Q-omics provides the consensus-scored SRR profile across patient tissues and cancer cell-line models. SRR expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, SRR is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, SRR RNA expression shows 19,539 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, KIRC, and UVM as cancer lineages where SRR 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 SRR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRR survival associations across molecular data types. SRR RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 SRR RNA expression–survival associations across cancer types. High SRR expression shows unfavorable associations in KICH, but favorable associations in UCEC, KIRP, KIRC, SCLC and PAAD. The UCEC 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 UCEC as the clearest survival context for SRR RNA expression.
This table summarizes SRR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SRR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRR shows lower tumor expression in KIRC, KICH, THCA, BLCA, COAD and LUSC. The KIRC box plot shows higher SRR RNA expression in normal versus tumor tissue (log2 FC = −0.655, t-test p < 0.001).
This table shows molecular features associated with SRR in patient tissues and cancer cell lines. In patient samples, SRR shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SRR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and CNS.
