Q-omics provides the consensus-scored RETN profile across patient tissues and cancer cell-line models. RETN expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, RETN is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, RETN protein abundance shows 25,698 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight SCLC, KIRC, and PDAC as cancer lineages where RETN 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 RETN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RETN survival associations across molecular data types. RETN RNA expression shows survival associations in the most cancer types (22), followed by mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RETN RNA expression–survival associations across cancer types. High RETN expression shows unfavorable associations in SCLC, LUSC, KIRP, KIRC and HNSC, but favorable associations in SKCM. The SCLC 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 SCLC as the clearest survival context for RETN RNA expression.
This table summarizes RETN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RETN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RETN shows lower tumor expression in LUAD and LUSC and higher tumor expression in KIRC, COAD, THCA and STAD. The KIRC box plot shows higher RETN RNA expression in tumor versus normal tissue (log2 FC = +1.172, t-test p < 0.001).
This table shows molecular features associated with RETN in patient tissues and cancer cell lines. In patient samples, RETN shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, RETN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
