Q-omics provides the consensus-scored JCAD profile across patient tissues and cancer cell-line models. JCAD expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, JCAD is differentially expressed in 17, with the highest sampling consensus in KIRC. Additionally, JCAD protein abundance shows 28,550 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, KIRC, and LSCC as cancer lineages where JCAD 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 JCAD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes JCAD survival associations across molecular data types. JCAD RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible JCAD RNA expression–survival associations across cancer types. High JCAD expression shows unfavorable associations in UVM, KIRP and STAD, but favorable associations in KIRC, THCA and HNSC. 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 JCAD RNA expression.
This table summarizes JCAD tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for JCAD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. JCAD shows lower tumor expression in KICH, KIRP, UCEC and LUSC and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher JCAD RNA expression in tumor versus normal tissue (log2 FC = +1.099, t-test p < 0.001).
This table shows molecular features associated with JCAD in patient tissues and cancer cell lines. In patient samples, JCAD shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, JCAD 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 OVARY and LUNG_NSCLC_LUAD.
