Q-omics provides the consensus-scored KLRC4-KLRK1 profile across patient tissues and cancer cell-line models. KLRC4-KLRK1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, KLRC4-KLRK1 is differentially expressed in 9, with the highest sampling consensus in LUSC. Additionally, KLRC4-KLRK1 RNA expression shows 15,698 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight SKCM, LUSC, and THYM as cancer lineages where KLRC4-KLRK1 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 KLRC4-KLRK1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLRC4-KLRK1 survival associations across molecular data types. KLRC4-KLRK1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KLRC4-KLRK1 RNA expression–survival associations across cancer types. High KLRC4-KLRK1 expression shows unfavorable associations in ACC, but favorable associations in SKCM, HNSC, BRCA, BLCA and LIHC. 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 KLRC4-KLRK1 RNA expression.
This table summarizes KLRC4-KLRK1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for KLRC4-KLRK1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLRC4-KLRK1 shows lower tumor expression in LUSC, BRCA, THCA, READ and UCEC and higher tumor expression in KIRC. The LUSC box plot shows higher KLRC4-KLRK1 RNA expression in normal versus tumor tissue (log2 FC = −0.266, t-test p < 0.001).
This table shows molecular features associated with KLRC4-KLRK1 in patient tissues and cancer cell lines. In patient samples, KLRC4-KLRK1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, KLRC4-KLRK1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD.
