Q-omics provides the consensus-scored FBP2 profile across patient tissues and cancer cell-line models. FBP2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, FBP2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, FBP2 protein abundance shows 30,886 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, HNSC, and GBM as cancer lineages where FBP2 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 FBP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FBP2 survival associations across molecular data types. FBP2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (9) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FBP2 RNA expression–survival associations across cancer types. High FBP2 expression shows unfavorable associations in LGG and MESO, but favorable associations in LUAD, UVM, BLCA and READ. The LUAD 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 LUAD as the clearest survival context for FBP2 RNA expression.
This table summarizes FBP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 12. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for FBP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FBP2 shows lower tumor expression in HNSC, KIRC and KICH and higher tumor expression in UCEC, LIHC and READ. The HNSC box plot shows higher FBP2 RNA expression in normal versus tumor tissue (log2 FC = −2.047, t-test p < 0.001).
This table shows molecular features associated with FBP2 in patient tissues and cancer cell lines. In patient samples, FBP2 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, FBP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and KIDNEY.
