Q-omics provides the consensus-scored SEMA4B profile across patient tissues and cancer cell-line models. SEMA4B expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, SEMA4B is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SEMA4B RNA expression shows 19,893 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight PAAD, HNSC, and UVM as cancer lineages where SEMA4B 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 SEMA4B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEMA4B survival associations across molecular data types. SEMA4B RNA expression shows survival associations in the most cancer types (25), 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 SEMA4B RNA expression–survival associations across cancer types. High SEMA4B expression shows unfavorable associations in PAAD, KIRP, LUAD, UVM and KIRC, but favorable associations in LGG. The PAAD 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 PAAD as the clearest survival context for SEMA4B RNA expression.
This table summarizes SEMA4B 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 6. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SEMA4B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEMA4B shows higher tumor expression in HNSC, LUAD, KIRC, LUSC, BRCA and KIRP. The HNSC box plot shows higher SEMA4B RNA expression in tumor versus normal tissue (log2 FC = +1.257, t-test p < 0.001).
This table shows molecular features associated with SEMA4B in patient tissues and cancer cell lines. In patient samples, SEMA4B shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SEMA4B 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 LUNG_SCLC and BLOOD_Leukemia.
