Q-omics provides the consensus-scored ALG14 profile across patient tissues and cancer cell-line models. ALG14 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ALG14 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, ALG14 RNA expression shows 19,612 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, and ACC as cancer lineages where ALG14 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 ALG14 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ALG14 survival associations across molecular data types. ALG14 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ALG14 RNA expression–survival associations across cancer types. High ALG14 expression shows unfavorable associations in KICH, UVM, LGG, SCLC and KIRP, but favorable associations in KIRC. The KICH 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 KICH as the clearest survival context for ALG14 RNA expression.
This table summarizes ALG14 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in KICH for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ALG14. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ALG14 shows lower tumor expression in KICH and THCA and higher tumor expression in LIHC, KIRC, BLCA and STAD. The KICH box plot shows higher ALG14 RNA expression in normal versus tumor tissue (log2 FC = −0.821, t-test p < 0.001).
This table shows molecular features associated with ALG14 in patient tissues and cancer cell lines. In patient samples, ALG14 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, ALG14 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT.
