Q-omics provides the consensus-scored RELN profile across patient tissues and cancer cell-line models. RELN expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RELN is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, RELN RNA expression shows 18,786 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, COAD, and GBM as cancer lineages where RELN 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 RELN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RELN survival associations across molecular data types. RELN RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RELN RNA expression–survival associations across cancer types. High RELN expression shows unfavorable associations in ACC, UCEC and SCLC, but favorable associations in CESC, PAAD and KIRP. 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 RELN RNA expression.
This table summarizes RELN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 2. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RELN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RELN shows lower tumor expression in COAD, THCA, KIRC, STAD, BRCA and UCEC. The COAD box plot shows higher RELN RNA expression in normal versus tumor tissue (log2 FC = −1.137, t-test p < 0.001).
This table shows molecular features associated with RELN in patient tissues and cancer cell lines. In patient samples, RELN 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, RELN 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 BLOOD_Myeloma and LARGE_INTESTINE.
