Q-omics provides the consensus-scored HSD17B7P2 profile across patient tissues and cancer cell-line models. HSD17B7P2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, HSD17B7P2 is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, HSD17B7P2 RNA expression shows 17,663 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, COAD, and UVM as cancer lineages where HSD17B7P2 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 HSD17B7P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HSD17B7P2 survival associations across molecular data types. HSD17B7P2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) 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 HSD17B7P2 RNA expression–survival associations across cancer types. High HSD17B7P2 expression shows unfavorable associations in ACC, KIRC, UVM and LIHC, but favorable associations in SKCM and MESO. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for HSD17B7P2 RNA expression.
This table summarizes HSD17B7P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for HSD17B7P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HSD17B7P2 shows lower tumor expression in KICH and higher tumor expression in COAD, KIRC, LIHC, ESCA and BLCA. The COAD box plot shows higher HSD17B7P2 RNA expression in tumor versus normal tissue (log2 FC = +1.025, t-test p < 0.001).
This table shows molecular features associated with HSD17B7P2 in patient tissues and cancer cell lines. In patient samples, HSD17B7P2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, HSD17B7P2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SKIN.
