Q-omics provides the consensus-scored SEC22C profile across patient tissues and cancer cell-line models. SEC22C expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SEC22C is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SEC22C RNA expression shows 20,364 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where SEC22C 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 SEC22C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEC22C survival associations across molecular data types. SEC22C RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEC22C RNA expression–survival associations across cancer types. High SEC22C expression shows unfavorable associations in LIHC, BLCA, LUSC and ACC, but favorable associations in KIRC and SKCM. The LIHC 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 LIHC as the clearest survival context for SEC22C RNA expression.
This table summarizes SEC22C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SEC22C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEC22C shows lower tumor expression in THCA, KIRC, LUSC and LUAD and higher tumor expression in HNSC and LIHC. The HNSC box plot shows higher SEC22C RNA expression in tumor versus normal tissue (log2 FC = +0.654, t-test p < 0.001).
This table shows molecular features associated with SEC22C in patient tissues and cancer cell lines. In patient samples, SEC22C 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, SEC22C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
