Background: Identification of genomic alterations present in cancer patients may aid in cancer diagnosis, prognosis and therapeutic target discovery. In this study, we aimed to identify clinically actionable variants present in stage IV breast cancer (BC) samples. Materials and Methods: DNA was extracted from formalin-fixed paraffin-embedded samples of BC (n = 41). DNA was sequenced using MammaSeq, a BC-specific next-generation sequencing panel targeting 79 genes and 1369 mutations. Ion Torrent Suite 4.0 was used to make variant calls on the raw data, and the resulting single nucleotide variants were annotated using the CRAVAT toolkit. Single nucleotide variations (SNVs) were filtered to remove common polymorphisms and germline variants. CNVkit was employed to identify copy number variations (CNVs). The Precision Medicine Knowledgebase (PMKB) and OncoKB Precision Oncology Database were used to associate clinical significance with the identified variants. Results: A total of 41 samples from Turkish patients with BC were sequenced (read depth of 94-13,340; median of 1529). These patients were diagnosed with various BC subtypes including invasive ductal carcinoma, invasive lobular carcinoma, apocrine BC, and micropapillary BC. In total, 59 different alterations (49 SNVs and 10 CNVs) were identified. From these, 8 alterations (3 CNVs – ERBB2, FGFR1, and AR copy number gains and 5 SNVs – IDH1.R132H, TP53.E204∗, PI3KCA.E545K, PI3KCA.H1047R, and PI3KCA.R88Q) were identified to have some clinical significance by PMKB and OncoKB. Moreover, the top 5 genes with the most SNVs included PIK3CA, TP53, MAP3K1, ATM, and NCOR1. Additionally, copy number gains and losses were found in ERBB2, GRB7, IGFR1, AR, FGFR1, MYC, and IKBKB, and BRCA2, RUNX1, and RB1, respectively. Conclusion: We identified 59 unique alterations in 38 genes in 41 stage IV BC tissue samples using MammaSeqTM. Eight of these alterations were found to have some clinical significance by OncoKB and PKMB. This study highlights the potential use of cancer specific next-generation sequencing panels in clinic to get better insight into the patient-specific genomic alterations.