Q-omics provides the consensus-scored SEMA3F profile across patient tissues and cancer cell-line models. SEMA3F expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SEMA3F is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, SEMA3F RNA expression shows 19,339 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, and ACC as cancer lineages where SEMA3F 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 SEMA3F — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEMA3F survival associations across molecular data types. SEMA3F RNA expression shows survival associations in the most cancer types (24), followed by mutation status (10) 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 SEMA3F RNA expression–survival associations across cancer types. High SEMA3F expression shows unfavorable associations in UVM, ACC, COAD and LIHC, but favorable associations in KIRC and BRCA. 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 SEMA3F RNA expression.
This table summarizes SEMA3F 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 4. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SEMA3F. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEMA3F shows higher tumor expression in KIRC, COAD, LIHC, THCA, BRCA and LUSC. The KIRC box plot shows higher SEMA3F RNA expression in tumor versus normal tissue (log2 FC = +1.506, t-test p < 0.001).
This table shows molecular features associated with SEMA3F in patient tissues and cancer cell lines. In patient samples, SEMA3F 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, SEMA3F 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_NSCLC_LUAD and BREAST.
