Q-omics provides the consensus-scored EXOC4 profile across patient tissues and cancer cell-line models. EXOC4 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EXOC4 is differentially expressed in 14, with the highest sampling consensus in KIRP. Additionally, EXOC4 RNA expression shows 19,004 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, KIRP, and ACC as cancer lineages where EXOC4 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 EXOC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EXOC4 survival associations across molecular data types. EXOC4 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EXOC4 RNA expression–survival associations across cancer types. High EXOC4 expression shows unfavorable associations in PAAD, MESO and CESC, but favorable associations in KIRC, HNSC and UCS. 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 EXOC4 RNA expression.
This table summarizes EXOC4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for EXOC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EXOC4 shows higher tumor expression in KIRP, KIRC, COAD, LIHC, LUAD and HNSC. The KIRP box plot shows higher EXOC4 RNA expression in tumor versus normal tissue (log2 FC = +0.833, t-test p < 0.001).
This table shows molecular features associated with EXOC4 in patient tissues and cancer cell lines. In patient samples, EXOC4 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, EXOC4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
