Q-omics provides the consensus-scored FHDC1 profile across patient tissues and cancer cell-line models. FHDC1 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FHDC1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, FHDC1 RNA expression shows 19,152 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, KIRC, and THYM as cancer lineages where FHDC1 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 FHDC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FHDC1 survival associations across molecular data types. FHDC1 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (5) and 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 FHDC1 RNA expression–survival associations across cancer types. High FHDC1 expression shows unfavorable associations in UVM, LIHC, ACC and UCEC, but favorable associations in LGG and PAAD. 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 FHDC1 RNA expression.
This table summarizes FHDC1 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 8. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FHDC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FHDC1 shows lower tumor expression in KIRC, THCA and LUAD and higher tumor expression in LIHC, KICH and BRCA. The KIRC box plot shows higher FHDC1 RNA expression in normal versus tumor tissue (log2 FC = −1.163, t-test p < 0.001).
This table shows molecular features associated with FHDC1 in patient tissues and cancer cell lines. In patient samples, FHDC1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, FHDC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and SKIN.
