immunoglobulin kappa constantGenealiases: HCAK1 · IGKCD · Km
Q-omics provides the consensus-scored IGKC profile across patient tissues and cancer cell-line models. IGKC expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IGKC is differentially expressed in 7, with the highest sampling consensus in COAD. Additionally, IGKC protein abundance shows 23,265 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight HNSC, COAD, and PDAC as cancer lineages where IGKC 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 IGKC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGKC survival associations across molecular data types. IGKC RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) 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 IGKC RNA expression–survival associations across cancer types. High IGKC expression shows unfavorable associations in KIRC, but favorable associations in HNSC, SKCM, BRCA, CESC and SARC. 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 IGKC RNA expression.
This table summarizes IGKC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 6. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for IGKC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGKC shows lower tumor expression in COAD, LIHC, BRCA and KICH and higher tumor expression in LUAD and KIRC. The COAD box plot shows higher IGKC RNA expression in normal versus tumor tissue (log2 FC = −2.417, t-test p < 0.001).
This table shows molecular features associated with IGKC in patient tissues and cancer cell lines. In patient samples, IGKC shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, IGKC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in NCI60_ALL.
