Q-omics provides the consensus-scored SEMA4F profile across patient tissues and cancer cell-line models. SEMA4F 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, SEMA4F is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SEMA4F RNA expression shows 19,222 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where SEMA4F 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 SEMA4F — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEMA4F survival associations across molecular data types. SEMA4F RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEMA4F RNA expression–survival associations across cancer types. High SEMA4F expression shows unfavorable associations in KIRC, DLBC, UCEC, BLCA, MESO and LIHC. The KIRC 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 KIRC as the clearest survival context for SEMA4F RNA expression.
This table summarizes SEMA4F tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SEMA4F. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEMA4F shows higher tumor expression in HNSC, BLCA, LIHC, KIRP, COAD and STAD. The HNSC box plot shows higher SEMA4F RNA expression in tumor versus normal tissue (log2 FC = +1.796, t-test p < 0.001).
This table shows molecular features associated with SEMA4F in patient tissues and cancer cell lines. In patient samples, SEMA4F shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SEMA4F RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
