Q-omics provides the consensus-scored INKA1 profile across patient tissues and cancer cell-line models. INKA1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, INKA1 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, INKA1 RNA expression shows 20,456 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where INKA1 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 INKA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INKA1 survival associations across molecular data types. INKA1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible INKA1 RNA expression–survival associations across cancer types. High INKA1 expression shows unfavorable associations in MESO and KIRP, but favorable associations in HNSC, UVM, PAAD and ESCA. The HNSC 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 HNSC as the clearest survival context for INKA1 RNA expression.
This table summarizes INKA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for INKA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INKA1 shows lower tumor expression in LUAD, KICH, UCEC and KIRP and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher INKA1 RNA expression in tumor versus normal tissue (log2 FC = +1.260, t-test p < 0.001).
This table shows molecular features associated with INKA1 in patient tissues and cancer cell lines. In patient samples, INKA1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, INKA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
