Q-omics provides the consensus-scored UBAP2 profile across patient tissues and cancer cell-line models. UBAP2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, UBAP2 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, UBAP2 RNA expression shows 21,206 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where UBAP2 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 UBAP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UBAP2 survival associations across molecular data types. UBAP2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 UBAP2 RNA expression–survival associations across cancer types. High UBAP2 expression shows unfavorable associations in ACC, LIHC, BLCA and KICH, but favorable associations in KIRC and OV. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for UBAP2 RNA expression.
This table summarizes UBAP2 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 7. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for UBAP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UBAP2 shows lower tumor expression in THCA and higher tumor expression in COAD, STAD, BLCA, LIHC and HNSC. The COAD box plot shows higher UBAP2 RNA expression in tumor versus normal tissue (log2 FC = +0.980, t-test p < 0.001).
This table shows molecular features associated with UBAP2 in patient tissues and cancer cell lines. In patient samples, UBAP2 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, UBAP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Lymphoma.
