MHC class I polypeptide-related sequence F (pseudogene)Genealiases: []
Q-omics provides the consensus-scored MICF profile across patient tissues and cancer cell-line models. MICF expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, MICF is differentially expressed in 7, with the highest sampling consensus in LIHC. Additionally, MICF RNA expression shows 8,993 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight LUAD, LIHC, and THYM as cancer lineages where MICF 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 MICF — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MICF survival associations across molecular data types. MICF RNA expression shows survival associations in the most cancer types (18). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MICF RNA expression–survival associations across cancer types. High MICF expression shows unfavorable associations in LUAD and LUSC, but favorable associations in LGG, SARC, BLCA and LIHC. The LUAD 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 LUAD as the clearest survival context for MICF RNA expression.
This table summarizes MICF tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for MICF. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MICF shows lower tumor expression in LUSC, KICH and READ and higher tumor expression in LIHC, KIRC and CHOL. The LIHC box plot shows higher MICF RNA expression in tumor versus normal tissue (log2 FC = +0.346, t-test p < 0.001).
This table shows molecular features associated with MICF in patient tissues and cancer cell lines. In patient samples, MICF shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set.
