Q-omics provides the consensus-scored CBLB profile across patient tissues and cancer cell-line models. CBLB expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, CBLB is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, CBLB RNA expression shows 21,134 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LUSC, HNSC, and THYM as cancer lineages where CBLB 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 CBLB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CBLB survival associations across molecular data types. CBLB RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CBLB RNA expression–survival associations across cancer types. High CBLB expression shows unfavorable associations in LUSC and KICH, but favorable associations in HNSC, CHOL, SKCM and LGG. The LUSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LUSC as the clearest survival context for CBLB RNA expression.
This table summarizes CBLB 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 8. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for CBLB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CBLB shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, LIHC, LUAD and STAD. The HNSC box plot shows higher CBLB RNA expression in tumor versus normal tissue (log2 FC = +1.630, t-test p < 0.001).
This table shows molecular features associated with CBLB in patient tissues and cancer cell lines. In patient samples, CBLB shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, CBLB 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 BLOOD_Leukemia and LARGE_INTESTINE.
