Q-omics provides the consensus-scored PSORS1C2 profile across patient tissues and cancer cell-line models. PSORS1C2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, PSORS1C2 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PSORS1C2 RNA expression shows 13,723 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight BRCA, KIRC, and TGCT as cancer lineages where PSORS1C2 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 PSORS1C2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSORS1C2 survival associations across molecular data types. PSORS1C2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PSORS1C2 RNA expression–survival associations across cancer types. High PSORS1C2 expression shows unfavorable associations in BRCA, LGG, KIRC, UVM and LAML, but favorable associations in ESCA. The BRCA 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 BRCA as the clearest survival context for PSORS1C2 RNA expression.
This table summarizes PSORS1C2 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PSORS1C2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSORS1C2 shows higher tumor expression in KIRC, LUSC, KIRP, COAD, BLCA and CHOL. The KIRC box plot shows higher PSORS1C2 RNA expression in tumor versus normal tissue (log2 FC = +0.564, t-test p < 0.001).
This table shows molecular features associated with PSORS1C2 in patient tissues and cancer cell lines. In patient samples, PSORS1C2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PSORS1C2 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 CNS.
