Q-omics provides the consensus-scored PYHIN1 profile across patient tissues and cancer cell-line models. PYHIN1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PYHIN1 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, PYHIN1 RNA expression shows 18,841 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, KIRC, and LSCC as cancer lineages where PYHIN1 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 PYHIN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PYHIN1 survival associations across molecular data types. PYHIN1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) 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 PYHIN1 RNA expression–survival associations across cancer types. High PYHIN1 expression shows favorable associations in SKCM, HNSC, CESC, LIHC, BRCA and LUAD. 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 PYHIN1 RNA expression.
This table summarizes PYHIN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PYHIN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PYHIN1 shows lower tumor expression in COAD, LUSC and THCA and higher tumor expression in KIRC, STAD and HNSC. The KIRC box plot shows higher PYHIN1 RNA expression in tumor versus normal tissue (log2 FC = +1.641, t-test p < 0.001).
This table shows molecular features associated with PYHIN1 in patient tissues and cancer cell lines. In patient samples, PYHIN1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PYHIN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
