Q-omics provides the consensus-scored ANXA9 profile across patient tissues and cancer cell-line models. ANXA9 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ANXA9 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ANXA9 RNA expression shows 19,999 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, and UVM as cancer lineages where ANXA9 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 ANXA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ANXA9 survival associations across molecular data types. ANXA9 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 ANXA9 RNA expression–survival associations across cancer types. High ANXA9 expression shows unfavorable associations in COAD, LIHC and LUAD, but favorable associations in HNSC, MESO and KIRC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for ANXA9 RNA expression.
This table summarizes ANXA9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ANXA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ANXA9 shows lower tumor expression in HNSC, KIRC, KIRP, THCA and KICH and higher tumor expression in LIHC. The HNSC box plot shows higher ANXA9 RNA expression in normal versus tumor tissue (log2 FC = −2.795, t-test p < 0.001).
This table shows molecular features associated with ANXA9 in patient tissues and cancer cell lines. In patient samples, ANXA9 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ANXA9 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 LUNG_NSCLC_LUAD and BREAST.
