Q-omics provides the consensus-scored RBSN profile across patient tissues and cancer cell-line models. RBSN expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, RBSN is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, RBSN protein abundance shows 30,767 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KICH, LIHC, and LUAD as cancer lineages where RBSN 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 RBSN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RBSN survival associations across molecular data types. RBSN RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RBSN RNA expression–survival associations across cancer types. High RBSN expression shows unfavorable associations in KICH, ACC and LUSC, but favorable associations in HNSC, KIRC and LGG. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KICH as the clearest survival context for RBSN RNA expression.
This table summarizes RBSN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RBSN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RBSN shows lower tumor expression in LUAD, LUSC, KICH, THCA and BRCA and higher tumor expression in LIHC. The LIHC box plot shows higher RBSN RNA expression in tumor versus normal tissue (log2 FC = +0.908, t-test p < 0.001).
This table shows molecular features associated with RBSN in patient tissues and cancer cell lines. In patient samples, RBSN shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, RBSN 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 CNS and UPPER_AERODIGESTIVE_TRACT.
