Q-omics provides the consensus-scored SVIL-AS1 profile across patient tissues and cancer cell-line models. SVIL-AS1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, SVIL-AS1 is differentially expressed in 11, with the highest sampling consensus in KICH. Additionally, SVIL-AS1 RNA expression shows 19,930 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight CESC, KICH, and UVM as cancer lineages where SVIL-AS1 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 SVIL-AS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SVIL-AS1 survival associations across molecular data types. SVIL-AS1 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SVIL-AS1 RNA expression–survival associations across cancer types. High SVIL-AS1 expression shows unfavorable associations in CESC, LIHC, BLCA, ACC and UVM, but favorable associations in KIRC. The CESC 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 CESC as the clearest survival context for SVIL-AS1 RNA expression.
This table summarizes SVIL-AS1 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 THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SVIL-AS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SVIL-AS1 shows lower tumor expression in KICH, THCA, BRCA and COAD and higher tumor expression in LIHC and HNSC. The KICH box plot shows higher SVIL-AS1 RNA expression in normal versus tumor tissue (log2 FC = −1.236, t-test p < 0.001).
This table shows molecular features associated with SVIL-AS1 in patient tissues and cancer cell lines. In patient samples, SVIL-AS1 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, SVIL-AS1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia.
