Q-omics provides the consensus-scored ACTBL2 profile across patient tissues and cancer cell-line models. ACTBL2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ACTBL2 is differentially expressed in 8, with the highest sampling consensus in THCA. Additionally, ACTBL2 protein abundance shows 29,930 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, THCA, and LSCC as cancer lineages where ACTBL2 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 ACTBL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTBL2 survival associations across molecular data types. ACTBL2 RNA expression shows survival associations in the most cancer types (22), 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 ACTBL2 RNA expression–survival associations across cancer types. High ACTBL2 expression shows unfavorable associations in KIRP, OV, HNSC, PAAD, KIRC and MESO. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify KIRP as the clearest survival context for ACTBL2 RNA expression.
This table summarizes ACTBL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ACTBL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTBL2 shows lower tumor expression in BRCA and higher tumor expression in THCA, LUAD, HNSC, STAD and BLCA. The THCA box plot shows higher ACTBL2 RNA expression in tumor versus normal tissue (log2 FC = +1.341, t-test p < 0.001).
This table shows molecular features associated with ACTBL2 in patient tissues and cancer cell lines. In patient samples, ACTBL2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ACTBL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BREAST.
