopsis of the initial scRNAseq findings on the interesting epithelial cell responses to inflammation. In summary, these new studies have implicated roles for T and B cells and subsets like NKT cells in tumor development and progression. The current studies identified diverse subsets of macrophages and mast cells in the tumor microenvironment, however, additional studies to determine their roles in promoting cancer growth are needed. Some groups specifically focus on the less prevalent ILC2 cell type that may contribute to early cancer development. ScRNAseq analysis also reveals that stromal cells, e.g., fibroblasts and endothelial cells, regulate inflammation and promote metastasis, making them key targets for future investigations. While evaluating the outcomes, we also highlight the gaps in the current findings and provide an assessment of what this technology holds for gastric cancer research in the coming years. With scRNAseq technology expanding rapidly, we stress the need for periodic review of the findings and assess the available scRNAseq analytical tools to guide future work on immunological mechanisms of gastric carcinogenesis.

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Clinicopathological features of hepatoid adenocarcinoma and non‐hepatoid adenocarcinoma of the stomach: A systematic review and meta‐analysis

Ling,

Liu,

Huang

et al. 2024

Cancer Medicine

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BackgroundHepatoid adenocarcinoma of the stomach (HAS) is an extremely rare and unique malignant gastric tumor with a significantly worse prognosis than non‐hepatoid adenocarcinoma of the stomach (non‐HAS). The present study explored the clinicopathological features of HAS and non‐HAS patients to provide insights into HAS treatment strategies.MethodsFrom December 26, 2023, we performed a comprehensive search of the PubMed, Web of Science, Cochrane Library, and Embase.com databases for relevant studies. Two authors independently screened the studies, evaluated their quality, extracted data, and performed the analyses. This study was registered with PROSPERO on January 2, 2024.ResultsNine retrospective studies were included for analysis after screening 833 articles. A total of 350 and 924 patients were enrolled in the HAS and non‐HAS groups, respectively. While no significant differences were observed in age, sex, tumor size, T3 or T4 stage, and N2 or N3 stage between the two groups, the HAS group exhibited higher rates of lymph node metastasis (OR = 1.93, 95% CI: 1.19–3.13, p = 0.007), liver metastasis (OR = 3.45, 95% CI: 2.26–5.28, p < 0.001), and vascular invasion (OR = 2.76, 95% CI: 2.05–3.71, p < 0.001). Additionally, the HAS group had lower 3‐year survival rates (HR = 2.35, 95% CI: 1.70–3.25, p < 0.001) and 5‐year survival rates (HR = 3.63, 95% CI: 1.49–8.88, p = 0.005), but lower rates of lymphatic permeation (OR = 0.68, 95% CI: 0.47–0.99, p = 0.040).ConclusionBased on the current clinical evidence, patients with HAS present distinct clinicopathological features, greater invasiveness, and poorer prognosis than non‐HAS patients. Further research is warranted to develop optimal treatment strategies for HAS.

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Genomic and transcriptomic profiling of hepatoid adenocarcinoma of the stomach

Cited by 26 publications

References 70 publications

NF-κB-Related Metabolic Gene Signature Predicts the Prognosis and Immunotherapy Response in Gastric Cancer

NF-κB-Related Metabolic Gene Signature Predicts the Prognosis and Immunotherapy Response in Gastric Cancer

Discovering Immune-Mediated Mechanisms of Gastric Carcinogenesis Through Single-Cell RNA Sequencing

Clinicopathological features of hepatoid adenocarcinoma and non‐hepatoid adenocarcinoma of the stomach: A systematic review and meta‐analysis

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