Q-omics provides the consensus-scored RBPMS2 profile across patient tissues and cancer cell-line models. RBPMS2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, RBPMS2 is differentially expressed in 16, with the highest sampling consensus in BLCA. Additionally, RBPMS2 RNA expression shows 16,974 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and BLCA as cancer lineages where RBPMS2 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 RBPMS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RBPMS2 survival associations across molecular data types. RBPMS2 RNA expression shows survival associations in the most cancer types (24), 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 RBPMS2 RNA expression–survival associations across cancer types. High RBPMS2 expression shows unfavorable associations in ACC, UVM and LGG, but favorable associations in KIRC, KIRP and THCA. 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 RBPMS2 RNA expression.
This table summarizes RBPMS2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 5. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RBPMS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RBPMS2 shows lower tumor expression in BLCA, COAD, THCA, KIRP and STAD and higher tumor expression in LIHC. The BLCA box plot shows higher RBPMS2 RNA expression in normal versus tumor tissue (log2 FC = −4.692, t-test p < 0.001).
This table shows molecular features associated with RBPMS2 in patient tissues and cancer cell lines. In patient samples, RBPMS2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, RBPMS2 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 BONE and SOFT_TISSUE.
