adaptor related protein complex 2 subunit sigma 1Genealiases: AP17 · CLAPS2 · FBH3 · FBHOk · HHC3
Q-omics provides the consensus-scored AP2S1 profile across patient tissues and cancer cell-line models. AP2S1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AP2S1 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, AP2S1 protein abundance shows 27,738 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where AP2S1 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 AP2S1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AP2S1 survival associations across molecular data types. AP2S1 RNA expression shows survival associations in the most cancer types (28), followed by mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AP2S1 RNA expression–survival associations across cancer types. High AP2S1 expression shows unfavorable associations in ACC, UVM, HNSC, MESO, LIHC and LUAD. The ACC 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 ACC as the clearest survival context for AP2S1 RNA expression.
This table summarizes AP2S1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AP2S1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AP2S1 shows higher tumor expression in KIRC, HNSC, BLCA, COAD, STAD and LUSC. The KIRC box plot shows higher AP2S1 RNA expression in tumor versus normal tissue (log2 FC = +0.769, t-test p < 0.001).
This table shows molecular features associated with AP2S1 in patient tissues and cancer cell lines. In patient samples, AP2S1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, AP2S1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and SOFT_TISSUE.
