Q-omics provides the consensus-scored ARSG profile across patient tissues and cancer cell-line models. ARSG expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, ARSG is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, ARSG RNA expression shows 19,174 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight PAAD, THCA, and THYM as cancer lineages where ARSG 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 ARSG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARSG survival associations across molecular data types. ARSG RNA expression shows survival associations in the most cancer types (23), followed by mutation status (9) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARSG RNA expression–survival associations across cancer types. High ARSG expression shows unfavorable associations in UVM, MESO and BLCA, but favorable associations in PAAD, HNSC and BRCA. The PAAD 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 PAAD as the clearest survival context for ARSG RNA expression.
This table summarizes ARSG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ARSG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARSG shows lower tumor expression in THCA, UCEC and HNSC and higher tumor expression in KIRP, LIHC and BRCA. The THCA box plot shows higher ARSG RNA expression in normal versus tumor tissue (log2 FC = −1.262, t-test p < 0.001).
This table shows molecular features associated with ARSG in patient tissues and cancer cell lines. In patient samples, ARSG shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ARSG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BREAST.
