Q-omics provides the consensus-scored NACA profile across patient tissues and cancer cell-line models. NACA expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, NACA is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, NACA protein abundance shows 32,319 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, KIRC, and LSCC as cancer lineages where NACA 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 NACA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NACA survival associations across molecular data types. NACA RNA expression shows survival associations in the most cancer types (27), followed by mutation status (9) 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 NACA RNA expression–survival associations across cancer types. High NACA expression shows unfavorable associations in LIHC, KIRP, KICH, LUAD, ACC and PAAD. The LIHC 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 LIHC as the clearest survival context for NACA RNA expression.
This table summarizes NACA 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 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NACA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NACA shows lower tumor expression in BRCA and higher tumor expression in KIRC, LIHC, KIRP, COAD and CHOL. The KIRC box plot shows higher NACA RNA expression in tumor versus normal tissue (log2 FC = +0.894, t-test p < 0.001).
This table shows molecular features associated with NACA in patient tissues and cancer cell lines. In patient samples, NACA shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, NACA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
