insulin like growth factor binding protein 2Genealiases: IBP2 · IGF-BP53
Q-omics provides the consensus-scored IGFBP2 profile across patient tissues and cancer cell-line models. IGFBP2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, IGFBP2 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, IGFBP2 protein abundance shows 16,163 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where IGFBP2 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 IGFBP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGFBP2 survival associations across molecular data types. IGFBP2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IGFBP2 RNA expression–survival associations across cancer types. High IGFBP2 expression shows unfavorable associations in UVM, KIRP, LGG, UCS and MESO, but favorable associations in PAAD. The UVM 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 UVM as the clearest survival context for IGFBP2 RNA expression.
This table summarizes IGFBP2 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 6. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for IGFBP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGFBP2 shows lower tumor expression in KIRC, KICH and KIRP and higher tumor expression in HNSC, THCA and LUSC. The KIRC box plot shows higher IGFBP2 RNA expression in normal versus tumor tissue (log2 FC = −2.878, t-test p < 0.001).
This table shows molecular features associated with IGFBP2 in patient tissues and cancer cell lines. In patient samples, IGFBP2 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, IGFBP2 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 UPPER_AERODIGESTIVE_TRACT and BONE.
