Q-omics provides the consensus-scored HSPG2 profile across patient tissues and cancer cell-line models. HSPG2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HSPG2 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, HSPG2 protein abundance shows 29,798 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, HNSC, and PDAC as cancer lineages where HSPG2 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 HSPG2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HSPG2 survival associations across molecular data types. HSPG2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (9) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HSPG2 RNA expression–survival associations across cancer types. High HSPG2 expression shows unfavorable associations in BLCA, MESO, CESC, LGG and KIRP, but favorable associations in KIRC. The KIRC 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 KIRC as the clearest survival context for HSPG2 RNA expression.
This table summarizes HSPG2 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 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for HSPG2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HSPG2 shows lower tumor expression in UCEC, BLCA and BRCA and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher HSPG2 RNA expression in tumor versus normal tissue (log2 FC = +2.557, t-test p < 0.001).
This table shows molecular features associated with HSPG2 in patient tissues and cancer cell lines. In patient samples, HSPG2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, HSPG2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
