Q-omics provides the consensus-scored HES2 profile across patient tissues and cancer cell-line models. HES2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HES2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, HES2 RNA expression shows 13,653 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight MESO, HNSC, and ESCA as cancer lineages where HES2 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 HES2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HES2 survival associations across molecular data types. HES2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (1) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HES2 RNA expression–survival associations across cancer types. High HES2 expression shows unfavorable associations in MESO, ACC, UVM, BLCA and SKCM, but favorable associations in KIRP. 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 HES2 RNA expression.
This table summarizes HES2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HES2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HES2 shows lower tumor expression in KIRP and higher tumor expression in HNSC, THCA, LUSC, LIHC and BLCA. The HNSC box plot shows higher HES2 RNA expression in tumor versus normal tissue (log2 FC = +1.857, t-test p < 0.001).
This table shows molecular features associated with HES2 in patient tissues and cancer cell lines. In patient samples, HES2 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, HES2 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
