Q-omics provides the consensus-scored QSER1 profile across patient tissues and cancer cell-line models. QSER1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, QSER1 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, QSER1 protein abundance shows 27,390 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight ACC, BLCA, and HNSC as cancer lineages where QSER1 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 QSER1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes QSER1 survival associations across molecular data types. QSER1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible QSER1 RNA expression–survival associations across cancer types. High QSER1 expression shows unfavorable associations in ACC, KICH, LIHC and MESO, but favorable associations in READ and KIRC. The ACC 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 ACC as the clearest survival context for QSER1 RNA expression.
This table summarizes QSER1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for QSER1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. QSER1 shows lower tumor expression in THCA and higher tumor expression in BLCA, LIHC, HNSC, KIRP and LUSC. The BLCA box plot shows higher QSER1 RNA expression in tumor versus normal tissue (log2 FC = +0.803, t-test p < 0.001).
This table shows molecular features associated with QSER1 in patient tissues and cancer cell lines. In patient samples, QSER1 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, QSER1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
