Q-omics provides the consensus-scored CELSR2 profile across patient tissues and cancer cell-line models. CELSR2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, CELSR2 is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, CELSR2 RNA expression shows 20,134 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight BRCA, KICH, and KIRP as cancer lineages where CELSR2 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for CELSR2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CELSR2 survival associations across molecular data types. CELSR2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (11) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CELSR2 RNA expression–survival associations across cancer types. High CELSR2 expression shows unfavorable associations in MESO and LAML, but favorable associations in BRCA, UVM, KIRC and READ. The BRCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify BRCA as the clearest survival context for CELSR2 RNA expression.
This table summarizes CELSR2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CELSR2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CELSR2 shows lower tumor expression in KICH and KIRC and higher tumor expression in LUSC, LIHC, HNSC and COAD. The KICH box plot shows higher CELSR2 RNA expression in normal versus tumor tissue (log2 FC = −2.903, t-test p < 0.001).
This table shows molecular features associated with CELSR2 in patient tissues and cancer cell lines. In patient samples, CELSR2 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, CELSR2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
