Q-omics provides the consensus-scored CENPV profile across patient tissues and cancer cell-line models. CENPV expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CENPV is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, CENPV protein abundance shows 23,298 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight UVM, KICH, and HNSC as cancer lineages where CENPV 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 CENPV — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CENPV survival associations across molecular data types. CENPV RNA expression shows survival associations in the most cancer types (26), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CENPV RNA expression–survival associations across cancer types. High CENPV expression shows unfavorable associations in MESO and LGG, but favorable associations in UVM, KIRC, UCS and READ. The UVM 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 UVM as the clearest survival context for CENPV RNA expression.
This table summarizes CENPV tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CENPV. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CENPV shows lower tumor expression in KICH, THCA, KIRC and KIRP and higher tumor expression in STAD and COAD. The KICH box plot shows higher CENPV RNA expression in normal versus tumor tissue (log2 FC = −2.996, t-test p < 0.001).
This table shows molecular features associated with CENPV in patient tissues and cancer cell lines. In patient samples, CENPV shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, CENPV 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 OESOPHAGUS and BONE.
