Biology subjects

Wesolowski, R.

Publications and source records attributed to Wesolowski, R..

4 recordsLinked to original sources

bioRxiv2022

Augmentation of extracellular ATP synergizes with chemotherapy in triple negative breast cancer

IntroductionBreast cancer affects two million women worldwide every year and is the most common cause of cancer-related death among women. The triple-negative breast cancer (TNBC) sub-type is associated with an especially poor prognosis because currently available therapies, fail to induce long-lasting responses. Therefore, there is an urgent need to develop novel therapies that result in durable responses. One universal characteristic of the tumor microenvironment is a markedly elevated concentration of extracellular adenosine triphosphate (eATP). Chemotherapy exposure results in further increases in eATP through its release into the extracellular space of cancer cells via P2RX channels. eATP levels are reduced by eATPases. Given that high concentrations of eATP are cytotoxic, we hypothesized that augmenting the release of eATP through P2RX channels and inhibiting extracellular ATPases would sensitize TNBC cells to chemotherapy. MethodsTNBC cell lines MDA-MB 231, Hs 578t and MDA-MB 468 and non-tumorigenic immortalized mammary epithelial MCF-10A cells were treated with increasing concentrations the chemotherapeutic agent paclitaxel in the presence of eATPase inhibitors, specific agonists or antagonists of P2RXs with cell viability and eATP content being measured. Additionally, the mRNA, protein and cell surface expressions of the purinergic receptors P2RX4 and P2RX7 were evaluated in all examined cell lines via qRT-PCR, western blot, and flow cytometry analyses, respectively. ResultsIn the present study, we observed dose-dependent declines in cell viability and increases in eATP in paclitaxel-treated TNBC cell lines in the presence of inhibitors of eATPases. These effects were reversed by specific antagonists of P2RXs. Similar results were observed with P2RX activators. All examined cell lines expressed both P2RX4 and P2RX7 at the mRNA, protein and cell surface levels. ConclusionThese results reveal that eATP modulates the chemotherapeutic response in TNBC cell lines which could be exploited to enhance the efficacy of chemotherapy regimens for TNBC.

cancer biology↗

bioRxiv2019

Machine learning predicts rapid relapse of triple negative breast cancer

PurposeMetastatic relapse of triple-negative breast cancer (TNBC) within 2 years of diagnosis is associated with particularly aggressive disease and a distinct clinical course relative to TNBCs that relapse beyond 2 years. We hypothesized that rapid relapse TNBCs (rrTNBC; metastatic relapse or death <2 years) reflect unique genomic features relative to late relapse (lrTNBC; >2 years).\n\nPatients and MethodsWe identified 453 primary TNBCs from three publicly-available datasets and characterized each as rrTNBc, lrTNBC, or no relapse (nrTNBC: no relapse/death with at least 5 years follow-up). We compiled primary tumor clinical and multi-omic data, including transcriptome (n=453), copy number alterations (CNAs; n=317), and mutations in 171 cancer-related genes (n=317), then calculated published gene expression and immune signatures.\n\nResultsPatients with rrTNBC were higher stage at diagnosis (Chi-square p<0.0001) while lrTNBC were more likely to be non-basal PAM50 subtype (Chi-square p=0.03). Among 125 expression signatures, five immune signatures were significantly higher in nrTNBCs while lrTNBC were enriched for eight estrogen/luminal signatures (all FDR p<0.05). There was no significant difference in tumor mutation burden or percent genome altered across the groups. Among mutations, only TP53 mutations were significantly more frequent in rrTNBC compared to lrTNBC (Fisher exact FDR p=0.009). To develop an optimal classifier, we used 77 significant clinical and omic features to evaluate six modeling approaches encompassing simple, machine learning, and artificial neural network (ANN). Support vector machine outperformed other models with average receiver-operator characteristic area under curve >0.75.\n\nConclusionsWe provide a new approach to define TNBCs based on timing of relapse. We identify distinct clinical and genomic features that can be incorporated into machine learning models to predict rapid relapse of TNBC.

cancer biology↗

bioRxiv2018

Coupling between cerebral blood flow and cerebral blood volume: Contributions of different vascular compartments

A better understanding of the coupling between changes in cerebral blood flow (CBF) and cerebral blood volume (CBV) is vital for furthering our understanding of the BOLD response. The aim of this study was to measure CBF-CBV coupling in different vascular compartments during neural activation. Three haemodynamic parameters were measured during a visual stimulus. Look-Locker Flow-sensitive Alternating Inversion Recovery (LL-FAIR) was used to measure changes in CBF and arterial CBV (CBVa) using sequence parameters optimised for each contrast. Changes in total CBV (CBVtot) were measured using a Gadolinium based contrast agent technique. Haemodynamic changes were extracted from a region of interest based on voxels that were activated in the CBF experiments. The CBF-CBVtot coupling constant tot was measured as 0.16{+/-}0.14 and the CBF-CBVa coupling constant a was measured as 0.65{+/-}0.24. Using a two compartment model of the vasculature (arterial and venous), the change in venous CBV (CBVv) was predicted for an assumed value of baseline arterial and venous blood volume. These results will enhance the accuracy and reliability of applications that rely on models of the BOLD response, such as calibrated BOLD.

neuroscience↗

bioRxiv2017

Protein Interaction Screen on Peptide Matrix (PRISMA) reveals interaction footprints and the PTM-dependent interactome of intrinsically disordered C/EBPβ

CCAAT enhancer binding protein beta (C/EBP{beta}) is a pioneer transcription factor that specifies cell differentiation. C/EBP{beta} is intrinsically unstructured, a molecular feature common to many proteins involved in signal processing and epigenetics. The structure of C/EBP{beta} differs depending on alternative translation start site usage and multiple post-translational modifications (PTM). Mutation of distinct PTM sites in C/EBP{beta} alters designated protein interactions and cell differentiation, suggesting a C/EBP{beta} PTM indexing code determines epigenetic outcomes. Herein, we systematically explored the interactome of C/EBP{beta} using an array of spot-synthesised C/EBP{beta}-derived linear tiling peptides with and without PTM, combined with mass spectrometric proteomic analysis of protein interactions. We identified interaction footprints of ~1300 proteins in nuclear cell extracts, many with chromatin modifying, remodelling and RNA processing functions. The results suggest C/EBP{beta} acts as a multi-tasking molecular switchboard, integrating signal-dependent modifications and structural plasticity to orchestrate interactions with numerous protein complexes directing cell fate and function.\n\nHighlightsO_LIPeptide array based interaction proteomics map SLiM and PTM dependent C/EBP{beta} interactome\nC_LIO_LINovel links between C/EBP{beta}, RNA processing, transcription elongation, MLL, NuRD were revealed\nC_LIO_LIC/EBP{beta} structure organizes modular hub function for gene regulatory machinery\nC_LIO_LIPRISMA is suitable to resolve protein interactions and networks based on intrinsically disordered proteins\nC_LI

biochemistry↗