Q-omics provides the consensus-scored JAK3 profile across patient tissues and cancer cell-line models. JAK3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, JAK3 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, JAK3 RNA expression shows 22,101 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where JAK3 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 JAK3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes JAK3 survival associations across molecular data types. JAK3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 JAK3 RNA expression–survival associations across cancer types. High JAK3 expression shows unfavorable associations in KIRC, but favorable associations in HNSC, ACC, CESC, SKCM and LUAD. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for JAK3 RNA expression.
This table summarizes JAK3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for JAK3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. JAK3 shows higher tumor expression in KIRC, HNSC, THCA, LUAD, STAD and KIRP. The KIRC box plot shows higher JAK3 RNA expression in tumor versus normal tissue (log2 FC = +2.066, t-test p < 0.001).
This table shows molecular features associated with JAK3 in patient tissues and cancer cell lines. In patient samples, JAK3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, JAK3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
