Q-omics provides the consensus-scored PNISR profile across patient tissues and cancer cell-line models. PNISR expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PNISR is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, PNISR protein abundance shows 23,775 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KICH, and GBM as cancer lineages where PNISR 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 PNISR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PNISR survival associations across molecular data types. PNISR RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PNISR RNA expression–survival associations across cancer types. High PNISR expression shows unfavorable associations in KIRC, KICH and ACC, but favorable associations in BLCA, UCS and SKCM. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for PNISR RNA expression.
This table summarizes PNISR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PNISR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PNISR shows lower tumor expression in KICH, BRCA, UCEC and LUAD and higher tumor expression in LIHC and CHOL. The KICH box plot shows higher PNISR RNA expression in normal versus tumor tissue (log2 FC = −1.398, t-test p < 0.001).
This table shows molecular features associated with PNISR in patient tissues and cancer cell lines. In patient samples, PNISR 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, PNISR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in BONE and SOFT_TISSUE.
