Integrated Multi-Omics Landscape of Liver Metastases

Yang, Shuai; Qian, Ling; Li, Zhixuan; Li, Ye; Bai, Jian; Zheng, Bo; Chen, Kun; Qiu, Xinyao; Cai, Guoxiang; Wang, Shan; Huang, Haiyan; Wu, Jianmin; Zhu, Yanjing; Zhangyang, Qianwen; Feng, Long-Hai; Wu, Tong; Wu, Rui; Yang, Aixia; Wang, Kaiting; Wang, Ruiru; Zhang, Yani; Zhao, Yan; Wang, Wenwen; Bao, Jinxia; Shen, Siyun; Hu, Ji; Wu, Xuan; Zhou, Tao; Meng, Zhiqiang; Liu, Weiwei; Wang, Hongyang; Wang, Peng; Chen, Lei

doi:10.1053/j.gastro.2022.11.029

Cited by 37 publications

(34 citation statements)

References 60 publications

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“…Yang et al. ( 39 ) used a collection of 50 primary liver cancers and 100 liver metastases to explore tumor immune microenvironment and found that SLC2A1 showed a negative correlation with T cell infiltration. Additionally, Fang et al.…”

Section: Discussionmentioning

confidence: 99%

Prediction of liver cancer prognosis based on immune cell marker genes

Liu

et al. 2023

Front. Immunol.

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IntroductionMonitoring the response after treatment of liver cancer and timely adjusting the treatment strategy are crucial to improve the survival rate of liver cancer. At present, the clinical monitoring of liver cancer after treatment is mainly based on serum markers and imaging. Morphological evaluation has limitations, such as the inability to measure small tumors and the poor repeatability of measurement, which is not applicable to cancer evaluation after immunotherapy or targeted treatment. The determination of serum markers is greatly affected by the environment and cannot accurately evaluate the prognosis. With the development of single cell sequencing technology, a large number of immune cell-specific genes have been identified. Immune cells and microenvironment play an important role in the process of prognosis. We speculate that the expression changes of immune cell-specific genes can indicate the process of prognosis.MethodTherefore, this paper first screened out the immune cell-specific genes related to liver cancer, and then built a deep learning model based on the expression of these genes to predict metastasis and the survival time of liver cancer patients. We verified and compared the model on the data set of 372 patients with liver cancer.ResultThe experiments found that our model is significantly superior to other methods, and can accurately identify whether liver cancer patients have metastasis and predict the survival time of liver cancer patients according to the expression of immune cell-specific genes.DiscussionWe found these immune cell-specific genes participant multiple cancer-related pathways. We fully explored the function of these genes, which would support the development of immunotherapy for liver cancer.

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Section: Discussionmentioning

confidence: 99%

Prediction of liver cancer prognosis based on immune cell marker genes

Liu

et al. 2023

Front. Immunol.

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“…SLC2A1, a hypoxia-related molecule, has been identified as a critical regulator of the immunosuppressive microenvironment in metastatic liver cancer via modulation of the chemotaxis of SPP1-expressing TAMs [ 99 ]. SPP1-expressing TAMs are suggested to influence the endothelial–mesenchymal transition, generating a subpopulation of protumor CAFs, and this cell-to-cell communication might be mediated by the SPP1/CD44 axis [ 100 ].…”

Section: Significance Of Spp1 Expression In Tams In Malignant Tumors ...mentioning

confidence: 99%

The Significance of SPP1 in Lung Cancers and Its Impact as a Marker for Protumor Tumor-Associated Macrophages

Matsubara

Yano

Pan

et al. 2023

Cancers

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Macrophages are a representative cell type in the tumor microenvironment. Macrophages that infiltrate the cancer microenvironment are referred to as tumor-associated macrophages (TAMs). TAMs exhibit protumor functions related to invasion, metastasis, and immunosuppression, and an increased density of TAMs is associated with a poor clinical course in many cancers. Phosphoprotein 1 (SPP1), also known as osteopontin, is a multifunctional secreted phosphorylated glycoprotein. Although SPP1 is produced in a variety of organs, at the cellular level, it is expressed on only a few cell types, such as osteoblasts, fibroblasts, macrophages, dendritic cells, lymphoid cells, and mononuclear cells. SPP1 is also expressed by cancer cells, and previous studies have demonstrated correlations between levels of circulating SPP1 and/or increased SPP1 expression on tumor cells and poor prognosis in many types of cancer. We recently revealed that SPP1 expression on TAMs is correlated with poor prognosis and chemoresistance in lung adenocarcinoma. In this review, we summarize the significance of TAMs in lung cancers and discuss the importance of SPP1 as a new marker for the protumor subpopulation of monocyte-derived TAMs in lung adenocarcinoma. Several studies have shown that the SPP1/CD44 axis contribute to cancer chemoresistance in solid cancers, so the SPP1/CD44 axis may represent one of the most critical mechanisms for cell-to-cell communication between cancer cells and TAMs.

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“…Second, the protein abundances of primary TAMs are reduced continuously in tissue dissociation and FACS processing, which are the necessary steps of TAM collection. Third, the comparison between TAMs and their precursor cells from individual mice but not from pooled samples is important, not only because independent-complete biological repetitions are essential to acquire objective results but also because paired comparison could reduce the effect of the individual difference, which may conceal cross-organ communication and individual-specific systemic regulation. − Together, the difficulties mentioned above prompt us to rethink what experimental workflow should be designed to conduct a comprehensive proteomics analysis of TAMs and their precursor cells in tumor progression.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Proteomics Analysis Reveals Dynamic Phenotypes of Tumor-Associated Macrophages and Their Precursor Cells in Tumor Progression

Liu,

Liu

et al. 2024

J. Proteome Res.

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Tumor-associated macrophages (TAMs) are key regulators in tumor progression, but the precise role of bone marrow-derived monocytes (Mons) as TAM precursors and their dynamic phenotypes regulated by the tumor microenvironment (TME) remain unclear. Here, we developed an optimized microproteomics workflow to analyze lowcell-number mouse myeloid cells. We sorted TAMs and their corresponding Mons (1 × 10 5 per sample) from individual melanoma mouse models at both the early and late stages. We established the protein expression profiles for these cells by mass spectrometry. Subsequently, we analyzed the dynamics phenotypes of TAMs and identified a characteristic protein expression profile characterized by upregulated cholesterol metabolism and downregulated immune responses during tumor progression. Moreover, we found the downregulation of both STAT5 and PYCARD expression not only in late-stage TAMs but also in late-stage Mons, indicating a loss of the ability to induce inflammatory responses prior to Mons infiltration into TME. Taken together, our study provides valuable insights into the progression-dependent transitions between TAMs and their precursor cells, as well as the cross-organ communications of tumor and bone marrow.

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Integrated Multi-Omics Landscape of Liver Metastases

Cited by 37 publications

References 60 publications

Prediction of liver cancer prognosis based on immune cell marker genes

Prediction of liver cancer prognosis based on immune cell marker genes

The Significance of SPP1 in Lung Cancers and Its Impact as a Marker for Protumor Tumor-Associated Macrophages

Comprehensive Proteomics Analysis Reveals Dynamic Phenotypes of Tumor-Associated Macrophages and Their Precursor Cells in Tumor Progression

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