Q-omics provides the consensus-scored IGF1R profile across patient tissues and cancer cell-line models. IGF1R expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, IGF1R is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, IGF1R protein abundance shows 27,843 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UCS, HNSC, and LSCC as cancer lineages where IGF1R 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 IGF1R — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGF1R survival associations across molecular data types. IGF1R RNA expression shows survival associations in the most cancer types (22), followed by mutation status (11) 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 IGF1R RNA expression–survival associations across cancer types. High IGF1R expression shows unfavorable associations in MESO, ACC and COAD, but favorable associations in UCS, BRCA and KIRC. The UCS 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 UCS as the clearest survival context for IGF1R RNA expression.
This table summarizes IGF1R tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IGF1R. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGF1R shows lower tumor expression in UCEC and higher tumor expression in HNSC, LUSC, BRCA, COAD and CHOL. The HNSC box plot shows higher IGF1R RNA expression in tumor versus normal tissue (log2 FC = +1.572, t-test p < 0.001).
This table shows molecular features associated with IGF1R in patient tissues and cancer cell lines. In patient samples, IGF1R shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, IGF1R RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BONE.
