Q-omics provides the consensus-scored TGIF2LY profile across patient tissues and cancer cell-line models. TGIF2LY expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, TGIF2LY is differentially expressed in 1, with the highest sampling consensus in LIHC. Additionally, TGIF2LY RNA expression shows 7,650 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LUSC, LIHC, and TGCT as cancer lineages where TGIF2LY 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 TGIF2LY — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TGIF2LY survival associations across molecular data types. TGIF2LY RNA expression shows survival associations in the most cancer types (8), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TGIF2LY RNA expression–survival associations across cancer types. High TGIF2LY expression shows unfavorable associations in LUSC, PCPG, LIHC, MESO and BRCA, but favorable associations in SCLC. The LUSC 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 LUSC as the clearest survival context for TGIF2LY RNA expression.
This table summarizes TGIF2LY tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for TGIF2LY. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TGIF2LY shows higher tumor expression in LIHC. The LIHC box plot shows higher TGIF2LY RNA expression in tumor versus normal tissue (log2 FC = +0.078, t-test p = .025).
This table shows molecular features associated with TGIF2LY in patient tissues and cancer cell lines. In patient samples, TGIF2LY shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, TGIF2LY 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 LUNG_NSCLC_LUSC and BREAST.
