Nature Protocols, Journal Year: 2023, Volume and Issue: 18(8), P. 2404 - 2414
Published: June 30, 2023
Language: Английский
Cell, Journal Year: 2024, Volume and Issue: 187(9), P. 2324 - 2335.e19
Published: April 1, 2024
Microbial communities are resident to multiple niches of the human body and important modulators host immune system responses anticancer therapies. Recent studies have shown that complex microbial present within primary tumors. To investigate presence relevance microbiome in metastases, we integrated mapping assembly-based metagenomics, genomics, transcriptomics, clinical data 4,160 metastatic tumor biopsies. We identified organ-specific tropisms microbes, enrichments anaerobic bacteria hypoxic tumors, associations between diversity tumor-infiltrating neutrophils, association Fusobacterium with resistance checkpoint blockade (ICB) lung cancer. Furthermore, longitudinal sampling revealed temporal evolution depleted upon ICB. Together, generated a pan-cancer resource may contribute advancing treatment strategies.
Language: Английский
Citations
52
Molecular Cell, Journal Year: 2024, Volume and Issue: 84(2), P. 261 - 276.e18
Published: Jan. 1, 2024
A hallmark of high-risk childhood medulloblastoma is the dysregulation RNA translation. Currently, it unknown whether dysregulates translation putatively oncogenic non-canonical open reading frames (ORFs). To address this question, we performed ribosome profiling 32 tissues and cell lines observed widespread ORF We then developed a stepwise approach using multiple CRISPR-Cas9 screens to elucidate ORFs putative microproteins implicated in survival. determined that lncRNA-ORFs upstream (uORFs) exhibited selective functionality independent main coding sequences. microprotein encoded by one these ORFs, ASNSD1-uORF or ASDURF, was upregulated, associated with MYC-family oncogenes, promoted survival through engagement prefoldin-like chaperone complex. Our findings underscore fundamental importance provide rationale include future studies seeking define new cancer targets.
Language: Английский
Citations
36
Computational and Structural Biotechnology Journal, Journal Year: 2024, Volume and Issue: 23, P. 2798 - 2810
Published: June 29, 2024
The widespread use of high-throughput sequencing technologies has revolutionized the understanding biology and cancer heterogeneity. Recently, several machine-learning models based on transcriptional data have been developed to accurately predict patients' outcome clinical response. However, an open-source R package covering state-of-the-art algorithms for user-friendly access yet be developed. Thus, we proposed a flexible computational framework construct machine learning-based integration model with elegant performance (Mime). Mime streamlines process developing predictive high accuracy, leveraging complex datasets identify critical genes associated prognosis. An in silico combined de novo PIEZO1-associated signatures constructed by demonstrated accuracy predicting outcomes patients compared other published models. Furthermore, could also precisely infer immunotherapy response applying different Mime. Finally, SDC1 selected from potential as glioma target. Taken together, our provides solution constructing will greatly expanded provide valuable insights into current fields. is available GitHub (https://github.com/l-magnificence/Mime).
Language: Английский
Citations
18
Blood, Journal Year: 2024, Volume and Issue: 144(20), P. 2121 - 2135
Published: Aug. 22, 2024
Language: Английский
Citations
17
Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 15
Published: Jan. 17, 2025
Disulfidptosis is a newly discovered form of cell death associated with tumorigenesis, particularly under oxidative stress and metabolic disorder conditions. Currently, the biological mechanisms disulfidptosis-related genes (DRGs) in head neck squamous carcinoma (HNSCC) remain unclear. The study includes sections on methodologies, data sources, clinical collection, subtype establishment, identification analysis differentially expressed genes, genetic variation, construction validation DRG prognostic model. Various analyses are conducted, including relationship between risk scores model clinicopathological features, immune status, checkpoints, tumor mutational burden (TMB), microsatellite instability (MSI), ESTIMATE, mRNAsi, drug sensitivity. also covers single-cell DNA methylation DRGs, prediction potential microRNA long non-coding RNA target genes. Prognostic DRGs expression HNSCC validated through RT-qPCR immunohistochemistry. model's predictive capability confirmed using external cohorts from GEO datasets tissue samples. role DSTN further gene knockout experiments. We identified four valuable (SLC3A2, NUBPL, ACTB, DSTN) constructed model, along identifying two DRG-related subtypes. Analysis score revealed that low-risk group had better prognosis compared to high-risk group. Significant correlations were found immunotherapy response, sensitivity, related epigenetic modifications. Low-risk patients as beneficiaries checkpoint inhibitor (ICI) therapy. A regulatory axis involving DSTN, hsa-miR-181c-5p, LUCAT1, IGFL2-AS1 was for HNSCC. IHC upregulation demonstrated excellent performance patients. Additionally, significantly overexpressed cells; its knockdown inhibited proliferation, migration, invasion. effectively predicts outcomes, promotes growth, inhibits
Language: Английский
Citations
3
Computational and Structural Biotechnology Journal, Journal Year: 2020, Volume and Issue: 18, P. 2851 - 2859
Published: Jan. 1, 2020
Extracellular vesicles (EVs) are complex ecosystems that can be derived from all body cells and circulated in the fluids. Characterizing tissue-cellular source contributing to circulating EVs provides biological information about cell or tissue of origin their functional states. However, relative proportion fluid has not been thoroughly characterized. Here, we developed an approach for digital quantification, called EV-origin, enables enumerating contribution plasma extracellular long RNA sequencing profiles. EV-origin was constructed by input matrix gene expression signatures robust deconvolution algorithm, collectively used separate proportions each type interest. respectively predicted enrichment seven types hemopoietic sixteen solid subsets exLR-seq profile. Using approach, depicted integrated landscape traceability system healthy individuals. We also compared heterogenous components samples with diverse disease status. Notably, aberrant liver fraction could reflect development progression hepatic disease. The serve as a diagnostic indicator effectively HCC patients normal decipher heterogeneity EVs. Our inform exLR-based applications liquid biopsy.
Language: Английский
Citations
132
Cancer Cell International, Journal Year: 2021, Volume and Issue: 21(1)
Published: Oct. 20, 2021
Cancer-associated fibroblasts (CAFs) contribute notably to colorectal cancer (CRC) tumorigenesis, stiffness, angiogenesis, immunosuppression and metastasis, could serve as a promising therapeutic target. Our purpose was construct CAF-related prognostic signature for CRC.We performed bioinformatics analysis on single-cell transcriptome data derived from Gene Expression Omnibus (GEO) identified 208 differentially expressed cell markers cluster. Bulk gene expression of CRC obtained The Cancer Genome Atlas (TCGA) GEO databases. Univariate Cox regression least absolute shrinkage operator (LASSO) analyses were TCGA training cohort (n = 308) model construction, validated in validation 133), total 441), GSE39582 470) GSE17536 177) datasets. Microenvironment Cell Populations-counter (MCP-counter) Estimate the Proportion Immune cells (EPIC) methods applied evaluated CAFs infiltrations bulk data. Real-time polymerase chain reaction (qPCR) tissue microarrays containing 80 colon samples further validate value CAF model. pRRophetic Tumor Dysfunction Exclusion (TIDE) algorithms utilized predict chemosensitivity immunotherapy response. Human Protein (HPA) databases immunohistochemistry used evaluate protein expressions.A nine-gene established cohort. Kaplan-Meier survival revealed patients with higher risk scores correlated adverse prognosis each MCP-counter EPIC results consistently significantly high group. Patients more prone not respond immunotherapy, but sensitive several conventional chemotherapeutics, suggesting potential strategy combining chemotherapy anti-CAF therapy improve efficacy current T-cell based immunotherapies. multivariate verified an independent indicator predicting overall survival, CAF-based nomogram then built clinical utility CRC.To conclude, robust CRC, which provides novel genomics evidence immunotherapeutic strategies.
Language: Английский
Citations
97
Nucleic Acids Research, Journal Year: 2021, Volume and Issue: 50(D1), P. D1391 - D1397
Published: Sept. 16, 2021
Abstract Syngeneic mouse models are tumors derived from murine cancer cells engrafted on genetically identical strains. They widely used tools for studying tumor immunity and immunotherapy response in the context of a fully functional immune system. Large volumes syngeneic expression profiles under different treatments have been generated, although lack systematic collection analysis makes data reuse challenging. We present Tumor Immune MOuse (TISMO), database with an extensive model interactive visualization features. TISMO contains 605 vitro RNA-seq samples 49 cell lines across 23 types, which 195 underwent cytokine treatment. also includes 1518 vivo 68 19 832 were checkpoint blockade (ICB) studies. manually annotated sample metadata, such as line, strain, transplantation site, treatment, status, uniformly processed quality-controlled data. Besides download, provides web interfaces to investigate whether specific gene expression, pathway enrichment, or infiltration level is associated differential response. available at http://tismo.cistrome.org.
Language: Английский
Citations
83
Pharmacological Research, Journal Year: 2022, Volume and Issue: 183, P. 106376 - 106376
Published: July 30, 2022
Language: Английский
Citations
59
Frontiers in Molecular Biosciences, Journal Year: 2021, Volume and Issue: 8
Published: Oct. 8, 2021
Background: Cancer-associated fibroblasts (CAFs) are the most prominent cellular components in gastric cancer (GC) stroma that contribute to GC progression, treatment resistance, and immunosuppression. This study aimed at exploring stromal CAF-related factors developing a classifier for predicting prognosis therapeutic effects GC. Methods: We downloaded mRNA expression clinical information of 431 samples from Gene Expression Omnibus (GEO) 330 The Cancer Genome Atlas (TCGA) databases. CAF infiltrations were quantified by estimate proportion immune cells (EPIC) method, scores calculated via Estimation STromal Immune MAlignant Tumors using data (ESTIMATE) algorithm. Stromal genes identified weighted gene co-expression network analysis (WGCNA). A risk signature was then developed univariate least absolute shrinkage selection operator method (LASSO) Cox regression model. applied Spearman test determine correlation among score, markers, (estimated EPIC, xCell, microenvironment cell populations-counter (MCP-counter), Tumor Dysfunction Exclusion (TIDE) algorithms). TIDE algorithm further used assess immunotherapy response. set enrichment (GSEA) clarify molecular mechanisms. Results: 4-gene (COL8A1, SPOCK1, AEBP1, TIMP2) prognostic model constructed. patients classified into high– low–CAF-risk groups accordance with their median high–CAF-risk group had significant worse prognosis. analyses revealed score strongly positively correlated infiltrations, four also exhibited positive correlations markers. Furthermore, less likely respond immunotherapy. GSEA epithelial–mesenchymal transition (EMT), TGF-β signaling, hypoxia, angiogenesis sets significantly enriched patients. Conclusion: present four-gene not only reliable but competent response patients, which might provide implications guiding tailored anti-CAF therapy combination
Language: Английский
Citations
58