Q-omics provides the consensus-scored PBX2 profile across patient tissues and cancer cell-line models. PBX2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, PBX2 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PBX2 RNA expression shows 20,313 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UCS, KIRC, and ACC as cancer lineages where PBX2 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 PBX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PBX2 survival associations across molecular data types. PBX2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PBX2 RNA expression–survival associations across cancer types. High PBX2 expression shows unfavorable associations in COAD, ACC and UCEC, but favorable associations in UCS, OV and THYM. The UCS 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 UCS as the clearest survival context for PBX2 RNA expression.
This table summarizes PBX2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PBX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PBX2 shows lower tumor expression in KICH and UCEC and higher tumor expression in KIRC, HNSC, LIHC and KIRP. The KIRC box plot shows higher PBX2 RNA expression in tumor versus normal tissue (log2 FC = +0.660, t-test p < 0.001).
This table shows molecular features associated with PBX2 in patient tissues and cancer cell lines. In patient samples, PBX2 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, PBX2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
