Q-omics provides the consensus-scored IFI27L1 profile across patient tissues and cancer cell-line models. IFI27L1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, IFI27L1 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, IFI27L1 RNA expression shows 17,112 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where IFI27L1 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 IFI27L1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IFI27L1 survival associations across molecular data types. IFI27L1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible IFI27L1 RNA expression–survival associations across cancer types. High IFI27L1 expression shows unfavorable associations in ACC, UVM, LGG and LIHC, but favorable associations in READ and MESO. The ACC 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 ACC as the clearest survival context for IFI27L1 RNA expression.
This table summarizes IFI27L1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for IFI27L1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IFI27L1 shows lower tumor expression in LUAD and KICH and higher tumor expression in LIHC, HNSC, KIRP and ESCA. The LIHC box plot shows higher IFI27L1 RNA expression in tumor versus normal tissue (log2 FC = +1.253, t-test p < 0.001).
This table shows molecular features associated with IFI27L1 in patient tissues and cancer cell lines. In patient samples, IFI27L1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, IFI27L1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia.
