Q-omics provides the consensus-scored KLHDC2 profile across patient tissues and cancer cell-line models. KLHDC2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, KLHDC2 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, KLHDC2 RNA expression shows 21,169 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where KLHDC2 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 KLHDC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLHDC2 survival associations across molecular data types. KLHDC2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) 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 KLHDC2 RNA expression–survival associations across cancer types. High KLHDC2 expression shows unfavorable associations in ACC, but favorable associations in KIRC, UCEC, BRCA, MESO and UCS. The KIRC 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 KIRC as the clearest survival context for KLHDC2 RNA expression.
This table summarizes KLHDC2 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 5. The strongest signals are observed in BRCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for KLHDC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLHDC2 shows lower tumor expression in THCA, BRCA, LUSC, UCEC, READ and STAD. The THCA box plot shows higher KLHDC2 RNA expression in normal versus tumor tissue (log2 FC = −0.355, t-test p = .023).
This table shows molecular features associated with KLHDC2 in patient tissues and cancer cell lines. In patient samples, KLHDC2 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, KLHDC2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
