Q-omics provides the consensus-scored PVALB profile across patient tissues and cancer cell-line models. PVALB expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PVALB is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, PVALB protein abundance shows 22,500 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KIRP, and GBM as cancer lineages where PVALB 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 PVALB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PVALB survival associations across molecular data types. PVALB RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PVALB RNA expression–survival associations across cancer types. High PVALB expression shows unfavorable associations in KIRC and UCS, but favorable associations in BRCA, LGG, LUAD and CHOL. The KIRC 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 KIRC as the clearest survival context for PVALB RNA expression.
This table summarizes PVALB 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PVALB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PVALB shows lower tumor expression in KIRP, KIRC, LIHC, COAD and LUAD and higher tumor expression in KICH. The KIRP box plot shows higher PVALB RNA expression in normal versus tumor tissue (log2 FC = −4.920, t-test p < 0.001).
This table shows molecular features associated with PVALB in patient tissues and cancer cell lines. In patient samples, PVALB 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, PVALB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BREAST.
