acidic nuclear phosphoprotein 32 family member BGenealiases: APRIL · PHAPI2 · SSP29
Q-omics provides the consensus-scored ANP32B profile across patient tissues and cancer cell-line models. ANP32B 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, ANP32B is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, ANP32B protein abundance shows 26,546 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where ANP32B 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 ANP32B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ANP32B survival associations across molecular data types. ANP32B RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ANP32B RNA expression–survival associations across cancer types. High ANP32B expression shows unfavorable associations in ACC, LUAD, KIRP, MESO and LIHC, but favorable associations in KIRC. 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 ANP32B RNA expression.
This table summarizes ANP32B 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 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ANP32B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ANP32B shows higher tumor expression in HNSC, COAD, LUSC, STAD, LIHC and KIRP. The HNSC box plot shows higher ANP32B RNA expression in tumor versus normal tissue (log2 FC = +1.329, t-test p < 0.001).
This table shows molecular features associated with ANP32B in patient tissues and cancer cell lines. In patient samples, ANP32B shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ANP32B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
