glycophorin C (Gerbich blood group)Genealiases: CD236 · CD236R · GE · GPC · GPD · GYPD
Q-omics provides the consensus-scored GYPC profile across patient tissues and cancer cell-line models. GYPC expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, GYPC is differentially expressed in 17, with the highest sampling consensus in KIRC. Additionally, GYPC RNA expression shows 27,294 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UCEC, KIRC, and LSCC as cancer lineages where GYPC 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 GYPC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GYPC survival associations across molecular data types. GYPC RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GYPC RNA expression–survival associations across cancer types. High GYPC expression shows unfavorable associations in SKCM, but favorable associations in UCEC, HNSC, KIRC, CESC and UVM. The UCEC 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 UCEC as the clearest survival context for GYPC RNA expression.
This table summarizes GYPC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for GYPC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GYPC shows lower tumor expression in BLCA, LUAD, COAD, THCA and LUSC and higher tumor expression in KIRC. The KIRC box plot shows higher GYPC RNA expression in tumor versus normal tissue (log2 FC = +1.368, t-test p < 0.001).
This table shows molecular features associated with GYPC in patient tissues and cancer cell lines. In patient samples, GYPC 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, GYPC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SKIN.
