Q-omics provides the consensus-scored SETP6 profile across patient tissues and cancer cell-line models. SETP6 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SETP6 is differentially expressed in 3, with the highest sampling consensus in HNSC. Additionally, SETP6 RNA expression shows 10,076 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where SETP6 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 SETP6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SETP6 survival associations across molecular data types. SETP6 RNA expression shows survival associations in the most cancer types (14). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SETP6 RNA expression–survival associations across cancer types. High SETP6 expression shows unfavorable associations in KIRC, UVM, LUSC, STAD, ACC and ESCA. 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 SETP6 RNA expression.
This table summarizes SETP6 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SETP6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SETP6 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC. The HNSC box plot shows higher SETP6 RNA expression in tumor versus normal tissue (log2 FC = +0.047, t-test p = .001).
This table shows molecular features associated with SETP6 in patient tissues and cancer cell lines. In patient samples, SETP6 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set.
