Q-omics provides the consensus-scored PJVK profile across patient tissues and cancer cell-line models. PJVK expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PJVK is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, PJVK RNA expression shows 19,122 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, KICH, and UVM as cancer lineages where PJVK 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 PJVK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PJVK survival associations across molecular data types. PJVK RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PJVK RNA expression–survival associations across cancer types. High PJVK expression shows unfavorable associations in KIRC, KICH and GBM, but favorable associations in LAML, UCS and KIRP. 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 PJVK RNA expression.
This table summarizes PJVK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for PJVK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PJVK shows lower tumor expression in KICH, BRCA, UCEC and THCA and higher tumor expression in LIHC and COAD. The KICH box plot shows higher PJVK RNA expression in normal versus tumor tissue (log2 FC = −1.167, t-test p < 0.001).
This table shows molecular features associated with PJVK in patient tissues and cancer cell lines. In patient samples, PJVK shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, PJVK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
