Q-omics provides the consensus-scored PRECSIT profile across patient tissues and cancer cell-line models. PRECSIT expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PRECSIT is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, PRECSIT RNA expression shows 17,584 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and COAD as cancer lineages where PRECSIT 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 PRECSIT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRECSIT survival associations across molecular data types. PRECSIT RNA expression shows survival associations in the most cancer types (25). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRECSIT RNA expression–survival associations across cancer types. High PRECSIT expression shows unfavorable associations in UVM, BLCA, OV, LGG and ACC, but favorable associations in UCEC. The UVM 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 UVM as the clearest survival context for PRECSIT RNA expression.
This table summarizes PRECSIT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for PRECSIT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRECSIT shows lower tumor expression in KICH and higher tumor expression in COAD, LUAD, STAD, BLCA and LIHC. The COAD box plot shows higher PRECSIT RNA expression in tumor versus normal tissue (log2 FC = +1.360, t-test p < 0.001).
This table shows molecular features associated with PRECSIT in patient tissues and cancer cell lines. In patient samples, PRECSIT 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, PRECSIT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE.
