IGF like family member 1Genealiases: APRG644 · UNQ644
Q-omics provides the consensus-scored IGFL1 profile across patient tissues and cancer cell-line models. IGFL1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, IGFL1 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, IGFL1 RNA expression shows 9,142 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight SKCM, COAD, and ESCA as cancer lineages where IGFL1 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 IGFL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGFL1 survival associations across molecular data types. IGFL1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IGFL1 RNA expression–survival associations across cancer types. High IGFL1 expression shows unfavorable associations in SKCM, HNSC, PAAD, UVM, LIHC and COAD. The SKCM 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 SKCM as the clearest survival context for IGFL1 RNA expression.
This table summarizes IGFL1 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 2. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IGFL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGFL1 shows lower tumor expression in KIRP and higher tumor expression in COAD, THCA, BLCA, LUSC and UCEC. The COAD box plot shows higher IGFL1 RNA expression in tumor versus normal tissue (log2 FC = +0.829, t-test p < 0.001).
This table shows molecular features associated with IGFL1 in patient tissues and cancer cell lines. In patient samples, IGFL1 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, IGFL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and URINARY_TRACT.
