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A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

ABSTRACT: Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2⁺ macrophages, exhausted CD8⁺ T cells, tolerant CD8⁺ T cells, exhausted CD4⁺ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2⁺ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

SUBMITTER: Bao X

PROVIDER: S-EPMC10897549 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Bao Xuanwen X Li Qiong Q Chen Dong D Dai Xiaomeng X Liu Chuan C Tian Weihong W Zhang Hangyu H Jin Yuzhi Y Wang Yin Y Cheng Jinlin J Lai Chunyu C Ye Chanqi C Xin Shan S Li Xin X Su Ge G Ding Yongfeng Y Xiong Yangyang Y Xie Jindong J Tano Vincent V Wang Yanfang Y Fu Wenguang W Deng Shuiguang S Fang Weijia W Sheng Jianpeng J Ruan Jian J Zhao Peng P

Cell reports. Medicine 20240201 2

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2<sup>+</sup> macrophages, exhausted CD8 ...[more]

PMID: 38307032

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Project description:IntroductionUlcerative colitis [UC] is a chronic disease with rising incidence and unclear aetiology. Deep molecular phenotyping by multiomics analyses may provide novel insights into disease processes and characteristic features of remission states.MethodsUC pathomechanisms were assessed by proteome profiling of human tissue specimens, obtained from five distinct colon locations for each of the 12 patients included in the study. Systemic disease-associated alterations were evaluated thanks to a cross-sectional setting of mass spectrometry-based multiomics analyses comprising proteins, metabolites, and eicosanoids of plasma obtained from UC patients during acute episodes and upon remission, in comparison with healthy controls.ResultsTissue proteome profiling indicated colitis-associated activation of neutrophils, macrophages, B and T cells, fibroblasts, endothelial cells and platelets, and hypoxic stress, and suggested a general downregulation of mitochondrial proteins accompanying the establishment of apparent wound healing-promoting activities including scar formation. Whereas pro-inflammatory proteins were apparently upregulated by immune cells, the colitis-associated epithelial cells, fibroblasts, endothelial cells, and platelets seemed to predominantly contribute anti-inflammatory and wound healing-promoting proteins. Blood plasma proteomics indicated chronic inflammation and platelet activation, whereas plasma metabolomics identified disease-associated deregulations of gut and gut microbiome-derived metabolites. Upon remission several, but not all, molecular candidate biomarker levels recovered back to normal.ConclusionThe findings may indicate that microvascular damage and platelet deregulation hardly resolve upon remission, but apparently persist as disease-associated molecular signatures. This study presents local and systemic molecular alterations integrated in a model for UC pathomechanisms, potentially supporting the assessment of disease and remission states in UC patients.

Project description:BackgroundMutations in KRAS and BRAF genes are prevalent in colorectal cancer (CRC), which strikingly promote tumorigenesis and lead to poor response to a variety of treatments including immunotherapy by activating the MAPK/ERK pathway. Thus, there is an urgent need to discover effective therapeutic targets and strategies.MethodsCRISPR-Cas9 lentiviral knockout library was used to screen the suppressors of anti-PD1 immunotherapy. Bioinformatic analysis was used to analyze the correlation between PHF8 expression and immune indicators in CRC. In vitro and in vivo experiments were utilized to determine the effects of PHF8 on the immune indexes and malignant phenotypes of CRC cells. qRT-PCR, western blotting, immunohistochemical (IHC) staining, and chromatin immunoprecipitation (ChIP)-qPCR assays were used to determine the regulatory effects of PHF8 on PD-L1, KRAS, BRAF, and c-Myc and the regulatory effect c-Myc/miR-22-3p signaling axis on PHF8 expression in CRC cells.ResultsThis study identified histone lysine demethylase PHF8 as a negative regulator for the efficacy of anti-PD1 therapy and found that it was highly expressed in CRCs and strongly associated with poor patient survival. Functional studies showed that PHF8 played an oncogenic role in KRAS- or BRAF-mutant CRC cells, but not in wild-type ones. Mechanistically, PHF8 up-regulated the expression of PD-L1, KRAS, BRAF, and c-Myc by increasing the levels of transcriptional activation marks H3K4me3 and H3K27ac and decreasing the levels of transcriptional repression mark H3K9me2 within their promoter regions, promoting immune escape and tumor progression. Besides, our data also demonstrated that PHF8 was up-regulated by the c-Myc/miR-22-3p signaling axis to form a positive feedback loop. Targeting PHF8 substantially improved the efficacy of anti-PD1 therapy and inhibited the malignant phenotypes of KRAS- or BRAF-mutant CRC cells.ConclusionOur data demonstrate that PHF8 may be an effective therapeutic target for KRAS- or BRAF-mutant CRCs.

Dataset Information

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Publications

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

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