Q-omics provides the consensus-scored CALCOCO2 profile across patient tissues and cancer cell-line models. CALCOCO2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CALCOCO2 is differentially expressed in 17, with the highest sampling consensus in COAD. Additionally, CALCOCO2 protein abundance shows 22,306 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, COAD, and PDAC as cancer lineages where CALCOCO2 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 CALCOCO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CALCOCO2 survival associations across molecular data types. CALCOCO2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CALCOCO2 RNA expression–survival associations across cancer types. High CALCOCO2 expression shows unfavorable associations in KIRP and KICH, but favorable associations in KIRC, SKCM, BRCA and READ. 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 CALCOCO2 RNA expression.
This table summarizes CALCOCO2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 9. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for CALCOCO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CALCOCO2 shows lower tumor expression in COAD, THCA, KICH and LUSC and higher tumor expression in KIRC and LIHC. The COAD box plot shows higher CALCOCO2 RNA expression in normal versus tumor tissue (log2 FC = −1.143, t-test p < 0.001).
This table shows molecular features associated with CALCOCO2 in patient tissues and cancer cell lines. In patient samples, CALCOCO2 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, CALCOCO2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
