Q-omics provides the consensus-scored C4A profile across patient tissues and cancer cell-line models. C4A expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, C4A is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, C4A RNA expression shows 19,460 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where C4A 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 C4A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C4A survival associations across molecular data types. C4A RNA expression shows survival associations in the most cancer types (21), followed by mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C4A RNA expression–survival associations across cancer types. High C4A expression shows unfavorable associations in UVM, but favorable associations in KIRC, MESO, SKCM, HNSC and ACC. The KIRC 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 KIRC as the clearest survival context for C4A RNA expression.
This table summarizes C4A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for C4A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C4A shows lower tumor expression in LUAD, KICH and LUSC and higher tumor expression in KIRC, STAD and BRCA. The KIRC box plot shows higher C4A RNA expression in tumor versus normal tissue (log2 FC = +2.649, t-test p < 0.001).
This table shows molecular features associated with C4A in patient tissues and cancer cell lines. In patient samples, C4A 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, C4A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Myeloma.
