Q-omics provides the consensus-scored MRPS23 profile across patient tissues and cancer cell-line models. MRPS23 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, MRPS23 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, MRPS23 protein abundance shows 19,761 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, HNSC, and LSCC as cancer lineages where MRPS23 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 MRPS23 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRPS23 survival associations across molecular data types. MRPS23 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) 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 MRPS23 RNA expression–survival associations across cancer types. High MRPS23 expression shows unfavorable associations in LIHC, HNSC, KICH, UVM, UCS and SCLC. The LIHC 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 LIHC as the clearest survival context for MRPS23 RNA expression.
This table summarizes MRPS23 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MRPS23. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRPS23 shows higher tumor expression in HNSC, COAD, KIRP, LIHC, LUAD and BLCA. The HNSC box plot shows higher MRPS23 RNA expression in tumor versus normal tissue (log2 FC = +0.919, t-test p < 0.001).
This table shows molecular features associated with MRPS23 in patient tissues and cancer cell lines. In patient samples, MRPS23 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, MRPS23 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 BONE and BLOOD_Lymphoma.
