DNA damage inducible transcript 4 likeGenealiases: REDD2 · Rtp801L
Q-omics provides the consensus-scored DDIT4L profile across patient tissues and cancer cell-line models. DDIT4L expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, DDIT4L is differentially expressed in 14, with the highest sampling consensus in LUAD. Additionally, DDIT4L RNA expression shows 17,616 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UVM, LUAD, and TGCT as cancer lineages where DDIT4L 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 DDIT4L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DDIT4L survival associations across molecular data types. DDIT4L RNA expression shows survival associations in the most cancer types (24), 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 DDIT4L RNA expression–survival associations across cancer types. High DDIT4L expression shows unfavorable associations in UVM, LGG, THCA and STAD, but favorable associations in KIRC and ACC. The UVM 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 UVM as the clearest survival context for DDIT4L RNA expression.
This table summarizes DDIT4L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for DDIT4L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DDIT4L shows lower tumor expression in THCA, HNSC, BRCA, BLCA and KICH and higher tumor expression in LUAD. The LUAD box plot shows higher DDIT4L RNA expression in tumor versus normal tissue (log2 FC = +1.948, t-test p < 0.001).
This table shows molecular features associated with DDIT4L in patient tissues and cancer cell lines. In patient samples, DDIT4L 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, DDIT4L 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 OVARY and BLOOD_Leukemia.
