GIPC PDZ domain containing family member 2Genealiases: SEMCAP-2 · SEMCAP2
Q-omics provides the consensus-scored GIPC2 profile across patient tissues and cancer cell-line models. GIPC2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, GIPC2 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, GIPC2 RNA expression shows 17,761 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where GIPC2 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 GIPC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GIPC2 survival associations across molecular data types. GIPC2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GIPC2 RNA expression–survival associations across cancer types. High GIPC2 expression shows unfavorable associations in SCLC, but favorable associations in KIRC, READ, HNSC, THCA and BRCA. 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 GIPC2 RNA expression.
This table summarizes GIPC2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GIPC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GIPC2 shows lower tumor expression in HNSC, KICH, KIRP, THCA, LUSC and COAD. The HNSC box plot shows higher GIPC2 RNA expression in normal versus tumor tissue (log2 FC = −0.988, t-test p < 0.001).
This table shows molecular features associated with GIPC2 in patient tissues and cancer cell lines. In patient samples, GIPC2 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, GIPC2 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 BREAST and LARGE_INTESTINE.
