Q-omics provides the consensus-scored PAICSP1 profile across patient tissues and cancer cell-line models. PAICSP1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PAICSP1 is differentially expressed in 6, with the highest sampling consensus in LIHC. Additionally, PAICSP1 RNA expression shows 17,863 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and LIHC as cancer lineages where PAICSP1 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 PAICSP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PAICSP1 survival associations across molecular data types. PAICSP1 RNA expression shows survival associations in the most cancer types (26). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PAICSP1 RNA expression–survival associations across cancer types. High PAICSP1 expression shows unfavorable associations in ACC, KICH, LIHC and PRAD, but favorable associations in LUAD and UCS. The ACC 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 ACC as the clearest survival context for PAICSP1 RNA expression.
This table summarizes PAICSP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for PAICSP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PAICSP1 shows lower tumor expression in THCA, BRCA, KIRC and PAAD and higher tumor expression in LIHC and CHOL. The LIHC box plot shows higher PAICSP1 RNA expression in tumor versus normal tissue (log2 FC = +0.183, t-test p < 0.001).
This table shows molecular features associated with PAICSP1 in patient tissues and cancer cell lines. In patient samples, PAICSP1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
