Q-omics provides the consensus-scored ASIC1 profile across patient tissues and cancer cell-line models. ASIC1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ASIC1 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, ASIC1 RNA expression shows 17,645 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRP, COAD, and THYM as cancer lineages where ASIC1 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 ASIC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ASIC1 survival associations across molecular data types. ASIC1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ASIC1 RNA expression–survival associations across cancer types. High ASIC1 expression shows unfavorable associations in KIRP, KIRC, ACC, UVM and BLCA, but favorable associations in LGG. 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 ASIC1 RNA expression.
This table summarizes ASIC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 3. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ASIC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ASIC1 shows lower tumor expression in KIRC and higher tumor expression in COAD, LUAD, LUSC, LIHC and KICH. The COAD box plot shows higher ASIC1 RNA expression in tumor versus normal tissue (log2 FC = +2.405, t-test p < 0.001).
This table shows molecular features associated with ASIC1 in patient tissues and cancer cell lines. In patient samples, ASIC1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ASIC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and OVARY.
