Q-omics provides the consensus-scored CROT profile across patient tissues and cancer cell-line models. CROT expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, CROT is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, CROT RNA expression shows 20,304 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight BRCA, KIRC, and UVM as cancer lineages where CROT 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 CROT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CROT survival associations across molecular data types. CROT RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CROT RNA expression–survival associations across cancer types. High CROT expression shows unfavorable associations in LGG and SCLC, but favorable associations in BRCA, KIRC, LUAD and BLCA. The BRCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify BRCA as the clearest survival context for CROT RNA expression.
This table summarizes CROT 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CROT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CROT shows lower tumor expression in KIRC, COAD, THCA, KICH, STAD and UCEC. The KIRC box plot shows higher CROT RNA expression in normal versus tumor tissue (log2 FC = −1.116, t-test p < 0.001).
This table shows molecular features associated with CROT in patient tissues and cancer cell lines. In patient samples, CROT 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, CROT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
