Q-omics provides the consensus-scored HSPB1P2 profile across patient tissues and cancer cell-line models. HSPB1P2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, HSPB1P2 is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, HSPB1P2 RNA expression shows 14,375 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight LIHC, and ESCA as cancer lineages where HSPB1P2 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 HSPB1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HSPB1P2 survival associations across molecular data types. HSPB1P2 RNA expression shows survival associations in the most cancer types (24). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HSPB1P2 RNA expression–survival associations across cancer types. High HSPB1P2 expression shows unfavorable associations in LIHC, LGG, MESO and LAML, but favorable associations in ACC and UCEC. 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 HSPB1P2 RNA expression.
This table summarizes HSPB1P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for HSPB1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HSPB1P2 shows higher tumor expression in LIHC, KIRC, LUSC, KIRP, BRCA and COAD. The LIHC box plot shows higher HSPB1P2 RNA expression in tumor versus normal tissue (log2 FC = +0.811, t-test p < 0.001).
This table shows molecular features associated with HSPB1P2 in patient tissues and cancer cell lines. In patient samples, HSPB1P2 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set.
