Q-omics provides the consensus-scored MRPS9 profile across patient tissues and cancer cell-line models. MRPS9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, MRPS9 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, MRPS9 protein abundance shows 25,372 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LUAD, LIHC, and LSCC as cancer lineages where MRPS9 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 MRPS9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MRPS9 survival associations across molecular data types. MRPS9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MRPS9 RNA expression–survival associations across cancer types. High MRPS9 expression shows unfavorable associations in LUAD, ACC, LIHC, KICH and UCS, but favorable associations in KIRC. The LUAD 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 LUAD as the clearest survival context for MRPS9 RNA expression.
This table summarizes MRPS9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 10. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MRPS9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MRPS9 shows lower tumor expression in KICH and higher tumor expression in LIHC, HNSC, LUAD, LUSC and STAD. The LIHC box plot shows higher MRPS9 RNA expression in tumor versus normal tissue (log2 FC = +0.794, t-test p < 0.001).
This table shows molecular features associated with MRPS9 in patient tissues and cancer cell lines. In patient samples, MRPS9 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, MRPS9 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 SOFT_TISSUE.
