Q-omics provides the consensus-scored CPLX2 profile across patient tissues and cancer cell-line models. CPLX2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, CPLX2 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, CPLX2 RNA expression shows 17,791 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight DLBC, LIHC, and GBM as cancer lineages where CPLX2 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 CPLX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CPLX2 survival associations across molecular data types. CPLX2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CPLX2 RNA expression–survival associations across cancer types. High CPLX2 expression shows unfavorable associations in DLBC and KIRP, but favorable associations in LGG, SCLC, PAAD and READ. The DLBC 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 DLBC as the clearest survival context for CPLX2 RNA expression.
This table summarizes CPLX2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in LIHC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CPLX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CPLX2 shows lower tumor expression in COAD and ESCA and higher tumor expression in LIHC, UCEC, KIRP and BRCA. The LIHC box plot shows higher CPLX2 RNA expression in tumor versus normal tissue (log2 FC = +4.798, t-test p < 0.001).
This table shows molecular features associated with CPLX2 in patient tissues and cancer cell lines. In patient samples, CPLX2 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, CPLX2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
