A study analyzed a metastatic lobular breast cancer tumor profiled at single nucleotide resolution, revealing 32 somatic non-synonymous coding mutations. These mutations were compared between the metastatic tumor and the primary tumor from the same patient, which had developed 9 years earlier. Five mutations were prevalent in the primary tumor, six were present at lower frequencies, 19 were not detected, and two were undetermined. The combined analysis of genome and transcriptome data identified two new RNA-editing events that altered the amino acid sequences of SRP9 and COG3. The study shows that single nucleotide mutational heterogeneity can be a property of low or intermediate grade primary breast cancers, and that significant evolution can occur with disease progression. Lobular breast cancer is an estrogen-receptor-positive subtype, accounting for approximately 15% of all breast cancers. The study sequenced the genome and transcriptome of a metastatic lobular breast cancer specimen, revealing 1,456 new coding nonsynonymous SNVs. Sanger sequencing confirmed 437 positions as non-synonymous coding variants. The study also identified two different heterozygous truncating variants in HAUS3, a member of the augmin complex, which is involved in genome stability. The study found that some mutations were present in the primary tumor at frequencies consistent with germline alleles, while others were present in minor subclones of tumor cells. The study also identified RNA-editing events, including two confirmed high frequency non-synonymous transcript editing events in COG3 and SRP9, resulting in variant protein sequences. The study emphasizes the importance of integrating RNA-seq data with tumor genomes in assessing protein variation. The study also highlights the importance of sequencing tumor samples early and late in the evolution of tumors to estimate allele frequency. The study suggests that sequencing primary breast cancers and pre-invasive malignancy may reveal significantly fewer candidates for tumor initiating mutations. The study used next generation sequencing and other methods to analyze the genomic landscape of the tumor, revealing the presence of mutations and RNA-editing events. The study also discusses the methods used for sequencing and analysis, including the use of a Binomial mixture model for SNV identification and a hidden Markov model for segmental copy number inference. The study was supported by various funding sources and acknowledges the contributions of multiple researchers and institutions.A study analyzed a metastatic lobular breast cancer tumor profiled at single nucleotide resolution, revealing 32 somatic non-synonymous coding mutations. These mutations were compared between the metastatic tumor and the primary tumor from the same patient, which had developed 9 years earlier. Five mutations were prevalent in the primary tumor, six were present at lower frequencies, 19 were not detected, and two were undetermined. The combined analysis of genome and transcriptome data identified two new RNA-editing events that altered the amino acid sequences of SRP9 and COG3. The study shows that single nucleotide mutational heterogeneity can be a property of low or intermediate grade primary breast cancers, and that significant evolution can occur with disease progression. Lobular breast cancer is an estrogen-receptor-positive subtype, accounting for approximately 15% of all breast cancers. The study sequenced the genome and transcriptome of a metastatic lobular breast cancer specimen, revealing 1,456 new coding nonsynonymous SNVs. Sanger sequencing confirmed 437 positions as non-synonymous coding variants. The study also identified two different heterozygous truncating variants in HAUS3, a member of the augmin complex, which is involved in genome stability. The study found that some mutations were present in the primary tumor at frequencies consistent with germline alleles, while others were present in minor subclones of tumor cells. The study also identified RNA-editing events, including two confirmed high frequency non-synonymous transcript editing events in COG3 and SRP9, resulting in variant protein sequences. The study emphasizes the importance of integrating RNA-seq data with tumor genomes in assessing protein variation. The study also highlights the importance of sequencing tumor samples early and late in the evolution of tumors to estimate allele frequency. The study suggests that sequencing primary breast cancers and pre-invasive malignancy may reveal significantly fewer candidates for tumor initiating mutations. The study used next generation sequencing and other methods to analyze the genomic landscape of the tumor, revealing the presence of mutations and RNA-editing events. The study also discusses the methods used for sequencing and analysis, including the use of a Binomial mixture model for SNV identification and a hidden Markov model for segmental copy number inference. The study was supported by various funding sources and acknowledges the contributions of multiple researchers and institutions.