Q-omics provides the consensus-scored RBM19 profile across patient tissues and cancer cell-line models. RBM19 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, RBM19 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, RBM19 protein abundance shows 35,535 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, HNSC, and LSCC as cancer lineages where RBM19 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 RBM19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RBM19 survival associations across molecular data types. RBM19 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RBM19 RNA expression–survival associations across cancer types. High RBM19 expression shows unfavorable associations in LIHC, MESO, HNSC, LGG, COAD and KICH. 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 RBM19 RNA expression.
This table summarizes RBM19 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RBM19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RBM19 shows higher tumor expression in HNSC, KIRP, COAD, KIRC, LIHC and BLCA. The HNSC box plot shows higher RBM19 RNA expression in tumor versus normal tissue (log2 FC = +1.209, t-test p < 0.001).
This table shows molecular features associated with RBM19 in patient tissues and cancer cell lines. In patient samples, RBM19 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, RBM19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and SKIN.
