Q-omics provides the consensus-scored RBM17 profile across patient tissues and cancer cell-line models. RBM17 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RBM17 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, RBM17 protein abundance shows 38,631 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where RBM17 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 RBM17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RBM17 survival associations across molecular data types. RBM17 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RBM17 RNA expression–survival associations across cancer types. High RBM17 expression shows unfavorable associations in ACC, LIHC, KIRP, COAD and KIRC, but favorable associations in LGG. 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 RBM17 RNA expression.
This table summarizes RBM17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for RBM17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RBM17 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, STAD, COAD and BLCA. The HNSC box plot shows higher RBM17 RNA expression in tumor versus normal tissue (log2 FC = +0.881, t-test p < 0.001).
This table shows molecular features associated with RBM17 in patient tissues and cancer cell lines. In patient samples, RBM17 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, RBM17 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 BLOOD_Lymphoma.
