Q-omics provides the consensus-scored CKMT2 profile across patient tissues and cancer cell-line models. CKMT2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CKMT2 is differentially expressed in 16, with the highest sampling consensus in KIRP. Additionally, CKMT2 protein abundance shows 25,403 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRP, and HNSC as cancer lineages where CKMT2 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 CKMT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CKMT2 survival associations across molecular data types. CKMT2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CKMT2 RNA expression–survival associations across cancer types. High CKMT2 expression shows unfavorable associations in KIRP, BLCA and KICH, but favorable associations in MESO, LUAD and READ. The KIRP 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 KIRP as the clearest survival context for CKMT2 RNA expression.
This table summarizes CKMT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRP for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CKMT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CKMT2 shows lower tumor expression in KIRP, KIRC, STAD, HNSC, BLCA and LUSC. The KIRP box plot shows higher CKMT2 RNA expression in normal versus tumor tissue (log2 FC = −3.127, t-test p < 0.001).
This table shows molecular features associated with CKMT2 in patient tissues and cancer cell lines. In patient samples, CKMT2 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, CKMT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
