Q-omics provides the consensus-scored ASCL1 profile across patient tissues and cancer cell-line models. ASCL1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ASCL1 is differentially expressed in 9, with the highest sampling consensus in BRCA. Additionally, ASCL1 RNA expression shows 12,382 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, BRCA, and GBM as cancer lineages where ASCL1 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 ASCL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ASCL1 survival associations across molecular data types. ASCL1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) 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 ASCL1 RNA expression–survival associations across cancer types. High ASCL1 expression shows unfavorable associations in KIRP, KIRC, LUSC and OV, but favorable associations in READ and UCS. The KIRP 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 KIRP as the clearest survival context for ASCL1 RNA expression.
This table summarizes ASCL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for ASCL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ASCL1 shows lower tumor expression in COAD, LIHC and THCA and higher tumor expression in BRCA, KICH and KIRC. The BRCA box plot shows higher ASCL1 RNA expression in tumor versus normal tissue (log2 FC = +0.902, t-test p < 0.001).
This table shows molecular features associated with ASCL1 in patient tissues and cancer cell lines. In patient samples, ASCL1 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, ASCL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and LUNG_SCLC.
