Q-omics provides the consensus-scored SEMA3D profile across patient tissues and cancer cell-line models. SEMA3D expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SEMA3D is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, SEMA3D RNA expression shows 17,991 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, THCA, and THYM as cancer lineages where SEMA3D 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 SEMA3D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEMA3D survival associations across molecular data types. SEMA3D RNA expression shows survival associations in the most cancer types (28), followed by mutation status (8) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEMA3D RNA expression–survival associations across cancer types. High SEMA3D expression shows unfavorable associations in UVM, BLCA, MESO and KIRP, but favorable associations in KIRC and HNSC. 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 SEMA3D RNA expression.
This table summarizes SEMA3D 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 THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SEMA3D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEMA3D shows lower tumor expression in THCA, KICH, COAD, LUAD and KIRC and higher tumor expression in HNSC. The THCA box plot shows higher SEMA3D RNA expression in normal versus tumor tissue (log2 FC = −4.890, t-test p < 0.001).
This table shows molecular features associated with SEMA3D in patient tissues and cancer cell lines. In patient samples, SEMA3D shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SEMA3D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SKIN.
