A macrophage related signature for predicting prognosis and drug sensitivity in ovarian cancer based on integrative machine learning

BMC Medical Genomics, Journal Year: 2023, Volume and Issue: 16(1)

Published: Oct. 2, 2023

Abstract Background Ovarian cancer ranks the leading cause of gynecologic cancer-related death in United States and fifth most common mortality among American women. Increasing evidences have highlighted vital role macrophages M2/M1 proportion tumor progression, prognosis immunotherapy. Methods Weighted gene co-expression network analysis (WGCNA) was performed to identify related markers. Integrative procedure including 10 machine learning algorithms were develop a prognostic macrophage signature (MRS) with TCGA, GSE14764, GSE140082 datasets. The MRS microenvironment (TME) therapy response evaluated data CIBERSORT, MCPcounter, QUANTISEQ, XCELL, CIBERSORT-ABS, TIMER EPIC, GSE91061 IMvigor210 dataset. Results optimal developed by combination CoxBoost StepCox[forward] algorithm served as an independent risk factor ovarian cancer. Compared stage, grade other established signatures, current had better performance predicting overall survival rate patients. Low score indicated higher TME score, level immune cells, immunophenoscore, mutational burden, lower TIDE IC50 value prediction nomogram good potential for clinical application 1-, 3-, 5-year Conclusion All all, study constructed powerful patients using algorithms. This could predict drug sensitivity

Language: Английский

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Identification of GUCA2A and COL3A1 as prognostic biomarkers in colorectal cancer by integrating analysis of RNA-Seq data and qRT-PCR validation

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Oct. 10, 2023

Abstract By 2030, it is anticipated that there will be 2.2 million new instances of colorectal cancer worldwide, along with 1.1 yearly deaths. Therefore, critical to develop novel biomarkers could help in CRC early detection. We performed an integrated analysis four RNA-Seq data sets and TCGA datasets this study find for diagnostic, prediction, as potential therapeutic malignancy, well determine the molecular mechanisms carcinogenesis. Four were downloaded from Sequence Read Archive (SRA) database. The metaSeq package was used integrate differentially expressed genes (DEGs). protein–protein interaction (PPI) network DEGs constructed using string platform, hub identified cytoscape software. gene ontology KEGG pathway enrichment enrichR package. Gene diagnostic sensitivity its association clinicopathological characteristics demonstrated by statistical approaches. qRT-PCR, GUCA2A COL3A1 examined colon rectal cancer. 5037 genes, including (4752 upregulated, 285 downregulated) across studies between normal tissues. analyses showed highest proportion up-regulated involved RNA binding transport. Integral component plasma membrane mineral absorption pathways containing down-regulated DEGs. Similar expression patterns seen qRT-PCR analysis. Additionally, may play a significant role development CRC.

Language: Английский

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Cellular and Molecular Mechanisms of the Tumor Stroma in Colorectal Cancer: Insights into Disease Progression and Therapeutic Targets

Biomedicines, Journal Year: 2023, Volume and Issue: 11(9), P. 2361 - 2361

Published: Aug. 23, 2023

Colorectal cancer (CRC) is a major health burden worldwide and the third most common type of cancer. The early detection diagnosis CRC critical to improve patient outcomes. This review explores intricate interplay between tumor microenvironment, stromal interactions, progression metastasis colorectal begins by assessing gut microbiome’s influence on development, emphasizing its association with gut-associated lymphoid tissue (GALT). role Wnt signaling pathway in stroma scrutinized, elucidating impact disease progression. Tumor budding, effect stroma, implications for prognosis are investigated. also identifies conserved oncogenic signatures (COS) within their potential as therapeutic targets. Lastly, seed soil hypothesis employed contextualize metastasis, accentuating significance both cells surrounding metastatic propensity. highlights interdependence providing valuable insights into prospective approaches targeting tumor–stroma interactions.

Language: Английский

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SG-Transunet: A segmentation-guided Transformer U-Net model for KRAS gene mutation status identification in colorectal cancer

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 173, P. 108293 - 108293

Published: March 20, 2024

Language: Английский

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S1PR1 suppresses lung adenocarcinoma progression through p-STAT1/miR-30c-5 p/FOXA1 pathway

Journal of Experimental & Clinical Cancer Research, Journal Year: 2024, Volume and Issue: 43(1)

Published: Nov. 18, 2024

Abstract Background Sphingosine-1-phosphate receptor 1 (S1PR1) is considered to be closely related a variety of malignant tumors, but the role and mechanism S1PR1 in lung adenocarcinoma are not fully understood. In this study, we aim explore downstream signaling pathways biological functions (LUAD). Methods Bioinformatics analysis, RT-qPCR, western blot immunohistochemistry (IHC) were was used investigate expression LUAD. The prognosis also analyzed. CCK-8 assay, colony formation scratch transwell migration invasion cell adhesion assay performed examine effect on RNA sequencing employed analyze DEGs LUAD cells overexpressing S1PR1. Enrichment pathway analysis using KEGG, GO, GSEA conducted predict potential targets. chromatin immunoprecipitation (ChIP) dual luciferase reporter verify direct regulation between FOXA1 target genes. Then overexpression functional rescue experiments. miRNA-30c-5p identified as microRNA regulating by assay. detected clarify specific regulates miR-30c-5p. Results significantly decreased positively correlated with prognosis. Overexpression inhibits proliferation, migration, function suppressing COL5A1, MMP1, SERPINE1. key transcription factor COL5A1 through p-STAT1/miR-30c-5p, thereby cells. Conclusions downregulated LUAD, which inhibiting MMP1 SERPINE1 p-STAT1/miR-30c-5p/FOXA1 pathway.

Language: Английский

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Combined High—Throughput Proteomics and Random Forest Machine-Learning Approach Differentiates and Classifies Metabolic, Immune, Signaling and ECM Intra-Tumor Heterogeneity of Colorectal Cancer

Cells, Journal Year: 2024, Volume and Issue: 13(16), P. 1311 - 1311

Published: Aug. 6, 2024

Colorectal cancer (CRC) is a frequent, worldwide tumor described for its huge complexity, including inter-/intra-heterogeneity and microenvironment (TME) variability. Intra-tumor heterogeneity connections with metabolic reprogramming epithelial-mesenchymal transition (EMT) were investigated explorative shotgun proteomics complemented by Random Forest (RF) machine-learning approach. Deep superficial regions distant-site non-tumor samples from the same patients (n = 16) analyzed. Among 2009 proteins analyzed, 91 proteins, 23 novel potential CRC hallmarks, showed significant quantitative changes. In addition, 98.4% accurate classification of three analyzed tissues was obtained RF using set 21 proteins. Subunit E1 2-oxoglutarate dehydrogenase (OGDH-E1) best classifying factor region, while sorting nexin-18 coatomer-beta protein (beta-COP), implicated in trafficking, classified deep region. Down- up-regulations checkpoints involved different tumors. Analogously to immune affecting TME, cytoskeleton extracellular matrix (ECM) dynamics crucial EMT. Galectin-3, basigin, S100A9, fibronectin TME-CRC-ECM crosstalk found be differently variated both regions. Different strategies appeared adopted two uncouple Krebs cycle cytosolic glucose metabolism, promote lipogenesis, amino acid synthesis, down-regulate bioenergetics mitochondria, up-regulate oxidative stress. Finally, correlations Dukes stage budding supported finding hallmarks therapeutic targets.

Language: Английский

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Tumor Heterogeneity in Gastrointestinal Cancer based on Multimodal Data Analysis

Published: Aug. 14, 2024

The abstract should be a total of about 250 words and structured to contain the following headings: Background/Objectives, Methods, Results, Conclusions. Background/Objectives: Place question addressed in broad context highlight purpose study; Methods: Describe briefly main methods or treatments applied. Include any relevant preregistration numbers, species strains animals used; Results: Summarize article’s findings; Conclusions: Indicate conclusions interpretations. an objective representation article: it must not results which are presented substantiated text exaggerate conclusions. Clinical trial abstracts include items that CONSORT group has identified as essential.

Language: Английский

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Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis

Heliyon, Journal Year: 2023, Volume and Issue: 9(8), P. e18869 - e18869

Published: Aug. 1, 2023

Preoperative radiochemotherapy is a promising therapeutic method for locally advanced rectal cancer patients. However, the response of colorectal (CRC) patients to preoperative radiotherapy varies widely. In this study, we aimed identify novel biomarkers that could predict tumors treatment using systems biology approach. We applied Weighted Gene Co-Expression Network Analysis construct co-expression networks and evaluated correlation these with radiation module-trait relationship. then identified hub genes related transcription factors in selected module. Our analysis seven constructed modules revealed one module, which contained 113 nodes 6066 edges, had strongest effects on CRC (correlation = 0.85; p-value 6e-7). By analyzing module CytoHubba plugin, four genes, including ZEB2, JAM2, NDN, PPAP2A. also important factors, KLF4, SUZ12, TCF4, NANOG, POU5F1, SOX2, SMARCA4, may play essential roles regulating genes. summary, our findings suggest PPAP2A, along be associated chemoradiotherapy.

Language: Английский

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Potential biomarkers: The hypomethylation of cg18949415 and cg22193385 sites in colon adenocarcinoma

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 169, P. 107884 - 107884

Published: Dec. 22, 2023

Language: Английский

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Assessing the impact of green and roasted coffee extracts on colorectal cancer cells in a 3D cell culture model

Phytomedicine Plus, Journal Year: 2024, Volume and Issue: 4(3), P. 100599 - 100599

Published: June 13, 2024

Colorectal cancer (CRC) is one of the most common and deadly malignant neoplasms worldwide. It associated with multiple lifestyle risk factors such as poor diet, physical inactivity, alcohol red meat consumption, smoking, obesity. Consequently, studies have been conducted on protective activity bioactive compounds present in some foods against CRC, making it necessary to understand how diet can affect human health. In this sense, coffee, second consumed beverage world, a major source phytochemicals possible antitumor effect CRC cells. This study aimed analyze chemopreventive potential green roasted coffee extracts HT-29 cells cultured 2D 3D models. Flow cytometry was employed quantify propidium iodide DiOC6 uptake, ROS production, phosphatidylserine exposure, cell cycle progression. addition, spheroids were analyzed by light microscopy identify morphological changes. The results showed that, under conditions, treatment both had concentration-dependent cytotoxic effect. Decreased viability mitochondrial membrane hyperpolarization, prooxidant effect, increased changes G1 phase cycle. For evaluated markers, cultures required higher doses achieve significant effects when compared monolayer cultures. Since favor formation complex cell–cell interactions, model offers closer look at vivo conditions for evaluating toxicity preclinical efficacy agents CRC. experimental evidence from supports 3R principles replacement, reduction, refinement toxicological research pharmaceutical industry.

Language: Английский

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