Q-omics provides the consensus-scored QRSL1P2 profile across patient tissues and cancer cell-line models. QRSL1P2 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, QRSL1P2 is differentially expressed in 1, with the highest sampling consensus in UCEC. Additionally, QRSL1P2 RNA expression shows 7,909 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LIHC, UCEC, and PDAC as cancer lineages where QRSL1P2 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 QRSL1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes QRSL1P2 survival associations across molecular data types. QRSL1P2 RNA expression shows survival associations in the most cancer types (13). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible QRSL1P2 RNA expression–survival associations across cancer types. High QRSL1P2 expression shows unfavorable associations in LIHC, READ, PAAD, THYM, UVM and COAD. The LIHC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify LIHC as the clearest survival context for QRSL1P2 RNA expression.
This table summarizes QRSL1P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for QRSL1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. QRSL1P2 shows higher tumor expression in UCEC. The UCEC box plot shows higher QRSL1P2 RNA expression in tumor versus normal tissue (log2 FC = +0.031, t-test p = .044).
This table shows molecular features associated with QRSL1P2 in patient tissues and cancer cell lines. In patient samples, QRSL1P2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set.
