Q-omics provides the consensus-scored SCRN3 profile across patient tissues and cancer cell-line models. SCRN3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SCRN3 is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, SCRN3 RNA expression shows 21,134 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where SCRN3 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 SCRN3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCRN3 survival associations across molecular data types. SCRN3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) 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 SCRN3 RNA expression–survival associations across cancer types. High SCRN3 expression shows unfavorable associations in KIRP, CESC and KICH, but favorable associations in KIRC, UCS and SARC. The KIRC 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 KIRC as the clearest survival context for SCRN3 RNA expression.
This table summarizes SCRN3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SCRN3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCRN3 shows lower tumor expression in THCA and KICH and higher tumor expression in BRCA, LIHC, BLCA and LUSC. The THCA box plot shows higher SCRN3 RNA expression in normal versus tumor tissue (log2 FC = −1.052, t-test p < 0.001).
This table shows molecular features associated with SCRN3 in patient tissues and cancer cell lines. In patient samples, SCRN3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SCRN3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
