Q-omics provides the consensus-scored ITGA2 profile across patient tissues and cancer cell-line models. ITGA2 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, ITGA2 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, ITGA2 RNA expression shows 19,676 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, THCA, and THYM as cancer lineages where ITGA2 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 ITGA2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ITGA2 survival associations across molecular data types. ITGA2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) 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 ITGA2 RNA expression–survival associations across cancer types. High ITGA2 expression shows unfavorable associations in MESO, UVM, KIRP, ACC and PAAD, but favorable associations in KIRC. 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 ITGA2 RNA expression.
This table summarizes ITGA2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ITGA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ITGA2 shows lower tumor expression in KIRC and KICH and higher tumor expression in THCA, COAD, HNSC and LIHC. The THCA box plot shows higher ITGA2 RNA expression in tumor versus normal tissue (log2 FC = +2.845, t-test p < 0.001).
This table shows molecular features associated with ITGA2 in patient tissues and cancer cell lines. In patient samples, ITGA2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ITGA2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and SKIN.
