Q-omics provides the consensus-scored ALPI profile across patient tissues and cancer cell-line models. ALPI expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, ALPI is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, ALPI RNA expression shows 10,803 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LUAD, COAD, and TGCT as cancer lineages where ALPI 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 ALPI — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ALPI survival associations across molecular data types. ALPI RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ALPI RNA expression–survival associations across cancer types. High ALPI expression shows unfavorable associations in LUAD, ACC, DLBC, PAAD and PCPG, but favorable associations in KIRC. The LUAD 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 LUAD as the clearest survival context for ALPI RNA expression.
This table summarizes ALPI tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for ALPI. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ALPI shows lower tumor expression in COAD, KICH, READ and KIRP and higher tumor expression in KIRC and LIHC. The COAD box plot shows higher ALPI RNA expression in normal versus tumor tissue (log2 FC = −3.944, t-test p < 0.001).
This table shows molecular features associated with ALPI in patient tissues and cancer cell lines. In patient samples, ALPI shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ALPI RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and LARGE_INTESTINE.
