Q-omics provides the consensus-scored NEK6 profile across patient tissues and cancer cell-line models. NEK6 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NEK6 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, NEK6 protein abundance shows 23,677 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, KIRC, and LSCC as cancer lineages where NEK6 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 NEK6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NEK6 survival associations across molecular data types. NEK6 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NEK6 RNA expression–survival associations across cancer types. High NEK6 expression shows unfavorable associations in ACC, MESO, LUSC, LGG and LIHC, but favorable associations in KIRC. The ACC 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 ACC as the clearest survival context for NEK6 RNA expression.
This table summarizes NEK6 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NEK6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NEK6 shows higher tumor expression in KIRC, HNSC, COAD, LUAD, STAD and UCEC. The KIRC box plot shows higher NEK6 RNA expression in tumor versus normal tissue (log2 FC = +2.777, t-test p < 0.001).
This table shows molecular features associated with NEK6 in patient tissues and cancer cell lines. In patient samples, NEK6 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, NEK6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in OVARY and UPPER_AERODIGESTIVE_TRACT.
