Q-omics provides the consensus-scored CD5L profile across patient tissues and cancer cell-line models. CD5L expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CD5L is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, CD5L protein abundance shows 24,693 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, KIRC, and HNSC as cancer lineages where CD5L 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 CD5L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CD5L survival associations across molecular data types. CD5L RNA expression shows survival associations in the most cancer types (17), followed by mutation status (8) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CD5L RNA expression–survival associations across cancer types. High CD5L expression shows unfavorable associations in UVM, UCS and READ, but favorable associations in LIHC, SKCM and KIRC. The UVM 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 UVM as the clearest survival context for CD5L RNA expression.
This table summarizes CD5L 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 9. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CD5L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CD5L shows lower tumor expression in LUAD, LUSC, LIHC and CHOL and higher tumor expression in KIRC and KIRP. The KIRC box plot shows higher CD5L RNA expression in tumor versus normal tissue (log2 FC = +1.392, t-test p < 0.001).
This table shows molecular features associated with CD5L in patient tissues and cancer cell lines. In patient samples, CD5L 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, CD5L 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 LIVER and LARGE_INTESTINE.
