Q-omics provides the consensus-scored CD46 profile across patient tissues and cancer cell-line models. CD46 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, CD46 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, CD46 protein abundance shows 22,839 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight CESC, COAD, and HNSC as cancer lineages where CD46 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 CD46 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CD46 survival associations across molecular data types. CD46 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) 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 CD46 RNA expression–survival associations across cancer types. High CD46 expression shows unfavorable associations in CESC, LGG, ACC and KIRP, but favorable associations in KIRC and SKCM. The CESC 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 CESC as the clearest survival context for CD46 RNA expression.
This table summarizes CD46 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CD46. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CD46 shows lower tumor expression in KIRC and higher tumor expression in COAD, LIHC, STAD, BLCA and BRCA. The COAD box plot shows higher CD46 RNA expression in tumor versus normal tissue (log2 FC = +1.297, t-test p < 0.001).
This table shows molecular features associated with CD46 in patient tissues and cancer cell lines. In patient samples, CD46 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, CD46 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Lymphoma.
