Q-omics provides the consensus-scored AZI2 profile across patient tissues and cancer cell-line models. AZI2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, AZI2 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, AZI2 RNA expression shows 20,138 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight BLCA, KIRC, and ACC as cancer lineages where AZI2 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 AZI2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AZI2 survival associations across molecular data types. AZI2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AZI2 RNA expression–survival associations across cancer types. High AZI2 expression shows unfavorable associations in BLCA, ACC, CESC and LIHC, but favorable associations in KIRC and UCS. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify BLCA as the clearest survival context for AZI2 RNA expression.
This table summarizes AZI2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for AZI2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AZI2 shows lower tumor expression in KIRC, THCA, LUSC, KICH and LUAD and higher tumor expression in LIHC. The KIRC box plot shows higher AZI2 RNA expression in normal versus tumor tissue (log2 FC = −0.621, t-test p < 0.001).
This table shows molecular features associated with AZI2 in patient tissues and cancer cell lines. In patient samples, AZI2 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, AZI2 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_Lymphoma and OESOPHAGUS.
