Q-omics provides the consensus-scored ACRBP profile across patient tissues and cancer cell-line models. ACRBP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ACRBP is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, ACRBP RNA expression shows 17,959 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, KIRC, and TGCT as cancer lineages where ACRBP 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 ACRBP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACRBP survival associations across molecular data types. ACRBP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) 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 ACRBP RNA expression–survival associations across cancer types. High ACRBP expression shows unfavorable associations in UVM and LGG, but favorable associations in SKCM, HNSC, KIRC and CESC. The UVM 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 UVM as the clearest survival context for ACRBP RNA expression.
This table summarizes ACRBP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACRBP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACRBP shows lower tumor expression in KICH, THCA and LUSC and higher tumor expression in KIRC, KIRP and STAD. The KIRC box plot shows higher ACRBP RNA expression in tumor versus normal tissue (log2 FC = +1.295, t-test p < 0.001).
This table shows molecular features associated with ACRBP in patient tissues and cancer cell lines. In patient samples, ACRBP shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ACRBP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BONE.
