Q-omics provides the consensus-scored SEC14L3 profile across patient tissues and cancer cell-line models. SEC14L3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SEC14L3 is differentially expressed in 7, with the highest sampling consensus in THCA. Additionally, SEC14L3 protein abundance shows 29,392 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, THCA, and PDAC as cancer lineages where SEC14L3 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 SEC14L3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEC14L3 survival associations across molecular data types. SEC14L3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEC14L3 RNA expression–survival associations across cancer types. High SEC14L3 expression shows unfavorable associations in KIRC, ACC, COAD, LGG and LUSC, but favorable associations in LIHC. The KIRC 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 KIRC as the clearest survival context for SEC14L3 RNA expression.
This table summarizes SEC14L3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SEC14L3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEC14L3 shows lower tumor expression in THCA, LUSC, LUAD and CHOL and higher tumor expression in KIRC and BLCA. The THCA box plot shows higher SEC14L3 RNA expression in normal versus tumor tissue (log2 FC = −1.269, t-test p < 0.001).
This table shows molecular features associated with SEC14L3 in patient tissues and cancer cell lines. In patient samples, SEC14L3 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, SEC14L3 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 BONE and LARGE_INTESTINE.
