Q-omics provides the consensus-scored TBC1D9B profile across patient tissues and cancer cell-line models. TBC1D9B expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, TBC1D9B is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, TBC1D9B protein abundance shows 21,309 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KICH, KIRC, and LSCC as cancer lineages where TBC1D9B 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 TBC1D9B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TBC1D9B survival associations across molecular data types. TBC1D9B RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) 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 TBC1D9B RNA expression–survival associations across cancer types. High TBC1D9B expression shows unfavorable associations in KICH, HNSC, LGG, CESC and LUSC, but favorable associations in KIRC. The KICH 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 KICH as the clearest survival context for TBC1D9B RNA expression.
This table summarizes TBC1D9B 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TBC1D9B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TBC1D9B shows lower tumor expression in THCA and KICH and higher tumor expression in KIRC, COAD, HNSC and LIHC. The KIRC box plot shows higher TBC1D9B RNA expression in tumor versus normal tissue (log2 FC = +0.713, t-test p < 0.001).
This table shows molecular features associated with TBC1D9B in patient tissues and cancer cell lines. In patient samples, TBC1D9B shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, TBC1D9B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
