Information from Noise: Measuring Dyslexia Risk Using Rasch-like Matrix Factorization with a Procedure for Equating Instruments.

This study examines the psychometric properties of a screening protocol for dyslexia and demonstrates a special form of matrix factorization called Nous based on the Alternating Least Squares algorithm. Dyslexia presents an intrinsically multidimensional complex of cognitive loads. By building and enforcing a common 6-dimensional space, Nous extracts a multidimensional signal for each person and item from test data that increases the Shannon entropy of the dataset while at the same time being constrained to meet the special objectivity requirements of the Rasch model. The resulting Dyslexia Risk Scale (DRS) yields linear equal-interval measures that are comparable regardless of the subset of items taken by the examinee. Each measure and cell estimate is accompanied by an efficiently calculated standard error. By incorporating examinee age into the calibration process, the DRS can be generalized to all age groups to allow the tracking of individual dyslexia risk over time. The methodology was implemented using a 2019 calibration sample of 828 persons aged 7 to 82 with varying degrees of dyslexia risk. The analysis yielded high reliability (0.95) and excellent receiver operating characteristics (AUC = 0.96). The analysis is accompanied by a discussion of the information-theoretic properties of matrix factorization.

An Immune-Related Gene Expression Signature Predicts Benefit from Adding Atezolizumab to FOLFOXIRI plus Bevacizumab in Metastatic Colorectal Cancer.

PURPOSE: AtezoTRIBE phase II randomized study demonstrated that adding atezolizumab to first-line FOLFOXIRI (5-fluorouracil, oxaliplatin, irinotecan) plus bevacizumab prolongs progression-free survival (PFS) of patients with metastatic colorectal cancer (mCRC), with a modest benefit among proficient mismatch repair (pMMR). DetermaIO is an immune-related 27-gene expression signature able to predict benefit from immune checkpoint inhibition in triple-negative breast cancer. In this analysis of AtezoTRIBE, we investigated the predictive impact of DetermaIO in mCRC. EXPERIMENTAL DESIGN: Patients with mCRC unselected for MMR status were randomly assigned (1:2) to FOLFOXIRI plus bevacizumab (control arm) or the same regimen with atezolizumab (atezolizumab arm). qRT-PCR by DetermaIO was performed on RNA purified from pretreatment tumors of 132 (61%) of 218 enrolled patients. A binary result (IOpos vs. IOneg) adopting the preestablished DetermaIO cut-off point (0.09) was obtained, and an exploratory optimized cut-off point (IOOPT) was computed in the overall population and in pMMR subgroup (IOOPTpos vs. IOOPTneg). RESULTS: DetermaIO was successfully determined in 122 (92%) cases, and 23 (27%) tumors were IOpos. IOpos tumors achieved higher PFS benefit from atezolizumab arm than IOneg (HR: 0.39 vs. 0.83; Pinteraction = 0.066). In pMMR tumors (N = 110), a similar trend was observed (HR: 0.47 vs. 0.93; Pinteraction = 0.139). In the overall population, with the computed IOOPT cut-off point (0.277), 16 (13%) tumors were IOOPTpos and they derived higher PFS benefit from atezolizumab than IOOPTneg (HR: 0.10 vs. 0.85, Pinteraction = 0.004). Similar results were found in the pMMR subgroup. CONCLUSIONS: DetermaIO may be useful to predict benefit of adding atezolizumab to first-line FOLFOXIRI plus bevacizumab in mCRC. The exploratory IOOPT cut-off point should be validated in independent mCRC cohorts.

The 27-gene IO score is associated with efficacy of PD-1/L1 inhibitors independent of FGFR expression in a real-world metastatic urothelial carcinoma cohort.

Multiple targeted therapeutics have been approved by the FDA for mUC, including immune checkpoint inhibitors (ICIs) and more recently targeted agents for both FGFR and Nectin-4. FGFR3-aberrant and Nectin-4 expressing cells have been associated with an immunosuppressed phenotype. Given that less than half of all patients respond to these agents as monotherapies and less than 20% are eligible to receive salvage therapy, effective personalized treatment plans are critical. Typical biomarkers for ICIs such as PD-L1 and TMB have not been definitive in mUC, yet a biomarker-driven optimization of first-line therapy and subsequent sequencing have the potential to achieve higher and more durable response rates. The IO score is a 27-gene tumor immune microenvironment (TIME) classifier that has been associated with the clinical benefits of ICIs in multiple cancer types, including mUC. This study demonstrates that the IO score was associated with both progression-free survival (PFS) and overall survival (OS) in a real-world cohort of mUC patients treated with ICIs. Furthermore, the IO score was independent of and provided information incremental to TMB. Interestingly, the IO score predicted benefit in patients with high FGFR expression, despite conflicting data regarding response rates among the FGFR aberrant population. Taken together, these results demonstrate that the IO score assessment of the TIME is associated with a clinical benefit from ICI therapy and that this novel biomarker may inform therapeutic sequencing decisions in mUC, potentially improving outcomes for this notoriously difficult-to-treat disease.

27-gene Immuno-Oncology (IO) Score is Associated With Efficacy of Checkpoint Immunotherapy in Advanced NSCLC: A Retrospective BC Cancer Study.

BACKGROUND: Immune checkpoint inhibitors (ICI) are standard of care in advanced non-small cell lung cancer (NSCLC). However, not all patients benefit, even among PD-L1 tumor proportional score (TPS) ≥50%, indicating an unmet need for additional biomarkers such as those assessing the tumor immune microenvironment (TIME). DetermaIO is a 27-gene assay that classifies TIME and has previously demonstrated association with ICI response. METHODS: FFPE samples were selected from BC Cancer and West Clinic Cancer Center patients with performance status (PS) ≤2 who received at least 2 cycles of ICI monotherapy in the first (1L) or second line (2L). IO scores were generated and analyzed for association with PFS and OS. RESULTS: In the entire cohort (N=147), IO score was significantly associated with OS (HR=0.68, 95%CI 0.47-0.99, P = .042) and PFS (HR=0.62, 95%CI 0.43-0.88, P = .0069). In 1L treated patients (PD-L1≥50%, N=78), IO score was significantly associated with PFS (HR=0.55, 95%CI 0.32-0.94, P = .028). In exploratory analyses, IO score was associated with benefit in 1L PS2 patients for OS (HR = 0.26, 95%CI 0.091-0.74, P = .012) and PFS (HR = 0.27, 95%CI 0.098-0.72, P = .0095) which was confirmed in PFS subgroup analysis in the independent West Cancer Center study (N=13 HR=0.14, 95%CI 0.027-0.76, P = .023). CONCLUSION: These data confirm the association of DetermaIO with ICI clinical benefit in NSCLC, and expand on previous studies by demonstrating that first line treated PD-L1≥50% patients can further be stratified by IO score to identify efficacy. Exploratory analysis suggested that the IO score identifies benefit in patients with poor PS.

Translation of the 27-gene immuno-oncology test (IO score) to predict outcomes in immune checkpoint inhibitor treated metastatic urothelial cancer patients.

BACKGROUND: The IO Score is a 27-gene immuno-oncology (IO) classifier that has previously predicted benefit to immune checkpoint inhibitor (ICI) therapy in triple negative breast cancer (TNBC) and non-small cell lung cancer (NSCLC). It generates both a continuous score and a binary result using a defined threshold that is conserved between breast and lung. Herein, we aimed to evaluate the IO Score's binary threshold in ICI-naïve TCGA bladder cancer patients (TCGA-BLCA) and assess its clinical utility in metastatic urothelial cancer (mUC) using the IMvigor210 clinical trial treated with the ICI, atezolizumab. METHODS: We identified a list of tumor immune microenvironment (TIME) related genes expressed across the TCGA breast, lung squamous and lung adenocarcinoma cohorts (TCGA-BRCA, TCGA-LUSQ, and TCGA-LUAD, 939 genes total) and then examined the expression of these 939 genes in TCGA-BLCA, to identify patients as having high inflammatory gene expression. Using this as a test of classification, we assessed the previously established threshold of IO Score. We then evaluated the IO Score with this threshold in the IMvigor210 cohort for its association with overall survival (OS). RESULTS: In TCGA-BLCA, IO Score positive patients had a strong concordance with high inflammatory gene expression (p < 0.0001). Given this concordance, we applied the IO Score to the ICI treated IMvigor210 patients. IO Score positive patients (40%) had a significant Cox proportional hazard ratio (HR) of 0.59 (95% CI 0.45-0.78 p < 0.001) for OS and improved median OS (15.6 versus 7.5 months) compared to IO Score negative patients. The IO Score remained significant in bivariate models combined with all other clinical factors and biomarkers, including PD-L1 protein expression and tumor mutational burden. CONCLUSION: The IMvigor210 results demonstrate the potential for the IO Score as a clinically useful biomarker in mUC. As this is the third tumor type assessed using the same algorithm and threshold, the IO Score may be a promising candidate as a tissue agnostic marker of ICI clinical benefit. The concordance between IO Score and inflammatory gene expression suggests that the classifier is capturing common features of the TIME across cancer types.

Association of a novel 27-gene immuno-oncology assay with efficacy of immune checkpoint inhibitors in advanced non-small cell lung cancer.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapies represent a major advance in treating a variety of advanced-stage malignancies. Nevertheless, only a subset of patients benefit, even when selected based on approved biomarkers such as PD-L1 and tumor mutational burden. New biomarkers are needed to maximize the therapeutic ratio of these therapies. METHODS: In this retrospective cohort, we assessed a 27-gene RT-qPCR immuno-oncology (IO) gene expression assay of the tumor immune microenvironment and determined its association with the efficacy of ICI therapy in 67 advanced-stage NSCLC patients. The 27-gene IO test score (IO score), programmed cell death ligand 1 immunohistochemistry tumor proportion score (PD-L1 TPS), and tumor mutational burden (TMB) were analyzed as continuous variables for response and as binary variables for one-year progression free survival. The threshold for the IO score was prospectively set based upon a previously described training cohort. Prognostic implications of the IO score were evaluated in a separate cohort of 104 advanced-stage NSCLC patients from The Cancer Genome Atlas (TCGA) who received non-ICI therapy. RESULTS: The IO score was significantly different between responders or non-responders (p = 0.007) and associated with progression-free survival (p = 0.001). Bivariate analysis established that the IO score was independent of PD-L1 TPS and TMB in identifying patients benefiting from ICI therapy. In a separate cohort of late-stage NSCLC patients from TCGA, the IO score was not prognostic of outcome from non-ICI-treated patients. CONCLUSIONS: This study is the first application of this 27-gene IO RT-qPCR assay in a clinical cohort with outcome data. IO scores were significantly associated with response to ICI therapy and prolonged progression-free survival. Together, these data suggest the IO score should be further studied to define its role in informing clinical decision-making for ICI treatment in NSCLC.

Changes in Triple-Negative Breast Cancer Molecular Subtypes in Patients Without Pathologic Complete Response After Neoadjuvant Systemic Chemotherapy.

PURPOSE: Lehmann et al have identified four molecular subtypes of triple-negative breast cancer (TNBC)-basal-like (BL) 1, BL2, mesenchymal (M), and luminal androgen receptor-and an immunomodulatory (IM) gene expression signature modifier. Our group previously showed that the response of TNBC to neoadjuvant systemic chemotherapy (NST) differs by molecular subtype, but whether NST affects the subtype was unknown. Here, we tested the hypothesis that in patients without pathologic complete response, TNBC subtypes can change after NST. Moreover, in cases with the changed subtype, we determined whether epithelial-to-mesenchymal transition (EMT) had occurred. MATERIALS AND METHODS: From the Pan-Pacific TNBC Consortium data set containing TNBC patient samples from four countries, we examined 64 formalin-fixed, paraffin-embedded pairs of matched pre- and post-NST tumor samples. The TNBC subtype was determined using the TNBCtype-IM assay. We analyzed a partial EMT gene expression scoring metric using mRNA data. RESULTS: Of the 64 matched pairs, 36 (56%) showed a change in the TNBC subtype after NST. The most frequent change was from BL1 to M subtypes (38%). No tumors changed from M to BL1. The IM signature was positive in 14 (22%) patients before NST and eight (12.5%) patients after NST. The EMT score increased after NST in 28 (78%) of the 36 patients with the changed subtype (v 39% of the 28 patients without change; P = .002254). CONCLUSION: We report, to our knowledge, for the first time that the TNBC molecular subtype and IM signature frequently change after NST. Our results also suggest that EMT is promoted by NST. Our findings may lead to innovative adjuvant therapy strategies in TNBC cases with residual tumor after NST.

A Novel Immunomodulatory 27-Gene Signature to Predict Response to Neoadjuvant Immunochemotherapy for Primary Triple-Negative Breast Cancer.

A precise predictive biomarker for TNBC response to immunochemotherapy is urgently needed. We previously established a 27-gene IO signature for TNBC derived from a previously established 101-gene model for classifying TNBC. Here we report a pilot study to assess the performance of a 27-gene IO signature in predicting the pCR of TNBC to preoperative immunochemotherapy. We obtained RNA sequencing data from the primary tumors of 55 patients with TNBC, who received neoadjuvant immunochemotherapy with the PD-L1 blocker durvalumab. We determined the power and accuracy in predicting pCR for the immunomodulatory (IM) subtype identified by the 101-gene model, the 27-gene IO signature, and PD-L1 expression by immunohistochemistry (IHC). The pCR rate was 45% (25/55). The odds ratios for pCR were as follows: IM subtype by 101-gene model, 3.14 (p = 0.054); 27-gene IO signature, 4.13 (p = 0.012); PD-L1 expression by IHC, 2.63 (p = 0.106); 27-gene IO signature in combination with PD-L1 expression by IHC, 6.53 (p = 0.003). The 27-gene IO signature has the potential to predict the pCR of primary TNBC to neoadjuvant immunochemotherapy. Further analysis in a large cohort is needed.

Characterization of the tumor immune-microenvironment of adenocarcinoma of lung with a metastatic lesion in the pancreas treated successfully with first-line, single-agent pembrolizumab.

Single-agent immune checkpoint inhibitor therapy in advanced non-small cell lung cancer can significantly prolong progression-free and overall survival when compared with cytotoxic chemotherapy. Here, we report a case of newly diagnosed adenocarcinoma of the lung with a solitary brain metastasis and a biopsy confirmed adenocarcinoma in the tail of the pancreas. Cytomorphology and immunohistochemistry suggested the lung and pancreas tumors were distinct primaries. However, molecular analysis of the lung primary and tumor in the pancreas revealed the same mutations of functional significance in PIK3CA, NF1 and TP53, suggesting the tumors were clonal. A total of three cycles of single-agent pembrolizumab, and radiation to the lung and brain administered between cycles 1 and 2, resulted in marked responses in lung, brain and pancreatic tumors. Despite the discontinuation of the pembrolizumab after three cycles due to severe immune-mediated toxicities, the patient has had no progression 11 months after stopping all active treatment. Results of a novel 27-gene immuno-oncology (IO) expression assay revealed strong IO scores for the lung and pancreatic tumors, indicating a favorable tumor immune-microenvironment and possibly explaining the significant response.

A novel immuno-oncology algorithm measuring tumor microenvironment to predict response to immunotherapies.

Immune checkpoint inhibitor (ICI) therapies can improve clinical outcomes for patients with solid tumors, but relatively few patients respond. Because ICI therapies support an adaptive immune response, patients with an active tumor microenvironment (TME) may be more likely to respond, and thus biomarkers capable of discerning an active from a quiescent TME may be useful in patient selection. We developed an algorithm optimized for genes expressed in the mesenchymal and immunomodulatory subtypes of a 101-gene triple negative breast cancer model (Ring, BMC Cancer, 2016, 16:143) as a means to capture the immunological state of the TME. We compared the outcome of the algorithm (IO score) with the 101-gene model and found 88% concordance, indicating the models are correlated but not identical, and may be measuring different TME features. We found 92.5% correlation between IO scores of matched tumor epithelial and adjacent stromal tissues, indicating the IO score is not specific to these tissues, but reflects the TME as a whole. We observed a significant difference in IO score (p = 0.0092) between samples with high tumor-infiltrating lymphocytes and samples with increased neutrophil load, demonstrating agreement between IO score and these two prognostic markers. Finally, among non-small cell lung cancer patients receiving immunotherapy, we observed a significant difference in IO score (p = 0.0035) between responders and non-responders, and a significant odds ratio (OR = 5.76, 95% CI 1.30-25.51, p = 0.021), indicating the IO score can predict patient response. The immuno-oncology algorithm may offer independent and incremental predictive value over current biomarkers in the clinic.

Identification of triple-negative breast cancer cell lines classified under the same molecular subtype using different molecular characterization techniques: Implications for translational research.

The original algorithm that classified triple-negative breast cancer (TNBC) into six subtypes has recently been revised. The revised algorithm (TNBCtype-IM) classifies TNBC into five subtypes and a modifier based on immunological (IM) signatures. The molecular signature may differ between cancer cells in vitro and their respective tumor xenografts. We identified cell lines with concordant molecular subtypes regardless of classification algorithm or analysis of cells in vitro or in vivo, to establish a panel of clinically relevant molecularly stable TNBC models for translational research. Gene expression data were used to classify TNBC cell lines using the original and the revised algorithms. Tumor xenografts were established from 17 cell lines and subjected to gene expression profiling with the original 2188-gene algorithm TNBCtype and the revised 101-gene algorithm TNBCtype-IM. A total of six cell lines (SUM149PT (BL2), HCC1806 (BL2), SUM149PT (BL2), BT549 (M), MDA-MB-453 (LAR), and HCC2157 (BL1)) maintained their subtype classification between in vitro and tumor xenograft analyses across both algorithms. For TNBC molecular classification-guided translational research, we recommend using these TNBC cell lines with stable molecular subtypes.

Performance of a RT-PCR Assay in Comparison to FISH and Immunohistochemistry for the Detection of ALK in Non-Small Cell Lung Cancer.

Patients with lung cancers harboring an activating anaplastic lymphoma kinase (ALK) rearrangement respond favorably to ALK inhibitor therapy. Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) are validated and widely used screening tests for ALK rearrangements but both methods have limitations. The ALK RGQ RT-PCR Kit (RT-PCR) is a single tube quantitative real-time PCR assay for high throughput and automated interpretation of ALK expression. In this study, we performed a direct comparison of formalin-fixed paraffin-embedded (FFPE) lung cancer specimens using all three ALK detection methods. The RT-PCR test (diagnostic cut-off ΔCt of ≤8) was shown to be highly sensitive (100%) when compared to FISH and IHC. Sequencing of RNA detected full-length ALK transcripts or EML4-ALK and KIF5B-ALK fusion variants in discordant cases in which ALK expression was detected by the ALK RT-PCR test but negative by FISH and IHC. The overall specificity of the RT-PCR test for the detection of ALK in cases without full-length ALK expression was 94% in comparison to FISH and sequencing. These data support the ALK RT-PCR test as a highly efficient and reliable diagnostic screening approach to identify patients with non-small cell lung cancer whose tumors are driven by oncogenic ALK.

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.

A spatial assessment of baseline nutrient and water quality values in the Ashepoo-Combahee-Edisto (ACE) Basin, South Carolina, USA.

The Ashepoo-Combahee-Edisto (ACE) Basin (South Carolina, USA) National Estuarine Research Reserve System (NERRS) encompasses some of the least developed USA coastline. Yet, periodic sampling showed that certain regions have higher nutrient, fecal coliform, and chlorophyll a levels, often with lower dissolved oxygen, than other South Carolina estuaries. To evaluate the spatial extent of these issues, a summer (2008) baseline study was conducted. Physical water quality, total nitrogen and phosphorus, chlorophyll a, dissolved organic carbon, and suspended solids were measured from surface waters of 67 stations (30 tidal creek, 37 open water). Nutrient and chlorophyll a levels were significantly (p<0.01) and negatively correlated with the extent of open water (% land cover), and chlorophyll a and nitrogen levels were, at times, elevated relative to concentrations typical of other estuaries in the state, reinforcing previous findings. This survey also identified several creeks not previously monitored that exhibited elevated nutrients.

Porcine sialoadhesin: a newly identified xenogeneic innate immune receptor.

Extracorporeal porcine liver perfusion is being developed as a bridge to liver allotransplantation for patients with fulminant hepatic failure. This strategy is limited by porcine Kupffer cell destruction of human erythrocytes, mediated by lectin binding of a sialic acid motif in the absence of antibody and complement. Sialoadhesin, a macrophage restricted lectin that binds sialic acid, was originally described as a sheep erythrocyte binding receptor. Given similarities between sialoadhesin and the unidentified macrophage lectin in our model, we hypothesized porcine sialoadhesin contributed to recognition of human erythrocytes. Two additional types of macrophages were identified to bind human erythrocytes-spleen and alveolar. Expression of sialoadhesin was confirmed by immunofluorescence in porcine tissues and by flow cytometry on primary macrophages. A stable transgenic cell line expressing porcine sialoadhesin (pSn CHO) bound human erythrocytes, while a sialoadhesin mutant cell line did not. Porcine macrophage and pSn CHO recognition of human erythrocytes was inhibited approximately 90% by an antiporcine sialoadhesin monoclonal antibody and by human erythrocyte glycoproteins. Furthermore, this binding was substantially reduced by sialidase treatment of erythrocytes. These data support the hypothesis that porcine sialoadhesin is a xenogeneic receptor that mediates porcine macrophage binding of human erythrocytes in a sialic acid-dependent manner.

Transgenic expression of Spi-C impairs B-cell development and function by affecting genes associated with BCR signaling.

Spi-C is an Ets family transcription factor closely related to PU.1 and Spi-B. Expression of Spi-C is developmentally regulated in the B-cell lineage, but its function remains unknown. To determine the function of Spi-C in B-cell development, we generated mice expressing a B-cell-specific Spi-C transgene under the control of the IgH intronic enhancer. Spi-C transgenic mice had 50% fewer B cells than wild-type littermates. Flow cytometric analyses showed that splenic transitional B cells and bone marrow pre-B or immature B cells from transgenic mice were dramatically reduced compared with those of wild type. Both nonspecific and Ag-specific serum IgM levels were significantly increased in transgenic mice, while serum IgG levels were significantly decreased compared with wild type. Spi-C transgenic B cells proliferated poorly after stimulation by anti-IgM or anti-CD40 in vitro, although they responded normally to LPS stimulation. Using real-time RT-PCR, we found that several BCR signaling-related mediators were downregulated at pre-B-cell and mature B-cell stages in transgenic mice, while an inhibitor of BCR signaling was upregulated. Taken together, these data indicate that ectopic expression of Spi-C can impair B-cell development and function by affecting genes associated with BCR signaling.

Reduction in PU.1 activity results in a block to B-cell development, abnormal myeloid proliferation, and neonatal lethality.

OBJECTIVE: It has been demonstrated that high concentration of the transcription factor PU.1 (encoded by Sfpi1) promotes macrophage development, whereas low concentration induces B-cell development in vitro. This has led to the hypothesis that lower levels of PU.1 activity are required for B cell than for macrophage development in vivo. We utilized an allele of Sfpi1 (termed BN) with a mutation in the first coding exon, which resulted in a reduction of PU.1 expression in order to test this hypothesis. MATERIALS AND METHODS: Using gene targeting in embryonic stem cells, two ATG-start site codons of PU.1 were mutated, resulting in reduced PU.1 expression originating from a third start codon. Mice were assayed for phenotypic abnormalities using fluorescence-activated cell sorting, microscopy, and colony-forming ability. In addition, isolated cells were tested for their differentiation potential in vitro and in vivo. RESULTS: Lymphoid and myeloid cells derived from cultured Sfpi1(BN/BN) fetal liver cells had reduced levels of PU.1 expression and activity. B-cell development was intrinsically blocked in cells isolated from Sfpi1(BN/BN) mice. In addition, myeloid development was impaired in Sfpi1(BN/BN) fetal liver. However, neonatal Sfpi1(BN/BN) mice had a dramatic expansion and infiltration of immature myeloid cells. CONCLUSION: Contrary to our original hypothesis, high levels of PU.1 activity are required to induce both myeloid and B-cell development. In addition, neonatal mice homozygous for the hypomorphic allele acquire a myeloproliferative disorder and die within 1 month of age.

Regulation of the interleukin-7 receptor alpha promoter by the Ets transcription factors PU.1 and GA-binding protein in developing B cells.

Signaling through the IL-7 receptor (IL-7R) is required for development and maintenance of the immune system. The receptor for IL-7 is heterodimeric, consisting of a common gamma chain (gammac, encoded by Il2rg) and an alpha subunit (IL-7Ralpha, encoded by Il7r). The Il7r gene is expressed specifically in the immune system in a developmental stage-specific manner. It is not known how the Il7r gene is transcriptionally regulated during B cell development. The goal of this study is to elucidate the function of the Il7r promoter region in developing B cells. Using a combination of 5' rapid amplification of cDNA ends analysis, transient transfection assays, and DNase I hypersensitivity mapping, we identified the location of the Il7r promoter. Using a combination of electrophoretic mobility shift analysis, chromatin immunoprecipitation experiments, and RNA interference experiments, we found that the Ets transcription factors PU.1 and GA-binding protein (GABP) activate the Il7r promoter by interacting with a highly conserved Ets binding site. In committed B lineage cells, GABP can promote Il7r transcription in the absence of PU.1. However, the results of retroviral gene transfer experiments suggest that PU.1 is uniquely required to initiate transcription of the Il7r locus at the earliest stages of progenitor B cell generation. In summary, these results suggest that Il7r transcription is regulated by both PU.1 and GABP in developing B cells.