Q-omics provides the consensus-scored ABO profile across patient tissues and cancer cell-line models. ABO expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ABO is differentially expressed in 15, with the highest sampling consensus in KICH. Additionally, ABO RNA expression shows 16,800 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, KICH, and THYM as cancer lineages where ABO 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 ABO — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABO survival associations across molecular data types. ABO RNA expression shows survival associations in the most cancer types (29), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ABO RNA expression–survival associations across cancer types. High ABO expression shows unfavorable associations in UVM, but favorable associations in HNSC, KIRC, CESC, BRCA and LGG. The HNSC 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 HNSC as the clearest survival context for ABO RNA expression.
This table summarizes ABO 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 4. The strongest signals are observed in KICH for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ABO. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABO shows lower tumor expression in KICH, KIRC, LUSC, THCA, UCEC and BRCA. The KICH box plot shows higher ABO RNA expression in normal versus tumor tissue (log2 FC = −3.815, t-test p < 0.001).
This table shows molecular features associated with ABO in patient tissues and cancer cell lines. In patient samples, ABO 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, ABO RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BONE and LUNG_NSCLC_LUAD.
