Triple negative breast cancer (TNBC) is one of the most aggressive form of breast cancer (BC) with the highest mortality due to high rate of relapse, resistance, and lack of an effective treatment. Various molecular approaches have been used to target TNBC but with little success. Here, using machine learning algorithms, we analyzed the available BC data from the Cancer Genome Atlas Network (TCGA) and have identified two potential genes, TBC1D9 (TBC1 domain family member 9) and MFGE8 (Milk Fat Globule-EGF Factor 8 Protein), that could successfully differentiate TNBC from non-TNBC, irrespective of their heterogeneity. TBC1D9 is under-expressed in TNBC as compared to non-TNBC patients, while MFGE8 is over-expressed. Overexpression of TBC1D9 has a better prognosis whereas overexpression of MFGE8 correlates with a poor prognosis. Protein-protein interaction analysis by affinity purification mass spectrometry (AP-MS) and proximity biotinylation (BioID) experiments identified a role for TBC1D9 in maintaining cellular integrity, whereas MFGE8 would be involved in various tumor survival processes. These promising genes could serve as biomarkers for TNBC and deserve further investigation as they have the potential to be developed as therapeutic targets for TNBC. Triple negative breast cancer (TNBC) accounts for 10-20% of all breast cancers (BC). They are characterized by lack of the hormonal receptors estrogen (ER) and progesterone (PR), and the overexpression of human epidermal growth factor receptor 2 (HER2) 1. It is the most aggressive form of BC and is very heterogeneous 2. The complexity of TNBC increases due to its high risk of relapse, and poor progression-free survival (PFS) and overall survival (OS) 3. The PFS for metastatic TNBC patients is 3-4 months after treatment failure 4. The 5-year mortality rate for early stage TNBC after surgery is 37%, whereas half of them relapse 5. According to gene expression pattern, TNBC has been classified in 6 different molecular subtypes namely Basal like (BL)1, BL2, Luminal androgen receptor (LAR), Immunomodulatory (IM), Mesenchymal (M) and Mesenchymal stem like (MSL), with some that cannot be classified 6. Lehmann et al., 2011, have shown that each of these subgroups can be further divided into intrinsic subtypes of BC (Luminal A, Luminal B, HER2, normal breast like, Basal like and unclassified) based on their gene expression 6. This stipulates why TNBC has different clinicopathological outcomes for different patients, rendering treatment arduous. On March 8, 2019, FDA approved immunotherapy Atezolizumab (targeting PD-L1) in combination with chemotherapy (nab-paclitaxel) for initial treatment of women with advanced TNBC positive for PD-L1 protein expression 7,8. Nevertheless, there is no FDA approved target therapy for TNBC patients as a whole so far 9. TNBC heterogeneity and aggressiveness call for an unmet need to identify genes that could serve as biomarkers to differentiate TNBC from other BCs, as well as serve as potential targets therapy irrespective of their heterogene...

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Bromodomains (BRDs) are a family of evolutionarily conserved domains that are the main readers of acetylated lysine (Kac) residues on proteins. Recently, numerous BRD-containing proteins have been proven essential for transcriptional regulation in numerous contexts. This is exemplified by the multi-subunit mSWI/SNF chromatin remodeling complexes, which incorporate up to 10 BRDs within five distinct subunits, allowing for extensive integration of Kac signaling to inform transcriptional regulation. As dysregulated transcription promotes oncogenesis, we sought to characterize how BRD-containing subunits contribute molecularly to mSWI/SNF functions. By combining genome editing, functional proteomics, and cellular biology, we found that loss of any single BRD-containing mSWI/SNF subunit altered but did not fully disrupt the various mSWI/SNF complexes. In addition, we report that the downregulation of BRD7 is common in invasive lobular carcinoma and modulates the interactome of its homologue, BRD9. We show that these alterations exacerbate sensitivities to inhibitors targeting epigenetic regulatorsnotably, inhibitors targeting the BRDs of non-mSWI/SNF proteins. Our results highlight the interconnections between distinct mSWI/SNF complexes and their far-reaching impacts on transcriptional regulation in human health and disease. The mass spectrometry data generated have been deposited to MassIVE and ProteomeXchange and assigned the identifiers MSV000089357, MSV000089362, and PXD033572.