ATP synthase F1 subunit gammaGenealiases: ATP5C · ATP5C1 · ATP5CL1
Q-omics provides the consensus-scored ATP5F1C profile across patient tissues and cancer cell-line models. ATP5F1C expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ATP5F1C is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, ATP5F1C protein abundance shows 25,890 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, LIHC, and GBM as cancer lineages where ATP5F1C 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 ATP5F1C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP5F1C survival associations across molecular data types. ATP5F1C RNA expression shows survival associations in the most cancer types (30), followed by mutation status (7) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP5F1C RNA expression–survival associations across cancer types. High ATP5F1C expression shows unfavorable associations in UVM, LIHC, BRCA, ACC and LAML, but favorable associations in LGG. The UVM 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 UVM as the clearest survival context for ATP5F1C RNA expression.
This table summarizes ATP5F1C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATP5F1C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP5F1C shows lower tumor expression in THCA, KICH and KIRC and higher tumor expression in LIHC, LUSC and BLCA. The LIHC box plot shows higher ATP5F1C RNA expression in tumor versus normal tissue (log2 FC = +0.881, t-test p < 0.001).
This table shows molecular features associated with ATP5F1C in patient tissues and cancer cell lines. In patient samples, ATP5F1C 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, ATP5F1C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
