Q-omics provides the consensus-scored ELFN2 profile across patient tissues and cancer cell-line models. ELFN2 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, ELFN2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, ELFN2 RNA expression shows 17,954 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where ELFN2 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 ELFN2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ELFN2 survival associations across molecular data types. ELFN2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (10) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ELFN2 RNA expression–survival associations across cancer types. High ELFN2 expression shows unfavorable associations in KIRC, UCEC, ACC and COAD, but favorable associations in LGG and UVM. The KIRC 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 KIRC as the clearest survival context for ELFN2 RNA expression.
This table summarizes ELFN2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ELFN2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ELFN2 shows higher tumor expression in HNSC, KIRP, LIHC, THCA, BRCA and PAAD. The HNSC box plot shows higher ELFN2 RNA expression in tumor versus normal tissue (log2 FC = +0.588, t-test p < 0.001).
This table shows molecular features associated with ELFN2 in patient tissues and cancer cell lines. In patient samples, ELFN2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ELFN2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
