Q-omics provides the consensus-scored ERLEC1 profile across patient tissues and cancer cell-line models. ERLEC1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ERLEC1 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, ERLEC1 RNA expression shows 20,062 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, BLCA, and ACC as cancer lineages where ERLEC1 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 ERLEC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERLEC1 survival associations across molecular data types. ERLEC1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ERLEC1 RNA expression–survival associations across cancer types. High ERLEC1 expression shows unfavorable associations in KIRP, MESO, CESC, BLCA, SCLC and LIHC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRP as the clearest survival context for ERLEC1 RNA expression.
This table summarizes ERLEC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ERLEC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERLEC1 shows lower tumor expression in THCA and higher tumor expression in BLCA, LIHC, KIRC, HNSC and BRCA. The BLCA box plot shows higher ERLEC1 RNA expression in tumor versus normal tissue (log2 FC = +0.485, t-test p < 0.001).
This table shows molecular features associated with ERLEC1 in patient tissues and cancer cell lines. In patient samples, ERLEC1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ERLEC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BONE.
