Q-omics provides the consensus-scored MICALCL profile across patient tissues and cancer cell-line models. MICALCL expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MICALCL is differentially expressed in 15, with the highest sampling consensus in LUAD. Additionally, MICALCL RNA expression shows 17,830 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight MESO, LUAD, and KIRP as cancer lineages where MICALCL 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 MICALCL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MICALCL survival associations across molecular data types. MICALCL RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MICALCL RNA expression–survival associations across cancer types. High MICALCL expression shows unfavorable associations in MESO, UVM, LUSC and CESC, but favorable associations in SCLC and READ. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify MESO as the clearest survival context for MICALCL RNA expression.
This table summarizes MICALCL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for MICALCL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MICALCL shows lower tumor expression in LUAD, COAD and LUSC and higher tumor expression in HNSC, BLCA and BRCA. The LUAD box plot shows higher MICALCL RNA expression in normal versus tumor tissue (log2 FC = −1.800, t-test p < 0.001).
This table shows molecular features associated with MICALCL in patient tissues and cancer cell lines. In patient samples, MICALCL shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, MICALCL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and LARGE_INTESTINE.
