Q-omics provides the consensus-scored RASA4B profile across patient tissues and cancer cell-line models. RASA4B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, RASA4B is differentially expressed in 7, with the highest sampling consensus in UCEC. Additionally, RASA4B RNA expression shows 11,975 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight DLBC, UCEC, and THYM as cancer lineages where RASA4B 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 RASA4B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RASA4B survival associations across molecular data types. RASA4B RNA expression shows survival associations in the most cancer types (24), followed by 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 RASA4B RNA expression–survival associations across cancer types. High RASA4B expression shows unfavorable associations in ACC, STAD, KIRP and THCA, but favorable associations in DLBC and PAAD. The DLBC 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 DLBC as the clearest survival context for RASA4B RNA expression.
This table summarizes RASA4B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 3. The strongest signals are observed in UCEC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for RASA4B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RASA4B shows lower tumor expression in UCEC, BRCA, KICH and LUSC and higher tumor expression in LIHC and THCA. The UCEC box plot shows higher RASA4B RNA expression in normal versus tumor tissue (log2 FC = −0.184, t-test p < 0.001).
This table shows molecular features associated with RASA4B in patient tissues and cancer cell lines. In patient samples, RASA4B shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, RASA4B 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 CNS and UPPER_AERODIGESTIVE_TRACT.
