Q-omics provides the consensus-scored PTGES3L-AARSD1 profile across patient tissues and cancer cell-line models. PTGES3L-AARSD1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PTGES3L-AARSD1 is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, PTGES3L-AARSD1 RNA expression shows 16,612 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and HNSC as cancer lineages where PTGES3L-AARSD1 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.
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This table summarizes PTGES3L-AARSD1 survival associations across molecular data types. PTGES3L-AARSD1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PTGES3L-AARSD1 RNA expression–survival associations across cancer types. High PTGES3L-AARSD1 expression shows unfavorable associations in UVM, SCLC, THCA, LGG, LIHC and COAD. 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 PTGES3L-AARSD1 RNA expression.
This table summarizes PTGES3L-AARSD1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PTGES3L-AARSD1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTGES3L-AARSD1 shows lower tumor expression in BLCA, UCEC and PRAD and higher tumor expression in HNSC, LUSC and LIHC. The HNSC box plot shows higher PTGES3L-AARSD1 RNA expression in tumor versus normal tissue (log2 FC = +0.356, t-test p < 0.001).
This table shows molecular features associated with PTGES3L-AARSD1 in patient tissues and cancer cell lines. In patient samples, PTGES3L-AARSD1 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, PTGES3L-AARSD1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in CNS.
