Q-omics provides the consensus-scored QTRT2 profile across patient tissues and cancer cell-line models. QTRT2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, QTRT2 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, QTRT2 protein abundance shows 25,029 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where QTRT2 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 QTRT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes QTRT2 survival associations across molecular data types. QTRT2 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible QTRT2 RNA expression–survival associations across cancer types. High QTRT2 expression shows unfavorable associations in ACC, LGG, LIHC and UCEC, but favorable associations in KIRC and SCLC. The KIRC 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 KIRC as the clearest survival context for QTRT2 RNA expression.
This table summarizes QTRT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for QTRT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. QTRT2 shows lower tumor expression in THCA and higher tumor expression in HNSC, BLCA, STAD, COAD and LIHC. The HNSC box plot shows higher QTRT2 RNA expression in tumor versus normal tissue (log2 FC = +1.294, t-test p < 0.001).
This table shows molecular features associated with QTRT2 in patient tissues and cancer cell lines. In patient samples, QTRT2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, QTRT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SKIN.
