Q-omics provides the consensus-scored CAPSL profile across patient tissues and cancer cell-line models. CAPSL expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CAPSL is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, CAPSL RNA expression shows 12,797 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KICH, and TGCT as cancer lineages where CAPSL 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 CAPSL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CAPSL survival associations across molecular data types. CAPSL RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CAPSL RNA expression–survival associations across cancer types. High CAPSL expression shows unfavorable associations in LIHC, STAD, SCLC and LUAD, but favorable associations in ACC and READ. The ACC 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 ACC as the clearest survival context for CAPSL RNA expression.
This table summarizes CAPSL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CAPSL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CAPSL shows lower tumor expression in KICH, KIRC, THCA, LUAD and LUSC and higher tumor expression in LIHC. The KICH box plot shows higher CAPSL RNA expression in normal versus tumor tissue (log2 FC = −1.700, t-test p < 0.001).
This table shows molecular features associated with CAPSL in patient tissues and cancer cell lines. In patient samples, CAPSL 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, CAPSL 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 CNS and BONE.
