Q-omics provides the consensus-scored SEC14L6 profile across patient tissues and cancer cell-line models. SEC14L6 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, SEC14L6 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, SEC14L6 RNA expression shows 16,615 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LGG, KIRC, and LSCC as cancer lineages where SEC14L6 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 SEC14L6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEC14L6 survival associations across molecular data types. SEC14L6 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEC14L6 RNA expression–survival associations across cancer types. High SEC14L6 expression shows unfavorable associations in LGG, UVM, LUSC and LIHC, but favorable associations in KIRC and CESC. The LGG 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 LGG as the clearest survival context for SEC14L6 RNA expression.
This table summarizes SEC14L6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SEC14L6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEC14L6 shows lower tumor expression in KICH, COAD, LUSC and LUAD and higher tumor expression in KIRC and THCA. The KIRC box plot shows higher SEC14L6 RNA expression in tumor versus normal tissue (log2 FC = +0.948, t-test p < 0.001).
This table shows molecular features associated with SEC14L6 in patient tissues and cancer cell lines. In patient samples, SEC14L6 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SEC14L6 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 SKIN and BLOOD_Leukemia.
