Q-omics provides the consensus-scored PSORS1C1 profile across patient tissues and cancer cell-line models. PSORS1C1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PSORS1C1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, PSORS1C1 RNA expression shows 14,062 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, HNSC, and TGCT as cancer lineages where PSORS1C1 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 PSORS1C1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSORS1C1 survival associations across molecular data types. PSORS1C1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PSORS1C1 RNA expression–survival associations across cancer types. High PSORS1C1 expression shows unfavorable associations in HNSC, UVM, LGG, COAD and LIHC, but favorable associations in ACC. The ACC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for PSORS1C1 RNA expression.
This table summarizes PSORS1C1 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 PSORS1C1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSORS1C1 shows lower tumor expression in LUSC and UCEC and higher tumor expression in HNSC, KIRC, KIRP and LIHC. The HNSC box plot shows higher PSORS1C1 RNA expression in tumor versus normal tissue (log2 FC = +1.520, t-test p < 0.001).
This table shows molecular features associated with PSORS1C1 in patient tissues and cancer cell lines. In patient samples, PSORS1C1 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, PSORS1C1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BONE.
