Q-omics provides the consensus-scored HTT profile across patient tissues and cancer cell-line models. HTT expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HTT is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, HTT RNA expression shows 20,139 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, LIHC, and ACC as cancer lineages where HTT 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 HTT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HTT survival associations across molecular data types. HTT RNA expression shows survival associations in the most cancer types (19), followed by mutation status (8) 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 HTT RNA expression–survival associations across cancer types. High HTT expression shows unfavorable associations in MESO, ACC and LIHC, but favorable associations in HNSC, SCLC and 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 HTT RNA expression.
This table summarizes HTT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HTT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HTT shows lower tumor expression in LUAD and higher tumor expression in LIHC, CHOL, HNSC, STAD and THCA. The LIHC box plot shows higher HTT RNA expression in tumor versus normal tissue (log2 FC = +1.407, t-test p < 0.001).
This table shows molecular features associated with HTT in patient tissues and cancer cell lines. In patient samples, HTT shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, HTT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and LARGE_INTESTINE.
