Q-omics provides the consensus-scored PGRMC1 profile across patient tissues and cancer cell-line models. PGRMC1 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, PGRMC1 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PGRMC1 protein abundance shows 21,134 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight KIRC, and HNSC as cancer lineages where PGRMC1 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 PGRMC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PGRMC1 survival associations across molecular data types. PGRMC1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) 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 PGRMC1 RNA expression–survival associations across cancer types. High PGRMC1 expression shows unfavorable associations in HNSC and UVM, but favorable associations in KIRC, LIHC, OV and LUSC. 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 PGRMC1 RNA expression.
This table summarizes PGRMC1 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 3. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PGRMC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PGRMC1 shows lower tumor expression in KICH, THCA, CHOL and PRAD and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher PGRMC1 RNA expression in tumor versus normal tissue (log2 FC = +1.266, t-test p < 0.001).
This table shows molecular features associated with PGRMC1 in patient tissues and cancer cell lines. In patient samples, PGRMC1 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, PGRMC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
