Q-omics provides the consensus-scored C16orf70 profile across patient tissues and cancer cell-line models. C16orf70 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, C16orf70 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, C16orf70 protein abundance shows 20,873 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, COAD, and GBM as cancer lineages where C16orf70 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 C16orf70 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C16orf70 survival associations across molecular data types. C16orf70 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C16orf70 RNA expression–survival associations across cancer types. High C16orf70 expression shows unfavorable associations in BLCA, MESO and LUSC, but favorable associations in KIRC, SCLC and UCEC. The BLCA 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 BLCA as the clearest survival context for C16orf70 RNA expression.
This table summarizes C16orf70 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for C16orf70. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C16orf70 shows lower tumor expression in THCA and higher tumor expression in COAD, KIRC, BLCA, HNSC and LUAD. The COAD box plot shows higher C16orf70 RNA expression in tumor versus normal tissue (log2 FC = +0.689, t-test p < 0.001).
This table shows molecular features associated with C16orf70 in patient tissues and cancer cell lines. In patient samples, C16orf70 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, C16orf70 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 BONE and LARGE_INTESTINE.
