Q-omics provides the consensus-scored SEMA4G profile across patient tissues and cancer cell-line models. SEMA4G expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SEMA4G is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, SEMA4G protein abundance shows 30,331 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, KICH, and LSCC as cancer lineages where SEMA4G 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 SEMA4G — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEMA4G survival associations across molecular data types. SEMA4G RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEMA4G RNA expression–survival associations across cancer types. High SEMA4G expression shows unfavorable associations in ACC, LUAD, CESC, LUSC and CHOL, but favorable associations in LGG. The ACC 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 ACC as the clearest survival context for SEMA4G RNA expression.
This table summarizes SEMA4G tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SEMA4G. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEMA4G shows lower tumor expression in KICH, COAD and READ and higher tumor expression in KIRC, STAD and LIHC. The KICH box plot shows higher SEMA4G RNA expression in normal versus tumor tissue (log2 FC = −1.689, t-test p < 0.001).
This table shows molecular features associated with SEMA4G in patient tissues and cancer cell lines. In patient samples, SEMA4G shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SEMA4G RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
