Q-omics provides the consensus-scored CXCL9 profile across patient tissues and cancer cell-line models. CXCL9 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, CXCL9 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, CXCL9 RNA expression shows 16,251 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, KIRC, and UVM as cancer lineages where CXCL9 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 CXCL9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CXCL9 survival associations across molecular data types. CXCL9 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CXCL9 RNA expression–survival associations across cancer types. High CXCL9 expression shows unfavorable associations in UVM and LGG, but favorable associations in SKCM, OV, CESC and HNSC. The SKCM 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 SKCM as the clearest survival context for CXCL9 RNA expression.
This table summarizes CXCL9 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 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CXCL9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CXCL9 shows higher tumor expression in KIRC, HNSC, STAD, BRCA, COAD and BLCA. The KIRC box plot shows higher CXCL9 RNA expression in tumor versus normal tissue (log2 FC = +4.062, t-test p < 0.001).
This table shows molecular features associated with CXCL9 in patient tissues and cancer cell lines. In patient samples, CXCL9 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, CXCL9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BONE and SKIN.
