Q-omics provides the consensus-scored JAK1 profile across patient tissues and cancer cell-line models. JAK1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, JAK1 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, JAK1 protein abundance shows 26,860 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, KICH, and LSCC as cancer lineages where JAK1 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 JAK1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes JAK1 survival associations across molecular data types. JAK1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (10) 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 JAK1 RNA expression–survival associations across cancer types. High JAK1 expression shows unfavorable associations in LUSC and OV, but favorable associations in KIRC, BRCA, UCS and HNSC. The KIRC 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 KIRC as the clearest survival context for JAK1 RNA expression.
This table summarizes JAK1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for JAK1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. JAK1 shows lower tumor expression in KICH, UCEC, LUSC and BRCA and higher tumor expression in HNSC and KIRC. The KICH box plot shows higher JAK1 RNA expression in normal versus tumor tissue (log2 FC = −1.290, t-test p < 0.001).
This table shows molecular features associated with JAK1 in patient tissues and cancer cell lines. In patient samples, JAK1 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, JAK1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and SKIN.
