Q-omics provides the consensus-scored CBLC profile across patient tissues and cancer cell-line models. CBLC expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CBLC is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, CBLC RNA expression shows 12,567 significant gene co-expression associations, with the highest sampling consensus in PAAD. Together, these results highlight KIRP, KIRC, and PAAD as cancer lineages where CBLC 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 CBLC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CBLC survival associations across molecular data types. CBLC RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 CBLC RNA expression–survival associations across cancer types. High CBLC expression shows unfavorable associations in SKCM, LUAD, PAAD and READ, but favorable associations in KIRP and BLCA. The KIRP Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify KIRP as the clearest survival context for CBLC RNA expression.
This table summarizes CBLC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CBLC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CBLC shows lower tumor expression in KIRC, THCA and KIRP and higher tumor expression in LUSC, LUAD and BLCA. The KIRC box plot shows higher CBLC RNA expression in normal versus tumor tissue (log2 FC = −2.397, t-test p < 0.001).
This table shows molecular features associated with CBLC in patient tissues and cancer cell lines. In patient samples, CBLC shows the broadest associations at the RNA and protein expression levels, with PAAD recurring as the lineage with the largest associated feature set. In cancer cell lines, CBLC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LUNG_SCLC.
