SLIT-ROBO Rho GTPase activating protein 2D (pseudogene)Genealiases: []
Q-omics provides the consensus-scored SRGAP2D profile across patient tissues and cancer cell-line models. SRGAP2D expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SRGAP2D is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, SRGAP2D RNA expression shows 18,304 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where SRGAP2D 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 SRGAP2D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRGAP2D survival associations across molecular data types. SRGAP2D RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRGAP2D RNA expression–survival associations across cancer types. High SRGAP2D expression shows unfavorable associations in UVM, ACC, KIRP, HNSC and KICH, but favorable associations in KIRC. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UVM as the clearest survival context for SRGAP2D RNA expression.
This table summarizes SRGAP2D tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SRGAP2D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRGAP2D shows lower tumor expression in LUAD and KICH and higher tumor expression in KIRC, HNSC, LIHC and BLCA. The KIRC box plot shows higher SRGAP2D RNA expression in tumor versus normal tissue (log2 FC = +0.804, t-test p < 0.001).
This table shows molecular features associated with SRGAP2D in patient tissues and cancer cell lines. In patient samples, SRGAP2D shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SRGAP2D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
