ribosomal protein L23aGenealiases: L23A · MDA20 · uL23
Q-omics provides the consensus-scored RPL23A profile across patient tissues and cancer cell-line models. RPL23A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RPL23A is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, RPL23A protein abundance shows 18,895 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where RPL23A 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 RPL23A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPL23A survival associations across molecular data types. RPL23A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RPL23A RNA expression–survival associations across cancer types. High RPL23A expression shows unfavorable associations in ACC, KIRP, LIHC, OV, SCLC and KICH. 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 RPL23A RNA expression.
This table summarizes RPL23A 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPL23A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPL23A shows lower tumor expression in KICH and higher tumor expression in KIRC, KIRP, COAD, LIHC and CHOL. The KIRC box plot shows higher RPL23A RNA expression in tumor versus normal tissue (log2 FC = +1.039, t-test p < 0.001).
This table shows molecular features associated with RPL23A in patient tissues and cancer cell lines. In patient samples, RPL23A shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, RPL23A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and CNS.
