Q-omics provides the consensus-scored MAGEC1 profile across patient tissues and cancer cell-line models. MAGEC1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, MAGEC1 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, MAGEC1 RNA expression shows 8,834 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight HNSC, and TGCT as cancer lineages where MAGEC1 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 MAGEC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAGEC1 survival associations across molecular data types. MAGEC1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAGEC1 RNA expression–survival associations across cancer types. High MAGEC1 expression shows unfavorable associations in HNSC, KIRP, KICH, BLCA, KIRC and PAAD. The HNSC 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 HNSC as the clearest survival context for MAGEC1 RNA expression.
This table summarizes MAGEC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MAGEC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAGEC1 shows lower tumor expression in KIRC and higher tumor expression in HNSC, LIHC, LUAD, BRCA and LUSC. The HNSC box plot shows higher MAGEC1 RNA expression in tumor versus normal tissue (log2 FC = +0.570, t-test p = .016).
This table shows molecular features associated with MAGEC1 in patient tissues and cancer cell lines. In patient samples, MAGEC1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, MAGEC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and LUNG_SCLC.
