Q-omics provides the consensus-scored MIGA2 profile across patient tissues and cancer cell-line models. MIGA2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MIGA2 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, MIGA2 RNA expression shows 19,732 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight ACC, KIRC, and UVM as cancer lineages where MIGA2 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 MIGA2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MIGA2 survival associations across molecular data types. MIGA2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MIGA2 RNA expression–survival associations across cancer types. High MIGA2 expression shows unfavorable associations in ACC, KIRC and KICH, but favorable associations in KIRP, HNSC and PAAD. 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 MIGA2 RNA expression.
This table summarizes MIGA2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MIGA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MIGA2 shows lower tumor expression in KIRC, COAD, THCA and HNSC and higher tumor expression in CHOL and LIHC. The KIRC box plot shows higher MIGA2 RNA expression in normal versus tumor tissue (log2 FC = −0.779, t-test p < 0.001).
This table shows molecular features associated with MIGA2 in patient tissues and cancer cell lines. In patient samples, MIGA2 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, MIGA2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
