Q-omics provides the consensus-scored YDJC profile across patient tissues and cancer cell-line models. YDJC expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, YDJC is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, YDJC RNA expression shows 19,060 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, KIRC, and THYM as cancer lineages where YDJC 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 YDJC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YDJC survival associations across molecular data types. YDJC RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YDJC RNA expression–survival associations across cancer types. High YDJC expression shows unfavorable associations in UVM, ACC, LIHC, KIRC, LGG and LUAD. 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 YDJC RNA expression.
This table summarizes YDJC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for YDJC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YDJC shows higher tumor expression in KIRC, BLCA, COAD, HNSC, KIRP and STAD. The KIRC box plot shows higher YDJC RNA expression in tumor versus normal tissue (log2 FC = +0.790, t-test p < 0.001).
This table shows molecular features associated with YDJC in patient tissues and cancer cell lines. In patient samples, YDJC shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, YDJC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
