Q-omics provides the consensus-scored RRM2B profile across patient tissues and cancer cell-line models. RRM2B expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, RRM2B is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, RRM2B protein abundance shows 21,887 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, LIHC, and GBM as cancer lineages where RRM2B 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 RRM2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RRM2B survival associations across molecular data types. RRM2B RNA expression shows survival associations in the most cancer types (18), followed by mutation status (5) 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 RRM2B RNA expression–survival associations across cancer types. High RRM2B expression shows unfavorable associations in UVM, LGG and BRCA, but favorable associations in KIRC, COAD and LUAD. 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 RRM2B RNA expression.
This table summarizes RRM2B 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 4. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RRM2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RRM2B shows lower tumor expression in LUSC and LUAD and higher tumor expression in LIHC, HNSC, STAD and CHOL. The LIHC box plot shows higher RRM2B RNA expression in tumor versus normal tissue (log2 FC = +1.180, t-test p < 0.001).
This table shows molecular features associated with RRM2B in patient tissues and cancer cell lines. In patient samples, RRM2B 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, RRM2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and UPPER_AERODIGESTIVE_TRACT.
