unconventional SNARE in the ER 1Genealiases: D12 · MDS032 · P31 · SLT1
Q-omics provides the consensus-scored USE1 profile across patient tissues and cancer cell-line models. USE1 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, USE1 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, USE1 protein abundance shows 23,149 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, KIRC, and PDAC as cancer lineages where USE1 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 USE1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes USE1 survival associations across molecular data types. USE1 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible USE1 RNA expression–survival associations across cancer types. High USE1 expression shows unfavorable associations in ACC, COAD, STAD and UCEC, but favorable associations in DLBC and ESCA. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify ACC as the clearest survival context for USE1 RNA expression.
This table summarizes USE1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 9. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for USE1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. USE1 shows lower tumor expression in KICH and higher tumor expression in KIRC, LIHC, COAD, ESCA and LUSC. The KIRC box plot shows higher USE1 RNA expression in tumor versus normal tissue (log2 FC = +0.893, t-test p < 0.001).
This table shows molecular features associated with USE1 in patient tissues and cancer cell lines. In patient samples, USE1 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, USE1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
