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transcriptome data of human cancer cell lines (ccls)  (Broad Institute Inc)

 
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    Broad Institute Inc transcriptome data of human cancer cell lines (ccls)
    Identification of the diverse patterns based on the PANoptosis gene list. (a) A total of 226 PANoptosis-related genes belonging to necroptosis, apoptosis, and pyroptosis were collected for downstream analysis. (b) The univariate Cox regression analysis and Spearman's sum rank test were performed in the HOVON cohort, which was set as the training cohort. 28 genes with prognostic prediction were screened out with p value <0.05. (c) An interaction network of prognostic PANoptosis-related genes. (d) The 618 patients in HOVON cohort were divided into three clusters, according to the consensus clustering analysis based on the <t>transcriptome</t> profile of PANoptosis-related genes. (e) The KM curves showing the differential overall survival among the three subgroups. (f) A heat map showing the expression of the prognostic PANoptosis related genes in different subgroups. The two-sided p value <0.05 was considered significant for all statistical analyses and shown as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.
    Transcriptome Data Of Human Cancer Cell Lines (Ccls), supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/transcriptome data of human cancer cell lines (ccls)/product/Broad Institute Inc
    Average 90 stars, based on 1 article reviews
    transcriptome data of human cancer cell lines (ccls) - by Bioz Stars, 2026-05
    90/100 stars

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    1) Product Images from "Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy"

    Article Title: Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy

    Journal: International Journal of Clinical Practice

    doi: 10.1155/2024/5113990

    Identification of the diverse patterns based on the PANoptosis gene list. (a) A total of 226 PANoptosis-related genes belonging to necroptosis, apoptosis, and pyroptosis were collected for downstream analysis. (b) The univariate Cox regression analysis and Spearman's sum rank test were performed in the HOVON cohort, which was set as the training cohort. 28 genes with prognostic prediction were screened out with p value <0.05. (c) An interaction network of prognostic PANoptosis-related genes. (d) The 618 patients in HOVON cohort were divided into three clusters, according to the consensus clustering analysis based on the transcriptome profile of PANoptosis-related genes. (e) The KM curves showing the differential overall survival among the three subgroups. (f) A heat map showing the expression of the prognostic PANoptosis related genes in different subgroups. The two-sided p value <0.05 was considered significant for all statistical analyses and shown as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.
    Figure Legend Snippet: Identification of the diverse patterns based on the PANoptosis gene list. (a) A total of 226 PANoptosis-related genes belonging to necroptosis, apoptosis, and pyroptosis were collected for downstream analysis. (b) The univariate Cox regression analysis and Spearman's sum rank test were performed in the HOVON cohort, which was set as the training cohort. 28 genes with prognostic prediction were screened out with p value <0.05. (c) An interaction network of prognostic PANoptosis-related genes. (d) The 618 patients in HOVON cohort were divided into three clusters, according to the consensus clustering analysis based on the transcriptome profile of PANoptosis-related genes. (e) The KM curves showing the differential overall survival among the three subgroups. (f) A heat map showing the expression of the prognostic PANoptosis related genes in different subgroups. The two-sided p value <0.05 was considered significant for all statistical analyses and shown as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

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    transcriptome data of human cancer cell lines (ccls)  (Broad Institute Inc)
    90
    Broad Institute Inc transcriptome data of human cancer cell lines (ccls)
    Identification of the diverse patterns based on the PANoptosis gene list. (a) A total of 226 PANoptosis-related genes belonging to necroptosis, apoptosis, and pyroptosis were collected for downstream analysis. (b) The univariate Cox regression analysis and Spearman's sum rank test were performed in the HOVON cohort, which was set as the training cohort. 28 genes with prognostic prediction were screened out with p value <0.05. (c) An interaction network of prognostic PANoptosis-related genes. (d) The 618 patients in HOVON cohort were divided into three clusters, according to the consensus clustering analysis based on the <t>transcriptome</t> profile of PANoptosis-related genes. (e) The KM curves showing the differential overall survival among the three subgroups. (f) A heat map showing the expression of the prognostic PANoptosis related genes in different subgroups. The two-sided p value <0.05 was considered significant for all statistical analyses and shown as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.
    Transcriptome Data Of Human Cancer Cell Lines (Ccls), supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/transcriptome data of human cancer cell lines (ccls)/product/Broad Institute Inc
    Average 90 stars, based on 1 article reviews
    transcriptome data of human cancer cell lines (ccls) - by Bioz Stars, 2026-05
    90/100 stars
    		  Buy from Supplier

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    Identification of the diverse patterns based on the PANoptosis gene list. (a) A total of 226 PANoptosis-related genes belonging to necroptosis, apoptosis, and pyroptosis were collected for downstream analysis. (b) The univariate Cox regression analysis and Spearman's sum rank test were performed in the HOVON cohort, which was set as the training cohort. 28 genes with prognostic prediction were screened out with p value <0.05. (c) An interaction network of prognostic PANoptosis-related genes. (d) The 618 patients in HOVON cohort were divided into three clusters, according to the consensus clustering analysis based on the transcriptome profile of PANoptosis-related genes. (e) The KM curves showing the differential overall survival among the three subgroups. (f) A heat map showing the expression of the prognostic PANoptosis related genes in different subgroups. The two-sided p value <0.05 was considered significant for all statistical analyses and shown as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

    Journal: International Journal of Clinical Practice

    Article Title: Machine Learning-Based Integrated Analysis of PANoptosis Patterns in Acute Myeloid Leukemia Reveals a Signature Predicting Survival and Immunotherapy

    doi: 10.1155/2024/5113990

    Figure Lengend Snippet: Identification of the diverse patterns based on the PANoptosis gene list. (a) A total of 226 PANoptosis-related genes belonging to necroptosis, apoptosis, and pyroptosis were collected for downstream analysis. (b) The univariate Cox regression analysis and Spearman's sum rank test were performed in the HOVON cohort, which was set as the training cohort. 28 genes with prognostic prediction were screened out with p value <0.05. (c) An interaction network of prognostic PANoptosis-related genes. (d) The 618 patients in HOVON cohort were divided into three clusters, according to the consensus clustering analysis based on the transcriptome profile of PANoptosis-related genes. (e) The KM curves showing the differential overall survival among the three subgroups. (f) A heat map showing the expression of the prognostic PANoptosis related genes in different subgroups. The two-sided p value <0.05 was considered significant for all statistical analyses and shown as ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, and ∗∗∗∗ p < 0.0001.

    Article Snippet: Transcriptome data of human cancer cell lines (CCLs) were downloaded from the Broad Institute-Cancer Cell Line Encyclopedia project (CCLE, https://sites.broadinstitute.org/ccle/ ) and the CERES scores, the score to evaluate the dependency of the certain gene in the CCL, which indicated that the score was negative correlation with the possible significance of the gene in cell proliferation of the certain CCL, were downloaded from the dependency map portal (DepMap, https://depmap.org/portal/ ).

    Techniques: Expressing