MHC class I polypeptide-related sequence G (pseudogene)Genealiases: []
Q-omics provides the consensus-scored MICG profile across patient tissues and cancer cell-line models. MICG expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, MICG is differentially expressed in 5, with the highest sampling consensus in KIRC. Additionally, MICG RNA expression shows 5,555 significant gene co-expression associations, with the highest sampling consensus in THCA. Together, these results highlight UCEC, KIRC, and THCA as cancer lineages where MICG 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 MICG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MICG survival associations across molecular data types. MICG RNA expression shows survival associations in the most cancer types (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MICG RNA expression–survival associations across cancer types. High MICG expression shows unfavorable associations in UCEC, THCA, LGG, LUSC and BLCA, but favorable associations in KIRC. The UCEC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UCEC as the clearest survival context for MICG RNA expression.
This table summarizes MICG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for MICG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MICG shows higher tumor expression in KIRC, LUAD, THCA, HNSC and KIRP. The KIRC box plot shows higher MICG RNA expression in tumor versus normal tissue (log2 FC = +0.561, t-test p < 0.001).
This table shows molecular features associated with MICG in patient tissues and cancer cell lines. In patient samples, MICG shows the broadest associations at the RNA and protein expression levels, with THCA recurring as the lineage with the largest associated feature set.
