Q-omics provides the consensus-scored HNRNPH2 profile across patient tissues and cancer cell-line models. HNRNPH2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HNRNPH2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, HNRNPH2 protein abundance shows 21,905 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, HNSC, and PDAC as cancer lineages where HNRNPH2 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 HNRNPH2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HNRNPH2 survival associations across molecular data types. HNRNPH2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HNRNPH2 RNA expression–survival associations across cancer types. High HNRNPH2 expression shows unfavorable associations in COAD and UVM, but favorable associations in KIRC, MESO, BRCA and LGG. 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 HNRNPH2 RNA expression.
This table summarizes HNRNPH2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HNRNPH2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HNRNPH2 shows lower tumor expression in THCA, KICH and KIRC and higher tumor expression in HNSC, LIHC and STAD. The HNSC box plot shows higher HNRNPH2 RNA expression in tumor versus normal tissue (log2 FC = +0.447, t-test p < 0.001).
This table shows molecular features associated with HNRNPH2 in patient tissues and cancer cell lines. In patient samples, HNRNPH2 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, HNRNPH2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
