Q-omics provides the consensus-scored ITGA9 profile across patient tissues and cancer cell-line models. ITGA9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ITGA9 is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, ITGA9 RNA expression shows 24,220 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, BLCA, and LUAD as cancer lineages where ITGA9 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 ITGA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ITGA9 survival associations across molecular data types. ITGA9 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ITGA9 RNA expression–survival associations across cancer types. High ITGA9 expression shows unfavorable associations in ACC, COAD and KIRP, but favorable associations in KIRC, HNSC and BRCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for ITGA9 RNA expression.
This table summarizes ITGA9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ITGA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ITGA9 shows lower tumor expression in BLCA, KIRP, LUSC, LIHC, LUAD and BRCA. The BLCA box plot shows higher ITGA9 RNA expression in normal versus tumor tissue (log2 FC = −2.622, t-test p < 0.001).
This table shows molecular features associated with ITGA9 in patient tissues and cancer cell lines. In patient samples, ITGA9 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, ITGA9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
