Q-omics provides the consensus-scored ADGRF2 profile across patient tissues and cancer cell-line models. ADGRF2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, ADGRF2 is differentially expressed in 7, with the highest sampling consensus in THCA. Additionally, ADGRF2 RNA expression shows 10,756 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight PAAD, THCA, and TGCT as cancer lineages where ADGRF2 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 ADGRF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADGRF2 survival associations across molecular data types. ADGRF2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ADGRF2 RNA expression–survival associations across cancer types. High ADGRF2 expression shows unfavorable associations in PAAD, BLCA, STAD, COAD and LIHC, but favorable associations in ESCA. The PAAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify PAAD as the clearest survival context for ADGRF2 RNA expression.
This table summarizes ADGRF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for ADGRF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADGRF2 shows lower tumor expression in KICH and higher tumor expression in THCA, BRCA, LUSC, BLCA and KIRP. The THCA box plot shows higher ADGRF2 RNA expression in tumor versus normal tissue (log2 FC = +0.227, t-test p < 0.001).
This table shows molecular features associated with ADGRF2 in patient tissues and cancer cell lines. In patient samples, ADGRF2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ADGRF2 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 SKIN and LUNG_SCLC.
