mitochondrial ribosomal protein L9Genealiases: L9mt · bL9m
Q-omics provides the consensus-scored MRPL9 profile across patient tissues and cancer cell-line models. MRPL9 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, MRPL9 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, MRPL9 protein abundance shows 23,060 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, HNSC, and LSCC as cancer lineages where MRPL9 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 MRPL9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRPL9 survival associations across molecular data types. MRPL9 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) 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 MRPL9 RNA expression–survival associations across cancer types. High MRPL9 expression shows unfavorable associations in KIRP, ACC, LIHC, KICH, MESO and LGG. The KIRP 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 KIRP as the clearest survival context for MRPL9 RNA expression.
This table summarizes MRPL9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MRPL9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRPL9 shows higher tumor expression in HNSC, KIRC, LUAD, COAD, BLCA and LIHC. The HNSC box plot shows higher MRPL9 RNA expression in tumor versus normal tissue (log2 FC = +0.915, t-test p < 0.001).
This table shows molecular features associated with MRPL9 in patient tissues and cancer cell lines. In patient samples, MRPL9 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, MRPL9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and PANCREAS.
