Selection of optimal quantile protein biomarkers based on cell-level immunohistochemistry data.

BACKGROUND: Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells. RESULTS: We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells' cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers. CONCLUSION: The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level.

Quantile Index Biomarkers Based on Single-Cell Expression Data.

Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology platforms can provide distributions of cellular signal intensity (CSI) levels of biomolecules across the entire cell populations of interest within the sampled tumor tissue. However, the heterogeneity of CSI levels is usually ignored, and the simple mean signal intensity value is considered a cancer biomarker. Here we consider the entire distribution of CSI expression levels of a given biomolecule in the cancer cell population as a predictor of clinical outcome. The proposed quantile index (QI) biomarker is defined as the weighted average of CSI distribution quantiles in individual tumors. The weight for each quantile is determined by fitting a functional regression model for a clinical outcome. That is, the weights are optimized so that the resulting QI has the highest power to predict a relevant clinical outcome. The proposed QI biomarkers were derived for proteins expressed in cancer cells of malignant breast tumors and demonstrated improved prognostic value compared with the standard mean signal intensity predictors. The R package Qindex implementing QI biomarkers has been developed. The proposed approach is not limited to immunohistochemistry data and can be based on any cell-level expressions of proteins or nucleic acids.

Quantification of spatial tumor heterogeneity in immunohistochemistry staining images.

MOTIVATION: Quantitative immunofluorescence is often used for immunohistochemistry quantification of proteins that serve as cancer biomarkers. Advanced image analysis systems for pathology allow capturing expression levels in each individual cell or subcellular compartment. However, only the mean signal intensity within the cancer tissue region of interest is usually considered as biomarker completely ignoring the issue of tumor heterogeneity. RESULTS: We propose using immunohistochemistry image-derived information on the spatial distribution of cellular signal intensity (CSI) of protein expression within the cancer cell population to quantify both mean expression level and tumor heterogeneity of CSI levels. We view CSI levels as marks in a marked point process of cancer cells in the tissue and define spatial indices based on conditional mean and conditional variance of the marked point process. The proposed methodology provides objective metrics of cell-to-cell heterogeneity in protein expressions that allow discriminating between different patterns of heterogeneity. The prognostic utility of new spatial indices is investigated and compared to the standard mean signal intensity biomarkers using the protein expressions in tissue microarrays incorporating tumor tissues from 1000+ breast cancer patients. AVAILABILITY AND IMPLEMENTATION: THE R CODE FOR COMPUTING THE PROPOSED SPATIAL INDICES IS INCLUDED AS SUPPLEMENTARY MATERIAL: . SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Control of CCND1 ubiquitylation by the catalytic SAGA subunit USP22 is essential for cell cycle progression through G1 in cancer cells.

Overexpression of the deubiquitylase ubiquitin-specific peptidase 22 (USP22) is a marker of aggressive cancer phenotypes like metastasis, therapy resistance, and poor survival. Functionally, this overexpression of USP22 actively contributes to tumorigenesis, as USP22 depletion blocks cancer cell cycle progression in vitro, and inhibits tumor progression in animal models of lung, breast, bladder, ovarian, and liver cancer, among others. Current models suggest that USP22 mediates these biological effects via its role in epigenetic regulation as a subunit of the Spt-Ada-Gcn5-acetyltransferase (SAGA) transcriptional cofactor complex. Challenging the dogma, we report here a nontranscriptional role for USP22 via a direct effect on the core cell cycle machinery: that is, the deubiquitylation of the G1 cyclin D1 (CCND1). Deubiquitylation by USP22 protects CCND1 from proteasome-mediated degradation and occurs separately from the canonical phosphorylation/ubiquitylation mechanism previously shown to regulate CCND1 stability. We demonstrate that control of CCND1 is a key mechanism by which USP22 mediates its known role in cell cycle progression. Finally, USP22 and CCND1 levels correlate in patient lung and colorectal cancer samples and our preclinical studies indicate that targeting USP22 in combination with CDK inhibitors may offer an approach for treating cancer patients whose tumors exhibit elevated CCND1.

Neuronatin is a modifier of estrogen receptor-positive breast cancer incidence and outcome.

PURPOSE: Understanding the molecular mediators of breast cancer survival is critical for accurate disease prognosis and improving therapies. Here, we identified Neuronatin (NNAT) as a novel antiproliferative modifier of estrogen receptor-alpha (ER+) breast cancer. EXPERIMENTAL DESIGN: Genomic regions harboring breast cancer modifiers were identified by congenic mapping in a rat model of carcinogen-induced mammary cancer. Tumors from susceptible and resistant congenics were analyzed by RNAseq to identify candidate genes. Candidates were prioritized by correlation with outcome, using a consensus of three breast cancer patient cohorts. NNAT was transgenically expressed in ER+ breast cancer lines (T47D and ZR75), followed by transcriptomic and phenotypic characterization. RESULTS: We identified a region on rat chromosome 3 (142-178 Mb) that modified mammary tumor incidence. RNAseq of the mammary tumors narrowed the candidate list to three differentially expressed genes: NNAT, SLC35C2, and FAM210B. NNAT mRNA and protein also correlated with survival in human breast cancer patients. Quantitative immunohistochemistry of NNAT protein revealed an inverse correlation with survival in a univariate analysis of patients with invasive ER+ breast cancer (training cohort: n = 444, HR = 0.62, p = 0.031; validation cohort: n = 430, HR = 0.48, p = 0.004). NNAT also held up as an independent predictor of survival after multivariable adjustment (HR = 0.64, p = 0.038). NNAT significantly reduced proliferation and migration of ER+ breast cancer cells, which coincided with altered expression of multiple related pathways. CONCLUSIONS: Collectively, these data implicate NNAT as a novel mediator of cell proliferation and migration, which correlates with decreased tumorigenic potential and prolonged patient survival.

Validation of tumor protein marker quantification by two independent automated immunofluorescence image analysis platforms.

Protein marker levels in formalin-fixed, paraffin-embedded tissue sections traditionally have been assayed by chromogenic immunohistochemistry and evaluated visually by pathologists. Pathologist scoring of chromogen staining intensity is subjective and generates low-resolution ordinal or nominal data rather than continuous data. Emerging digital pathology platforms now allow quantification of chromogen or fluorescence signals by computer-assisted image analysis, providing continuous immunohistochemistry values. Fluorescence immunohistochemistry offers greater dynamic signal range than chromogen immunohistochemistry, and combined with image analysis holds the promise of enhanced sensitivity and analytic resolution, and consequently more robust quantification. However, commercial fluorescence scanners and image analysis software differ in features and capabilities, and claims of objective quantitative immunohistochemistry are difficult to validate as pathologist scoring is subjective and there is no accepted gold standard. Here we provide the first side-by-side validation of two technologically distinct commercial fluorescence immunohistochemistry analysis platforms. We document highly consistent results by (1) concordance analysis of fluorescence immunohistochemistry values and (2) agreement in outcome predictions both for objective, data-driven cutpoint dichotomization with Kaplan-Meier analyses or employment of continuous marker values to compute receiver-operating curves. The two platforms examined rely on distinct fluorescence immunohistochemistry imaging hardware, microscopy vs line scanning, and functionally distinct image analysis software. Fluorescence immunohistochemistry values for nuclear-localized and tyrosine-phosphorylated Stat5a/b computed by each platform on a cohort of 323 breast cancer cases revealed high concordance after linear calibration, a finding confirmed on an independent 382 case cohort, with concordance correlation coefficients >0.98. Data-driven optimal cutpoints for outcome prediction by either platform were reciprocally applicable to the data derived by the alternate platform, identifying patients with low Nuc-pYStat5 at ~3.5-fold increased risk of disease progression. Our analyses identified two highly concordant fluorescence immunohistochemistry platforms that may serve as benchmarks for testing of other platforms, and low interoperator variability supports the implementation of objective tumor marker quantification in pathology laboratories.

The Janus kinase 1 is critical for pancreatic cancer initiation and progression.

Interleukin-6 (IL-6)-class inflammatory cytokines signal through the Janus tyrosine kinase (JAK)/signal transducer and activator of transcription (STAT) pathway and promote the development of pancreatic ductal adenocarcinoma (PDAC); however, the functions of specific intracellular signaling mediators in this process are less well defined. Using a ligand-controlled and pancreas-specific knockout in adult mice, we demonstrate in this study that JAK1 deficiency prevents the formation of KRASG12D-induced pancreatic tumors, and we establish that JAK1 is essential for the constitutive activation of STAT3, whose activation is a prominent characteristic of PDAC. We identify CCAAT/enhancer binding protein δ (C/EBPδ) as a biologically relevant downstream target of JAK1 signaling, which is upregulated in human PDAC. Reinstating the expression of C/EBPδ was sufficient to restore the growth of JAK1-deficient cancer cells as tumorspheres and in xenografted mice. Collectively, the findings of this study suggest that JAK1 executes important functions of inflammatory cytokines through C/EBPδ and may serve as a molecular target for PDAC prevention and treatment.

Prolactin-Stat5 signaling in breast cancer is potently disrupted by acidosis within the tumor microenvironment.

INTRODUCTION: Emerging evidence in estrogen receptor-positive breast cancer supports the notion that prolactin-Stat5 signaling promotes survival and maintenance of differentiated luminal cells, and loss of nuclear tyrosine phosphorylated Stat5 (Nuc-pYStat5) in clinical breast cancer is associated with increased risk of antiestrogen therapy failure. However, the molecular mechanisms underlying loss of Nuc-pYStat5 in breast cancer remain poorly defined. METHODS: We investigated whether moderate extracellular acidosis of pH 6.5 to 6.9 frequently observed in breast cancer inhibits prolactin-Stat5 signaling, using in vitro and in vivo experimental approaches combined with quantitative immunofluorescence protein analyses to interrogate archival breast cancer specimens. RESULTS: Moderate acidosis at pH 6.8 potently disrupted signaling by receptors for prolactin but not epidermal growth factor, oncostatin M, IGF1, FGF or growth hormone. In breast cancer specimens there was mutually exclusive expression of Nuc-pYStat5 and GLUT1, a glucose transporter upregulated in glycolysis-dependent carcinoma cells and an indirect marker of lactacidosis. Mutually exclusive expression of GLUT1 and Nuc-pYStat5 occurred globally or regionally within tumors, consistent with global or regional acidosis. All prolactin-induced signals and transcripts were suppressed by acidosis, and the acidosis effect was rapid and immediately reversible, supporting a mechanism of acidosis disruption of prolactin binding to receptor. T47D breast cancer xenotransplants in mice displayed variable acidosis (pH 6.5 to 6.9) and tumor regions with elevated GLUT1 displayed resistance to exogenous prolactin despite unaltered levels of prolactin receptors and Stat5. CONCLUSIONS: Moderate extracellular acidosis effectively blocks prolactin signaling in breast cancer. We propose that acidosis-induced prolactin resistance represents a previously unrecognized mechanism by which breast cancer cells may escape homeostatic control.

Global profiling of prolactin-modulated transcripts in breast cancer in vivo.

BACKGROUND: Prolactin (PRL) is essential for normal mammary gland development. PRL promotes mammary tumor formation in rodents and elevated serum prolactin is associated with increased risk of estrogen-receptor positive breast cancer in women. On the other hand, PRL may also exert pro-differentiation effects and act to suppress invasive features of established breast cancer. Previously published limited global transcript profiling analyses of prolactin-regulated gene expression in human breast cancer cells have exclusively been performed in vitro. The present study aimed to shed new light on how PRL modulates estrogen receptor (ER)-positive breast cancer through global transcript profiling of a human breast cancer xenograft model in vivo. METHODS: The prolactin-responsive human T47D breast cancer cell line was xenotransplanted into nude mice and global transcript profiling was carried out following treatment with or without human PRL for 48 h. A subset of PRL-modulated transcripts was further validated using qRT-PCR and immunohistochemistry. RESULTS: The in vivo analyses identified 130 PRL-modulated transcripts, 75 upregulated and 55 downregulated, based on fold change >1.6 and P-value <0.05. From this initial panel of transcripts, a subset of 18 transcripts with established breast cancer-relevance were selected and validated by qRT-PCR. Some but not all of the transcripts were also PRL-modulated in vitro. The selected PRL-modulated transcripts were tested for dependence on Stat5, Jak1 or Jak2 activation, and for co-regulation by 17ß-estradiol (E2). The protein encoded by one of the PRL-regulated transcripts, PTHrP, was examined in a panel of 92 human breast cancers and found by in situ quantitative immunofluorescence analysis to be highly positively correlated with nuclear localized and tyrosine phosphorylated Stat5. Gene Ontology analysis revealed that PRL-upregulated genes were enriched in pathways involved in differentiation. Finally, a gene signature based on PRL-upregulated genes was associated with prolonged relapse-free and metastasis-free survival in breast cancer patients. CONCLUSIONS: This global analysis identified and validated a panel of PRL-modulated transcripts in an ER-positive human breast cancer xenotransplant model, which may have value as markers of relapse-free and metastasis-free survival. Gene products identified in the present study may facilitate ongoing deciphering of the pleiotropic effects of PRL on human breast cancer.

Machine learning reveals genetic modifiers of the immune microenvironment of cancer.

Heritability in the immune tumor microenvironment (iTME) has been widely observed yet remains largely uncharacterized. Here, we developed a machine learning approach to map iTME modifiers within loci from genome-wide association studies (GWASs) for breast cancer (BrCa) incidence. A random forest model was trained on a positive set of immune-oncology (I-O) targets, and then used to assign I-O target probability scores to 1,362 candidate genes in linkage disequilibrium with 155 BrCa GWAS loci. Cluster analysis of the most probable candidates revealed two subfamilies of genes related to effector functions and adaptive immune responses, suggesting that iTME modifiers impact multiple aspects of anticancer immunity. Two of the top ranking BrCa candidates, LSP1 and TLR1, were orthogonally validated as iTME modifiers using BrCa patient biopsies and comparative mapping studies, respectively. Collectively, these data demonstrate a robust and flexible framework for functionally fine-mapping GWAS risk loci to identify translatable therapeutic targets.

Tumor-Suppressive and Immune-Stimulating Roles of Cholesterol 25-hydroxylase in Pancreatic Cancer Cells.

Cholesterol dependence is an essential characteristic of pancreatic ductal adenocarcinoma (PDAC). Cholesterol 25-hydroxylase (CH25H) catalyzes monooxygenation of cholesterol into 25-hydroxycholesterol, which is implicated in inhibiting cholesterol biosynthesis and in cholesterol depletion. Here, we show that, within PDAC cells, accumulation of cholesterol was facilitated by the loss of CH25H. Methylation of the CH25H gene and decreased levels of CH25H expression occurred in human pancreatic cancers and was associated with poor prognosis. Knockout of Ch25h in mice accelerated progression of Kras-driven pancreatic intraepithelial neoplasia. Conversely, restoration of CH25H expression in human and mouse PDAC cells decreased their viability under conditions of cholesterol deficit, and decelerated tumor growth in immune competent hosts. Mechanistically, the loss of CH25H promoted autophagy resulting in downregulation of MHC-I and decreased CD8+ T-cell tumor infiltration. Re-expression of CH25H in PDAC cells combined with immune checkpoint inhibitors notably inhibited tumor growth. We discuss additional benefits that PDAC cells might gain from inactivation of CH25H and the potential translational importance of these findings for therapeutic approaches to PDAC. IMPLICATIONS: Loss of CH25H by pancreatic cancer cells may stimulate tumor progression and interfere with immunotherapies.

High PD-L2 Predicts Early Recurrence of ER-Positive Breast Cancer.

PURPOSE: T-cell-mediated cytotoxicity is suppressed when programmed cell death-1 (PD-1) is bound by PD-1 ligand-1 (PD-L1) or PD-L2. Although PD-1 inhibitors have been approved for triple-negative breast cancer, the lower response rates of 25%-30% in estrogen receptor-positive (ER+) breast cancer will require markers to identify likely responders. The focus of this study was to evaluate whether PD-L2, which has higher affinity than PD-L1 for PD-1, is a predictor of early recurrence in ER+ breast cancer. METHODS: PD-L2 protein levels in cancer cells and stromal cells of therapy-naive, localized or locoregional ER+ breast cancers were measured retrospectively by quantitative immunofluorescence histocytometry and correlated with progression-free survival (PFS) in the main study cohort (n = 684) and in an independent validation cohort (n = 273). All patients subsequently received standard-of-care adjuvant therapy without immune checkpoint inhibitors. RESULTS: Univariate analysis of the main cohort revealed that high PD-L2 expression in cancer cells was associated with shorter PFS (hazard ratio [HR], 1.8; 95% CI, 1.3 to 2.6; P = .001), which was validated in an independent cohort (HR, 2.3; 95% CI, 1.1 to 4.8; P = .026) and remained independently predictive after multivariable adjustment for common clinicopathological variables (HR, 2.0; 95% CI, 1.4 to 2.9; P < .001). Subanalysis of the ER+ breast cancer patients treated with adjuvant chemotherapy (n = 197) revealed that high PD-L2 levels in cancer cells associated with short PFS in univariate (HR, 2.5; 95% CI, 1.4 to 4.4; P = .003) and multivariable analyses (HR, 3.4; 95% CI, 1.9 to 6.2; P < .001). CONCLUSION: Up to one third of treatment-naive ER+ breast tumors expressed high PD-L2 levels, which independently predicted poor clinical outcome, with evidence of further elevated risk of progression in patients who received adjuvant chemotherapy. Collectively, these data warrant studies to gain a deeper understanding of PD-L2 in the progression of ER+ breast cancer and may provide rationale for immune checkpoint blockade for this patient group.

Low levels of Stat5a protein in breast cancer are associated with tumor progression and unfavorable clinical outcomes.

INTRODUCTION: Signal transducer and activator of transcripton-5a (Stat5a) and its close homologue, Stat5b, mediate key physiological effects of prolactin and growth hormone in mammary glands. In breast cancer, loss of nuclear localized and tyrosine phosphorylated Stat5a/b is associated with poor prognosis and increased risk of antiestrogen therapy failure. Here we quantify for the first time levels of Stat5a and Stat5b over breast cancer progression, and explore their potential association with clinical outcome. METHODS: Stat5a and Stat5b protein levels were quantified in situ in breast-cancer progression material. Stat5a and Stat5b transcript levels in breast cancer were correlated with clinical outcome in 936 patients. Stat5a protein was further quantified in four archival cohorts totaling 686 patients with clinical outcome data by using multivariate models. RESULTS: Protein levels of Stat5a but not Stat5b were reduced in primary breast cancer and lymph node metastases compared with normal epithelia. Low tumor levels of Stat5a but not Stat5b mRNA were associated with poor prognosis. Experimentally, only limited overlap between Stat5a- and Stat5b-modulated genes was found. In two cohorts of therapy-naïve, node-negative breast cancer patients, low nuclear Stat5a protein levels were an independent marker of poor prognosis. Multivariate analysis of two cohorts treated with antiestrogen monotherapy revealed that low nuclear Stat5a levels were associated with a more than fourfold risk of unfavorable outcome. CONCLUSIONS: Loss of Stat5a represents a new independent marker of poor prognosis in node-negative breast cancer and may be a predictor of response to antiestrogen therapy if validated in randomized clinical trials.

Spatial Metrics of Interaction between CD163-Positive Macrophages and Cancer Cells and Progression-Free Survival in Chemo-Treated Breast Cancer.

Tumor-associated macrophages (TAMs) promote progression of breast cancer and other solid malignancies via immunosuppressive, pro-angiogenic and pro-metastatic effects. Tumor-promoting TAMs tend to express M2-like macrophage markers, including CD163. Histopathological assessments suggest that the density of CD163-positive TAMs within the tumor microenvironment is associated with reduced efficacy of chemotherapy and unfavorable prognosis. However, previous analyses have required research-oriented pathologists to visually enumerate CD163+ TAMs, which is both laborious and subjective and hampers clinical implementation. Objective, operator-independent image analysis methods to quantify TAM-associated information are needed. In addition, since M2-like TAMs exert local effects on cancer cells through direct juxtacrine cell-to-cell interactions, paracrine signaling, and metabolic factors, we hypothesized that spatial metrics of adjacency of M2-like TAMs to breast cancer cells will have further information value. Immunofluorescence histo-cytometry of CD163+ TAMs was performed retrospectively on tumor microarrays of 443 cases of invasive breast cancer from patients who subsequently received adjuvant chemotherapy. An objective and automated algorithm was developed to phenotype CD163+ TAMs and calculate their density within the tumor stroma and derive several spatial metrics of interaction with cancer cells. Shorter progression-free survival was associated with a high density of CD163+ TAMs, shorter median cancer-to-CD163+ nearest neighbor distance, and a high number of either directly adjacent CD163+ TAMs (within juxtacrine proximity <12 µm to cancer cells) or communicating CD163+ TAMs (within paracrine communication distance <250 µm to cancer cells) after multivariable adjustment for clinical and pathological risk factors and correction for optimistic bias due to dichotomization.

Differential expression of arrestins is a predictor of breast cancer progression and survival.

Emerging evidence has implicated G protein-coupled receptors, such as CXCR4 and PAR2, in breast cancer progression and the development of metastatic breast cancer. However, the role of proteins that regulate the function of these receptors, such as arrestins, in breast cancer has yet to be determined. Examination of the expression of the two nonvisual arrestins, arrestin2 and 3, in various breast cancer cell lines revealed comparable expression of arrestin3 in basal and luminal lines while arrestin2 expression was much higher in the luminal lines compared to the more aggressive basal lines. Analysis of normal human breast tissue revealed that arrestin2 and 3 were expressed in both luminal and myoepithelial cells of mammary epithelia with arrestin2 highest in myoepithelial cells and arrestin3 comparable in both cell types. Quantitative immunofluorescence-based examination of primary breast tumors revealed that arrestin2 expression significantly decreased with cancer progression from ductal carcinoma in situ to invasive carcinoma and further to lymph node metastasis (P < 0.001). Moreover, decreased arrestin2 expression was associated with decreased survival (P = 0.0007) as well as positive lymph node status and increased tumor size and nuclear grade. In contrast, arrestin3 expression significantly increased during breast cancer progression (P < 0.001) and increased expression was associated with decreased survival (P = 0.014). Arrestin3 was also an independent prognostic marker of breast cancer with a hazard ratio of 1.65. Overall, these studies demonstrate that arrestin2 levels decrease while arrestin3 levels increase during breast cancer progression and these changes correlate with a poor clinical outcome.

PTP1B suppresses prolactin activation of Stat5 in breast cancer cells.

Basal levels of nuclear localized, tyrosine phosphorylated Stat5 are present in healthy human breast epithelia. In contrast, Stat5 phosphorylation is frequently lost during breast cancer progression, a finding that correlates with loss of histological differentiation and poor patient prognosis. Identifying the mechanisms underlying loss of Stat5 phosphorylation could provide novel targets for breast cancer therapy. Pervanadate, a general tyrosine phosphatase inhibitor, revealed marked phosphatase regulation of Stat5 activity in breast cancer cells. Lentiviral-mediated shRNA allowed specific examination of the regulatory role of five tyrosine phosphatases (PTP1B, TC-PTP, SHP1, SHP2, and VHR), previously implicated in Stat5 regulation in various systems. Enhanced and sustained prolactin-induced Stat5 tyrosine phosphorylation was observed in T47D and MCF7 breast cancer cells selectively in response to PTP1B depletion. Conversely, PTP1B overexpression suppressed prolactin-induced Stat5 tyrosine phosphorylation. Furthermore, PTP1B knockdown increased Stat5 reporter gene activity. Mechanistically, PTP1B suppression of Stat5 phosphorylation was mediated, at least in part, through inhibitory dephosphorylation of the Stat5 tyrosine kinase, Jak2. PTP1B knockdown enhanced sensitivity of T47D cells to prolactin phosphorylation of Stat5 by reducing the EC(50) from 7.2 nmol/L to 2.5 nmol/L. Immunohistochemical analyses of two independent clinical breast cancer materials revealed significant negative correlations between levels of active Stat5 and PTP1B, but not TC-PTP. Collectively, our data implicate PTP1B as an important negative regulator of Stat5 phosphorylation in invasive breast cancer.

Regulation of intercellular biomolecule transfer-driven tumor angiogenesis and responses to anticancer therapies.

Intercellular biomolecule transfer (ICBT) between malignant and benign cells is a major driver of tumor growth, resistance to anticancer therapies, and therapy-triggered metastatic disease. Here we characterized cholesterol 25-hydroxylase (CH25H) as a key genetic suppressor of ICBT between malignant and endothelial cells (ECs) and of ICBT-driven angiopoietin-2-dependent activation of ECs, stimulation of intratumoral angiogenesis, and tumor growth. Human CH25H was downregulated in the ECs from patients with colorectal cancer and the low levels of stromal CH25H were associated with a poor disease outcome. Knockout of endothelial CH25H stimulated angiogenesis and tumor growth in mice. Pharmacologic inhibition of ICBT by reserpine compensated for CH25H loss, elicited angiostatic effects (alone or combined with sunitinib), augmented the therapeutic effect of radio-/chemotherapy, and prevented metastatic disease induced by these regimens. We propose inhibiting ICBT to improve the overall efficacy of anticancer therapies and limit their prometastatic side effects.

NSG-Pro mouse model for uncovering resistance mechanisms and unique vulnerabilities in human luminal breast cancers.

Most breast cancer deaths are caused by estrogen receptor-α­positive (ER+) disease. Preclinical progress is hampered by a shortage of therapy-naïve ER+ tumor models that recapitulate metastatic progression and clinically relevant therapy resistance. Human prolactin (hPRL) is a risk factor for primary and metastatic ER+ breast cancer. Because mouse prolactin fails to activate hPRL receptors, we developed a prolactin-humanized Nod-SCID-IL2Rγ (NSG) mouse (NSG-Pro) with physiological hPRL levels. Here, we show that NSG-Pro mice facilitate establishment of therapy-naïve, estrogen-dependent PDX tumors that progress to lethal metastatic disease. Preclinical trials provide first-in-mouse efficacy of pharmacological hPRL suppression on residual ER+ human breast cancer metastases and document divergent biology and drug responsiveness of tumors grown in NSG-Pro versus NSG mice. Oncogenomic analyses of PDX lines in NSG-Pro mice revealed clinically relevant therapy-resistance mechanisms and unexpected, potently actionable vulnerabilities such as DNA-repair aberrations. The NSG-Pro mouse unlocks previously inaccessible precision medicine approaches for ER+ breast cancers.

Malignant cell-specific pro-tumorigenic role of type I interferon receptor in breast cancers.

Within the microenvironment of solid tumors, stress associated with deficit of nutrients and oxygen as well as tumor-derived factors triggers the phosphorylation-dependent degradation of the IFNAR1 chain of type I interferon (IFN1) receptor and ensuing suppression of the IFN1 pathway. Here we sought to examine the importance of these events in malignant mammary cells. Expression of non-degradable IFNAR1S526A mutant in mouse mammary adenocarcinoma cells stimulated the IFN1 pathway yet did not affect growth of these cells in vitro or ability to form subcutaneous tumors in the syngeneic mice. Remarkably, these cells exhibited a notably accelerated growth when transplanted orthotopically into mammary glands. Importantly, in human patients with either ER+ or ER- breast cancers, high levels of IFNAR1 were associated with poor prognosis. We discuss the putative mechanisms underlying the pro-tumorigenic role of IFNAR1 in malignant breast cells.

Cancer-associated fibroblasts downregulate type I interferon receptor to stimulate intratumoral stromagenesis.

Activation of cancer-associated fibroblasts (CAFs) and ensuing desmoplasia play an important role in the growth and progression of solid tumors. Here we demonstrate that, within colon and pancreatic ductal adenocarcinoma tumors, efficient stromagenesis relies on downregulation of the IFNAR1 chain of the type I interferon (IFN1) receptor. Expression of the fibroblast activation protein (FAP) and accumulation of the extracellular matrix (ECM) was notably impaired in tumors grown in the Ifnar1S526A (SA) knock-in mice, which are deficient in IFNAR1 downregulation. Primary fibroblasts from these mice exhibited elevated levels of Smad7, a negative regulator of the transforming growth factor-ß (TGFß) pathway. Knockdown of Smad7 alleviated deficient ECM production in SA fibroblasts in response to TGFß. Analysis of human colorectal cancers revealed an inverse correlation between IFNAR1 and FAP levels. Whereas growth of tumors in SA mice was stimulated by co-injection of wild type but not SA fibroblasts, genetic ablation of IFNAR1 in fibroblasts also accelerated tumor growth. We discuss how inactivation of IFNAR1 in CAFs acts to stimulate stromagenesis and tumor growth.