Q-omics provides the consensus-scored CR1L profile across patient tissues and cancer cell-line models. CR1L expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, CR1L is differentially expressed in 7, with the highest sampling consensus in KICH. Additionally, CR1L RNA expression shows 12,486 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight SKCM, KICH, and TGCT as cancer lineages where CR1L 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 CR1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CR1L survival associations across molecular data types. CR1L RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CR1L RNA expression–survival associations across cancer types. High CR1L expression shows unfavorable associations in LGG and THYM, but favorable associations in SKCM, SCLC, LUAD and HNSC. 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 CR1L RNA expression.
This table summarizes CR1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for CR1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CR1L shows lower tumor expression in LIHC and KIRP and higher tumor expression in KICH, HNSC, STAD and BRCA. The KICH box plot shows higher CR1L RNA expression in tumor versus normal tissue (log2 FC = +2.500, t-test p < 0.001).
This table shows molecular features associated with CR1L in patient tissues and cancer cell lines. In patient samples, CR1L 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, CR1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LIVER.
