Q-omics provides the consensus-scored ARMC3 profile across patient tissues and cancer cell-line models. ARMC3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ARMC3 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, ARMC3 RNA expression shows 15,280 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, and UVM as cancer lineages where ARMC3 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 ARMC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARMC3 survival associations across molecular data types. ARMC3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARMC3 RNA expression–survival associations across cancer types. High ARMC3 expression shows unfavorable associations in KICH, LIHC, BLCA, ACC and STAD, but favorable associations in BRCA. The KICH 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 KICH as the clearest survival context for ARMC3 RNA expression.
This table summarizes ARMC3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ARMC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARMC3 shows lower tumor expression in KICH, LUSC, THCA and LUAD and higher tumor expression in BRCA and COAD. The KICH box plot shows higher ARMC3 RNA expression in normal versus tumor tissue (log2 FC = −0.792, t-test p < 0.001).
This table shows molecular features associated with ARMC3 in patient tissues and cancer cell lines. In patient samples, ARMC3 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ARMC3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in CNS and LARGE_INTESTINE.
