Q-omics provides the consensus-scored SRGAP3 profile across patient tissues and cancer cell-line models. SRGAP3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SRGAP3 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, SRGAP3 protein abundance shows 22,796 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where SRGAP3 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 SRGAP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRGAP3 survival associations across molecular data types. SRGAP3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRGAP3 RNA expression–survival associations across cancer types. High SRGAP3 expression shows unfavorable associations in OV, but favorable associations in UVM, ACC, SKCM, LGG and CESC. The UVM 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 UVM as the clearest survival context for SRGAP3 RNA expression.
This table summarizes SRGAP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SRGAP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRGAP3 shows lower tumor expression in KIRC and KICH and higher tumor expression in LIHC, THCA, COAD and CHOL. The KIRC box plot shows higher SRGAP3 RNA expression in normal versus tumor tissue (log2 FC = −1.567, t-test p < 0.001).
This table shows molecular features associated with SRGAP3 in patient tissues and cancer cell lines. In patient samples, SRGAP3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SRGAP3 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 LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
