Q-omics provides the consensus-scored ZCCHC13 profile across patient tissues and cancer cell-line models. ZCCHC13 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in KICH. Additionally, ZCCHC13 RNA expression shows 8,417 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KICH, and TGCT as cancer lineages where ZCCHC13 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 ZCCHC13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZCCHC13 survival associations across molecular data types. ZCCHC13 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZCCHC13 RNA expression–survival associations across cancer types. High ZCCHC13 expression shows unfavorable associations in KICH, LIHC, THCA, KIRC, UCS and LAML. 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 ZCCHC13 RNA expression.
This table shows molecular features associated with ZCCHC13 in patient tissues and cancer cell lines. In patient samples, ZCCHC13 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ZCCHC13 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 LUNG_SCLC and STOMACH.
