Q-omics provides the consensus-scored CELSR1 profile across patient tissues and cancer cell-line models. CELSR1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, CELSR1 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, CELSR1 protein abundance shows 24,377 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight MESO, KICH, and LSCC as cancer lineages where CELSR1 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 CELSR1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CELSR1 survival associations across molecular data types. CELSR1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (12) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CELSR1 RNA expression–survival associations across cancer types. High CELSR1 expression shows unfavorable associations in MESO, UVM, LGG, HNSC and OV, but favorable associations in SCLC. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify MESO as the clearest survival context for CELSR1 RNA expression.
This table summarizes CELSR1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CELSR1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CELSR1 shows lower tumor expression in KICH and THCA and higher tumor expression in COAD, HNSC, STAD and KIRC. The KICH box plot shows higher CELSR1 RNA expression in normal versus tumor tissue (log2 FC = −3.970, t-test p < 0.001).
This table shows molecular features associated with CELSR1 in patient tissues and cancer cell lines. In patient samples, CELSR1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CELSR1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
