Q-omics provides the consensus-scored HDDC2 profile across patient tissues and cancer cell-line models. HDDC2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, HDDC2 is differentially expressed in 13, with the highest sampling consensus in LIHC. Additionally, HDDC2 protein abundance shows 28,812 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, and LSCC as cancer lineages where HDDC2 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 HDDC2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HDDC2 survival associations across molecular data types. HDDC2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HDDC2 RNA expression–survival associations across cancer types. High HDDC2 expression shows unfavorable associations in LIHC, KICH, LUAD and HNSC, but favorable associations in THCA and LGG. The LIHC 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 LIHC as the clearest survival context for HDDC2 RNA expression.
This table summarizes HDDC2 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 9. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for HDDC2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HDDC2 shows lower tumor expression in BRCA and KICH and higher tumor expression in LIHC, HNSC, CHOL and STAD. The LIHC box plot shows higher HDDC2 RNA expression in tumor versus normal tissue (log2 FC = +0.731, t-test p < 0.001).
This table shows molecular features associated with HDDC2 in patient tissues and cancer cell lines. In patient samples, HDDC2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, HDDC2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Lymphoma.
