Q-omics provides the consensus-scored MIR100HG profile across patient tissues and cancer cell-line models. MIR100HG expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, MIR100HG is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, MIR100HG RNA expression shows 21,402 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRP, BLCA, and LSCC as cancer lineages where MIR100HG 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 MIR100HG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MIR100HG survival associations across molecular data types. MIR100HG RNA expression shows survival associations in the most cancer types (20). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MIR100HG RNA expression–survival associations across cancer types. High MIR100HG expression shows unfavorable associations in KIRP, BLCA and LUSC, but favorable associations in UCS, LIHC and SKCM. The KIRP 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 KIRP as the clearest survival context for MIR100HG RNA expression.
This table summarizes MIR100HG tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in BLCA for RNA.
This table ranks reproducible tumor–normal expression differences for MIR100HG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MIR100HG shows lower tumor expression in BLCA, UCEC, LUSC, KIRP, KIRC and BRCA. The BLCA box plot shows higher MIR100HG RNA expression in normal versus tumor tissue (log2 FC = −3.234, t-test p < 0.001).
This table shows molecular features associated with MIR100HG in patient tissues and cancer cell lines. In patient samples, MIR100HG shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set.
