Q-omics provides the consensus-scored ANAPC1P2 profile across patient tissues and cancer cell-line models. ANAPC1P2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ANAPC1P2 is differentially expressed in 7, with the highest sampling consensus in KIRC. Additionally, ANAPC1P2 RNA expression shows 18,850 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where ANAPC1P2 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 ANAPC1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ANAPC1P2 survival associations across molecular data types. ANAPC1P2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ANAPC1P2 RNA expression–survival associations across cancer types. High ANAPC1P2 expression shows unfavorable associations in ACC, COAD and ESCA, but favorable associations in KIRC, SKCM and HNSC. 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 ANAPC1P2 RNA expression.
This table summarizes ANAPC1P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for ANAPC1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ANAPC1P2 shows lower tumor expression in BRCA, THCA and KICH and higher tumor expression in KIRC, COAD and LUSC. The KIRC box plot shows higher ANAPC1P2 RNA expression in tumor versus normal tissue (log2 FC = +0.635, t-test p < 0.001).
This table shows molecular features associated with ANAPC1P2 in patient tissues and cancer cell lines. In patient samples, ANAPC1P2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ANAPC1P2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SKIN.
