Q-omics provides the consensus-scored ARMC10 profile across patient tissues and cancer cell-line models. ARMC10 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ARMC10 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, ARMC10 protein abundance shows 19,281 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KICH, KIRC, and GBM as cancer lineages where ARMC10 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 ARMC10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ARMC10 survival associations across molecular data types. ARMC10 RNA expression shows survival associations in the most cancer types (24), followed by mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ARMC10 RNA expression–survival associations across cancer types. High ARMC10 expression shows unfavorable associations in KICH, PAAD, LIHC, LGG and GBM, but favorable associations in KIRC. 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 ARMC10 RNA expression.
This table summarizes ARMC10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ARMC10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ARMC10 shows higher tumor expression in KIRC, HNSC, COAD, LUAD, KIRP and LIHC. The KIRC box plot shows higher ARMC10 RNA expression in tumor versus normal tissue (log2 FC = +0.534, t-test p < 0.001).
This table shows molecular features associated with ARMC10 in patient tissues and cancer cell lines. In patient samples, ARMC10 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ARMC10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
