Loss of p73 Expression Contributes to Chronic Obstructive Pulmonary Disease.

Rationale: Multiciliated cell (MCC) loss and/or dysfunction is common in the small airways of patients with chronic obstructive pulmonary disease (COPD), but it is unclear if this contributes to COPD lung pathology. Objectives: To determine if loss of p73 causes a COPD-like phenotype in mice and explore whether smoking or COPD impact p73 expression. Methods: p73floxE7-E9 mice were crossed with Shh-Cre mice to generate mice lacking MCCs in the airway epithelium. The resulting p73Δairway mice were analyzed using electron microscopy, flow cytometry, morphometry, forced oscillation technique, and single-cell RNA sequencing. Furthermore, the effects of cigarette smoke on p73 transcript and protein expression were examined using in vitro and in vivo models and in studies including airway epithelium from smokers and patients with COPD. Measurements and Main Results: Loss of functional p73 in the respiratory epithelium resulted in a near-complete absence of MCCs in p73Δairway mice. In adulthood, these mice spontaneously developed neutrophilic inflammation and emphysema-like lung remodeling and had progressive loss of secretory cells. Exposure of normal airway epithelium cells to cigarette smoke rapidly and durably suppressed p73 expression in vitro and in vivo. Furthermore, tumor protein 73 mRNA expression was reduced in the airways of current smokers (n = 82) compared with former smokers (n = 69), and p73-expressing MCCs were reduced in the small airways of patients with COPD (n = 11) compared with control subjects without COPD (n = 12). Conclusions: Loss of functional p73 in murine airway epithelium results in the absence of MCCs and promotes COPD-like lung pathology. In smokers and patients with COPD, loss of p73 may contribute to MCC loss or dysfunction.

First international TNBC conference meeting report.

Recently, Georgia State University's Centennial Hall was the premier location for the 2017 International Conference on Triple Negative Breast Cancer (TNBC): Illuminating Actionable Biology, which was held from Sept. 18 to 20, 2017, in Atlanta, USA. The conference featured a stellar line-up of domestic and international speakers and diverse participants including TNBC survivors, luminaries in breast cancer research, medical students and fellows, clinicians, translational researchers, epidemiologists, biostatisticians, bioinformaticians, and representatives from the industry. This report distills the burning questions that spiked the event and summarizes key themes, findings, unique opportunities and future directions that emerged from this confluence of thought leaders.

Estimating relative mitochondrial DNA copy number using high throughput sequencing data.

We hypothesize that the relative mitochondria copy number (MTCN) can be estimated by comparing the abundance of mitochondrial DNA to nuclear DNA reads using high throughput sequencing data. To test this hypothesis, we examined relative MTCN across 13 breast cancer cell lines using the RT-PCR based NovaQUANT Human Mitochondrial to Nuclear DNA Ratio Kit as the gold standard. Six distinct computational approaches were used to estimate the relative MTCN in order to compare to the RT-PCR measurements. The results demonstrate that relative MTCN correlates well with the RT-PCR measurements using exome sequencing data, but not RNA-seq data. Through analysis of copy number variants (CNVs) in The Cancer Genome Atlas, we show that the two nuclear genes used in the NovaQUANT assay to represent the nuclear genome often experience CNVs in tumor cells, questioning the accuracy of this gold-standard method when it is applied to tumor cells.

Comparison of triple-negative breast cancer molecular subtyping using RNA from matched fresh-frozen versus formalin-fixed paraffin-embedded tissue.

BACKGROUND: Triple negative breast cancer (TNBC) is a heterogeneous disease that lacks unifying molecular alterations that can guide therapy decisions. We previously identified distinct molecular subtypes of TNBC (TNBCtype) using gene expression data generated on a microarray platform using frozen tumor specimens. Tumors and cell lines representing the identified subtypes have distinct enrichment in biologically relevant transcripts with differing sensitivity to standard chemotherapies and targeted agents. Since our initial discoveries, RNA-sequencing (RNA-seq) has evolved as a sensitive and quantitative tool to measure transcript abundance. METHODS: To demonstrate that TNBC subtypes were similar between platforms, we compared gene expression from matched specimens profiled by both microarray and RNA-seq from The Cancer Genome Atlas (TCGA). In the clinical care of patients with TNBC, tumor specimens collected for diagnostic purposes are processed by formalin fixation and paraffin-embedding (FFPE). Thus, for TNBCtype to eventually have broad and practical clinical utility we performed RNA-seq gene expression and molecular classification comparison between fresh-frozen (FF) and FFPE tumor specimens. RESULTS: Analysis of TCGA showed consistent subtype calls between 91% of evaluable samples demonstrating conservation of TNBC subtypes across microarray and RNA-seq platforms. We compared RNA-seq performed on 21-paired FF and FFPE TNBC specimens and evaluated genome alignment, transcript coverage, differential transcript enrichment and concordance of TNBC molecular subtype calls. We demonstrate that subtype accuracy between matched FF and FFPE samples increases with sequencing depth and correlation strength to an individual TNBC subtype. CONCLUSIONS: TNBC subtypes were reliably identified from FFPE samples, with highest accuracy if the samples were less than 4 years old and reproducible subtyping increased with sequencing depth. To reproducibly subtype tumors using gene expression, it is critical to select genes that do not vary due to platform type, tissue processing or RNA isolation method. The majority of differentially expressed transcripts between matched FF and FFPE samples could be attributed to transcripts selected for by RNA enrichment method. While differentially expressed transcripts did not impact TNBC subtyping, they will provide guidance on determining which transcripts to avoid when implementing a gene set size reduction strategy. TRIAL REGISTRATION: NCT00930930 07/01/2009.

Generation of an algorithm based on minimal gene sets to clinically subtype triple negative breast cancer patients.

BACKGROUND: Recently, a gene expression algorithm, TNBCtype, was developed that can divide triple-negative breast cancer (TNBC) into molecularly-defined subtypes. The algorithm has potential to provide predictive value for TNBC subtype-specific response to various treatments. TNBCtype used in a retrospective analysis of neoadjuvant clinical trial data of TNBC patients demonstrated that TNBC subtype and pathological complete response to neoadjuvant chemotherapy were significantly associated. Herein we describe an expression algorithm reduced to 101 genes with the power to subtype TNBC tumors similar to the original 2188-gene expression algorithm and predict patient outcomes. METHODS: The new classification model was built using the same expression data sets used for the original TNBCtype algorithm. Gene set enrichment followed by shrunken centroid analysis were used for feature reduction, then elastic-net regularized linear modeling was used to identify genes for a centroid model classifying all subtypes, comprised of 101 genes. The predictive capability of both this new "lean" algorithm and the original 2188-gene model were applied to an independent clinical trial cohort of 139 TNBC patients treated initially with neoadjuvant doxorubicin/cyclophosphamide and then randomized to receive either paclitaxel or ixabepilone to determine association of pathologic complete response within the subtypes. RESULTS: The new 101-gene expression model reproduced the classification provided by the 2188-gene algorithm and was highly concordant in the same set of seven TNBC cohorts used to generate the TNBCtype algorithm (87%), as well as in the independent clinical trial cohort (88%), when cases with significant correlations to multiple subtypes were excluded. Clinical responses to both neoadjuvant treatment arms, found BL2 to be significantly associated with poor response (Odds Ratio (OR) =0.12, p=0.03 for the 2188-gene model; OR = 0.23, p < 0.03 for the 101-gene model). Additionally, while the BL1 subtype trended towards significance in the 2188-gene model (OR = 1.91, p = 0.14), the 101-gene model demonstrated significant association with improved response in patients with the BL1 subtype (OR = 3.59, p = 0.02). CONCLUSIONS: These results demonstrate that a model using small gene sets can recapitulate the TNBC subtypes identified by the original 2188-gene model and in the case of standard chemotherapy, the ability to predict therapeutic response.

Subtyping of triple-negative breast cancer: implications for therapy.

Triple-negative breast cancer (TNBC) is a heterogeneous disease; gene expression analyses recently identified 6 distinct TNBC subtypes, each of which displays a unique biology. Exploring novel approaches for the treatment of these subtypes is critical, especially because the median survival for women with metastatic TNBC is less than 12 months, and virtually all women with metastatic TNBC ultimately will die of their disease despite systemic therapy. To date, not a single targeted therapy has been approved for the treatment of TNBC, and cytotoxic chemotherapy remains the standard treatment. In this review, the authors discuss recent developments in subtyping TNBC and the current and upcoming therapeutic strategies being explored in an attempt to target TNBC.

Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with distinct molecular subtypes that respond differentially to chemotherapy and targeted agents. The absence of high-frequency molecular alterations and a limited number of known biomarkers have limited the development of therapeutic strategies for the disease. Herein, we summarize the results of the first round of targeted therapy approaches in TNBC and discuss new preclinical strategies. Common themes emerge from the proposed strategies, such as the use of biomarkers to identify tumours with genomic instability, targeting adapted molecular states resulting from tumour suppressor loss, and targeting altered metabolic pathways.

Detection of internal exon deletion with exon Del.

BACKGROUND: Exome sequencing allows researchers to study the human genome in unprecedented detail. Among the many types of variants detectable through exome sequencing, one of the most over looked types of mutation is internal deletion of exons. Internal exon deletions are the absence of consecutive exons in a gene. Such deletions have potentially significant biological meaning, and they are often too short to be considered copy number variation. Therefore, to the need for efficient detection of such deletions using exome sequencing data exists. RESULTS: We present ExonDel, a tool specially designed to detect homozygous exon deletions efficiently. We tested ExonDel on exome sequencing data generated from 16 breast cancer cell lines and identified both novel and known IEDs. Subsequently, we verified our findings using RNAseq and PCR technologies. Further comparisons with multiple sequencing-based CNV tools showed that ExonDel is capable of detecting unique IEDs not found by other CNV tools. CONCLUSIONS: ExonDel is an efficient way to screen for novel and known IEDs using exome sequencing data. ExonDel and its source code can be downloaded freely at https://github.com/slzhao/ExonDel.

PIK3CA mutations in androgen receptor-positive triple negative breast cancer confer sensitivity to the combination of PI3K and androgen receptor inhibitors.

INTRODUCTION: Triple negative breast cancer (TNBC) is a heterogeneous collection of biologically diverse cancers, which contributes to variable clinical outcomes. Previously, we identified a TNBC subtype that has a luminal phenotype and expresses the androgen receptor (AR+). TNBC cells derived from these luminal AR + tumors have high frequency phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) mutations. The purpose of this study was to determine if targeting phosphoinositide 3-kinase (PI3K) alone or in combination with an AR antagonist is effective in AR + TNBC. METHODS: We determined the frequency of activating PIK3CA mutations in AR + and AR- TNBC clinical cases. Using AR + TNBC cell line and xenograft models we evaluated the effectiveness of PI3K inhibitors, used alone or in combination with an AR antagonist, on tumor cell growth and viability. RESULTS: PIK3CA kinase mutations were highly clonal, more frequent in AR + vs. AR- TNBC (40% vs. 4%), and often associated with concurrent amplification of the PIK3CA locus. PI3K/mTOR inhibitors had an additive growth inhibitory effect when combined with genetic or pharmacological AR targeting in AR + TNBC cells. We also analyzed the combination of bicalutamide +/- the pan-PI3K inhibitor GDC-0941 or the dual PI3K/mTOR inhibitor GDC-0980 in xenograft tumor studies and observed additive effects. CONCLUSIONS: While approximately one third of TNBC patients respond to neoadjuvant/adjuvant chemotherapy, recent studies have shown that patients with AR + TNBC are far less likely to benefit from the current standard of care chemotherapy regimens and novel targeted approaches need to be investigated. In this study, we show that activating PIK3CA mutations are enriched in AR + TNBC; and, we show that the growth and viability of AR + TNBC cell line models is significantly reduced after treatment with PI3K inhibitors used in combination with an AR antagonist. These results provide rationale for pre-selection of TNBC patients with a biomarker (AR expression) to investigate the use of AR antagonists in combination with PI3K/mTOR inhibitors.

Transforming growth factor beta receptor type III is a tumor promoter in mesenchymal-stem like triple negative breast cancer.

INTRODUCTION: There is a major need to better understand the molecular basis of triple negative breast cancer (TNBC) in order to develop effective therapeutic strategies. Using gene expression data from 587 TNBC patients we previously identified six subtypes of the disease, among which a mesenchymal-stem like (MSL) subtype. The MSL subtype has significantly higher expression of the transforming growth factor beta (TGF-ß) pathway-associated genes relative to other subtypes, including the TGF-ß receptor type III (TßRIII). We hypothesize that TßRIII is tumor promoter in mesenchymal-stem like TNBC cells. METHODS: Representative MSL cell lines SUM159, MDA-MB-231 and MDA-MB-157 were used to study the roles of TßRIII in the MSL subtype. We stably expressed short hairpin RNAs specific to TßRIII (TßRIII-KD). These cells were then used for xenograft tumor studies in vivo; and migration, invasion, proliferation and three dimensional culture studies in vitro. Furthermore, we utilized human gene expression datasets to examine TßRIII expression patterns across all TNBC subtypes. RESULTS: TßRIII was the most differentially expressed TGF-ß signaling gene in the MSL subtype. Silencing TßRIII expression in MSL cell lines significantly decreased cell motility and invasion. In addition, when TßRIII-KD cells were grown in a three dimensional (3D) culture system or nude mice, there was a loss of invasive protrusions and a significant decrease in xenograft tumor growth, respectively. In pursuit of the mechanistic underpinnings for the observed TßRIII-dependent phenotypes, we discovered that integrin-α2 was expressed at higher level in MSL cells after TßRIII-KD. Stable knockdown of integrin-α2 in TßRIII-KD MSL cells rescued the ability of the MSL cells to migrate and invade at the same level as MSL control cells. CONCLUSIONS: We have found that TßRIII is required for migration and invasion in vitro and xenograft growth in vivo. We also show that TßRIII-KD elevates expression of integrin-α2, which is required for the reduced migration and invasion, as determined by siRNA knockdown studies of both TßRIII and integrin-α2. Overall, our results indicate a potential mechanism in which TßRIII modulates integrin-α2 expression to effect MSL cell migration, invasion, and tumorigenicity.

Atezolizumab in Combination With Carboplatin and Survival Outcomes in Patients With Metastatic Triple-Negative Breast Cancer: The TBCRC 043 Phase 2 Randomized Clinical Trial.

Importance: Agents targeting programmed death ligand 1 (PD-L1) have demonstrated efficacy in triple-negative breast cancer (TNBC) when combined with chemotherapy and are now the standard of care in patients with PD-L1-positive metastatic disease. In contrast to microtubule-targeting agents, the effect of combining platinum compounds with programmed cell death 1 (PD-1)/PD-L1 immunotherapy has not been extensively determined. Objective: To evaluate the efficacy of atezolizumab with carboplatin in patients with metastatic TNBC. Design, Setting, and Participants: This phase 2 randomized clinical trial was conducted in 6 centers from August 2017 to June 2021. Interventions: Patients with metastatic TNBC were randomized to receive carboplatin area under the curve (AUC) 6 alone or with atezolizumab, 1200 mg, every 3 weeks until disease progression or unacceptable toxic effects with a 3-year duration of follow-up. Main Outcome and Measures: The primary end point was investigator-assessed progression-free survival (PFS). Secondary end points included overall response rate (ORR), clinical benefit rate (CBR), and overall survival (OS). Other objectives included correlation of response with tumor PD-L1 levels, tumor-infiltrating lymphocytes (TILs), tumor DNA- and RNA-sequenced biomarkers, TNBC subtyping, and multiplex analyses of immune markers. Results: All 106 patients with metastatic TNBC who were enrolled were female with a mean (range) age of 55 (27-79) years, of which 12 (19%) identified as African American/Black, 1 (1%) as Asian, 73 (69%) as White, and 11 (10%) as unknown. Patients were randomized and received either carboplatin (n = 50) or carboplatin and atezolizumab (n = 56). The combination improved PFS (hazard ratio [HR], 0.66; 95% CI, 0.44-1.01; P = .05) from a median of 2.2 to 4.1 months, increased ORR from 8.0% (95% CI, 3.2%-18.8%) to 30.4% (95% CI, 19.9%-43.3%), increased CBR at 6 months from 18.0% (95% CI, 9.8%-30.1%) to 37.5% (95% CI, 26.0%-50.6%), and improved OS (HR, 0.60; 95% CI, 0.37-0.96; P = .03) from a median of 8.6 to 12.6 months. Subgroup analysis showed PD-L1-positive tumors did not benefit more from adding atezolizumab (HR, 0.62; 95% CI, 0.23-1.65; P = .35). Patients with high TILs (HR, 0.12; 95% CI, 0.30-0.50), high mutation burden (HR, 0.50; 95% CI, 0.23-1.06), and prior chemotherapy (HR, 0.59; 95% CI, 0.36-0.95) received greater benefit on the combination. Patients with obesity and patients with more than 125 mg/dL on-treatment blood glucose levels were associated with better PFS (HR, 0.35; 95% CI, 0.10-1.80) on the combination. TNBC subtypes benefited from adding atezolizumab, except the luminal androgen receptor subtype. Conclusions and Relevance: In this randomized clinical trial, the addition of atezolizumab to carboplatin significantly improved survival of patients with metastatic TNBC regardless of PD-L1 status. Further, lower risk of disease progression was associated with increased TILs, higher mutation burden, obesity, and uncontrolled blood glucose levels. Trial Registration: ClinicalTrials.gov Identifier: NCT03206203.

NKG2A Is a Therapeutic Vulnerability in Immunotherapy Resistant MHC-I Heterogeneous Triple-Negative Breast Cancer.

Despite the success of immune checkpoint inhibition (ICI) in treating cancer, patients with triple-negative breast cancer (TNBC) often develop resistance to therapy, and the underlying mechanisms are unclear. MHC-I expression is essential for antigen presentation and T-cell-directed immunotherapy responses. This study demonstrates that TNBC patients display intratumor heterogeneity in regional MHC-I expression. In murine models, loss of MHC-I negates antitumor immunity and ICI response, whereas intratumor MHC-I heterogeneity leads to increased infiltration of natural killer (NK) cells in an IFNγ-dependent manner. Using spatial technologies, MHC-I heterogeneity is associated with clinical resistance to anti-programmed death (PD) L1 therapy and increased NK:T-cell ratios in human breast tumors. MHC-I heterogeneous tumors require NKG2A to suppress NK-cell function. Combining anti-NKG2A and anti-PD-L1 therapies restores complete response in heterogeneous MHC-I murine models, dependent on the presence of activated, tumor-infiltrating NK and CD8+ T cells. These results suggest that similar strategies may enhance patient benefit in clinical trials. SIGNIFICANCE: Clinical resistance to immunotherapy is common in breast cancer, and many patients will likely require combination therapy to maximize immunotherapeutic benefit. This study demonstrates that heterogeneous MHC-I expression drives resistance to anti-PD-L1 therapy and exposes NKG2A on NK cells as a target to overcome resistance. This article is featured in Selected Articles from This Issue, p. 201.

Epithelial Expressed B7-H4 Drives Differential Immunotherapy Response in Murine and Human Breast Cancer.

Combinations of immune checkpoint inhibitors (ICI, including anti-PD-1/PD-L1) and chemotherapy have been FDA approved for metastatic and early-stage triple-negative breast cancer (TNBC), but most patients do not benefit. B7-H4 is a B7 family ligand with proposed immunosuppressive functions being explored as a cancer immunotherapy target and may be associated with anti-PD-L1 resistance. However, little is known about its regulation and effect on immune cell function in breast cancers. We assessed murine and human breast cancer cells to identify regulation mechanisms of B7-H4 in vitro. We used an immunocompetent anti-PD-L1-sensitive orthotopic mammary cancer model and induced ectopic expression of B7-H4. We assessed therapy response and transcriptional changes at baseline and under treatment with anti-PD-L1. We observed B7-H4 was highly associated with epithelial cell status and transcription factors and found to be regulated by PI3K activity. EMT6 tumors with cell-surface B7-H4 expression were more resistant to immunotherapy. In addition, tumor-infiltrating immune cells had reduced immune activation signaling based on transcriptomic analysis. Paradoxically, in human breast cancer, B7-H4 expression was associated with survival benefit for patients with metastatic TNBC treated with carboplatin plus anti-PD-L1 and was associated with no change in response or survival for patients with early breast cancer receiving chemotherapy plus anti-PD-1. While B7-H4 induces tumor resistance to anti-PD-L1 in murine models, there are alternative mechanisms of signaling and function in human cancers. In addition, the strong correlation of B7-H4 to epithelial cell markers suggests a potential regulatory mechanism of B7-H4 independent of PD-L1. SIGNIFICANCE: This translational study confirms the association of B7-H4 expression with a cold immune microenvironment in breast cancer and offers preclinical studies demonstrating a potential role for B7-H4 in suppressing response to checkpoint therapy. However, analysis of two clinical trials with checkpoint inhibitors in the early and metastatic settings argue against B7-H4 as being a mechanism of clinical resistance to checkpoints, with clear implications for its candidacy as a therapeutic target.

Patient-derived breast tumor xenografts facilitating personalized cancer therapy.

Despite improved detection and reduction of breast cancer-related deaths over the recent decade, breast cancer remains the second leading cause of cancer death for women in the US, with 39,510 women expected to succumb to metastatic disease in 2012 alone (American Cancer Society, Cancer Facts &Figures 2012. Atlanta: American Cancer Society; 2012). Continued efforts in classification of breast cancers based on gene expression profiling and genomic sequencing have revealed an underlying complexity and molecular heterogeneity within the disease that continues to challenge therapeutic interventions. To successfully identify and translate new treatment regimens to the clinic, it is imperative that our preclinical models recapitulate this complexity and heterogeneity. In this review article, we discuss the recent advances in development and classification of patient-derived human breast tumor xenograft models that have the potential to facilitate the next phase of drug discovery for personalized cancer therapy based on the unique driver signaling pathways in breast tumor subtypes.

Transcriptome Meta-Analysis of Triple-Negative Breast Cancer Response to Neoadjuvant Chemotherapy.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with varying responses to neoadjuvant chemotherapy (NAC). The identification of biomarkers to predict NAC response and inform personalized treatment strategies is essential. In this study, we conducted large-scale gene expression meta-analyses to identify genes associated with NAC response and survival outcomes. The results showed that immune, cell cycle/mitotic, and RNA splicing-related pathways were significantly associated with favorable clinical outcomes. Furthermore, we integrated and divided the gene association results from NAC response and survival outcomes into four quadrants, which provided more insights into potential NAC response mechanisms and biomarker discovery.

Molecular signature incorporating the immune microenvironment enhances thyroid cancer outcome prediction.

Genomic and transcriptomic analysis has furthered our understanding of many tumors. Yet, thyroid cancer management is largely guided by staging and histology, with few molecular prognostic and treatment biomarkers. Here, we utilize a large cohort of 251 patients with 312 samples from two tertiary medical centers and perform DNA/RNA sequencing, spatial transcriptomics, and multiplex immunofluorescence to identify biomarkers of aggressive thyroid malignancy. We identify high-risk mutations and discover a unique molecular signature of aggressive disease, the Molecular Aggression and Prediction (MAP) score, which provides improved prognostication over high-risk mutations alone. The MAP score is enriched for genes involved in epithelial de-differentiation, cellular division, and the tumor microenvironment. The MAP score also identifies aggressive tumors with lymphocyte-rich stroma that may benefit from immunotherapy. Future clinical profiling of the stromal microenvironment of thyroid cancer could improve prognostication, inform immunotherapy, and support development of novel therapeutics for thyroid cancer and other stroma-rich tumors.

LR Hunting: A Random Forest Based Cell-Cell Interaction Discovery Method for Single-Cell Gene Expression Data.

Cell-cell interactions (CCIs) and cell-cell communication (CCC) are critical for maintaining complex biological systems. The availability of single-cell RNA sequencing (scRNA-seq) data opens new avenues for deciphering CCIs and CCCs through identifying ligand-receptor (LR) gene interactions between cells. However, most methods were developed to examine the LR interactions of individual pairs of genes. Here, we propose a novel approach named LR hunting which first uses random forests (RFs)-based data imputation technique to link the data between different cell types. To guarantee the robustness of the data imputation procedure, we repeat the computation procedures multiple times to generate aggregated imputed minimal depth index (IMDI). Next, we identify significant LR interactions among all combinations of LR pairs simultaneously using unsupervised RFs. We demonstrated LR hunting can recover biological meaningful CCIs using a mouse cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) dataset and a triple-negative breast cancer scRNA-seq dataset.

Tissue-specific expression of p73 and p63 isoforms in human tissues.

p73 and p63 are members of the p53 family that exhibit overlapping and distinct functions in development and homeostasis. The evaluation of p73 and p63 isoform expression across human tissue can provide greater insight to the functional interactions between family members. We determined the mRNA isoform expression patterns of TP73 and TP63 across a panel of 36 human tissues and protein expression within the highest-expressing tissues. TP73 and TP63 expression significantly correlated across tissues. In tissues with concurrent mRNA expression, nuclear co-expression of both proteins was observed in a majority of cells. Using GTEx data, we quantified p73 and p63 isoform expression in human tissue and identified that the α-isoforms of TP73 and TP63 were the predominant isoform expressed in nearly all tissues. Further, we identified a previously unreported p73 mRNA product encoded by exons 4 to 14. In sum, these data provide the most comprehensive tissue-specific atlas of p73 and p63 protein and mRNA expression patterns in human and murine samples, indicating coordinate expression of these transcription factors in the majority of tissues in which they are expressed.

Annexin A1 Is Required for Efficient Tumor Initiation and Cancer Stem Cell Maintenance in a Model of Human Breast Cancer.

Triple-negative breast cancer (TNBC) has a poor outcome compared to other breast cancer subtypes, and new therapies that target the molecular alterations driving tumor progression are needed. Annexin A1 is an abundant multi-functional Ca2+ binding and membrane-associated protein. Reported roles of Annexin A1 in breast cancer progression and metastasis are contradictory. Here, we sought to clarify the functions of Annexin A1 in the development and progression of TNBC. The association of Annexin A1 expression with patient prognosis in subtypes of TNBC was examined. Annexin A1 was stably knocked down in a panel of human and murine TNBC cell lines with high endogenous Annexin A1 expression that were then evaluated for orthotopic growth and spontaneous metastasis in vivo and for alterations in cell morphology in vitro. The impact of Annexin A1 knockdown on the expression of genes involved in mammary epithelial cell differentia tion and epithelial to mesenchymal transition was also determined. Annexin A1 mRNA levels correlated with poor patient prognosis in basal-like breast tumors and also in the basal-like 2 subset of TNBCs. Unexpectedly, loss of Annexin A1 expression had no effect on either primary tumor growth or spontaneous metastasis of MDA-MB-231_HM xenografts, but abrogated the growth rate of SUM149 orthotopic tumors. In an MMTV-PyMT driven allograft model of breast cancer, Annexin A1 depletion markedly delayed tumor formation in both immuno-competent and immuno-deficient mice and induced epithelial to mesenchymal transition and upregulation of basal markers. Finally, loss of Annexin A1 resulted in the loss of a discrete CD24+/Sca1- population containing putative tumor initiating cells. Collectively, our data demonstrate a novel cell-autonomous role for Annexin A1 in the promotion of tumor-forming capacity in a model of human breast cancer and suggest that some basal-like TNBCs may require high endogenous tumor cell Annexin A1 expression for continued growth.