Q-omics provides the consensus-scored ALG8 profile across patient tissues and cancer cell-line models. ALG8 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ALG8 is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, ALG8 RNA expression shows 19,297 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where ALG8 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 ALG8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ALG8 survival associations across molecular data types. ALG8 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) 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 ALG8 RNA expression–survival associations across cancer types. High ALG8 expression shows unfavorable associations in UVM, LUAD, KIRP, KICH, ACC and BLCA. The UVM 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 UVM as the clearest survival context for ALG8 RNA expression.
This table summarizes ALG8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ALG8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ALG8 shows higher tumor expression in HNSC, KIRC, BLCA, KIRP, LIHC and LUAD. The HNSC box plot shows higher ALG8 RNA expression in tumor versus normal tissue (log2 FC = +0.833, t-test p < 0.001).
This table shows molecular features associated with ALG8 in patient tissues and cancer cell lines. In patient samples, ALG8 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, ALG8 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 LARGE_INTESTINE and UPPER_AERODIGESTIVE_TRACT.
