Q-omics provides the consensus-scored TBC1D22B profile across patient tissues and cancer cell-line models. TBC1D22B expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TBC1D22B is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, TBC1D22B protein abundance shows 22,801 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LIHC, and GBM as cancer lineages where TBC1D22B 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 TBC1D22B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TBC1D22B survival associations across molecular data types. TBC1D22B RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TBC1D22B RNA expression–survival associations across cancer types. High TBC1D22B expression shows unfavorable associations in KICH, UCEC, COAD, LIHC and ACC, but favorable associations in KIRC. 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 TBC1D22B RNA expression.
This table summarizes TBC1D22B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 8. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for TBC1D22B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TBC1D22B shows lower tumor expression in KICH and higher tumor expression in LIHC, KIRP, LUAD, CHOL and KIRC. The LIHC box plot shows higher TBC1D22B RNA expression in tumor versus normal tissue (log2 FC = +1.416, t-test p < 0.001).
This table shows molecular features associated with TBC1D22B in patient tissues and cancer cell lines. In patient samples, TBC1D22B shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, TBC1D22B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
