Q-omics provides the consensus-scored UPK3BL1 profile across patient tissues and cancer cell-line models. UPK3BL1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Additionally, UPK3BL1 RNA expression shows 4,762 significant gene co-expression associations, with the highest sampling consensus in SCLC. Together, these results highlight SKCM, and SCLC as cancer lineages where UPK3BL1 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 UPK3BL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes UPK3BL1 survival associations across molecular data types. UPK3BL1 RNA expression shows survival associations in the most cancer types (24). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible UPK3BL1 RNA expression–survival associations across cancer types. High UPK3BL1 expression shows unfavorable associations in SKCM, KICH and KIRC, but favorable associations in MESO, PAAD and ACC. The SKCM 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 SKCM as the clearest survival context for UPK3BL1 RNA expression.
This table shows molecular features associated with UPK3BL1 in patient tissues and cancer cell lines. In patient samples, UPK3BL1 shows the broadest associations at the RNA and protein expression levels, with SCLC recurring as the lineage with the largest associated feature set. In cancer cell lines, UPK3BL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
