Q-omics provides the consensus-scored JDP2 profile across patient tissues and cancer cell-line models. JDP2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, JDP2 is differentially expressed in 12, with the highest sampling consensus in LUAD. Additionally, JDP2 RNA expression shows 19,010 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight COAD, LUAD, and ACC as cancer lineages where JDP2 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 JDP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes JDP2 survival associations across molecular data types. JDP2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible JDP2 RNA expression–survival associations across cancer types. High JDP2 expression shows unfavorable associations in COAD, UVM, ACC and MESO, but favorable associations in KIRC and SKCM. The COAD 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 COAD as the clearest survival context for JDP2 RNA expression.
This table summarizes JDP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in LUAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for JDP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. JDP2 shows lower tumor expression in LUAD, BLCA, KIRP, KICH, THCA and LIHC. The LUAD box plot shows higher JDP2 RNA expression in normal versus tumor tissue (log2 FC = −1.358, t-test p < 0.001).
This table shows molecular features associated with JDP2 in patient tissues and cancer cell lines. In patient samples, JDP2 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, JDP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LUNG_SCLC.
