Q-omics provides the consensus-scored ALG9-IT1 profile across patient tissues and cancer cell-line models. ALG9-IT1 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, ALG9-IT1 is differentially expressed in 3, with the highest sampling consensus in STAD. Additionally, ALG9-IT1 RNA expression shows 8,506 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight COAD, STAD, and GBM as cancer lineages where ALG9-IT1 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 ALG9-IT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ALG9-IT1 survival associations across molecular data types. ALG9-IT1 RNA expression shows survival associations in the most cancer types (13). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ALG9-IT1 RNA expression–survival associations across cancer types. High ALG9-IT1 expression shows unfavorable associations in COAD, PAAD, BRCA, TGCT, DLBC and ACC. The COAD 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 COAD as the clearest survival context for ALG9-IT1 RNA expression.
This table summarizes ALG9-IT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for ALG9-IT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ALG9-IT1 shows higher tumor expression in STAD, KIRP and KIRC. The STAD box plot shows higher ALG9-IT1 RNA expression in tumor versus normal tissue (log2 FC = +0.102, t-test p = .015).
This table shows molecular features associated with ALG9-IT1 in patient tissues and cancer cell lines. In patient samples, ALG9-IT1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set.
