Q-omics provides the consensus-scored MICA profile across patient tissues and cancer cell-line models. MICA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, MICA is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, MICA RNA expression shows 17,920 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, HNSC, and ACC as cancer lineages where MICA 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 MICA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MICA survival associations across molecular data types. MICA RNA expression shows survival associations in the most cancer types (25). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MICA RNA expression–survival associations across cancer types. High MICA expression shows unfavorable associations in KICH, LGG, ACC, LIHC and CESC, but favorable associations in SCLC. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KICH as the clearest survival context for MICA RNA expression.
This table summarizes MICA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for MICA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MICA shows lower tumor expression in LUAD and LUSC and higher tumor expression in HNSC, COAD, LIHC and KIRC. The HNSC box plot shows higher MICA RNA expression in tumor versus normal tissue (log2 FC = +1.122, t-test p < 0.001).
This table shows molecular features associated with MICA in patient tissues and cancer cell lines. In patient samples, MICA shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, MICA 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 CNS and SOFT_TISSUE.
