Publications by authors named "Adrian V Lee"

153 Publications

Exosomes in breast cancer - Mechanisms of Action and Clinical Potential.

Mol Cancer Res 2021 Feb 24. Epub 2021 Feb 24.

Department of Pharmacology and Chemical Biology, University of Pittsburgh

Extracellular vesicles (EVs) are a heterogeneous group of cell-derived membrane vesicles comprising apoptotic bodies, microvesicles and small EVs also called as exosomes. Exosomes when initially identified were considered as a waste product but the advancement in research techniques have provided insight into the important roles of exosomes in cell-cell communication, various biological process and disease, including cancer. As an important component of EVs, exosomes contain various biomolecules such as microRNAs (miRs), lipids and proteins that largely reflect the characteristics of their parent cells. Notably, cancer cells generate and secrete many more exosomes than normal cells. A growing body of evidence suggests that exosomes, as mediators of intercellular crosstalk, play a role in tumorigenesis, cancer cell invasion, angiogenesis, tumor microenvironment (TME) formation and cancer metastasis. As we gain more insights into the association between exosomes and cancer, the potential of exosomes for clinical use is becoming more intriguing. This review is focused on the role of exosomes in breast cancer, in terms of breast cancer biology, mechanism of action, potential as biomarkers and therapeutic opportunities.
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http://dx.doi.org/10.1158/1541-7786.MCR-20-0952DOI Listing
February 2021

Comparative analysis of the AIB1 interactome in breast cancer reveals MTA2 as a repressive partner which silences E-Cadherin to promote EMT and associates with a pro-metastatic phenotype.

Oncogene 2021 Feb 8;40(7):1318-1331. Epub 2021 Jan 8.

Endocrine Oncology Research Group, Department of Surgery, Royal College of Surgeons in Ireland, Dublin, Ireland.

Steroid regulated cancer cells use nuclear receptors and associated regulatory proteins to orchestrate transcriptional networks to drive disease progression. In primary breast cancer, the coactivator AIB1 promotes estrogen receptor (ER) transcriptional activity to enhance cell proliferation. The function of the coactivator in ER metastasis however is not established. Here we describe AIB1 as a survival factor, regulator of pro-metastatic transcriptional pathways and a promising actionable target. Genomic alterations and functional expression of AIB1 associated with reduced disease-free survival in patients and enhanced metastatic capacity in novel CDX and PDX ex-vivo models of ER metastatic disease. Comparative analysis of the AIB1 interactome with complementary RNAseq characterized AIB1 as a transcriptional repressor. Specifically, we report that AIB1 interacts with MTA2 to form a repressive complex, inhibiting CDH1 (encoding E-cadherin) to promote EMT and drive progression. We further report that pharmacological and genetic inhibition of AIB1 demonstrates significant anti-proliferative activity in patient-derived models establishing AIB1 as a viable strategy to target endocrine resistant metastasis. This work defines a novel role for AIB1 in the regulation of EMT through transcriptional repression in advanced cancer cells with a considerable implication for prognosis and therapeutic interventions.
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http://dx.doi.org/10.1038/s41388-020-01606-3DOI Listing
February 2021

Acquired mutations and transcriptional remodeling in long-term estrogen-deprived locoregional breast cancer recurrences.

Breast Cancer Res 2021 Jan 6;23(1). Epub 2021 Jan 6.

Women's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.

Background: Endocrine therapy resistance is a hallmark of advanced estrogen receptor (ER)-positive breast cancer. In this study, we aimed to determine acquired genomic changes in endocrine-resistant disease.

Methods: We performed DNA/RNA hybrid-capture sequencing on 12 locoregional recurrences after long-term estrogen deprivation and identified acquired genomic changes versus each tumor's matched primary.

Results: Despite being up to 7 years removed from the primary lesion, most recurrences harbored similar intrinsic transcriptional and copy number profiles. Only two genes, AKAP9 and KMT2C, were found to have single nucleotide variant (SNV) enrichments in more than one recurrence. Enriched mutations in single cases included SNVs within transcriptional regulators such as ARID1A, TP53, FOXO1, BRD1, NCOA1, and NCOR2 with one local recurrence gaining three PIK3CA mutations. In contrast to DNA-level changes, we discovered recurrent outlier mRNA expression alterations were common-including outlier gains in TP63 (n = 5 cases [42%]), NTRK3 (n = 5 [42%]), NTRK2 (n = 4 [33%]), PAX3 (n = 4 [33%]), FGFR4 (n = 3 [25%]), and TERT (n = 3 [25%]). Recurrent losses involved ESR1 (n = 5 [42%]), RELN (n = 5 [42%]), SFRP4 (n = 4 [33%]), and FOSB (n = 4 [33%]). ESR1-depleted recurrences harbored shared transcriptional remodeling events including upregulation of PROM1 and other basal cancer markers.

Conclusions: Taken together, this study defines acquired genomic changes in long-term, estrogen-deprived disease; highlights the importance of longitudinal RNA profiling; and identifies a common ESR1-depleted endocrine-resistant breast cancer subtype with basal-like transcriptional reprogramming.
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http://dx.doi.org/10.1186/s13058-020-01379-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7788918PMC
January 2021

ADAM22/LGI1 complex as a new actionable target for breast cancer brain metastasis.

BMC Med 2020 11 19;18(1):349. Epub 2020 Nov 19.

Endocrine Oncology Research Group, Department of Surgery, Royal College of Surgeons in Ireland, Dublin 2, Ireland.

Background: Metastatic breast cancer is a major cause of cancer-related deaths in woman. Brain metastasis is a common and devastating site of relapse for several breast cancer molecular subtypes, including oestrogen receptor-positive disease, with life expectancy of less than a year. While efforts have been devoted to developing therapeutics for extra-cranial metastasis, drug penetration of blood-brain barrier (BBB) remains a major clinical challenge. Defining molecular alterations in breast cancer brain metastasis enables the identification of novel actionable targets.

Methods: Global transcriptomic analysis of matched primary and metastatic patient tumours (n = 35 patients, 70 tumour samples) identified a putative new actionable target for advanced breast cancer which was further validated in vivo and in breast cancer patient tumour tissue (n = 843 patients). A peptide mimetic of the target's natural ligand was designed in silico and its efficacy assessed in in vitro, ex vivo and in vivo models of breast cancer metastasis.

Results: Bioinformatic analysis of over-represented pathways in metastatic breast cancer identified ADAM22 as a top ranked member of the ECM-related druggable genome specific to brain metastases. ADAM22 was validated as an actionable target in in vitro, ex vivo and in patient tumour tissue (n = 843 patients). A peptide mimetic of the ADAM22 ligand LGI1, LGI1MIM, was designed in silico. The efficacy of LGI1MIM and its ability to penetrate the BBB were assessed in vitro, ex vivo and in brain metastasis BBB 3D biometric biohybrid models, respectively. Treatment with LGI1MIM in vivo inhibited disease progression, in particular the development of brain metastasis.

Conclusion: ADAM22 expression in advanced breast cancer supports development of breast cancer brain metastasis. Targeting ADAM22 with a peptide mimetic LGI1MIM represents a new therapeutic option to treat metastatic brain disease.
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http://dx.doi.org/10.1186/s12916-020-01806-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7677775PMC
November 2020

Identifying Genomic Alterations in Patients With Stage IV Breast Cancer Using MammaSeq: An International Collaborative Study.

Clin Breast Cancer 2020 Aug 20. Epub 2020 Aug 20.

Magee-Womens Research Institute, Pittsburgh, PA; Women's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA; UPMC Hillman Cancer Center, Pittsburgh, PA; Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA; Institute for Precision Medicine, University of Pittsburgh Cancer Institute, Pittsburgh, PA. Electronic address:

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 MammaSeq. 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.
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http://dx.doi.org/10.1016/j.clbc.2020.08.009DOI Listing
August 2020

Single-Cell Transcriptomic Heterogeneity in Invasive Ductal and Lobular Breast Cancer Cells.

Cancer Res 2021 Jan 4;81(2):268-281. Epub 2020 Nov 4.

Women's Cancer Research Center, UPMC Hillman Cancer Center, Magee-Womens Research Institute, Pittsburgh, Pennsylvania.

Invasive lobular breast carcinoma (ILC), one of the major breast cancer histologic subtypes, exhibits unique features compared with the well-studied ductal cancer subtype (IDC). The pathognomonic feature of ILC is loss of E-cadherin, mainly caused by inactivating mutations, but the contribution of this genetic alteration to ILC-specific molecular characteristics remains largely understudied. To profile these features transcriptionally, we conducted single-cell RNA sequencing on a panel of IDC and ILC cell lines, and an IDC cell line (T47D) with CRISPR-Cas9-mediated E-cadherin knockout (KO). Inspection of intracell line heterogeneity illustrated genetically and transcriptionally distinct subpopulations in multiple cell lines and highlighted rare populations of MCF7 cells highly expressing an apoptosis-related signature, positively correlated with a preadaptation signature to estrogen deprivation. Investigation of E-cadherin KO-induced alterations showed transcriptomic membranous systems remodeling, elevated resemblance to ILCs in regulon activation, and increased sensitivity to IFNγ-mediated growth inhibition via activation of IRF1. This study reveals single-cell transcriptional heterogeneity in breast cancer cell lines and provides a resource to identify drivers of cancer progression and drug resistance. SIGNIFICANCE: This study represents a key step towards understanding heterogeneity in cancer cell lines and the role of E-cadherin depletion in contributing to the molecular features of invasive lobular breast carcinoma.
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http://dx.doi.org/10.1158/0008-5472.CAN-20-0696DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7856056PMC
January 2021

Neural Network Deconvolution Method for Resolving Pathway-Level Progression of Tumor Clonal Expression Programs With Application to Breast Cancer Brain Metastases.

Front Physiol 2020 4;11:1055. Epub 2020 Sep 4.

Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States.

Metastasis is the primary mechanism by which cancer results in mortality and there are currently no reliable treatment options once it occurs, making the metastatic process a critical target for new diagnostics and therapeutics. Treating metastasis before it appears is challenging, however, in part because metastases may be quite distinct genomically from the primary tumors from which they presumably emerged. Phylogenetic studies of cancer development have suggested that changes in tumor genomics over stages of progression often result from shifts in the abundance of clonal cellular populations, as late stages of progression may derive from or select for clonal populations rare in the primary tumor. The present study develops computational methods to infer clonal heterogeneity and dynamics across progression stages via deconvolution and clonal phylogeny reconstruction of pathway-level expression signatures in order to reconstruct how these processes might influence average changes in genomic signatures over progression. We show, via application to a study of gene expression in a collection of matched breast primary tumor and metastatic samples, that the method can infer coarse-grained substructure and stromal infiltration across the metastatic transition. The results suggest that genomic changes observed in metastasis, such as gain of the signaling pathway, are likely caused by early events in clonal evolution followed by expansion of minor clonal populations in metastasis, a finding that may have translational implications for early detection or prevention of metastasis.
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http://dx.doi.org/10.3389/fphys.2020.01055DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7499245PMC
September 2020

Proteomic and transcriptomic profiling identifies mediators of anchorage-independent growth and roles of inhibitor of differentiation proteins in invasive lobular carcinoma.

Sci Rep 2020 07 13;10(1):11487. Epub 2020 Jul 13.

Women's Cancer Research Center, University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center (HCC), Magee-Womens Research Institute, 204 Craft Avenue, Pittsburgh, PA, 15213, USA.

Invasive lobular carcinoma (ILC) is a histological subtype of breast cancer with distinct molecular and clinical features from the more common subtype invasive ductal carcinoma (IDC). ILC cells exhibit anchorage-independent growth in ultra-low attachment (ULA) suspension cultures, which is largely attributed to the loss of E-cadherin. In addition to anoikis resistance, herein we show that human ILC cell lines exhibit enhanced cell proliferation in ULA cultures as compared to IDC cells. Proteomic comparison of ILC and IDC cell lines identified induction of PI3K/Akt and p90-RSK pathways specifically in ULA culture in ILC cells. Further transcriptional profiling uncovered unique upregulation of the inhibitors of differentiation family transcription factors ID1 and ID3 in ILC ULA culture, the knockdown of which diminished the anchorage-independent growth of ILC cell lines through cell cycle arrest. We find that ID1 and ID3 expression is higher in human ILC tumors as compared to IDC, correlated with worse prognosis uniquely in patients with ILC and associated with upregulation of angiogenesis and matrisome-related genes. Altogether, our comprehensive study of anchorage independence in human ILC cell lines provides mechanistic insights and clinical implications for metastatic dissemination of ILC and implicates ID1 and ID3 as novel drivers and therapeutic targets for lobular breast cancer.
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http://dx.doi.org/10.1038/s41598-020-68141-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7359337PMC
July 2020

Robust and accurate deconvolution of tumor populations uncovers evolutionary mechanisms of breast cancer metastasis.

Bioinformatics 2020 07;36(Suppl_1):i407-i416

Department of computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

Motivation: Cancer develops and progresses through a clonal evolutionary process. Understanding progression to metastasis is of particular clinical importance, but is not easily analyzed by recent methods because it generally requires studying samples gathered years apart, for which modern single-cell sequencing is rarely an option. Revealing the clonal evolution mechanisms in the metastatic transition thus still depends on unmixing tumor subpopulations from bulk genomic data.

Methods: We develop a novel toolkit called robust and accurate deconvolution (RAD) to deconvolve biologically meaningful tumor populations from multiple transcriptomic samples spanning the two progression states. RAD uses gene module compression to mitigate considerable noise in RNA, and a hybrid optimizer to achieve a robust and accurate solution. Finally, we apply a phylogenetic algorithm to infer how associated cell populations adapt across the metastatic transition via changes in expression programs and cell-type composition.

Results: We validated the superior robustness and accuracy of RAD over alternative algorithms on a real dataset, and validated the effectiveness of gene module compression on both simulated and real bulk RNA data. We further applied the methods to a breast cancer metastasis dataset, and discovered common early events that promote tumor progression and migration to different metastatic sites, such as dysregulation of ECM-receptor, focal adhesion and PI3k-Akt pathways.

Availability And Implementation: The source code of the RAD package, models, experiments and technical details such as parameters, is available at https://github.com/CMUSchwartzLab/RAD.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btaa396DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355293PMC
July 2020

Differential Regulation and Targeting of Estrogen Receptor α Turnover in Invasive Lobular Breast Carcinoma.

Endocrinology 2020 09;161(9)

Women's Cancer Research Center, UPMC Hillman Cancer Center, Magee Womens Research Institute, Pittsburgh, Pennsylvania.

Invasive lobular breast carcinoma (ILC) accounts for 10% to 15% of breast cancers diagnosed annually. Evidence suggests that some aspects of endocrine treatment response might differ between invasive ductal carcinoma (IDC) and ILC, and that patients with ILC have worse long-term survival. We analyzed The Cancer Genome Atlas dataset and observed lower levels of ESR1 mRNA (P = 0.002) and ERα protein (P = 0.038) in ER+ ILC (n = 137) compared to IDC (n = 554), and further confirmed the mRNA difference in a local UPMC cohort (ILC, n = 143; IDC, n = 877; P < 0.005). In both datasets, the correlation between ESR1 mRNA and ERα protein was weaker in ILC, suggesting differential post-transcriptional regulation of ERα. In vitro, 17β-estradiol (E2) decreased the rate of degradation and increased the half-life of ERα in ILC cell lines, whereas the opposite was observed in IDC cell lines. Further, E2 failed to induce robust ubiquitination of ERα in ILC cells. To determine the potential clinical relevance of these findings, we evaluated the effect of 2 selective estrogen receptor downregulators (SERDs), ICI 182,780 and AZD9496, on ERα turnover and cell growth. While ICI 182,780 and AZD9496 showed similar effects in IDC cells, in ILC cell lines, AZD9496 was not as effective as ICI 182,780 in decreasing ERα stability and E2-induced proliferation. Furthermore, AZD9496 exhibited partial agonist activity in growth assays in ILC cell lines. Our study provides evidence for a distinct ERα regulation by SERDs in ILC cell lines, and therefore it is important to include ILC models into preclinical and clinical testing of novel SERDs.
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http://dx.doi.org/10.1210/endocr/bqaa109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438704PMC
September 2020

Patient treatment and outcome after breast cancer orbital and periorbital metastases: a comprehensive case series including analysis of lobular versus ductal tumor histology.

Breast Cancer Res 2020 06 26;22(1):70. Epub 2020 Jun 26.

University of Pittsburgh School of Medicine, Department of Medicine, Division of Hematology/Oncology, UPMC Hillman Cancer Center, Pittsburgh, PA, USA.

Background: Breast cancer is the most common malignancy to spread to the orbit and periorbit, and the invasive lobular carcinoma (ILC) histologic subtype of breast cancer has been reported to form these ophthalmic metastases (OM) more frequently than invasive ductal carcinomas (IDC). We herein report our single academic institution experience with breast cancer OM with respect to anatomical presentation, histology (lobular vs. ductal), treatment, and survival.

Methods: We employed the natural language processing platform, TIES (Text Information Extraction System), to search 2.3 million de-identified patient pathology and radiology records at our institution in order to identify patients with OM secondary to breast cancer. We then compared the resultant cohort, the "OM cohort," to two other representative metastatic breast cancer patient (MBC) databases from our institution. Histological analysis of selected patients was performed.

Results: Our TIES search and manual refinement ultimately identified 28 patients who were diagnosed with breast cancer between 1995 and 2016 that subsequently developed OM. Median age at diagnosis was 54 (range 28-77) years of age. ER, PR, and HER2 status from the 28 patients with OM did not differ from other patients with MBC from our institution. The relative proportion of patients with ILC was significantly higher in the OM cohort (32.1%) than in other MBC patients in our institution (11.3%, p = 0.007). Median time to first OM in the OM cohort was 46.7 months, and OM were the second most frequent first metastases after bony metastases. After diagnosis of the first distant metastasis of any kind, median survival of patients with ILC (21.4 months) was significantly shorter than that of patients with IDC (55.3 months, p = 0.03). Nine patients developed bilateral OM. We observed a significant co-occurrence of OM and central nervous system metastases (p = 0.0053). The histological analysis revealed an interesting case in which the primary tumor was of a mixed ILC/IDC subtype, while only ILC was present in the OM.

Conclusions: OM from breast cancer are illustrative of the difference in metastatic behavior of ILC versus IDC and should be considered when treating patients with ILC, especially in those with complaints of visual acuity changes.
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http://dx.doi.org/10.1186/s13058-020-01309-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318761PMC
June 2020

SNHG7 is a lncRNA oncogene controlled by Insulin-like Growth Factor signaling through a negative feedback loop to tightly regulate proliferation.

Sci Rep 2020 05 22;10(1):8583. Epub 2020 May 22.

Women's Cancer Research Center, University of Pittsburgh, Pittsburgh, USA.

Evidence suggests Insulin-like growth factor 1 (IGF1) signaling is involved in the initiation and progression of a subset of breast cancers by inducing cell proliferation and survival. Although the signaling cascade following IGF1 receptor activation is well-studied, the key elements of the transcriptional response governing IGF1's actions are not well understood. Recent studies reveal that the majority of the genome is transcribed and that there are more long non-coding RNAs (lncRNAs) than protein coding genes, several of which are dysregulated in human cancer. However, studies on the regulation and mechanism of action of these lncRNAs are in their infancy. Here we show that IGF1 alters the expression levels of a subset of lncRNAs. SNHG7, a member of the small nucleolar host gene family, is a highly-expressed lncRNA that is consistently and significantly down-regulated by IGF1 signaling by a post-transcriptional mechanism through the MAPK pathway. SNHG7 regulates proliferation of breast cancer cell lines in a dose-dependent manner, and silencing SNHG7 expression causes cell cycle arrest in G0/G1. Intriguingly, SNHG7 alters the expression of many IGF1 signaling intermediates and IGF1-regulated genes suggesting a feedback mechanism to tightly regulate the IGF1 response. Finally, we show in clinical data that SNHG7 is overexpressed in tumors of a subset of breast cancer patients and that these patients have lower disease-free survival than patients without elevated SNHG7 expression. We propose that SNHG7 is a lncRNA oncogene that is controlled by growth factor signaling in a feedback mechanism to prevent hyperproliferation, and that this regulation can be lost in the development or progression of breast cancer.
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http://dx.doi.org/10.1038/s41598-020-65109-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244715PMC
May 2020

IGF1R constitutive activation expands luminal progenitors and influences lineage differentiation during breast tumorigenesis.

Dev Biol 2020 07 4;463(1):77-87. Epub 2020 May 4.

Women's Cancer Research Center, Department of Pharmacology and Chemical Biology, UPMC Hillman Cancer Center, Magee Women's Research Institute, USA. Electronic address:

Breast tumors display tremendous heterogeneity in part due to varying molecular alterations, divergent cells of origin, and differentiation. Understanding where and how this heterogeneity develops is likely important for effective breast cancer eradication. Insulin-like growth factor (IGF) signaling is critical for normal mammary gland development and function, and has an established role in tumor development and resistance to therapy. Here we demonstrate that constitutive activation of the IGF1 receptor (IGF1R) influences lineage differentiation during mammary tumorigenesis. Transgenic IGF1R constitutive activation promotes tumors with mixed histologies, multiple cell lineages and an expanded bi-progenitor population. In these tumors, IGF1R expands the luminal-progenitor population while influencing myoepithelial differentiation. Mammary gland transplantation with IGF1R-infected mammary epithelial cells (MECs) resulted in hyperplastic, highly differentiated outgrowths and attenuated reconstitution. Restricting IGF1R constitutive activation to luminal versus myoepithelial lineage-sorted MECs resulted in ductal reconstitutions co-expressing high IGF1R levels in the opposite lineage of origin. Using in vitro models, IGF1R constitutively activated MCF10A cells showed increased mammosphere formation and CD44+/CD24-population, which was dependent upon Snail and NFκB signaling. These results suggest that IGF1R expands luminal progenitor populations while also stimulating myoepithelial cell differentiation. This ability to influence lineage differentiation may promote heterogeneous mammary tumors, and have implications for clinical treatment.
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http://dx.doi.org/10.1016/j.ydbio.2020.04.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297516PMC
July 2020

Metastatic breast cancers have reduced immune cell recruitment but harbor increased macrophages relative to their matched primary tumors.

J Immunother Cancer 2019 10 18;7(1):265. Epub 2019 Oct 18.

Womens Cancer Research Center, UPMC Hillman Cancer Center, Magee Womens Research Institute, Pittsburgh, USA.

The interplay between the immune system and tumor progression is well recognized. However, current human breast cancer immunophenotyping studies are mostly focused on primary tumors with metastatic breast cancer lesions remaining largely understudied. To address this gap, we examined exome-capture RNA sequencing data from 50 primary breast tumors (PBTs) and their patient-matched metastatic tumors (METs) in brain, ovary, bone and gastrointestinal tract. We used gene expression signatures as surrogates for tumor infiltrating lymphocytes (TILs) and compared TIL patterns in PBTs and METs. Enrichment analysis and deconvolution methods both revealed that METs had a significantly lower abundance of total immune cells, including CD8+ T cells, regulatory T cells and dendritic cells. An exception was M2-like macrophages, which were significantly higher in METs across the organ sites examined. Multiplex immunohistochemistry results were consistent with data from the in-silico analysis and showed increased macrophages in METs. We confirmed the finding of a significant reduction in immune cells in brain METs (BRMs) by pathologic assessment of TILs in a set of 49 patient-matched pairs of PBT/BRMs. These findings indicate that METs have an overall lower infiltration of immune cells relative to their matched PBTs, possibly due to immune escape. RNAseq analysis suggests that the relative levels of M2-like macrophages are increased in METs, and their potential role in promoting breast cancer metastasis warrants further study.
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http://dx.doi.org/10.1186/s40425-019-0755-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6798422PMC
October 2019

Systematic discovery of the functional impact of somatic genome alterations in individual tumors through tumor-specific causal inference.

PLoS Comput Biol 2019 07 5;15(7):e1007088. Epub 2019 Jul 5.

Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States of America.

Cancer is mainly caused by somatic genome alterations (SGAs). Precision oncology involves identifying and targeting tumor-specific aberrations resulting from causative SGAs. We developed a novel tumor-specific computational framework that finds the likely causative SGAs in an individual tumor and estimates their impact on oncogenic processes, which suggests the disease mechanisms that are acting in that tumor. This information can be used to guide precision oncology. We report a tumor-specific causal inference (TCI) framework, which estimates causative SGAs by modeling causal relationships between SGAs and molecular phenotypes (e.g., transcriptomic, proteomic, or metabolomic changes) within an individual tumor. We applied the TCI algorithm to tumors from The Cancer Genome Atlas (TCGA) and estimated for each tumor the SGAs that causally regulate the differentially expressed genes (DEGs) in that tumor. Overall, TCI identified 634 SGAs that are predicted to cause cancer-related DEGs in a significant number of tumors, including most of the previously known drivers and many novel candidate cancer drivers. The inferred causal relationships are statistically robust and biologically sensible, and multiple lines of experimental evidence support the predicted functional impact of both the well-known and the novel candidate drivers that are predicted by TCI. TCI provides a unified framework that integrates multiple types of SGAs and molecular phenotypes to estimate which genome perturbations are causally influencing one or more molecular/cellular phenotypes in an individual tumor. By identifying major candidate drivers and revealing their functional impact in an individual tumor, TCI sheds light on the disease mechanisms of that tumor, which can serve to advance our basic knowledge of cancer biology and to support precision oncology that provides tailored treatment of individual tumors.
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http://dx.doi.org/10.1371/journal.pcbi.1007088DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650088PMC
July 2019

FGFR4 overexpression and hotspot mutations in metastatic ER+ breast cancer are enriched in the lobular subtype.

NPJ Breast Cancer 2019 27;5:19. Epub 2019 Jun 27.

1Women's Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh, PA USA.

Invasive lobular carcinoma (ILC) is an understudied subtype of breast cancer that requires novel therapies in the advanced setting. To study acquired resistance to endocrine therapy in ILC, we have recently performed RNA-Sequencing on long-term estrogen deprived cell lines and identified FGFR4 overexpression as a top druggable target. Here, we show that FGFR4 expression also increases dramatically in endocrine-treated distant metastases, with an average fold change of 4.8 relative to the paired primary breast tumor for ILC, and 2.4-fold for invasive ductal carcinoma (IDC). In addition, we now report that FGFR4 hotspot mutations are enriched in metastatic breast cancer, with an additional enrichment for ILC, suggesting a multimodal selection of FGFR4 activation. These data collectively support the notion that FGFR4 is an important mediator of endocrine resistance in ILC, warranting future mechanistic studies on downstream signaling of overexpressed wild-type and mutant FGFR4.
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http://dx.doi.org/10.1038/s41523-019-0114-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6597581PMC
June 2019

Frequent amplifications of ESR1, ERBB2 and MDM4 in primary invasive lobular breast carcinoma.

Cancer Lett 2019 Oct 20;461:21-30. Epub 2019 Jun 20.

Women's Cancer Research Center, Magee-Womens Research Institute, University of Pittsburgh, Pittsburgh, PA, USA; UPMC Hillman Cancer Center, Pittsburgh, PA, USA; Department of Pharmacology and Chemical Biology; University of Pittsburgh, Pittsburgh, PA, USA.

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer following invasive ductal carcinoma (IDC). To identify potential genetic drivers of ILC progression, we used NanoString nCounter technology to investigate the DNA copy number (CN) in 70 well-curated primary ILC samples. We confirmed prior observations of frequent amplification of CCND1 (33%), and MYC (17%) in ILC, but additionally identified a substantial subset of ILCs with ESR1 and ERBB2 (19%) amplifications. Of interest, tumors with ESR1 CN gains (14%) and amplification (10%) were more likely to recur compared to those with normal CN. Finally, we observed that MDM4 (MDMX) was amplified in 17% of ILC samples. MDM4 knockdown in TP53 wild-type ILC cell lines caused increased apoptosis, decreased proliferation associated with cell cycle arrest, and concomitant activation of TP53 target genes. Similar effects were seen in TP53 mutant cells, indicting a TP53-independent role for MDM4 in ILC. To conclude, amplification of ESR1 and MDM4 are potential genetic drivers of ILC. These amplifications may represent actionable, targetable tumor dependencies, and thus have potential clinical implications and warrant further study.
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http://dx.doi.org/10.1016/j.canlet.2019.06.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6682463PMC
October 2019

Molecular Biology Information Service: an innovative medical library-based bioinformatics support service for biomedical researchers.

Brief Bioinform 2020 05;21(3):876-884

University of Pittsburgh, Health Sciences Library System.

Biomedical researchers are increasingly reliant on obtaining bioinformatics training in order to conduct their research. Here we present a model that academic institutions may follow to provide such training for their researchers, based on the Molecular Biology Information Service (MBIS) of the Health Sciences Library System, University of Pittsburgh (Pitt). The MBIS runs a four-facet service with the following goals: (1) identify, procure and implement commercially licensed bioinformatics software, (2) teach hands-on workshops using bioinformatics tools to solve research questions, (3) provide in-person and email consultations on software/databases and (4) maintain a web portal providing overall guidance on the access and use of bioinformatics resources and MBIS-created webtools. This paper describes these facets of MBIS activities from 2006 to 2018, including outcomes from a survey measuring attitudes of Pitt researchers about MBIS service and performance.
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http://dx.doi.org/10.1093/bib/bbz035DOI Listing
May 2020

Bad to the Bone: The Role of the Insulin-Like Growth Factor Axis in Osseous Metastasis.

Clin Cancer Res 2019 06 11;25(12):3479-3485. Epub 2019 Feb 11.

RCV Medicine, Boehringer Ingelheim RCV, Vienna, Austria.

Bone metastases are a frequent complication of cancer that are associated with considerable morbidity. Current treatments may temporarily palliate the symptoms of bone metastases but often fail to delay their progression. Bones provide a permissive environment because they are characterized by dynamic turnover, secreting factors required for bone maintenance but also stimulating the establishment and growth of metastases. Insulin-like growth factors (IGF) are the most abundant growth factors in bone and are required for normal skeletal development and function. Via activation of the IGF-1 receptors (IGF-1R) and variant insulin receptors, IGFs promote cancer progression, aggressiveness, and treatment resistance. Of specific relevance to bone biology, IGFs contribute to the homing, dormancy, colonization, and expansion of bone metastases. Furthermore, preclinical evidence suggests that tumor cells can be primed to metastasize to bone by a high IGF-1 environment in the primary tumor, suggesting that bone metastases may reflect IGF dependency. Therapeutic targeting of the IGF axis may therefore provide an effective method for treating bone metastases. Indeed, anti-IGF-1R antibodies, IGF-1R tyrosine kinase inhibitors, and anti-IGF-1/2 antibodies have demonstrated antitumor activity in preclinical models of prostate and breast cancer metastases, either alone or in combination with other agents. Several studies suggest that such treatments can inhibit bone metastases without affecting growth of the primary tumor. Although previous trials of anti-IGF-1R drugs have generated negative results in unselected patients, these considerations suggest that future clinical trials of IGF-targeted agents may be warranted in patients with bone metastases.
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http://dx.doi.org/10.1158/1078-0432.CCR-18-2697DOI Listing
June 2019

Network-guided prediction of aromatase inhibitor response in breast cancer.

PLoS Comput Biol 2019 02 11;15(2):e1006730. Epub 2019 Feb 11.

Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America.

Prediction of response to specific cancer treatments is complicated by significant heterogeneity between tumors in terms of mutational profiles, gene expression, and clinical measures. Here we focus on the response of Estrogen Receptor (ER)+ post-menopausal breast cancer tumors to aromatase inhibitors (AI). We use a network smoothing algorithm to learn novel features that integrate several types of high throughput data and new cell line experiments. These features greatly improve the ability to predict response to AI when compared to prior methods. For a subset of the patients, for which we obtained more detailed clinical information, we can further predict response to a specific AI drug.
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http://dx.doi.org/10.1371/journal.pcbi.1006730DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386390PMC
February 2019

Targeted mutation detection in breast cancer using MammaSeq™.

Breast Cancer Res 2019 02 8;21(1):22. Epub 2019 Feb 8.

Department of Pharmacology and Chemical Biology, and Human Genetics, UPMC Hillman Cancer Center, Magee-Womens Research Institute, University of Pittsburgh, 204 Craft Avenue, Pittsburgh, PA, 15213, USA.

Background: Breast cancer is the most common invasive cancer among women worldwide. Next-generation sequencing (NGS) has revolutionized the study of cancer across research labs around the globe; however, genomic testing in clinical settings remains limited. Advances in sequencing reliability, pipeline analysis, accumulation of relevant data, and the reduction of costs are rapidly increasing the feasibility of NGS-based clinical decision making.

Methods: We report the development of MammaSeq, a breast cancer-specific NGS panel, targeting 79 genes and 1369 mutations, optimized for use in primary and metastatic breast cancer. To validate the panel, 46 solid tumors and 14 plasma circulating tumor DNA (ctDNA) samples were sequenced to a mean depth of 2311× and 1820×, respectively. Variants were called using Ion Torrent Suite 4.0 and annotated with cravat CHASM. CNVKit was used to call copy number variants in the solid tumor cohort. The oncoKB Precision Oncology Database was used to identify clinically actionable variants. Droplet digital PCR was used to validate select ctDNA mutations.

Results: In cohorts of 46 solid tumors and 14 ctDNA samples from patients with advanced breast cancer, we identified 592 and 43 protein-coding mutations. Mutations per sample in the solid tumor cohort ranged from 1 to 128 (median 3), and the ctDNA cohort ranged from 0 to 26 (median 2.5). Copy number analysis in the solid tumor cohort identified 46 amplifications and 35 deletions. We identified 26 clinically actionable variants (levels 1-3) annotated by OncoKB, distributed across 20 out of 46 cases (40%), in the solid tumor cohort. Allele frequencies of ESR1 and FOXA1 mutations correlated with CA.27.29 levels in patient-matched blood draws.

Conclusions: In solid tumor biopsies and ctDNA, MammaSeq detects clinically actionable mutations (OncoKB levels 1-3) in 22/46 (48%) solid tumors and in 4/14 (29%) of ctDNA samples. MammaSeq is a targeted panel suitable for clinically actionable mutation detection in breast cancer.
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http://dx.doi.org/10.1186/s13058-019-1102-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6368740PMC
February 2019

Integration of Cancer Registry Data into the Text Information Extraction System: Leveraging the Structured Data Import Tool.

J Pathol Inform 2018 24;9:47. Epub 2018 Dec 24.

Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

Introduction/background: Cancer registries in the US collect timely and systematic data on new cancer cases, extent of disease, staging, biomarker status, treatment, survival, and mortality of cancer cases. Existing methodologies for accessing local cancer registry data for research are time-consuming and often rely on the manual merging of data by staff registrars. In addition, existing registries do not provide direct access to these data nor do they routinely provide linkage to discrete electronic health record (EHR) data, reports, or imaging data. Automation of such linkage can provide an impressive data resource and make valuable data available for translational cancer research.

Methods: The UPMC Network Cancer Registry collects highly structured, longitudinal data on all reportable cancer patients, from the point of the diagnosis throughout treatment and follow-up/outcomes. Using commercial registry software, we collect data in compliance with standards governed by the North American Association of Central Cancer Registries. This standardization ensures that the data are highly structured with standard coding and collection methods, which support data exchange among central cancer registries and the Centers for Disease Control and Prevention.

Results: At the UPMC Hillman Cancer Center and University of Pittsburgh, we explored the feasibility of linking this well-curated, structured cancer registry data with unstructured text (i.e., pathology and radiology reports), using the Text Information Extraction System (TIES). We used the TIES platform to integrate breast cancer cases from the UPMC Network Cancer Registry system and then combine these data with other EHR data as a pilot use case that can be replicated for other cancers.

Conclusions: As a result of this integration, we now have a single searchable repository of information for breast cancer patients from the UPMC registry, combined with their pathology and radiology reports. The system that we developed is easily scalable to other health systems and cancer centers.
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http://dx.doi.org/10.4103/jpi.jpi_38_18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6319041PMC
December 2018

Whole genome amplification of cell-free DNA enables detection of circulating tumor DNA mutations from fingerstick capillary blood.

Sci Rep 2018 11 23;8(1):17313. Epub 2018 Nov 23.

Women's Cancer Research Center, Department of Pharmacology and Chemical Biology, UPMC Hillman Cancer Center, Magee Womens Research Institute, Pittsburgh, PA, 15213, USA.

The ability to measure mutations in plasma cell-free DNA (cfDNA) has the potential to revolutionize cancer surveillance and treatment by enabling longitudinal monitoring not possible with solid tumor biopsies. However, obtaining sufficient quantities of cfDNA remains a challenge for assay development and clinical translation; consequently, large volumes of venous blood are typically required. Here, we test proof-of-concept for using smaller volumes via fingerstick collection. Matched venous and fingerstick blood were obtained from seven patients with metastatic breast cancer. Fingerstick blood was separated at point-of-care using a novel paper-based concept to isolate plasma centrifuge-free. Patient cfDNA was then analyzed with or without a new method for whole genome amplification via rolling-circle amplification (WG-RCA). We identified somatic mutations by targeted sequencing and compared the concordance of mutation detection from venous and amplified capillary samples by droplet-digital PCR. Patient mutations were detected with 100% concordance after WG-RCA, although in some samples, allele frequencies showed greater variation likely due to differential amplification or primer inaccessibility. These pilot findings provide physiological evidence that circulating tumor DNA is accessible by fingerstick and sustains presence/absence of mutation detection after whole-genome amplification. Further refinement may enable simpler and less-invasive methods for longitudinal or theranostic surveillance of metastatic cancer.
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http://dx.doi.org/10.1038/s41598-018-35470-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251935PMC
November 2018

Frequent ESR1 and CDK Pathway Copy-Number Alterations in Metastatic Breast Cancer.

Mol Cancer Res 2019 02 24;17(2):457-468. Epub 2018 Oct 24.

Women's Cancer Research Center, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania.

DNA sequencing has identified a limited number of driver mutations in metastatic breast cancer beyond single base-pair mutations in the estrogen receptor (). However, our previous studies and others have observed that structural variants, such as ESR1 fusions, may also play a role. Therefore, we expanded upon these observations by performing a comprehensive and highly sensitive characterization of copy-number (CN) alterations in a large clinical cohort of metastatic specimens. NanoString DNA hybridization was utilized to measure CN gains, amplifications, and deletions of 67 genes in 108 breast cancer metastases, and in 26 cases, the patient-matched primary tumor. For ESR1, a copyshift algorithm was applied to identify CN imbalances at exon-specific resolution and queried large data sets (>15,000 tumors) that had previously undergone next-generation sequencing (NGS). Interestingly, a subset of ER tumors showed increased ESR1 CN (11/82, 13%); three had CN amplifications (4%) and eight had gains (10%). Increased CN was enriched in metastatic specimens versus primary tumors, and this was orthogonally confirmed in a large NGS data set. -amplified tumors showed a site-specific enrichment for bone metastases and worse outcomes than nonamplified tumors. No CN amplifications and only one gain was identified in ER tumors. copyshift was present in 5 of the 11 ESR1-amplified tumors. Other frequent amplifications included , and cell-cycle pathway members and , which showed mutually exclusivity with deletions of , and . IMPLICATIONS: Copy-number alterations of and key CDK pathway genes are frequent in metastatic breast cancers, and their clinical relevance should be tested further.
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http://dx.doi.org/10.1158/1541-7786.MCR-18-0946DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359977PMC
February 2019

Circulating Tumor Cell Phenotyping via High-Throughput Acoustic Separation.

Small 2018 08 3;14(32):e1801131. Epub 2018 Jul 3.

Department of Mechanical Engineering and Material Science, Duke University, Durham, NC, 27708, USA.

The study of circulating tumor cells (CTCs) offers pathways to develop new diagnostic and prognostic biomarkers that benefit cancer treatments. In order to fully exploit and interpret the information provided by CTCs, the development of a platform is reported that integrates acoustics and microfluidics to isolate rare CTCs from peripheral blood in high throughput while preserving their structural, biological, and functional integrity. Cancer cells are first isolated from leukocytes with a throughput of 7.5 mL h , achieving a recovery rate of at least 86% while maintaining the cells' ability to proliferate. High-throughput acoustic separation enables statistical analysis of isolated CTCs from prostate cancer patients to be performed to determine their size distribution and phenotypic heterogeneity for a range of biomarkers, including the visualization of CTCs with a loss of expression for the prostate specific membrane antigen. The method also enables the isolation of even rarer, but clinically important, CTC clusters.
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http://dx.doi.org/10.1002/smll.201801131DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6105522PMC
August 2018

Transcriptome Characterization of Matched Primary Breast and Brain Metastatic Tumors to Detect Novel Actionable Targets.

J Natl Cancer Inst 2019 04;111(4):388-398

Endocrine Oncology Research Group, Department of Surgery, Royal College of Surgeons in Ireland, Dublin, Ireland.

Background: Breast cancer brain metastases (BrMs) are defined by complex adaptations to both adjuvant treatment regimens and the brain microenvironment. Consequences of these alterations remain poorly understood, as does their potential for clinical targeting. We utilized genome-wide molecular profiling to identify therapeutic targets acquired in metastatic disease.

Methods: Gene expression profiling of 21 patient-matched primary breast tumors and their associated brain metastases was performed by TrueSeq RNA-sequencing to determine clinically actionable BrM target genes. Identified targets were functionally validated using small molecule inhibitors in a cohort of resected BrM ex vivo explants (n = 4) and in a patient-derived xenograft (PDX) model of BrM. All statistical tests were two-sided.

Results: Considerable shifts in breast cancer cell-specific gene expression profiles were observed (1314 genes upregulated in BrM; 1702 genes downregulated in BrM; DESeq; fold change > 1.5, Padj < .05). Subsequent bioinformatic analysis for readily druggable targets revealed recurrent gains in RET expression and human epidermal growth factor receptor 2 (HER2) signaling. Small molecule inhibition of RET and HER2 in ex vivo patient BrM models (n = 4) resulted in statistically significantly reduced proliferation (P < .001 in four of four models). Furthermore, RET and HER2 inhibition in a PDX model of BrM led to a statistically significant antitumor response vs control (n = 4, % tumor growth inhibition [mean difference; SD], anti-RET = 86.3% [1176; 258.3], P < .001; anti-HER2 = 91.2% [1114; 257.9], P < .01).

Conclusions: RNA-seq profiling of longitudinally collected specimens uncovered recurrent gene expression acquisitions in metastatic tumors, distinct from matched primary tumors. Critically, we identify aberrations in key oncogenic pathways and provide functional evidence for their suitability as therapeutic targets. Altogether, this study establishes recurrent, acquired vulnerabilities in BrM that warrant immediate clinical investigation and suggests paired specimen expression profiling as a compelling and underutilized strategy to identify targetable dependencies in advanced cancers.
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http://dx.doi.org/10.1093/jnci/djy110DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449168PMC
April 2019

Loss of E-cadherin Enhances IGF1-IGF1R Pathway Activation and Sensitizes Breast Cancers to Anti-IGF1R/InsR Inhibitors.

Clin Cancer Res 2018 10 25;24(20):5165-5177. Epub 2018 Jun 25.

Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.

Insulin-like growth factor 1 (IGF1) signaling regulates breast cancer initiation and progression and associated cancer phenotypes. We previously identified E-cadherin () as a repressor of IGF1 signaling and in this study examined how loss of E-cadherin affects IGF1R signaling and response to anti-IGF1R/insulin receptor (InsR) therapies in breast cancer. Breast cancer cell lines were used to assess how altered E-cadherin levels regulate IGF1R signaling and response to two anti-IGF1R/InsR therapies. proximity ligation assay (PLA) was used to define interaction between IGF1R and E-cadherin. TCGA RNA-seq and RPPA data were used to compare IGF1R/InsR activation in estrogen receptor-positive (ER+) invasive lobular carcinoma (ILC) and invasive ductal carcinoma (IDC) tumors. ER+ ILC cell lines and xenograft tumor explant cultures were used to evaluate efficacy to IGF1R pathway inhibition in combination with endocrine therapy. Diminished functional E-cadherin increased both activation of IGF1R signaling and efficacy to anti-IGF1R/InsR therapies. PLA demonstrated a direct endogenous interaction between IGF1R and E-cadherin at points of cell-cell contact. Increased expression of IGF1 ligand and levels of IGF1R/InsR phosphorylation were observed in E-cadherin-deficient ER+ ILC compared with IDC tumors. IGF1R pathway inhibitors were effective in inhibiting growth in ER+ ILC cell lines and synergized with endocrine therapy and similarly IGF1R/InsR inhibition reduced proliferation in ILC tumor explant culture. We provide evidence that loss of E-cadherin hyperactivates the IGF1R pathway and increases sensitivity to IGF1R/InsR targeted therapy, thus identifying the IGF1R pathway as a potential novel target in E-cadherin-deficient breast cancers. .
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http://dx.doi.org/10.1158/1078-0432.CCR-18-0279DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6821389PMC
October 2018

Precision Medicine in Hormone Receptor-Positive Breast Cancer.

Front Oncol 2018 4;8:144. Epub 2018 May 4.

Women's Cancer Research Center, Department of Pharmacology and Chemical Biology, UPMC Hillman Cancer Center, Magee Womens Research Institute, Pittsburgh, PA, United States.

In recent decades, breast cancer has become largely manageable due to successes with hormone receptor targeting. Hormone receptor-positive tumors have favorable outcomes in comparison to estrogen receptor (ESR1, ER)/progesterone receptor-negative tumors given the targetable nature of these tumors, as well as their inherently less aggressive character. Nonetheless, treatment resistance is frequently encountered due to a variety of mechanisms, including mutations and loss of ER expression. A new era of precision medicine utilizes a range of methodologies to allow real-time analysis of individual genomic signatures in metastases and liquid biopsies with the goal of finding clinically actionable targets. Preliminary studies have shown improved progression-free survival and overall survival with implementation of this information for clinical decision making. In this review, we will discuss the opportunities and challenges in integrating precision medicine through next-generation genomic sequencing into the management of breast cancer.
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http://dx.doi.org/10.3389/fonc.2018.00144DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945817PMC
May 2018

Invasive lobular and ductal breast carcinoma differ in immune response, protein translation efficiency and metabolism.

Sci Rep 2018 05 8;8(1):7205. Epub 2018 May 8.

Womens Cancer Research Center, UPMC Hillman Cancer Center, Magee Womens Research Institute, Pittsburgh, PA, 15213, USA.

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer following invasive ductal carcinoma (IDC). ILC differs from IDC in a number of histological and clinical features, such as single strand growth, difficulty in detection, and frequent late recurrences. To understand the molecular pathways involved in the clinical characteristics of ILC, we compared the gene expression profiles of luminal A ILC and luminal A IDC using data from TCGA and utilized samples from METABRIC as a validation data set. Top pathways that were significantly enriched in ILC were related to immune response. ILC exhibited a higher activity of almost all types of immune cells based on cell type-specific signatures compared to IDC. Conversely, pathways that were less enriched in ILC were related to protein translation and metabolism, which we functionally validated in cell lines. The higher immune activity uncovered in our study highlights the currently unexplored potential of a response to immunotherapy in a subset of patients with ILC. Furthermore, the lower rates of protein translation and metabolism - known features of tumor dormancy - may play a role in the late recurrences of ILC and lower detection rate in mammography and PET scanning.
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http://dx.doi.org/10.1038/s41598-018-25357-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5940770PMC
May 2018