Q-omics provides the consensus-scored CNN3 profile across patient tissues and cancer cell-line models. CNN3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CNN3 is differentially expressed in 11, with the highest sampling consensus in LIHC. Additionally, CNN3 protein abundance shows 25,975 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, LIHC, and PDAC as cancer lineages where CNN3 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 CNN3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CNN3 survival associations across molecular data types. CNN3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CNN3 RNA expression–survival associations across cancer types. High CNN3 expression shows unfavorable associations in BLCA, SCLC, ACC, MESO and LGG, but favorable associations in KIRC. The KIRC 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 KIRC as the clearest survival context for CNN3 RNA expression.
This table summarizes CNN3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in LIHC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for CNN3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CNN3 shows lower tumor expression in LUSC, KICH, LUAD and BRCA and higher tumor expression in LIHC and CHOL. The LIHC box plot shows higher CNN3 RNA expression in tumor versus normal tissue (log2 FC = +1.240, t-test p < 0.001).
This table shows molecular features associated with CNN3 in patient tissues and cancer cell lines. In patient samples, CNN3 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, CNN3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
