Q-omics provides the consensus-scored PNMA3 profile across patient tissues and cancer cell-line models. PNMA3 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, PNMA3 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, PNMA3 RNA expression shows 16,330 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight PAAD, KICH, and GBM as cancer lineages where PNMA3 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 PNMA3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PNMA3 survival associations across molecular data types. PNMA3 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) 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 PNMA3 RNA expression–survival associations across cancer types. High PNMA3 expression shows unfavorable associations in UCEC and SCLC, but favorable associations in PAAD, LUAD, HNSC and LGG. The PAAD 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 PAAD as the clearest survival context for PNMA3 RNA expression.
This table summarizes PNMA3 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 1. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PNMA3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PNMA3 shows lower tumor expression in KICH, THCA and BRCA and higher tumor expression in LIHC, LUAD and LUSC. The KICH box plot shows higher PNMA3 RNA expression in normal versus tumor tissue (log2 FC = −1.210, t-test p < 0.001).
This table shows molecular features associated with PNMA3 in patient tissues and cancer cell lines. In patient samples, PNMA3 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, PNMA3 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 OESOPHAGUS and LARGE_INTESTINE.
