Q-omics provides the consensus-scored SEMA4C profile across patient tissues and cancer cell-line models. SEMA4C expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SEMA4C is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, SEMA4C RNA expression shows 19,913 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRP, and KIRC as cancer lineages where SEMA4C 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 SEMA4C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEMA4C survival associations across molecular data types. SEMA4C RNA expression shows survival associations in the most cancer types (28), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEMA4C RNA expression–survival associations across cancer types. High SEMA4C expression shows unfavorable associations in KIRP, ACC, COAD and LGG, but favorable associations in UCS and HNSC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for SEMA4C RNA expression.
This table summarizes SEMA4C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SEMA4C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEMA4C shows lower tumor expression in KICH and BLCA and higher tumor expression in KIRC, THCA, HNSC and LUAD. The KIRC box plot shows higher SEMA4C RNA expression in tumor versus normal tissue (log2 FC = +1.038, t-test p < 0.001).
This table shows molecular features associated with SEMA4C in patient tissues and cancer cell lines. In patient samples, SEMA4C shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, SEMA4C 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
