Q-omics provides the consensus-scored C1QL1 profile across patient tissues and cancer cell-line models. C1QL1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, C1QL1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, C1QL1 RNA expression shows 14,370 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KIRC, and TGCT as cancer lineages where C1QL1 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 C1QL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C1QL1 survival associations across molecular data types. C1QL1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C1QL1 RNA expression–survival associations across cancer types. High C1QL1 expression shows unfavorable associations in ACC, KIRP, LUAD, KIRC and UCEC, but favorable associations in LGG. The ACC 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 ACC as the clearest survival context for C1QL1 RNA expression.
This table summarizes C1QL1 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 1. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for C1QL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C1QL1 shows higher tumor expression in KIRC, HNSC, THCA, LUSC, LIHC and LUAD. The KIRC box plot shows higher C1QL1 RNA expression in tumor versus normal tissue (log2 FC = +3.497, t-test p < 0.001).
This table shows molecular features associated with C1QL1 in patient tissues and cancer cell lines. In patient samples, C1QL1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, C1QL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
