Q-omics provides the consensus-scored UBALD2 profile across patient tissues and cancer cell-line models. UBALD2 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, UBALD2 is differentially expressed in 14, with the highest sampling consensus in LIHC. Additionally, UBALD2 RNA expression shows 18,898 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight ACC, LIHC, and THYM as cancer lineages where UBALD2 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 UBALD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UBALD2 survival associations across molecular data types. UBALD2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) 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 UBALD2 RNA expression–survival associations across cancer types. High UBALD2 expression shows unfavorable associations in ACC, LIHC, UCS, LGG and LUAD, but favorable associations in CESC. 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 UBALD2 RNA expression.
This table summarizes UBALD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 2. The strongest signals are observed in LIHC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for UBALD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. UBALD2 shows higher tumor expression in LIHC, LUAD, BLCA, LUSC, HNSC and COAD. The LIHC box plot shows higher UBALD2 RNA expression in tumor versus normal tissue (log2 FC = +1.275, t-test p < 0.001).
This table shows molecular features associated with UBALD2 in patient tissues and cancer cell lines. In patient samples, UBALD2 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, UBALD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_SCLC.
