Q-omics provides the consensus-scored GALNT16 profile across patient tissues and cancer cell-line models. GALNT16 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, GALNT16 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, GALNT16 protein abundance shows 37,656 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight BLCA, COAD, and LUAD as cancer lineages where GALNT16 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 GALNT16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GALNT16 survival associations across molecular data types. GALNT16 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (8) 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 GALNT16 RNA expression–survival associations across cancer types. High GALNT16 expression shows unfavorable associations in BLCA, but favorable associations in KIRP, PAAD, BRCA, KICH and HNSC. The BLCA 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 BLCA as the clearest survival context for GALNT16 RNA expression.
This table summarizes GALNT16 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 11. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GALNT16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GALNT16 shows lower tumor expression in COAD, KIRC, HNSC, BLCA, LUAD and LUSC. The COAD box plot shows higher GALNT16 RNA expression in normal versus tumor tissue (log2 FC = −0.944, t-test p < 0.001).
This table shows molecular features associated with GALNT16 in patient tissues and cancer cell lines. In patient samples, GALNT16 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, GALNT16 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BONE.
