Q-omics provides the consensus-scored MGST2 profile across patient tissues and cancer cell-line models. MGST2 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, MGST2 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, MGST2 protein abundance shows 20,121 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, HNSC, and GBM as cancer lineages where MGST2 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 MGST2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MGST2 survival associations across molecular data types. MGST2 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (1) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MGST2 RNA expression–survival associations across cancer types. High MGST2 expression shows unfavorable associations in UVM, SCLC, LGG and UCS, but favorable associations in KIRC and UCEC. The UVM 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 UVM as the clearest survival context for MGST2 RNA expression.
This table summarizes MGST2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MGST2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MGST2 shows lower tumor expression in HNSC, CHOL, BRCA and THCA and higher tumor expression in KIRC and PRAD. The HNSC box plot shows higher MGST2 RNA expression in normal versus tumor tissue (log2 FC = −0.865, t-test p < 0.001).
This table shows molecular features associated with MGST2 in patient tissues and cancer cell lines. In patient samples, MGST2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, MGST2 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 KIDNEY and BLOOD_Leukemia.
