Q-omics provides the consensus-scored C1QA profile across patient tissues and cancer cell-line models. C1QA expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, C1QA is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, C1QA protein abundance shows 25,496 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight SKCM, KIRC, and LUAD as cancer lineages where C1QA 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 C1QA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C1QA survival associations across molecular data types. C1QA RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 C1QA RNA expression–survival associations across cancer types. High C1QA expression shows unfavorable associations in UVM, LGG and LUSC, but favorable associations in SKCM, CESC and CHOL. The SKCM 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 SKCM as the clearest survival context for C1QA RNA expression.
This table summarizes C1QA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for C1QA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C1QA shows lower tumor expression in COAD, LUAD and LUSC and higher tumor expression in KIRC, KIRP and THCA. The KIRC box plot shows higher C1QA RNA expression in tumor versus normal tissue (log2 FC = +3.091, t-test p < 0.001).
This table shows molecular features associated with C1QA in patient tissues and cancer cell lines. In patient samples, C1QA shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, C1QA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and SKIN.
