SLIT-ROBO Rho GTPase activating protein 2BGenealiases: SRGAP2L · SRGAP2P2
Q-omics provides the consensus-scored SRGAP2B profile across patient tissues and cancer cell-line models. SRGAP2B expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, SRGAP2B is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, SRGAP2B RNA expression shows 19,931 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, HNSC, and UVM as cancer lineages where SRGAP2B 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 SRGAP2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRGAP2B survival associations across molecular data types. SRGAP2B RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRGAP2B RNA expression–survival associations across cancer types. High SRGAP2B expression shows unfavorable associations in KICH, ACC, KIRP, UVM and COAD, but favorable associations in KIRC. The KICH 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 KICH as the clearest survival context for SRGAP2B RNA expression.
This table summarizes SRGAP2B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SRGAP2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRGAP2B shows lower tumor expression in KICH and LUAD and higher tumor expression in HNSC, BLCA, LIHC and BRCA. The HNSC box plot shows higher SRGAP2B RNA expression in tumor versus normal tissue (log2 FC = +0.756, t-test p < 0.001).
This table shows molecular features associated with SRGAP2B in patient tissues and cancer cell lines. In patient samples, SRGAP2B 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, SRGAP2B 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 LARGE_INTESTINE.
