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Neuroblastoma is a common pediatric cancer, where preclinical studies have suggested chemotherapy resistance is driven by a mesenchymal-like gene expression program. However, the poor clinical outcomes imply we need a better understanding of the relationship between patient tumors and preclinical models. Here, we generated single-cell RNA-seq maps of neuroblastoma cell lines, patient-derived xenograft models (PDX), and a genetically engineered mouse model (GEMM). We developed an unsupervised machine learning approach to compare the gene expression programs found in preclinical models to a large cohort of human neuroblastoma tumors. The dominant adrenergic programs were well preserved in preclinical models, but contrary to previous reports do not unambiguously map to an obvious cell of origin. The mesenchymal-like program was less clearly preserved, and primarily restricted to cancer-associated fibroblasts and Schwann-like cellsin vivo. Surprisingly however, we identified a subtle, weakly expressed, mesenchymal-like program in otherwise adrenergic cancer cells in some high-risk tumors. This program appears distinct from mesenchymal cell lines but was maintained in PDX and a similar program could be chemotherapy-induced in our GEMM after only 24 hours, suggesting an uncharacterized therapy-escape mechanism. Collectively, our findings advance the understanding of neuroblastoma heterogeneity and can inform the development of new treatments.

Combination chemotherapy is crucial for achieving durable cancer cures, however, developing safe and effective drug combinations has been a significant challenge. To improve this process, we conducted large-scale targeted CRISPR knockout screens in drug-treated cells, creating a genetic map of druggable genes that sensitize cells to commonly used chemotherapeutics. We prioritized neuroblastoma, the most common pediatric solid tumor, where 50% of high-risk patients do not survive. Our screen examined all druggable gene knockouts in 18 cell lines (10 neuroblastoma, 8 others) treated with 8 widely used drugs, resulting in 94,320 unique combination-cell line perturbations, which is comparable to the largest drug combination screens ever reported. Remarkably, using dense drug-drug rescreening, we found that the top CRISPR-nominated drug combinations were far more synergistic than standard-of-care combinations, suggesting existing combinations could be improved. As proof of principle, we discovered that inhibition of PRKDC, a component of the non-homologous end-joining pathway, sensitizes high-risk neuroblastoma cells to the standard-of-care drug doxorubicinin vitroandin vivousing PDX models. Our findings provide a valuable resource for the development of improved chemotherapeutic strategies and demonstrate the feasibility of using targeted CRISPR knockout to discover new combinations with common chemotherapeutics, a methodology with application across all cancers.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer. One major reason for this is that PDAC quickly metastasizes to other organs, thereby making its treatment difficult. The molecular machinery driving PDAC metastasis is still poorly understood. In this study, we applied an unbiased approach using CRISPR screening to identify genes that strongly regulate invasion (based on an in vitro assessment of their metastatic potential) in PANC-1, a PDAC cell line. Through CRISPR screening, we identified MBNL3 and KANSL2 as strong regulators of invasion in PANC-1 cells. We further validated MBNL3 and KANSL2 as regulators of PANC-1 cell invasion by using the doxycycline-inducible shRNA system. We also showed that MBNL3 and KANSL2 do not affect cell proliferation. Through our efforts, we have established a process to identify genes that regulate cell invasion and can be further investigated as potential targets for therapeutic intervention.

The 48 human nuclear receptors (NRs) form a superfamily of transcription factors that regulate major physiological and pathological processes. Emerging evidence suggests that NR crosstalk can fundamentally change our understanding of NR biology, but detailed molecular mechanisms of crosstalk are lacking. Here, we report the molecular basis of crosstalk between the pregnane X receptor (PXR) and constitutive androstane receptor (CAR), where they form a novel heterodimer, resulting in their mutual inhibition. PXR and CAR regulate drug metabolism and energy metabolism. Although they have been broadly perceived as functionally redundant, a growing number of reports suggests a mutual inhibitory relation, but their precise mode of coordinated action remains unknown. Using methods including RNA sequencing, small-angle X-ray scattering and crosslinking mass spectrometry we demonstrate that the mutual inhibition altered gene expression globally and is attributed to the novel PXR–CAR heterodimerization via the same interface used by each receptor to heterodimerize with its functional partner, retinoid X receptor (RXR). These findings establish an unexpected functional relation between PXR, CAR and RXR, change the perceived functional relation between PXR and CAR, open new perspectives on elucidating their role and designing approaches to regulate them, and highlight the importance to comprehensively investigate nuclear receptor crosstalk.

Spatial transcriptomics technologies have recently emerged as a powerful tool for measuring spatially resolved gene expression directly in tissues sections, revealing cell types and their dysfunction in unprecedented detail. However, spatial transcriptomics technologies are limited in their ability to separate transcriptionally similar cell types and can suffer further difficulties identifying cell types in slide regions where transcript capture is low. Here, we describe a conceptually novel methodology that can computationally integrate spatial transcriptomics data with cell-type-informative paired tissue images, obtained from, for example, the reverse side of the same tissue section, to improve inferences of tissue cell type composition in spatial transcriptomics data. The underlying statistical approach is generalizable to any spatial transcriptomics protocol where informative paired tissue images can be obtained. We demonstrate a use case leveraging cell-type-specific immunofluorescence markers obtained on mouse brain tissue sections and a use case for leveraging the output of AI annotated H&E tissue images, which we used to markedly improve the identification of clinically relevant immune cell infiltration in breast cancer tissue. Thus, combining spatial transcriptomics data with paired tissue images has the potential to improve the identification of cell types and hence to improve the applications of spatial transcriptomics that rely on accurate cell type identification.

Survival in high-risk pediatric neuroblastoma has remained around 50% for the last 20 years, with immunotherapies and targeted therapies having had minimal impact. Here, we identify the small molecule CX-5461 as selectively cytotoxic to high-risk neuroblastoma and synergistic with low picomolar concentrations of topoisomerase I inhibitors in improving survival in vivo in orthotopic patient-derived xenograft neuroblastoma mouse models. CX-5461 recently progressed through phase I clinical trial as a first-in-human inhibitor of RNA-POL I. However, we also use a comprehensive panel of in vitro and in vivo assays to demonstrate that CX-5461 has been mischaracterized and that its primary target at pharmacologically relevant concentrations, is in fact topoisomerase II beta (TOP2B), not RNA-POL I. This is important because existing clinically approved chemotherapeutics have well-documented off-target interactions with TOP2B, which have previously been shown to cause both therapy-induced leukemia and cardiotoxicity—often-fatal adverse events, which can emerge several years after treatment. Thus, while we show that combination therapies involving CX-5461 have promising anti-tumor activity in vivo in neuroblastoma, our identification of TOP2B as the primary target of CX-5461 indicates unexpected safety concerns that should be examined in ongoing phase II clinical trials in adult patients before pursuing clinical studies in children., CX-5461 recently progressed through phase I clinical trial as a first-inhuman inhibitor of RNA-POL I. Here, the authors demonstrate that CX-5461 synergizes with topoisomerase I inhibitors to inhibit neuroblastoma cells and that its primary target in this disease is topoisomerase II beta and not RNA-POL I.

Background Despite its relatively low incidence, pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer deaths because of the aggressive growth/metastasis of the tumor, the lack of early symptoms, and the poor treatment options. Basic research to identify potential therapeutic targets for PDAC is greatly needed. Methods We used a negative-selection genome-wide CRISPR screen to identify essential genes in the PANC-1 human pancreatic carcinoma cell line. We validated the top hits with follow-up siRNA screens, using the HPNE, HPAF-II, AsPC-1, and Mia PaCa-2 cell lines. Results The PSMA6 gene was an identified candidate hit after the CRISPR screen, siRNA validation screen, and siRNA deconvolution screen. Spheroid formation assays and flow cytometry analysis showed that PSMA6 is critical for survival in many pancreatic ductal carcinoma cell models. Lastly, as PSMA6 protein is a proteosomal subunit of the 20S core complex, we showed that bortezomib, a proteasome inhibitor, was especially toxic in PANC-1 cells. Conclusions Further study of PSMA6 and the proteasome subunit that it encodes, along with other hits identified in our CRISPR screens, may provide valuable insights into potential therapeutic targets for PDAC. Electronic supplementary material The online version of this article (10.1186/s12885-019-5455-1) contains supplementary material, which is available to authorized users.

Drug combinations are the basis of treatment for modern diseases but arriving at successful combination therapies is fraught with challenges. Decades ago, the limited number of drugs represented a tractable candidate list from which to design combination experiments. However, the current pool of single-agent drugs to potentially combine is far too large to brute-force screen, and purely computational predictions have performed poorly. Suitable screening methods are needed, but the design of experimental approaches has proven to be highly complex; researchers need to carefully balance many variables such as appropriate drug concentration ranges, number of doses, inclusion of replicates, and throughput. Perhaps the most significant obstacle facing these studies is the approach to data analysis, where conflicting definitions of synergy and unintuitive metrics serve to confuse researchers and render largely uninterpretable results. Collectively, these challenges hamper the progress of drug combination research and ultimately translational impact. To overcome these limitations, we have developed a fully self-contained framework to handle both the experimental design and analysis of drug combination experiments. Our method, called Combocat, provides a straightforward way to test and analyze any number of drug combinations and samples, and is suitable for high-throughput. Combocat provides a high-resolution of concentration combinations compared to most current approaches. This is automated by common instruments and uses scripts included within our protocol. Through careful template design, we were able to include 3 replicates of each 10x10 matrix, single-agent drugs, and controls - all within a single 384-well plate. We found our method to work robustly with varying sample types (Human cancer, bacteria, fungi), and readouts. After data generation, files can simply be dragged into our Combocat analysis tool directly. We provide a free, web-based software suite to fully automate the analysis after data collection. The Combocat web tool is intuitive and facilitates interactive exploration of synergy. It also provides a rich array of information such as dose-response curves, IC50 values, synergy matrices, ranked hit plots, and more. Data normalization, synergy algorithms, scoring functions, and other complex calculations are run swiftly and automatically in the background with no need for user input. Notably, we employ statistical testing by taking advantage of experimental replicates, which is a feature we found lacking in most methods. We use a well-documented synergy metric but also decided to formulate our own Combocat score which considers statistical measurements and assay quality. The Combocat score provides an easy interpretation of results and facilitates quick identification of top hits. Collectively, our platform will be used to enhance and expedite the selection of effective drug combinations. Citation Format: William C. Wright, Min Pan, Hyeong-Min Lee, Gregory A. Phelps, Jonathan Low, Duane Currier, Richard E. Lee, Taosheng Chen, Paul Geeleher. Combocat: A high-throughput framework for drug combination studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1907.

For over 100 years, the traditional tools of pathology, such as tissue-marking dyes (e.g. the H&E stain) have been used to study the disorganization and dysfunction of cells within tissues. This has represented a principal diagnostic and prognostic tool in cancer. However, in the last 5 years, new technologies have promised to revolutionize histopathology, with Spatial Transcriptomics technologies allowing us to measure gene expression directly in pathology-stained tissue sections. In parallel with these developments, Artificial Intelligence (AI) applied to histopathology tissue images now approaches pathologist level performance in cell type identification. However, these new technologies still have severe limitations, with Spatial Transcriptomics suffering difficulties distinguishing transcriptionally similar cell types, and AI-based pathology tools often performing poorly on real world out-of-batch test datasets. Thus, century-old techniques still represent standard-of-care in most areas of clinical cancer diagnostics and prognostics. Here, we present a new frontier in digital pathology: describing a conceptually novel computational methodology, based on Bayesian probabilistic modelling, that allows Spatial Transcriptomics data to be leveraged together with the output of deep learning-based AI used to computationally annotate H&E-stained sections of the same tumor. By leveraging cell-type annotations from multiple independent pathologists, we show that this integrated methodology achieves better performance than any given pathologist’s manual tissue annotation in the task of identifying regions of immune cell infiltration in breast cancer, and easily outperforms either technology alone. We also show that on a subset of histopathology slides examined, the methodology can identify regions of clinically relevant immune cell infiltration that were missed entirely by an initial pathologist’s manual annotation. While this use case has clear diagnostic and prognostic value in cancer (e.g. predicting response to immunotherapy), our methodology is generalizable to any type of pathology images and also has broad applications in spatial transcriptomics data analytics, where most applications (such as identifying cell-cell interactions) rely on correct cell type annotations having been established a priori. We anticipate that this work will spur many follow-up studies, including new computational innovations building on the approach. The work sets the stage for better-than-pathologist performance in other cell-type annotation tasks, with relevant applications in diagnostics and prognostics across almost all cancers. Citation Format: Asif Zubair, Rich Chapple, Sivaraman Natarajan, William C. Wright, Min Pan, Hyeong-Min Lee, Heather Tillman, John Easton, Paul Geeleher. Jointly leveraging spatial transcriptomics and deep learning models for image annotation achieves better-than-pathologist performance in cell type identification in tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 456.

The human cytochrome P450 (CYP) enzymes CYP3A4 and CYP3A5 metabolize most drugs and have high similarities in their structure and substrate preference. Whereas CYP3A4 is predominantly expressed in the liver, CYP3A5 is upregulated in cancer, contributing to drug resistance. Selective inhibitors of CYP3A5 are, therefore, critical to validating it as a therapeutic target. Here we report clobetasol propionate (clobetasol) as a potent and selective CYP3A5 inhibitor identified by high-throughput screening using enzymatic and cell-based assays. Molecular dynamics simulations suggest a close proximity of clobetasol to the heme in CYP3A5 but not in CYP3A4. UV-visible spectroscopy and electron paramagnetic resonance analyses confirmed the formation of an inhibitory type I heme-clobetasol complex in CYP3A5 but not in CYP3A4, thus explaining the CYP3A5 selectivity of clobetasol. Our results provide a structural basis for selective CYP3A5 inhibition, along with mechanistic insights, and highlight clobetasol as an important chemical tool for target validation.

Most currently-prescribed drugs are metabolized by the Cytochrome P450 3A (CYP3A) family. It is therefore critical to know whether drugs or compounds of interest inhibit these enzymes (primarily CYP3A4 and CYP3A5). Here, we describe an LC-MS/MS based method to measure CYP3A catalytic activity in cells. Our method allows for highly sensitive detection of drug-induced modulations in CYP3A activity, as well as endogenous (non-treated) activity. This is accomplished by exploiting the CYP3A-catalyzed hydroxylation of midazolam. We include DMSO and inhibitor controls to obtain a signal window capable of producing normalized dose-response curves. We also obtain tight error bars suitable for statistical interpretation, which highlights the reproducibility of the assay between replicates. While our method is performed in 384-well plates and is amenable to high-throughput screening – an optional plate freezing step allows for storage of samples before metabolite detection, making our protocol suitable for lower throughputs as well. We present a stepwise protocol starting from treatment of cells with a compound of interest to obtaining its IC50 value and determining CYP3A inhibition.

Increasing rates of drug-resistant Gram-negative (GN) infections, combined with a lack of new GN-effective antibiotic classes, are driving the need for the discovery of new agents. Bacterial metabolism represents an underutilized mechanism of action in current antimicrobial therapies. Therefore, we sought to identify novel antimetabolites that disrupt key metabolic pathways and explore the specific impacts of these agents on bacterial metabolism. This study describes the successful application of this approach to discover a new series of chemical probes, N-(phenyl)thioacetamide-linked 1,2,3-triazoles (TAT), that target cysteine synthase A (CysK), an enzyme unique to bacteria that is positioned at a key juncture between several fundamental pathways. The TAT class was identified using a high-throughput screen against Escherichia coli designed to identify modulators of pathways related to folate biosynthesis. TAT analog synthesis demonstrated a clear structure-activity relationship, and activity was confirmed against GN antifolate-resistant clinical isolates. Spontaneous TAT resistance mutations were tracked to CysK, and mode of action studies led to the identification of a false product formation mechanism between the CysK substrate O-acetyl-l-serine and the TATs. Global transcriptional responses to TAT treatment revealed that these antimetabolites impose substantial disruption of key metabolic networks beyond cysteine biosynthesis. This study highlights the potential of antimetabolite drug discovery as a promising approach to the discovery of novel GN antibiotics and the pharmacological promise of TAT CysK probes.

Pregnane X receptor (PXR) is activated by chemicals to transcriptionally regulate drug disposition and possibly decrease drug efficacy and increase resistance, suggesting therapeutic value for PXR antagonists. We previously reported the antagonist SPA70 and its analog SJB7, which unexpectedly is an agonist. Here, we describe another unexpected observation: mutating a single residue (W299A) within the PXR ligand-binding domain converts SPA70 to an agonist. After characterizing wild-type and W299A PXR activity profiles, we used molecular dynamics simulations to reveal that in wild-type PXR, agonists stabilize the activation function 2 (AF-2) helix in an "inward" position, but SPA70 displaces the AF-2. In W299A, however, SPA70 stabilizes the AF-2 "inward", like agonists. We validated our model by predicting the antagonist SJC2 to be a W299A agonist, which was confirmed experimentally. Our work correlates previously unobserved ligand-induced conformational changes to PXR cellular activity and, for the first time, reveals how PXR antagonists work.

The constitutive androstane receptor (CAR) and pregnane X receptor (PXR) are xenobiotic sensors that regulate the expression of drug-metabolizing enzymes and efflux transporters. CAR activation promotes drug elimination, thereby reducing therapeutic effectiveness, or causes adverse drug effects via toxic metabolites. CAR inhibitors could be used to attenuate these adverse drug effects. CAR and PXR share ligands and target genes, confounding the understanding of the regulation of receptor-specific activity. We previously identified a small-molecule inhibitor, CINPA1, that inhibits CAR (without activating PXR at lower concentrations) by altering CAR-coregulator interactions and reducing CAR recruitment to DNA response elements of regulated genes. However, solid evidence was not presented for the direct binding of CINPA1 to CAR. In this study, we demonstrate direct interaction of CINPA1 with the CAR ligand-binding domain (CAR-LBD) and identify key residues involved in such interactions through a combination of biophysical and computational methods. We found that CINPA1 resides in the ligand-binding pocket to stabilize the CAR-LBD in a more rigid, less fluid state. Molecular dynamics simulations, together with our previously reported docking model, enabled us to predict which CAR residues were critical for interactions with CINPA1. The importance of these residues for CINPA1 binding were then validated by directed mutations and testing the mutant CAR proteins in transcription reporter and coregulatory interaction assays. We demonstrated strong hydrogen bonding of CINPA1 with N165 and H203 and identified other residues involved in hydrophobic contacts with CINPA1. Overall, our data confirm that CINPA1 directly binds to CAR.

Background Cancer cells use several mechanisms to resist the cytotoxic effects of drugs, resulting in tumor progression and invasion. One such mechanism capitalizes on the body's natural defense against xenobiotics by increasing the rate of xenobiotic efflux and metabolic inactivation. Xenobiotic metabolism typically involves conversion of parent molecules to more soluble and easily excreted derivatives in reactions catalyzed by Phase I and Phase II drug metabolizing enzymes. Methods We performed a structured search of peer-reviewed literature on P450 (CYP) 3A, with a focus on CYP3A4 and CYP3A5. Results Recent reports indicate that components of the xenobiotic response system are upregulated in some diseases, including many cancers. Such components include the pregnane X receptor (PXR), CYP3A4 and CYP3A5 enzymes. The CYP3A enzymes are a subset of the numerous enzymes that are transcriptionally activated following the interaction of PXR and many ligands. Conclusion Intense research is ongoing to understand the functional ramifications of aberrant expression of these components in diseased states with the goal of designing novel drugs that can selectively target them.

Muscle differentiation is a complex process in which muscle progenitor cells undergo determination and eventually cellular fusion. This process is heavily regulated by such master transcription factors as MYOD and members of the MEF2 family. Here, we show that the transcription factor ZNF148 plays a direct role in human muscle cell differentiation. Downregulation of ZNF148 drives the formation of a muscle phenotype with rapid expression of myosin heavy chain, even in proliferative conditions. This phenotype was most likely mediated by the robust and swift upregulation of MYOD and MEF2C.

Pregnane X receptor (PXR) is a ligand-activated nuclear receptor that was originally identified as a master regulator of xenobiotic detoxification. It regulates the expression of drug-metabolizing enzymes and transporters to control the degradation and excretion of endobiotics and xenobiotics, including therapeutic agents. The metabolism and disposition of drugs might compromise their efficacy and possibly cause drug toxicity and/or drug resistance. Because many drugs can promiscuously bind and activate PXR, PXR antagonists might have therapeutic value in preventing and overcoming drug-induced PXR-mediated drug toxicity and drug resistance. Furthermore, PXR is now known to have broader cellular functions, including the regulation of cell proliferation and glucose and lipid metabolism. Thus, PXR might be involved in human diseases such as cancer and metabolic diseases. The importance of PXR antagonists is discussed in the context of the role of PXR in xenobiotic sensing and other disease-related pathways. This review focuses on the development of PXR antagonists, which has been hampered by the promiscuity of PXR ligand binding. However, substantial progress has been made in recent years, suggesting that it is feasible to develop selective PXR antagonists. We discuss the current status, challenges, and the strategies in developing selective PXR antagonists. The strategies are based on the molecular mechanisms of antagonism in related nuclear receptors that can be applied to the design of PXR antagonists, primarily driven by structural information.

The pregnane X receptor (PXR) is a principal xenobiotic receptor crucial in the detection, detoxification, and clearance of toxic substances from the body. PXR plays a vital role in the metabolism and disposition of drugs, and elevated PXR levels contribute to cancer drug resistance. Therefore, to modulate PXR activity and mitigate drug resistance, it is imperative to fully understand its regulation. To this end, we screened a transcription factor siRNA library in pancreatic cancer cells that express high levels of PXR. Through a comprehensive deconvolution process, we identified N-alpha-acetyltransferase 10 (NAA10) as a factor in the transcriptional machinery regulating PXR transcription. Because no one single factor has 100% operational control of PXR transcriptional regulation, our results together with other previous findings suggest that the transcriptional regulation of PXR is complex and that multiple factors contribute to the process including NAA10.

Willow Break LLC is a 3,370 acre (1,364 hectare) property located near Redwood, Mississippi. The main objective is to provide family-oriented outdoor recreation, primarily hunting for multiple game species. A secondary objective is to provide revenue through provision of environmental services. The forests consist of mixed, naturally regenerated hardwoods and hardwood plantations established under the Wetland Reserve Program of the U.S. Department of Agriculture. The long-term management goal is to provide optimal wildlife habitat by creating desired forest conditions as established by the Lower Mississippi Valley Joint Venture Forest Resource Conservation Working Group. This will require converting the current predominantly single-aged forest to a multi-aged, mixed hardwood forest over a 40-year planning horizon. This chapter describes the approach that was taken in the development of the plan for the property and the management prescriptions that were designed for the forested areas.

SummaryConcordance of polymorphic enzyme phenotypes in various comparisons of human normal and malignant cells in vitro and in vivo establishes isozyme stability after change to the malignant state and after long-term tissue culture. Such enzymes, therefore, can be used with considerable confidence to individually distinguish human tumor cell lines. The stability validates the use of phenotype frequency data obtained from surveys of normal human populations in the analysis of data on human tumor cell lines.We gratefully acknowledge the collaboration of Dr. Francis E. Sharkey and the Department of Pathology, Memorial Hospital, New York, for providing tissue specimens.

Numerous cell lines derived from human tumors are not HeLa contaminants. Of 192 lines established in this or other laboratories, 169 lines were found to be G6PD type B. Twenty-three lines were type A as HeLa; three of these were of Negroid origin. There is reasonable doubt that the remaining 20 lines will all be shown to be confounded with HeLa.

Eight of approximately 100 cell lines derived at the Scott and White Clinic from human solid tumors were found to have the same phenotypes when analyzed for 15 polymorphic enzymes at the Sloan-Kettering Institute for Cancer Research. These data were confirmed at the M. D. Anderson Hospital and Tumor Institute. The similarity was supported by cytogenetic studies at both institutions. The chronology of the establishment of these cell lines and isoenzyme and cytogenetic studies indicated that six of these lines have cross cell contamination. These include SW-527 and SW-613 mammary carcinomas, SW-598 meningioma, SW-608 astrocytoma, SW-732 cervix carcinoma, and SW-733 bladder carcinoma. Our data supported the authenticity of SW-480 and SW-620, which were derived from a colon carcinoma and its metastasis, respectively, from the same patient.

Previous studies have established that leukocyte phagocytosis and intracellular killing are normal in term and low-birthweight newborns who are well. To determine the effect of stress or illness on newborn leukocyte function, the phagocytic and bactericidal activity of leukocytes from 40 sick newborns was compared with that of leukocytes from 12 newborns and 23 normal adults. To eliminate abnormal phagocytosis resulting from serum opsonic defects in newborn sera, pooled adult sera were used in all assays. Twenty-five of the 40 stressed newborns (63%) had decreased in vitro activity against either Staphylococcus aureus 502A or Escherichia coli, or both, compared with decreased activity in two of 12 well infants (17%) and in four of 23 adult controls (17%). The mean bactericidal activity (percentage of organisms killed after two hours) of leukocytes from stressed newborns against S. aureus (83% ± 2 [SEM]) and E. coli (87% ± 4 [SEM]) was significantly less than in the combined well infant and adult control group (94% ± 1 for S. aureus and 97% ± .5 for E. coli). Although the more severely ill infants had an increased incidence of impaired antibacterial activity, the degree of impairment was not related to the severity of illness. No consistent relationship of decreased activity to birthweight, gestational age, age when studied, or specific diagnosis was seen. The leukocyte abnormality in stressed infants against S. aureus was principally a killing defect, while against E. coil both phagocytosis and killing were abnormal. This study indicates that a wide variety of neonatal disorders may affect one or more of the steps required for normal bacterial killing. The lability of leukocytic antibacterial function under stress is an additional mechanism for the newborn's increased susceptibility to infection.

The clinical and immunologic features of six patients with combined immunodeficiency with immunoglobulins are presented and are compared with 28 previously reported cases. Although the pathologic findings of these (thymic dysplasia with absence of Hassall's corpuscles and lymphoid hypoplasia and poor corticomedullarly differentiation) resemble those of severe combined immunodeficiency, there are sufficient features to characterize them as a distinct syndrome. Characteristic features are gradual onset, variable course, prolonged survival, lymphopenia with impaired cellular immunity, the presence of immunoglobulins and plasma cells, but with impaired antibody synthesis. We therefore feel that these cases can be recognized as a distinct primary immunodeficiency using the nomenclature cellular immunodeficiency with immunoglobulins.

A large collection of cultured human tumor cell lines was characterized for the phenotypes of 16 polymorphic enzyme loci: ACP1, ADA, AK1, ESD, FUCA, GLO1, GOT2, G6PD, ME2, PEPA, PEPB, PEPC, PEPD, PGD, PGM1, and PGM3 primarily to detect and monitor against cell line contamination. Among 100 highly characterized cell lines, 59 lines from different patients and 6 pairs of lines (each pair from the same patient's tumor) had unique phenotype combinations and were therefore presumed to be authentic, uncontaminated cell lines. Besides these 71 lines, the remaining 29 lines consisted of several small groups of two to three lines, each group having a different combination and being among the more frequent in the normal population. The 29 lines, therefore, were not suspected to be contaminants. Among unusual findings were the ME2 1 plus 2 phenotype determined for two bladder tumor lines, a G6PD A phenotype found in a line of Caucasian origin determined not to be a HeLa contaminant, and asymmetrical heterozygous phenotypes in several lines. Except for kidney tumor lines, there was no correlation of adenosine deaminase tissue isoenzymes between tumor lines and normal tissues of origin. For several enzymes significant deviations were found in proportions of the phenotypes observed in Caucasian cell lines from expected proportions on the basis of normal population data, indicating possible natural selection among these lines in tissue culture or among the patients of origin.

Publisher Summary The chapter discusses microelectrophoresis of enzymes in animal cell colonies. The starch gel microelectrophoresis includes potato starch gels that are extensively and successfully used as an anticonvection and molecular sieving matrix for the electrophoresis of many enzymes. The chapter presents an overview of the demonstration of microelectrophoresis, which was carried out as part of a human tumor cell line characterization project in the laboratory of Jorgen Fogh, Sloan-Kettering Institute, New York, N.Y. Thin strips of cellulose acetate in the nongel form and in the technically preferred gel form (Cellogel) are used for the electrophoresis of enzymes in macrosamples. The chapter discusses polyacrylamide gel microelectrophoresis and microelectrophoresis of single cells. Microelectrophoresis is more likely with microsamples having high concentrations of enzyme activity which can be achieved by harvesting cells in as small a volume as possible, storing samples at –20 to –80 o C until used, reducing the time required for electrophoresis by increasing voltages while maintaining adequate cooling, and increasing the sensitivity of the specific enzyme stains.

A new calculation of the relative efficiency of polymorphic enzyme markers, called the REB, was determined and compared with one of Fisher's determinations of the relative efficiency called REA here. The REA estimates the chance of failing, and 1-REA of succeeding, to show a phenotypic difference between two randomly selected persons or cultured cell lines (Case 1). In this study it was shown that the REA also estimates the chance of detecting a cell line mislabeling or similar mixup (Case 2) and a cell line cross-contamination leading to the complete replacement of an original line by contaminating line (Case 3). The new REB determines the probability of failing, and 1 - REB of succeeding, to detect a contamination of an original line by another line leading to their coexistence, or at least a sufficiently long period of transitional coexistence before one overgrows the other. The REA and REB also apply to determining the efficiency of polymorphic markers in detecting donor and recipient cells in tissue transplants.

At Temple University Hospital we insist that all infections be reported promptly to the hospital administrator or some similarly central person. This obtains recognition of the true state of affairs, which is not admitted by some and not recognized by others. Adherence can be obtained from certain reluctant staff members by holding the resident responsible for reporting. Residents usually have sufficient respect for authority to adhere to the rules. The department of bacteriology is one of the best sources for reporting infections. We appointed a committee made up of a chairman from general surgery, Dr. H. Taylor Caswell, and representatives from each surgical specialty, from pediatrics, anesthesiology, bacteriology, nursing, and medicine. They meet weekly, receive reports of infections from the administrator and the department of bacteriology, investigate each case, and make recommendations for conduct of hospital procedures, changes, etc. They are thus able to watch progress and to assess the