Q-omics provides the consensus-scored SEPTIN14 profile across patient tissues and cancer cell-line models. SEPTIN14 expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, SEPTIN14 is differentially expressed in 4, with the highest sampling consensus in THCA. Additionally, SEPTIN14 RNA expression shows 6,811 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LGG, THCA, and TGCT as cancer lineages where SEPTIN14 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 SEPTIN14 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEPTIN14 survival associations across molecular data types. SEPTIN14 RNA expression shows survival associations in the most cancer types (15), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEPTIN14 RNA expression–survival associations across cancer types. High SEPTIN14 expression shows unfavorable associations in LGG, KIRC, ACC and SCLC, but favorable associations in PAAD and CHOL. 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 SEPTIN14 RNA expression.
This table summarizes SEPTIN14 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SEPTIN14. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEPTIN14 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC and LUSC. The THCA box plot shows higher SEPTIN14 RNA expression in normal versus tumor tissue (log2 FC = −0.024, t-test p = .001).
This table shows molecular features associated with SEPTIN14 in patient tissues and cancer cell lines. In patient samples, SEPTIN14 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SEPTIN14 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
