Q-omics provides the consensus-scored CD163L1 profile across patient tissues and cancer cell-line models. CD163L1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CD163L1 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, CD163L1 RNA expression shows 15,681 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, COAD, and GBM as cancer lineages where CD163L1 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 CD163L1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CD163L1 survival associations across molecular data types. CD163L1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (10) and 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 CD163L1 RNA expression–survival associations across cancer types. High CD163L1 expression shows unfavorable associations in UVM, BRCA, KIRP, LUSC and UCS, but favorable associations in CHOL. 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 CD163L1 RNA expression.
This table summarizes CD163L1 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 4. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CD163L1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CD163L1 shows lower tumor expression in COAD, THCA, BLCA and BRCA and higher tumor expression in KIRC and LIHC. The COAD box plot shows higher CD163L1 RNA expression in normal versus tumor tissue (log2 FC = −3.096, t-test p < 0.001).
This table shows molecular features associated with CD163L1 in patient tissues and cancer cell lines. In patient samples, CD163L1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CD163L1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BONE.