Q-omics provides the consensus-scored PSG9 profile across patient tissues and cancer cell-line models. PSG9 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, PSG9 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, PSG9 RNA expression shows 6,601 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight MESO, KICH, and TGCT as cancer lineages where PSG9 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 PSG9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PSG9 survival associations across molecular data types. PSG9 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PSG9 RNA expression–survival associations across cancer types. High PSG9 expression shows unfavorable associations in MESO, READ, KIRP and OV, but favorable associations in ESCA and KICH. The MESO 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 MESO as the clearest survival context for PSG9 RNA expression.
This table summarizes PSG9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for PSG9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PSG9 shows lower tumor expression in KIRC and higher tumor expression in KICH, BRCA, HNSC, LUAD and LUSC. The KICH box plot shows higher PSG9 RNA expression in tumor versus normal tissue (log2 FC = +1.278, t-test p < 0.001).
This table shows molecular features associated with PSG9 in patient tissues and cancer cell lines. In patient samples, PSG9 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, PSG9 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 BLOOD_Leukemia and STOMACH.
