Q-omics provides the consensus-scored SEC23A-AS1 profile across patient tissues and cancer cell-line models. SEC23A-AS1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, SEC23A-AS1 is differentially expressed in 3, with the highest sampling consensus in LIHC. Additionally, SEC23A-AS1 RNA expression shows 6,336 significant gene co-expression associations, with the highest sampling consensus in DLBC. Together, these results highlight UCS, LIHC, and DLBC as cancer lineages where SEC23A-AS1 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 SEC23A-AS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEC23A-AS1 survival associations across molecular data types. SEC23A-AS1 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEC23A-AS1 RNA expression–survival associations across cancer types. High SEC23A-AS1 expression shows unfavorable associations in UCS, TGCT, LUSC and LAML, but favorable associations in LUAD and PAAD. The UCS Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .009). Together, the overview and detailed table identify UCS as the clearest survival context for SEC23A-AS1 RNA expression.
This table summarizes SEC23A-AS1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for SEC23A-AS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEC23A-AS1 shows lower tumor expression in KIRP and higher tumor expression in LIHC and PRAD. The LIHC box plot shows higher SEC23A-AS1 RNA expression in tumor versus normal tissue (log2 FC = +0.103, t-test p < 0.001).
This table shows molecular features associated with SEC23A-AS1 in patient tissues and cancer cell lines. In patient samples, SEC23A-AS1 shows the broadest associations at the RNA and protein expression levels, with DLBC recurring as the lineage with the largest associated feature set.
