Q-omics provides the consensus-scored TGIF2LX profile across patient tissues and cancer cell-line models. TGIF2LX expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TGIF2LX is differentially expressed in 4, with the highest sampling consensus in LIHC. Additionally, TGIF2LX RNA expression shows 8,917 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, LIHC, and TGCT as cancer lineages where TGIF2LX 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 TGIF2LX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TGIF2LX survival associations across molecular data types. TGIF2LX RNA expression shows survival associations in the most cancer types (13), followed by mutation status (5) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TGIF2LX RNA expression–survival associations across cancer types. High TGIF2LX expression shows unfavorable associations in KIRC, COAD, CESC, GBM, BRCA and LAML. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for TGIF2LX RNA expression.
This table summarizes TGIF2LX tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4, while mass-spec protein shows differences in 2. The strongest signals are observed in BRCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for TGIF2LX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TGIF2LX shows higher tumor expression in LIHC, BRCA, LUSC and LUAD. The LIHC box plot shows higher TGIF2LX RNA expression in tumor versus normal tissue (log2 FC = +0.340, t-test p < 0.001).
This table shows molecular features associated with TGIF2LX in patient tissues and cancer cell lines. In patient samples, TGIF2LX 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, TGIF2LX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and KIDNEY.
