Q-omics provides the consensus-scored KAZALD1 profile across patient tissues and cancer cell-line models. KAZALD1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, KAZALD1 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, KAZALD1 RNA expression shows 18,233 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where KAZALD1 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 KAZALD1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KAZALD1 survival associations across molecular data types. KAZALD1 RNA expression shows survival associations in the most cancer types (27), 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 KAZALD1 RNA expression–survival associations across cancer types. High KAZALD1 expression shows unfavorable associations in ACC, KIRP, THCA and MESO, but favorable associations in HNSC and OV. 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 KAZALD1 RNA expression.
This table summarizes KAZALD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for KAZALD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KAZALD1 shows lower tumor expression in KIRC and HNSC and higher tumor expression in LIHC, UCEC, LUAD and BRCA. The KIRC box plot shows higher KAZALD1 RNA expression in normal versus tumor tissue (log2 FC = −0.528, t-test p < 0.001).
This table shows molecular features associated with KAZALD1 in patient tissues and cancer cell lines. In patient samples, KAZALD1 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, KAZALD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and SOFT_TISSUE.
