Q-omics provides the consensus-scored KLC2 profile across patient tissues and cancer cell-line models. KLC2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, KLC2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, KLC2 RNA expression shows 20,331 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where KLC2 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 KLC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLC2 survival associations across molecular data types. KLC2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KLC2 RNA expression–survival associations across cancer types. High KLC2 expression shows unfavorable associations in HNSC, ACC, KICH, MESO, KIRC and LIHC. The HNSC 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 HNSC as the clearest survival context for KLC2 RNA expression.
This table summarizes KLC2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for KLC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLC2 shows higher tumor expression in HNSC, COAD, LIHC, LUAD, LUSC and STAD. The HNSC box plot shows higher KLC2 RNA expression in tumor versus normal tissue (log2 FC = +1.128, t-test p < 0.001).
This table shows molecular features associated with KLC2 in patient tissues and cancer cell lines. In patient samples, KLC2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, KLC2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and BLOOD_Leukemia.
