Q-omics provides the consensus-scored KIF9 profile across patient tissues and cancer cell-line models. KIF9 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, KIF9 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, KIF9 RNA expression shows 20,553 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, KICH, and ACC as cancer lineages where KIF9 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 KIF9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KIF9 survival associations across molecular data types. KIF9 RNA expression shows survival associations in the most cancer types (22), 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 KIF9 RNA expression–survival associations across cancer types. High KIF9 expression shows unfavorable associations in KICH, ACC and LGG, but favorable associations in KIRP, UVM and BRCA. The KIRP Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify KIRP as the clearest survival context for KIF9 RNA expression.
This table summarizes KIF9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for KIF9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KIF9 shows lower tumor expression in KICH, KIRC and THCA and higher tumor expression in COAD, STAD and LIHC. The KICH box plot shows higher KIF9 RNA expression in normal versus tumor tissue (log2 FC = −1.642, t-test p < 0.001).
This table shows molecular features associated with KIF9 in patient tissues and cancer cell lines. In patient samples, KIF9 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, KIF9 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 SOFT_TISSUE and BLOOD_Lymphoma.
