Q-omics provides the consensus-scored NLRP1 profile across patient tissues and cancer cell-line models. NLRP1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, NLRP1 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, NLRP1 RNA expression shows 21,253 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, HNSC, and GBM as cancer lineages where NLRP1 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 NLRP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NLRP1 survival associations across molecular data types. NLRP1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NLRP1 RNA expression–survival associations across cancer types. High NLRP1 expression shows unfavorable associations in LGG, but favorable associations in SKCM, HNSC, LUAD, SCLC and PAAD. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for NLRP1 RNA expression.
This table summarizes NLRP1 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 4. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for NLRP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NLRP1 shows lower tumor expression in UCEC, KICH and LUAD and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher NLRP1 RNA expression in tumor versus normal tissue (log2 FC = +0.921, t-test p < 0.001).
This table shows molecular features associated with NLRP1 in patient tissues and cancer cell lines. In patient samples, NLRP1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, NLRP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LUNG_SCLC.
