Q-omics provides the consensus-scored MAP1B profile across patient tissues and cancer cell-line models. MAP1B expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, MAP1B is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, MAP1B protein abundance shows 26,458 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight BLCA, KIRC, and HNSC as cancer lineages where MAP1B 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 MAP1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAP1B survival associations across molecular data types. MAP1B RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAP1B RNA expression–survival associations across cancer types. High MAP1B expression shows unfavorable associations in BLCA, UVM, HNSC, UCS and LGG, but favorable associations in SCLC. The BLCA 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 BLCA as the clearest survival context for MAP1B RNA expression.
This table summarizes MAP1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 9. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MAP1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAP1B shows lower tumor expression in BLCA and higher tumor expression in KIRC, LIHC, KIRP, HNSC and LUAD. The KIRC box plot shows higher MAP1B RNA expression in tumor versus normal tissue (log2 FC = +1.023, t-test p < 0.001).
This table shows molecular features associated with MAP1B in patient tissues and cancer cell lines. In patient samples, MAP1B shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, MAP1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and CNS.
