Q-omics provides the consensus-scored PNMA6F profile across patient tissues and cancer cell-line models. PNMA6F expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PNMA6F is differentially expressed in 6, with the highest sampling consensus in STAD. Additionally, PNMA6F RNA expression shows 11,089 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, STAD, and GBM as cancer lineages where PNMA6F 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 PNMA6F — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PNMA6F survival associations across molecular data types. PNMA6F RNA expression shows survival associations in the most cancer types (16). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PNMA6F RNA expression–survival associations across cancer types. High PNMA6F expression shows unfavorable associations in READ, LIHC and UCS, but favorable associations in UVM, SKCM and LUAD. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .005). Together, the overview and detailed table identify UVM as the clearest survival context for PNMA6F RNA expression.
This table summarizes PNMA6F tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in STAD for RNA.
This table ranks reproducible tumor–normal expression differences for PNMA6F. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PNMA6F shows lower tumor expression in STAD, READ and PRAD and higher tumor expression in KICH, LIHC and HNSC. The STAD box plot shows higher PNMA6F RNA expression in normal versus tumor tissue (log2 FC = −0.355, t-test p = .004).
This table shows molecular features associated with PNMA6F in patient tissues and cancer cell lines. In patient samples, PNMA6F 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, PNMA6F 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 LUNG_NSCLC_LUAD.
