Q-omics provides the consensus-scored CRAT profile across patient tissues and cancer cell-line models. CRAT expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CRAT is differentially expressed in 9, with the highest sampling consensus in THCA. Additionally, CRAT protein abundance shows 20,733 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, THCA, and GBM as cancer lineages where CRAT 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 CRAT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CRAT survival associations across molecular data types. CRAT RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CRAT RNA expression–survival associations across cancer types. High CRAT expression shows unfavorable associations in ACC, BLCA and MESO, but favorable associations in KIRC, KIRP and UCEC. 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 CRAT RNA expression.
This table summarizes CRAT 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 7. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CRAT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CRAT shows lower tumor expression in THCA, COAD, CHOL and HNSC and higher tumor expression in LUAD and BRCA. The THCA box plot shows higher CRAT RNA expression in normal versus tumor tissue (log2 FC = −0.669, t-test p < 0.001).
This table shows molecular features associated with CRAT in patient tissues and cancer cell lines. In patient samples, CRAT 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, CRAT 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 LUNG_NSCLC_LUAD and CNS.
