holocytochrome c synthaseGenealiases: CCHL · LSDMCA1 · MCOPS7 · MLS
Q-omics provides the consensus-scored HCCS profile across patient tissues and cancer cell-line models. HCCS expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HCCS is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, HCCS RNA expression shows 18,702 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight MESO, HNSC, and UVM as cancer lineages where HCCS 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 HCCS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HCCS survival associations across molecular data types. HCCS RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) 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 HCCS RNA expression–survival associations across cancer types. High HCCS expression shows unfavorable associations in MESO, BRCA, LIHC, LGG and LAML, but favorable associations in KIRC. The MESO 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 MESO as the clearest survival context for HCCS RNA expression.
This table summarizes HCCS 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HCCS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HCCS shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, STAD, LUAD and UCEC. The HNSC box plot shows higher HCCS RNA expression in tumor versus normal tissue (log2 FC = +0.347, t-test p < 0.001).
This table shows molecular features associated with HCCS in patient tissues and cancer cell lines. In patient samples, HCCS 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, HCCS 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 BLOOD_Lymphoma and BREAST.
