Q-omics provides the consensus-scored EXOC1L profile across patient tissues and cancer cell-line models. EXOC1L expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, EXOC1L is differentially expressed in 6, with the highest sampling consensus in BRCA. Additionally, EXOC1L RNA expression shows 4,288 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight ACC, BRCA, and STAD as cancer lineages where EXOC1L 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 EXOC1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EXOC1L survival associations across molecular data types. EXOC1L RNA expression shows survival associations in the most cancer types (15). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EXOC1L RNA expression–survival associations across cancer types. High EXOC1L expression shows unfavorable associations in ACC, THYM, BRCA, KICH, MESO and DLBC. The ACC 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 ACC as the clearest survival context for EXOC1L RNA expression.
This table summarizes EXOC1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for EXOC1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EXOC1L shows lower tumor expression in BRCA, HNSC, PRAD and LIHC and higher tumor expression in PAAD and COAD. The BRCA box plot shows higher EXOC1L RNA expression in normal versus tumor tissue (log2 FC = −0.421, t-test p < 0.001).
This table shows molecular features associated with EXOC1L in patient tissues and cancer cell lines. In patient samples, EXOC1L shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, EXOC1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia.
