Q-omics provides the consensus-scored HTR2C profile across patient tissues and cancer cell-line models. HTR2C expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HTR2C is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, HTR2C RNA expression shows 13,675 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where HTR2C 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 HTR2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HTR2C survival associations across molecular data types. HTR2C RNA expression shows survival associations in the most cancer types (23), followed by mutation status (14). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HTR2C RNA expression–survival associations across cancer types. High HTR2C expression shows unfavorable associations in KIRC, READ, ACC, HNSC and STAD, but favorable associations in LGG. The KIRC 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 KIRC as the clearest survival context for HTR2C RNA expression.
This table summarizes HTR2C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for HTR2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HTR2C shows higher tumor expression in HNSC, BLCA, LUSC, STAD and LUAD. The HNSC box plot shows higher HTR2C RNA expression in tumor versus normal tissue (log2 FC = +0.839, t-test p < 0.001).
This table shows molecular features associated with HTR2C in patient tissues and cancer cell lines. In patient samples, HTR2C shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, HTR2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in OVARY and STOMACH.
