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Simple Summary: Chromosomal alterations and other structural variants have been recurrently identified in Wilms tumors (WT) and are promising biomarkers for risk stratification. Chromosome 1q gain occurs in one in three WTs and is associated with poor prognosis, but its impact on tumor biology remains unknown. Here, we investigated the mutational mechanisms and functional effects of chromosomal alterations in WTs, and in particular 1q gain. We identified subgroups of tumors with typical activated biological processes: muscle differentiation, immune system, kidney development and proliferation. Combining these subgroups with genomic data showed that tumors with 1q gain occur in all subgroups and can be associated with different functional effects. Also, 1q gain tumors differ in mutational mechanisms and co-occurring tumor-specific mutations. In conclusion, we identified subgroups of tumors with 1q gain and therefore propose that incorporating expression data in risk stratification could improve the clinical utility of 1q gain. Chromosomal alterations have recurrently been identified in Wilms tumors (WTs) and some are associated with poor prognosis. Gain of 1q (1q+) is of special interest given its high prevalence and is currently actively studied for its prognostic value. However, the underlying mutational mechanisms and functional effects remain unknown. In a national unbiased cohort of 30 primary WTs, we integrated somatic SNVs, CNs and SVs with expression data and distinguished four clusters characterized by affected biological processes: muscle differentiation, immune system, kidney development and proliferation. Combined genome-wide CN and SV profiles showed that tumors profoundly differ in both their types of 1q+ and genomic stability and can be grouped into WTs with co-occurring 1p−/1q+, multiple chromosomal gains or CN neutral tumors. We identified 1q+ in eight tumors that differ in mutational mechanisms, subsequent rearrangements and genomic contexts. Moreover, 1q+ tumors were present in all four expression clusters reflecting activation of various biological processes, and individual tumors overexpress different genes on 1q. In conclusion, by integrating CNs, SVs and gene expression, we identified subgroups of 1q+ tumors reflecting differences in the functional effect of 1q gain, indicating that expression data is likely needed for further risk stratification of 1q+ WTs. [ABSTRACT FROM AUTHOR]