Q-omics provides the consensus-scored NSA2 profile across patient tissues and cancer cell-line models. NSA2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, NSA2 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, NSA2 protein abundance shows 25,195 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SCLC, KIRC, and LSCC as cancer lineages where NSA2 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 NSA2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NSA2 survival associations across molecular data types. NSA2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) 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 NSA2 RNA expression–survival associations across cancer types. High NSA2 expression shows unfavorable associations in SCLC, KICH and KIRP, but favorable associations in KIRC, BRCA and MESO. The SCLC 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 SCLC as the clearest survival context for NSA2 RNA expression.
This table summarizes NSA2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, 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 NSA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NSA2 shows lower tumor expression in BLCA, UCEC and LUSC and higher tumor expression in KIRC, LIHC and CHOL. The KIRC box plot shows higher NSA2 RNA expression in tumor versus normal tissue (log2 FC = +0.825, t-test p < 0.001).
This table shows molecular features associated with NSA2 in patient tissues and cancer cell lines. In patient samples, NSA2 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, NSA2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
