activin A receptor type 1CGenealiases: ACVRLK7 · ALK7
Q-omics provides the consensus-scored ACVR1C profile across patient tissues and cancer cell-line models. ACVR1C expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ACVR1C is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ACVR1C RNA expression shows 17,881 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, HNSC, and UVM as cancer lineages where ACVR1C 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 ACVR1C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACVR1C survival associations across molecular data types. ACVR1C RNA expression shows survival associations in the most cancer types (17), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACVR1C RNA expression–survival associations across cancer types. High ACVR1C expression shows unfavorable associations in KIRP, UVM, DLBC and KIRC, but favorable associations in LGG and ACC. The KIRP 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 KIRP as the clearest survival context for ACVR1C RNA expression.
This table summarizes ACVR1C 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 2. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ACVR1C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACVR1C shows lower tumor expression in KIRC, COAD and BRCA and higher tumor expression in HNSC, LUSC and BLCA. The HNSC box plot shows higher ACVR1C RNA expression in tumor versus normal tissue (log2 FC = +1.096, t-test p < 0.001).
This table shows molecular features associated with ACVR1C in patient tissues and cancer cell lines. In patient samples, ACVR1C 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, ACVR1C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and SOFT_TISSUE.
