Effects of clinical covariates on serum miRNA expression among women without ovarian cancer.

BACKGROUND: Serum microRNAs (miRNAs) are potential biomarkers for ovarian cancer; however, many factors may influence miRNA expression. To understand potential confounders in miRNA analysis, we examined how sociodemographic factors and comorbidities, including known ovarian cancer risk factors, influence serum miRNA levels in women without ovarian cancer. METHODS: Data from 1,576 women from the Mass General Brigham Biobank collected between 2012 and 2019, excluding subjects previously or subsequently diagnosed with ovarian cancer, were examined. Using a focused panel of 179 miRNA probes optimized for serum profiling, miRNA expression was measured by flow cytometry using the Abcam Fireplex® assay and correlated with subjects' electronic medical records. RESULTS: The study population broadly reflected the New England population. The median age of subjects was 49 years, 34% were current or prior smokers, 33% were obese (BMI >30kg/m2), 49% were postmenopausal, and 11% had undergone prior bilateral oophorectomy. Significant differences in miRNA expression were observed among ovarian risk factors such as age, obesity, menopause, BRCA1 or BRCA2 germline mutations or breast cancer in family history. Additionally, miRNA expression was significantly altered by prior bilateral oophorectomy, hypertension, and hypercholesterolemia. Other variables, such as smoking, parity, age at menarche, hormonal replacement therapy, oral contraception, breast, endometrial, or colon cancer, and diabetes were not associated with significant changes in the panel when corrected for multiple testing. CONCLUSIONS: Serum miRNA expression patterns are significantly affected by patient demographics, exposure history, and medical comorbidities. IMPACT: Understanding confounders in serum miRNA expression is important for refining clinical assays for cancer screening.

Differences in Serum miRNA Profiles by Race, Ethnicity, and Socioeconomic Status: Implications for Developing an Equitable Ovarian Cancer Screening Test.

Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. To inform equitable implementation of these tests, we investigated the effects of race, ethnicity, and socioeconomic status on serum miRNA profiles. Serum samples from a large institutional biobank were analyzed using a custom panel of 179 miRNA species highly expressed in human serum, measured using the Abcam Fireplex assay via flow cytometry. Data were log-transformed prior to analysis. Differences in miRNA by race and ethnicity were assessed using logistic regression. Pairwise t tests analyzed racial and ethnic differences among eight miRNAs previously associated with ovarian cancer risk. Pearson correlations determined the relationship between mean miRNA expression and the social deprivation index (SDI) for Massachusetts residents. Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. Understanding baseline differences in biomarker test characteristics prior to clinical implementation is essential to ensure instruments perform comparably across diverse populations. PREVENTION RELEVANCE: This study aimed to understand factors affecting miRNA expression, to ensure we create equitable screening tests for ovarian cancer that perform well in diverse populations. The goal is to ensure that we are detecting ovarian cancer cases earlier (secondary prevention) in women of all races, ethnic backgrounds, and socioeconomic means.

Identification of BRCA1/2 mutation female carriers using circulating microRNA profiles.

Identifying germline BRCA1/2 mutation carriers is vital for reducing their risk of breast and ovarian cancer. To derive a serum miRNA-based diagnostic test we used samples from 653 healthy women from six international cohorts, including 350 (53.6%) with BRCA1/2 mutations and 303 (46.4%) BRCA1/2 wild-type. All individuals were cancer-free before and at least 12 months after sampling. RNA-sequencing followed by differential expression analysis identified 19 miRNAs significantly associated with BRCA mutations, 10 of which were ultimately used for classification: hsa-miR-20b-5p, hsa-miR-19b-3p, hsa-let-7b-5p, hsa-miR-320b, hsa-miR-139-3p, hsa-miR-30d-5p, hsa-miR-17-5p, hsa-miR-182-5p, hsa-miR-421, hsa-miR-375-3p. The final logistic regression model achieved area under the receiver operating characteristic curve 0.89 (95% CI: 0.87-0.93), 93.88% sensitivity and 80.72% specificity in an independent validation cohort. Mutated gene, menopausal status or having preemptive oophorectomy did not affect classification performance. Circulating microRNAs may be used to identify BRCA1/2 mutations in patients of high risk of cancer, offering an opportunity to reduce screening costs.

Fast and robust imputation for miRNA expression data using constrained least squares.

BACKGROUND: High dimensional transcriptome profiling, whether through next generation sequencing techniques or high-throughput arrays, may result in scattered variables with missing data. Data imputation is a common strategy to maximize the inclusion of samples by using statistical techniques to fill in missing values. However, many data imputation methods are cumbersome and risk introduction of systematic bias. RESULTS: We present a new data imputation method using constrained least squares and algorithms from the inverse problems literature and present applications for this technique in miRNA expression analysis. The proposed technique is shown to offer an imputation orders of magnitude faster, with greater than or equal accuracy when compared to similar methods from the literature. CONCLUSIONS: This study offers a robust and efficient algorithm for data imputation, which can be used, e.g., to improve cancer prediction accuracy in the presence of missing data.

Molecular hallmarks of heterochronic parabiosis at single-cell resolution.

The ability to slow or reverse biological ageing would have major implications for mitigating disease risk and maintaining vitality1. Although an increasing number of interventions show promise for rejuvenation2, their effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. Here we performed single-cell RNA sequencing on 20 organs to reveal cell-type-specific responses to young and aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, haematopoietic stem cells and hepatocytes are among those cell types that are especially responsive. On the pathway level, young blood invokes new gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. We observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it in select cell types. Together, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

Ageing hallmarks exhibit organ-specific temporal signatures.

Ageing is the single greatest cause of disease and death worldwide, and understanding the associated processes could vastly improve quality of life. Although major categories of ageing damage have been identified-such as altered intercellular communication, loss of proteostasis and eroded mitochondrial function1-these deleterious processes interact with extraordinary complexity within and between organs, and a comprehensive, whole-organism analysis of ageing dynamics has been lacking. Here we performed bulk RNA sequencing of 17 organs and plasma proteomics at 10 ages across the lifespan of Mus musculus, and integrated these findings with data from the accompanying Tabula Muris Senis2-or 'Mouse Ageing Cell Atlas'-which follows on from the original Tabula Muris3. We reveal linear and nonlinear shifts in gene expression during ageing, with the associated genes clustered in consistent trajectory groups with coherent biological functions-including extracellular matrix regulation, unfolded protein binding, mitochondrial function, and inflammatory and immune response. Notably, these gene sets show similar expression across tissues, differing only in the amplitude and the age of onset of expression. Widespread activation of immune cells is especially pronounced, and is first detectable in white adipose depots during middle age. Single-cell RNA sequencing confirms the accumulation of T cells and B cells in adipose tissue-including plasma cells that express immunoglobulin J-which also accrue concurrently across diverse organs. Finally, we show how gene expression shifts in distinct tissues are highly correlated with corresponding protein levels in plasma, thus potentially contributing to the ageing of the systemic circulation. Together, these data demonstrate a similar yet asynchronous inter- and intra-organ progression of ageing, providing a foundation from which to track systemic sources of declining health at old age.

Unbiased Proteomic Profiling Uncovers a Targetable GNAS/PKA/PP2A Axis in Small Cell Lung Cancer Stem Cells.

Using unbiased kinase profiling, we identified protein kinase A (PKA) as an active kinase in small cell lung cancer (SCLC). Inhibition of PKA activity genetically, or pharmacologically by activation of the PP2A phosphatase, suppresses SCLC expansion in culture and in vivo. Conversely, GNAS (G-protein α subunit), a PKA activator that is genetically activated in a small subset of human SCLC, promotes SCLC development. Phosphoproteomic analyses identified many PKA substrates and mechanisms of action. In particular, PKA activity is required for the propagation of SCLC stem cells in transplantation studies. Broad proteomic analysis of recalcitrant cancers has the potential to uncover targetable signaling networks, such as the GNAS/PKA/PP2A axis in SCLC.

Integration of Tumor Genomic Data with Cell Lines Using Multi-dimensional Network Modules Improves Cancer Pharmacogenomics.

Leveraging insights from genomic studies of patient tumors is limited by the discordance between these tumors and the cell line models used for functional studies. We integrate omics datasets using functional networks to identify gene modules reflecting variation between tumors and show that the structure of these modules can be evaluated in cell lines to discover clinically relevant biomarkers of therapeutic responses. Applied to breast cancer, we identify 219 gene modules that capture recurrent alterations and subtype patients and quantitate various cell types within the tumor microenvironment. Comparison of modules between tumors and cell lines reveals that many modules composed primarily of gene expression and methylation are poorly preserved. In contrast, preserved modules are highly predictive of drug responses in a manner that is robust and clinically relevant. This work addresses a fundamental challenge in pharmacogenomics that can only be overcome by the joint analysis of patient and cell line data.

Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer.

Dysregulation of the PI3K-AKT-mTOR signaling network is a prominent feature of breast cancers. However, clinical responses to drugs targeting this pathway have been modest, possibly because of dynamic changes in cellular signaling that drive resistance and limit drug efficacy. Using a quantitative chemoproteomics approach, we mapped kinome dynamics in response to inhibitors of this pathway and identified signaling changes that correlate with drug sensitivity. Maintenance of AURKA after drug treatment was associated with resistance in breast cancer models. Incomplete inhibition of AURKA was a common source of therapy failure, and combinations of PI3K, AKT or mTOR inhibitors with the AURKA inhibitor MLN8237 were highly synergistic and durably suppressed mTOR signaling, resulting in apoptosis and tumor regression in vivo. This signaling map identifies survival factors whose presence limits the efficacy of targeted therapies and reveals new drug combinations that may unlock the full potential of PI3K-AKT-mTOR pathway inhibitors in breast cancer.

An examination of MCE filter morphology and implications on preparation and analysis of air samples for asbestos.

Morphological imperfections of mixed-cellulose ester filters and their possible influence on sample preparation and analysis of asbestos were examined. Filters were identified with large regions of non-porous "dead zones" which could negatively affect fiber deposition and, therefore, fiber recovery and analysis by Transmission Electron Microscopy (TEM). As these imperfections are effectively erased during the preparation of the sample, they may not be readily observed by TEM. Un-collapsed filters as well as those collapsed using dimethylformamide (DMF) and two acetone techniques were examined. In order to minimize negative sampling and analytical bias, it is suggested that MCE samples be collapsed utilizing a 35% DMF solution, etched with a correctly calibrated low-temperature etcher, carbon coated using a rotating and tilted stage, and analyzed with a strong analyst-independent grid square opening randomization scheme.

An Optimized Chromatographic Strategy for Multiplexing In Parallel Reaction Monitoring Mass Spectrometry: Insights from Quantitation of Activated Kinases.

Reliable quantitation of protein abundances in defined sets of cellular proteins is critical to numerous biological applications. Traditional immunodetection-based methods are limited by the quality and availability of specific antibodies, especially for site-specific post-translational modifications. Targeted proteomic methods, including the recently developed parallel reaction monitoring (PRM) mass spectrometry, have enabled accurate quantitative measurements of up to a few hundred specific target peptides. However, the degree of practical multiplexing in label-free PRM workflows remains a significant limitation for the technique. Here we present a strategy for significantly increasing multiplexing in label-free PRM that takes advantage of the superior separation characteristics and retention time stability of meter-scale monolithic silica-C18 column-based chromatography. We show the utility of the approach in quantifying kinase abundances downstream of previously developed active kinase enrichment methodology based on multidrug inhibitor beads. We examine kinase activation dynamics in response to three different MAP kinase inhibitors in colorectal carcinoma cells and demonstrate reliable quantitation of over 800 target peptides from over 150 kinases in a single label-free PRM run. The kinase activity profiles obtained from these analyses reveal compensatory activation of TGF-ß family receptors as a response to MAPK blockade. The gains achieved using this label-free PRM multiplexing strategy will benefit a wide array of biological applications.

Synthetic Lethal Targeting of ARID1A-Mutant Ovarian Clear Cell Tumors with Dasatinib.

New targeted approaches to ovarian clear cell carcinomas (OCCC) are needed, given the limited treatment options in this disease and the poor response to standard chemotherapy. Using a series of high-throughput cell-based drug screens in OCCC tumor cell models, we have identified a synthetic lethal (SL) interaction between the kinase inhibitor dasatinib and a key driver in OCCC, ARID1A mutation. Imposing ARID1A deficiency upon a variety of human or mouse cells induced dasatinib sensitivity, both in vitro and in vivo, suggesting that this is a robust synthetic lethal interaction. The sensitivity of ARID1A-deficient cells to dasatinib was associated with G1-S cell-cycle arrest and was dependent upon both p21 and Rb. Using focused siRNA screens and kinase profiling, we showed that ARID1A-mutant OCCC tumor cells are addicted to the dasatinib target YES1. This suggests that dasatinib merits investigation for the treatment of patients with ARID1A-mutant OCCC. Mol Cancer Ther; 15(7); 1472-84. ©2016 AACR.

Isocitrate Dehydrogenase Mutations Confer Dasatinib Hypersensitivity and SRC Dependence in Intrahepatic Cholangiocarcinoma.

UNLABELLED: Intrahepatic cholangiocarcinoma (ICC) is an aggressive liver bile duct malignancy exhibiting frequent isocitrate dehydrogenase (IDH1/IDH2) mutations. Through a high-throughput drug screen of a large panel of cancer cell lines, including 17 biliary tract cancers, we found that IDH mutant (IDHm) ICC cells demonstrate a striking response to the multikinase inhibitor dasatinib, with the highest sensitivity among 682 solid tumor cell lines. Using unbiased proteomics to capture the activated kinome and CRISPR/Cas9-based genome editing to introduce dasatinib-resistant "gatekeeper" mutant kinases, we identified SRC as a critical dasatinib target in IDHm ICC. Importantly, dasatinib-treated IDHm xenografts exhibited pronounced apoptosis and tumor regression. Our results show that IDHm ICC cells have a unique dependency on SRC and suggest that dasatinib may have therapeutic benefit against IDHm ICC. Moreover, these proteomic and genome-editing strategies provide a systematic and broadly applicable approach to define targets of kinase inhibitors underlying drug responsiveness. SIGNIFICANCE: IDH mutations define a distinct subtype of ICC, a malignancy that is largely refractory to current therapies. Our work demonstrates that IDHm ICC cells are hypersensitive to dasatinib and critically dependent on SRC activity for survival and proliferation, pointing to new therapeutic strategies against these cancers. Cancer Discov; 6(7); 727-39. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 681.

Oncogene mimicry as a mechanism of primary resistance to BRAF inhibitors.

Despite the development of potent RAF/mitogen-activated protein kinase (MAPK) pathway inhibitors, only a fraction of BRAF-mutant patients benefit from treatment with these drugs. Using a combined chemogenomics and chemoproteomics approach, we identify drug-induced RAS-RAF-MEK complex formation in a subset of BRAF-mutant cancer cells characterized by primary resistance to vemurafenib. In these cells, autocrine interleukin-6 (IL-6) secretion may contribute to the primary resistance phenotype via induction of JAK/STAT3 and MAPK signaling. In a subset of cell lines, combined IL-6/MAPK inhibition is able to overcome primary resistance to BRAF-targeted therapy. Overall, we show that the signaling plasticity exerted by primary resistant BRAF-mutant cells is achieved by their ability to mimic signaling features of oncogenic RAS, a strategy that we term "oncogene mimicry." This model may guide future strategies for overcoming primary resistance observed in these tumors.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins.

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype-phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or 'passenger', cancer mutations from causal, or 'driver', mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Amphibole asbestos in tree bark--a review of findings for this inhalational exposure source in Libby, Montana.

In June 2009, the U.S. Environmental Protection Agency (EPA) designated the town of Libby, Montana, a public health emergency--the first and only time the EPA has made such a determination under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). From about 1920 until 1990, the leading source of vermiculite ore for the United States and the world was from a mine near Libby. This vermiculite ore was contaminated with fibrous and asbestiform amphibole in veins throughout the deposit. Today, areas surrounding the abandoned vermiculite processing/mining facilities and much of the town of Libby are contaminated with these asbestos fibers, contributing to an outbreak of asbestos-related diseases in the Libby population. Trees in Libby and in forested areas surrounding the abandoned mine have accumulated amphibole asbestos fibers on their bark surface, providing for inhalational exposures. Several studies have been conducted to further understand this exposure pathway. To address exposures to the public, Libby amphibole (LA) was measured in personal breathing zone and Tyvek surface wipe samples collected during firewood harvesting simulations, as well as in the ash and emissions of woodstoves when amphibole-contaminated firewood was combusted. Occupational studies simulating wildland firefighting and routine U.S. Department of Agriculture (USDA) Forest Service activities have also been conducted in the forested areas surrounding the abandoned mine, demonstrating the potential for inhalational exposures during common regional workplace activities. We present a review of the findings of this emerging environmental health concern impacting not only the residents of Libby but applicable to other populations living near asbestos-contaminated areas.

C/EBPα and DEK coordinately regulate myeloid differentiation.

The transcription factor C/EBPα is a critical mediator of myeloid differentiation and is often functionally impaired in acute myeloid leukemia. Recent studies have suggested that oncogenic FLT3 activity disrupts wild-type C/EBPα function via phosphorylation on serine 21 (S21). Despite the apparent role of pS21 as a negative regulator of C/EBPα transcription activity, the mechanism by which phosphorylation tips the balance between transcriptionally competent and inhibited forms remains unresolved. In the present study, we used immuno-affinity purification combined with quantitative mass spectrometry to delineate the proteins associated with C/EBPα on chromatin. We identified DEK, a protein with genetic links to leukemia, as a member of the C/EBPα complexes, and demonstrate that this association is disrupted by S21 phosphorylation. We confirmed that DEK is recruited specifically to chromatin with C/EBPα to enhance GCSFR3 promoter activation. In addition, we demonstrated that genetic depletion of DEK reduces the ability of C/EBPα to drive the expression of granulocytic target genes in vitro and disrupts G-CSF-mediated granulocytic differentiation of fresh human BM-derived CD34(+) cells. Our data suggest that C/EBPα and DEK coordinately activate myeloid gene expression and that S21 phosphorylation on wild-type C/EBPα mediates protein interactions that regulate the differentiation capacity of hematopoietic progenitors.

Online nanoflow reversed phase-strong anion exchange-reversed phase liquid chromatography-tandem mass spectrometry platform for efficient and in-depth proteome sequence analysis of complex organisms.

The dynamic range of protein expression in complex organisms coupled with the stochastic nature of discovery-driven tandem mass spectrometry (MS/MS) analysis continues to impede comprehensive sequence analysis and often provides only limited information for low-abundance proteins. High-performance fractionation of proteins or peptides prior to mass spectrometry analysis can mitigate these effects, though achieving an optimal combination of automation, reproducibility, separation peak capacity, and sample yield remains a significant challenge. Here we demonstrate an automated nanoflow 3-D liquid chromatography (LC)-MS/MS platform based on high-pH reversed phase (RP), strong anion exchange (SAX), and low-pH reversed phase (RP) separation stages for analysis of complex proteomes. We observed that RP-SAX-RP outperformed RP-RP for analysis of tryptic peptides derived from Escherichia coli and enabled identification of proteins present at a level of 50 copies per cell in Saccharomyces cerevisiae, corresponding to an estimated detection limit of 500 amol, from 40 µg of total lysate on a low-resolution 3-D ion trap mass spectrometer. A similar study performed on a LTQ-Orbitrap yielded over 4000 unique proteins from 5 µg of total yeast lysate analyzed in a single, 101 fraction RP-SAX-RP LC-MS/MS acquisition, providing an estimated detection limit of 65 amol for proteins expressed at 50 copies per cell.

Online nanoflow multidimensional fractionation for high efficiency phosphopeptide analysis.

Despite intense, continued interest in global analyses of signaling cascades through mass spectrometry-based studies, the large-scale, systematic production of phosphoproteomics data has been hampered in-part by inefficient fractionation strategies subsequent to phosphopeptide enrichment. Here we explore two novel multidimensional fractionation strategies for analysis of phosphopeptides. In the first technique we utilize aliphatic ion pairing agents to improve retention of phosphopeptides at high pH in the first dimension of a two-dimensional RP-RP. The second approach is based on the addition of strong anion exchange as the second dimension in a three-dimensional reversed phase (RP)-strong anion exchange (SAX)-RP configuration. Both techniques provide for automated, online data acquisition, with the 3-D platform providing the highest performance both in terms of separation peak capacity and the number of unique phosphopeptide sequences identified per µg of cell lysate consumed. Our integrated RP-SAX-RP platform provides several analytical figures of merit, including: (1) orthogonal separation mechanisms in each dimension; (2) high separation peak capacity (3) efficient retention of singly- and multiply-phosphorylated peptides; (4) compatibility with automated, online LC-MS analysis. We demonstrate the reproducibility of RP-SAX-RP and apply it to the analysis of phosphopeptides derived from multiple biological contexts, including an in vitro model of acute myeloid leukemia in addition to primary polyclonal CD8(+) T-cells activated in vivo through bacterial infection and then purified from a single mouse.

Separation and characterization of respirable amphibole fibers from Libby, Montana.

The vermiculite mine in Libby, Montana, was in operation for over 70 yr and was contaminated with asbestos-like amphibole fibers. The mining, processing, and shipping of this vermiculite led to significant fiber inhalation exposure throughout the community, and residents of Libby have developed numerous pulmonary diseases such as lung cancer and mesothelioma. The present study describes the separation of Libby 6-mix into respirable and nonrespirable size fractions by means of aqueous elutriation. The elutriator, designed to separate fibers with aerodynamic diameters smaller than 2.5 microm (respirable) from larger fibers, used an upward flow rate of 3.4 x 10(- 4) cm s(-1). The resultant respirable fraction constituted only 13% of the raw Libby 6-mix mass, and less than 2% of the fibers in the elutriated fraction had aerodynamic diameters exceeding 2.5 microm. Surface area of the elutriated fibers was 5.3 m(- 2) g(-1), compared to 0.53 m(-2) g(-1) for the raw fibers. There were no detectable differences in chemical composition between the larger and smaller fibers. Such harvesting of respirable fractions will allow toxicological studies to be conducted within a controlled laboratory setting, utilizing fiber sizes that may more accurately simulate historical exposure of Libby residents' lungs. Importantly, this work describes a method that allows the use of material enriched in more uniform respirable material than raw Libby 6-mix, making comparisons with other known fiber preparations more valid on a mass basis.