ribosome production factor 2 homologGenealiases: BXDC1 · bA397G5.4
Q-omics provides the consensus-scored RPF2 profile across patient tissues and cancer cell-line models. RPF2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, RPF2 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, RPF2 protein abundance shows 22,038 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight HNSC, KIRC, and LUAD as cancer lineages where RPF2 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 RPF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RPF2 survival associations across molecular data types. RPF2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) 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 RPF2 RNA expression–survival associations across cancer types. High RPF2 expression shows unfavorable associations in HNSC, LIHC, KIRP, ACC, BRCA and KICH. The HNSC 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 HNSC as the clearest survival context for RPF2 RNA expression.
This table summarizes RPF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RPF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RPF2 shows higher tumor expression in KIRC, STAD, HNSC, COAD, LIHC and LUAD. The KIRC box plot shows higher RPF2 RNA expression in tumor versus normal tissue (log2 FC = +1.021, t-test p < 0.001).
This table shows molecular features associated with RPF2 in patient tissues and cancer cell lines. In patient samples, RPF2 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, RPF2 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 SKIN and BLOOD_Leukemia.
