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Q-omics provides the consensus-scored RSBN1L profile across patient tissues and cancer cell-line models. RSBN1L expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RSBN1L is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, RSBN1L protein abundance shows 23,044 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where RSBN1L 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 RSBN1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RSBN1L survival associations across molecular data types. RSBN1L RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RSBN1L RNA expression–survival associations across cancer types. High RSBN1L expression shows favorable associations in KIRC, UCS, BLCA, LUAD, BRCA and THYM. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for RSBN1L RNA expression.
This table summarizes RSBN1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RSBN1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RSBN1L shows lower tumor expression in THCA and higher tumor expression in KIRC, LIHC, BRCA, CHOL and HNSC. The KIRC box plot shows higher RSBN1L RNA expression in tumor versus normal tissue (log2 FC = +0.361, t-test p < 0.001).
This table shows molecular features associated with RSBN1L in patient tissues and cancer cell lines. In patient samples, RSBN1L 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, RSBN1L 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 BLOOD_Leukemia and BLOOD_Lymphoma.
