Patient-derived models recapitulate heterogeneity of molecular signatures and drug response in pediatric high-grade glioma

Pediatric high-grade glioma (pHGG) is a major contributor to cancer-related death in children. In vitro and in vivo disease models reflecting the intimate connection between developmental context and pathogenesis of pHGG are essential to advance understanding and identify therapeutic vulnerabilities. Here we report establishment of 21 patient-derived pHGG orthotopic xenograft (PDOX) models and eight matched cell lines from diverse groups of pHGG. These models recapitulate histopathology, DNA methylation signatures, mutations and gene expression patterns of the patient tumors from which they were derived, and include rare subgroups not well-represented by existing models. We deploy 16 new and existing cell lines for high-throughput screening (HTS). In vitro HTS results predict variable in vivo response to PI3K/mTOR and MEK pathway inhibitors. These unique new models and an online interactive data portal for exploration of associated detailed molecular characterization and HTS chemical sensitivity data provide a rich resource for pediatric brain tumor research.

An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability in response to targeted therapies is well known. The existence of additional genomic alterations among tumor cells can only partially explain this variability. As such, nongenetic factors are increasingly seen as critical contributors to tumor relapse and acquired resistance in cancer. Here, we show that both genetic and nongenetic factors contribute to targeted drug response variability in an experimental model of tumor heterogeneity. We observe significant variability to epidermal growth factor receptor (EGFR) inhibition among and within multiple versions and clonal sublines of PC9, a commonly used EGFR mutant nonsmall cell lung cancer (NSCLC) cell line. We resolve genetic, epigenetic, and stochastic components of this variability using a theoretical framework in which distinct genetic states give rise to multiple epigenetic "basins of attraction," across which cells can transition driven by stochastic noise. Using mutational impact analysis, single-cell differential gene expression, and correlations among Gene Ontology (GO) terms to connect genomics to transcriptomics, we establish a baseline for genetic differences driving drug response variability among PC9 cell line versions. Applying the same approach to clonal sublines, we conclude that drug response variability in all but one of the sublines is due to epigenetic differences; in the other, it is due to genetic alterations. Finally, using a clonal drug response assay together with stochastic simulations, we attribute subclonal drug response variability within sublines to stochastic cell fate decisions and confirm that one subline likely contains genetic resistance mutations that emerged in the absence of drug treatment.

Evolutionary dynamics at the tumor edge reveal metabolic imaging biomarkers

Human cancers are biologically and morphologically heterogeneous. A variety of clonal populations emerge within these neoplasms and their interaction leads to complex spatiotemporal dynamics during tumor growth. We studied the reshaping of metabolic activity in human cancers by means of continuous and discrete mathematical models and matched the results to positron emission tomography (PET) imaging data. Our models revealed that the location of increasingly active proliferative cellular spots progressively drifted from the center of the tumor to the periphery, as a result of the competition between gradually more aggressive phenotypes. This computational finding led to the development of a metric, normalized distance from 18F-fluorodeoxyglucose (18F-FDG) hotspot to centroid (NHOC), based on the separation from the location of the activity (proliferation) hotspot to the tumor centroid. The NHOC metric can be computed for patients using 18F-FDG PET-computed tomography (PET/CT) images where the voxel of maximum uptake (standardized uptake value [SUV]max) is taken as the activity hotspot. Two datasets of 18F-FDG PET/CT images were collected, one from 61 breast cancer patients and another from 161 non-small-cell lung cancer patients. In both cohorts, survival analyses were carried out for the NHOC and for other classical PET/CT-based biomarkers, finding that the former had a high prognostic value, outperforming the latter. In summary, our work offers additional insights into the evolutionary mechanisms behind tumor progression, provides a different PET/CT-based biomarker, and reveals that an activity hotspot closer to the tumor periphery is associated to a worst patient outcome.

Colorectal Cancer Cells Enter a Diapause-like DTP State to Survive Chemotherapy

Cancer cells enter a reversible drug-tolerant persister (DTP) state to evade death from chemotherapy and targeted agents. It is increasingly appreciated that DTPs are important drivers of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer models to identify and characterize DTPs in response to chemotherapy. Barcode analysis revealed no loss of clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fit a mathematical model where all cancer cells, and not a small subpopulation, possess an equipotent capacity to become DTPs. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides insight into how cancer cells use a developmentally conserved mechanism to drive the DTP state, pointing to novel therapeutic opportunities to target DTPs.

Single-cell RNA sequencing reveals a heterogeneous response to Glucocorticoids in breast cancer cells

Steroid hormone receptors such as the Glucocorticoid Receptor (GR) mediate transcriptional responses to hormones and are frequently targeted in the treatment of human diseases. Experiments using bulk populations of cells have provided a detailed picture of the global transcriptional hormone response but are unable to interrogate cell-to-cell transcriptional heterogeneity. To examine the glucocorticoid response in individual cells, we performed single cell RNA sequencing (scRNAseq) in a human breast cancer cell line. The transcriptional response to hormone was robustly detected in individual cells and scRNAseq provided additional statistical power to identify over 100 GR-regulated genes that were not detected in bulk RNAseq. scRNAseq revealed striking cell-to-cell variability in the hormone response. On average, individual hormone-treated cells showed a response at only 30% of the total set of GR target genes. Understanding the basis of this heterogeneity will be critical for the development of more precise models of steroid hormone signaling.

Ribosomal heterogeneity - A new inroad for pharmacological innovation

The paradigm of ribosome usage in protein translation has shifted from a stance proposed as scientists began to unpick the genetic code that each mRNA was partnered by its own, unique ribosome to a rapid reversal of this view that ribosomes are completely interchangeable and simply recruited to mRNAs from a completely homogenous cellular pool. Evidence that the ribosomal proteome, ribosomal gene transcriptome and ribosome protein and RNA modifications differ between cells and tissues points to the fact that ribosomes are heterogeneous in their composition and have a degree of specialisation in their function. It has also been posited that the tissue-specificity of ribosome diseases provides an indication of functional ribosome heterogeneity, but there are substantial caveats to this interpretation. Only now have proteomic technologies developed to a level enabling accurate stoichiometric comparison of the abundance of specific ribosomal proteins in actively translating ribosomes and to measure protein in non-denatured ribosomes. This poises the field for the provocation that ribosome heterogeneity offers a novel and powerful inroad for the pharmacological targeting of disease. Such ribosome-targeted treatments may extend beyond specific ribosomopathies through strategies such as targeting features of ribosomes that are unique to diseased cells, particularly cancer cells, or to activated immune cells, as well as augmenting the action of other drugs through weakening the production of new proteins in target tissues. We may also be able to harness the potential power in ribosome diversity and specialism to better tune synthetic biology for the production of pharmaceutical proteins.

Heterogeneity and dynamics of active Kras-induced dysplastic lineages from mouse corpus stomach

Dysplasia is considered a key transition state between pre-cancer and cancer in gastric carcinogenesis. However, the cellular or phenotypic heterogeneity and mechanisms of dysplasia progression have not been elucidated. We have established metaplastic and dysplastic organoid lines, derived from Mist1-Kras(G12D) mouse stomach corpus and studied distinct cellular behaviors and characteristics of metaplastic and dysplastic organoids. We also examined functional roles for Kras activation in dysplasia progression using Selumetinib, a MEK inhibitor, which is a downstream mediator of Kras signaling. Here, we report that dysplastic organoids die or show altered cellular behaviors and diminished aggressive behavior in response to MEK inhibition. However, the organoids surviving after MEK inhibition maintain cellular heterogeneity. Two dysplastic stem cell (DSC) populations are also identified in dysplastic cells, which exhibited different clonogenic potentials. Therefore, Kras activation controls cellular dynamics and progression to dysplasia, and DSCs might contribute to cellular heterogeneity in dysplastic cell lineages.

Characterizing smoking-induced transcriptional heterogeneity in the human bronchial epithelium at single-cell resolution

The human bronchial epithelium is composed of multiple distinct cell types that cooperate to defend against environmental insults. While studies have shown that smoking alters bronchial epithelial function and morphology, its precise effects on specific cell types and overall tissue composition are unclear. We used single-cell RNA sequencing to profile bronchial epithelial cells from six never and six current smokers. Unsupervised analyses led to the characterization of a set of toxin metabolism genes that localized to smoker ciliated cells, tissue remodeling associated with a loss of club cells and extensive goblet cell hyperplasia, and a previously unidentified peri-goblet epithelial subpopulation in smokers who expressed a marker of bronchial premalignant lesions. Our data demonstrate that smoke exposure drives a complex landscape of cellular alterations that may prime the human bronchial epithelium for disease.

Dissecting heterogeneity in malignant pleural mesothelioma through histo-molecular gradients for clinical applications

Malignant pleural mesothelioma (MPM) is recognized as heterogeneous based both on histology and molecular profiling. Histology addresses inter-tumor and intra-tumor heterogeneity in MPM and describes three major types: epithelioid, sarcomatoid and biphasic, a combination of the former two types. Molecular profiling studies have not addressed intra-tumor heterogeneity in MPM to date. Here, we use a deconvolution approach and show that molecular gradients shed new light on the intra-tumor heterogeneity of MPM, leading to a reconsideration of MPM molecular classifications. We show that each tumor can be decomposed as a combination of epithelioid-like and sarcomatoid-like components whose proportions are highly associated with the prognosis. Moreover, we show that this more subtle way of characterizing MPM heterogeneity provides a better understanding of the underlying oncogenic pathways and the related epigenetic regulation and immune and stromal contexts. We discuss the implications of these findings for guiding therapeutic strategies, particularly immunotherapies and targeted therapies.

Mechanisms of acquired resistance to rapalogs in metastatic renal cell carcinoma

The mechanistic target of rapamycin (mTOR) is an established therapeutic target in renal cell carcinoma (RCC). Mechanisms of secondary resistance to rapalog therapy in RCC have not been studied previously. We identified six patients with metastatic RCC who initially responded to mTOR inhibitor therapy and then progressed, and had pre-treatment and post-treatment tumor samples available for analysis. We performed deep whole exome sequencing on the paired tumor samples and a blood sample. Sequence data was analyzed using Mutect, CapSeg, Absolute, and Phylogic to identify mutations, copy number changes, and their changes over time. We also performed in vitro functional assays on PBRM1 in RCC cell lines. Five patients had clear cell and one had chromophobe RCC. 434 somatic mutations in 416 genes were identified in the 12 tumor samples. 201 (46%) of mutations were clonal in both samples while 129 (30%) were acquired in the post-treatment samples. Tumor heterogeneity or sampling issues are likely to account for some mutations that were acquired in the post-treatment samples. Three samples had mutations in TSC1; one in PTEN; and none in MTOR. PBRM1 was the only gene in which mutations were acquired in more than one post-treatment sample. We examined the effect of PBRM1 loss in multiple RCC cell lines, and could not identify any effect on rapalog sensitivity in in vitro culture assays. We conclude that mTOR pathway gene mutations did not contribute to rapalog resistance development in these six patients with advanced RCC. Furthermore, mechanisms of resistance to rapalogs in RCC remain unclear and our results suggest that PBRM1 loss may contribute to sensitivity through complex transcriptional effects.

Mammalian target of rapamycin (mTOR) inhibitors, everolimus and temsirolimus, are FDA-approved for treatment of metastatic renal cell carcinoma (mRCC), but molecular mechanisms of acquired or secondary resistance to these agents are unknown. We evaluated six mRCC patients with available pre-treatment specimens who were treated with mTOR inhibitors and had a good clinical outcome, and then had a second biopsy at the time of resistance. We found that mutations in PBRM1 appeared to be enriched in post-treatment samples. However, modulation of PBRM1 levels in vitro in cell lines had no apparent effect on rapalog sensitivity. We conclude that mechanisms of resistance to rapalog therapy in RCC are not easily explained by gene mutations in most cases, and may depend on more subtle transcriptional and/or epigenetic changes.

Tumor-stroma interactions differentially alter drug sensitivity based on the origin of stromal cells

Due to tumor heterogeneity, most believe that effective treatments should be tailored to the features of an individual tumor or tumor subclass. It is still unclear, however, what information should be considered for optimal disease stratification, and most prior work focuses on tumor genomics. Here, we focus on the tumor microenvironment. Using a large-scale coculture assay optimized to measure drug-induced cell death, we identify tumor-stroma interactions that modulate drug sensitivity. Our data show that the chemo-insensitivity typically associated with aggressive subtypes of breast cancer is not observed if these cells are grown in 2D or 3D monoculture, but is manifested when these cells are cocultured with stromal cells, such as fibroblasts. Furthermore, we find that fibroblasts influence drug responses in two distinct and divergent manners, associated with the tissue from which the fibroblasts were harvested. These divergent phenotypes occur regardless of the drug tested and result from modulation of apoptotic priming within tumor cells. Our study highlights unexpected diversity in tumor-stroma interactions, and we reveal new principles that dictate how fibroblasts alter tumor drug responses.

IsomiR processing during differentiation of myelogenous leukemic cell line K562 by phorbol ester PMA

Chronic myelocytic leukemia cell line K562 undergoes differentiation by phorbol esters to megakaryocytes and we have used this system to understand miRNA processing leading to isomiR generation. PMA treatment significantly altered the production of miRNA in K562 cells. Expression of 24.4% of miRNAs were found to be stimulated whereas expression of 10% miRNAs were inhibited by PMA treatment. Our results suggest that miRNA precursors are processed into isomiRs in a deterministic manner. The relative levels of different isomiRs of a miRNA remained mainly unchanged even after PMA treatment irrespective of overall changes in expression (either up-regulation or down-regulation). However, not all miRNAs behave in the same way, about 7% showed a variation of isomiR profiles after PMA treatment. Most of the later class of miRNAs were found to be oncogenic miRNAs. Further, it was also found that number of isomiRs was independent of abundance of a miRNA. Functional importance of different isomiRs was demonstrated using three different isomiRs of miR-22. Our results showed that different isomiRs could inhibit expression of targets genes with different efficiencies. Our study suggests that the heterogeneity of a miRNA population generated during processing is in general regulated and that variation in the generation of an isomiR can be a functionally important regulatory feature.

The temporal dynamics of chromosome instability in ovarian cancer cell lines and primary patient samples

Epithelial ovarian cancer (EOC) is the most prevalent form of ovarian cancer and has the highest mortality rate. Novel insight into EOC is required to minimize the morbidity and mortality rates caused by recurrent, drug resistant disease. Although numerous studies have evaluated genome instability in EOC, none have addressed the putative role chromosome instability (CIN) has in disease progression and drug resistance. CIN is defined as an increase in the rate at which whole chromosomes or large parts thereof are gained or lost, and can only be evaluated using approaches capable of characterizing genetic or chromosomal heterogeneity within populations of cells. Although CIN is associated with numerous cancer types, its prevalence and dynamics in EOC is unknown. In this study, we assessed CIN within serial samples collected from the ascites of five EOC patients, and in two well-established ovarian cancer cell models of drug resistance (PEO1/4 and A2780s/cp). We quantified and compared CIN (as measured by nuclear areas and CIN Score (CS) values) within and between serial samples to glean insight into the association and dynamics of CIN within EOC, with a particular focus on resistant and recurrent disease. Using quantitative, single cell analyses we determined that CIN is associated with every sample evaluated and further show that many EOC samples exhibit a large degree of nuclear size and CS value heterogeneity. We also show that CIN is dynamic and generally increases within resistant disease. Finally, we show that both drug resistance models (PEO1/4 and A2780s/cp) exhibit heterogeneity, albeit to a much lesser extent. Surprisingly, the two cell line models exhibit remarkably similar levels of CIN, as the nuclear areas and CS values are largely overlapping between the corresponding paired lines. Accordingly, these data suggest CIN may represent a novel biomarker capable of monitoring changes in EOC progression associated with drug resistance.

Reduced genomic tumor heterogeneity after neoadjuvant chemotherapy is related to favorable outcome in patients with esophageal adenocarcinoma

Neoadjuvant chemo(radio)therapy followed by surgery is the standard of care for patients with locally advanced resectable esophageal adenocarcinoma (EAC). There is increasing evidence that drug resistance might be related to genomic heterogeneity. We investigated whether genomic tumor heterogeneity is different after cytotoxic chemotherapy and is associated with EAC patient survival. We used arrayCGH and a quantitative assessment of the whole genome DNA copy number aberration patterns ('DNA copy number entropy') to establish the level of genomic tumor heterogeneity in 80 EAC treated with neoadjuvant chemotherapy followed by surgery (CS group) or surgery alone (S group). The association between DNA copy number entropy, clinicopathological variables and survival was investigated.DNA copy number entropy was reduced after chemotherapy, even if there was no morphological evidence of response to therapy (p<0.001). Low DNA copy number entropy was associated with improved survival in the CS group (p=0.011) but not in the S group (p=0.396).Our results suggest that cytotoxic chemotherapy reduces DNA copy number entropy, which might be a more sensitive tumor response marker than changes in the morphological tumor phenotype. The use of DNA copy number entropy in clinical practice will require validation of our results in a prospective study.

A multi-targeted approach to suppress tumor-promoting inflammation

Cancers harbor significant genetic heterogeneity and patterns of relapse following many therapies are due to evolved resistance to treatment. While efforts have been made to combine targeted therapies, significant levels of toxicity have stymied efforts to effectively treat cancer with multi-drug combinations using currently approved therapeutics. We discuss the relationship between tumor-promoting inflammation and cancer as part of a larger effort to develop a broad-spectrum therapeutic approach aimed at a wide range of targets to address this heterogeneity. Specifically, macrophage migration inhibitory factor, cyclooxygenase-2, transcription factor nuclear factor-κB, tumor necrosis factor alpha, inducible nitric oxide synthase, protein kinase B, and CXC chemokines are reviewed as important antiinflammatory targets while curcumin, resveratrol, epigallocatechin gallate, genistein, lycopene, and anthocyanins are reviewed as low-cost, low toxicity means by which these targets might all be reached simultaneously. Future translational work will need to assess the resulting synergies of rationally designed antiinflammatory mixtures (employing low-toxicity constituents), and then combine this with similar approaches targeting the most important pathways across the range of cancer hallmark phenotypes.

Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity

Cancer therapy exerts a strong selection pressure that shapes tumor evolution, yet our knowledge of how tumors change during treatment is limited. Here, we report the analysis of cellular heterogeneity for genetic and phenotypic features and their spatial distribution in breast tumors pre- and post-neoadjuvant chemotherapy. We found that intratumor genetic diversity was tumor-subtype specific, and it did not change during treatment in tumors with partial or no response. However, lower pretreatment genetic diversity was significantly associated with pathologic complete response. In contrast, phenotypic diversity was different between pre- and posttreatment samples. We also observed significant changes in the spatial distribution of cells with distinct genetic and phenotypic features. We used these experimental data to develop a stochastic computational model to infer tumor growth patterns and evolutionary dynamics. Our results highlight the importance of integrated analysis of genotypes and phenotypes of single cells in intact tissues to predict tumor evolution.

Intratumor heterogeneity and branched evolution revealed by multiregion sequencing

BACKGROUND

Intratumor heterogeneity may foster tumor evolution and adaptation and hinder personalized-medicine strategies that depend on results from single tumor-biopsy samples.

METHODS

To examine intratumor heterogeneity, we performed exome sequencing, chromosome aberration analysis, and ploidy profiling on multiple spatially separated samples obtained from primary renal carcinomas and associated metastatic sites. We characterized the consequences of intratumor heterogeneity using immunohistochemical analysis, mutation functional analysis, and profiling of messenger RNA expression.

RESULTS

Phylogenetic reconstruction revealed branched evolutionary tumor growth, with 63 to 69% of all somatic mutations not detectable across every tumor region. Intratumor heterogeneity was observed for a mutation within an autoinhibitory domain of the mammalian target of rapamycin (mTOR) kinase, correlating with S6 and 4EBP phosphorylation in vivo and constitutive activation of mTOR kinase activity in vitro. Mutational intratumor heterogeneity was seen for multiple tumor-suppressor genes converging on loss of function; SETD2, PTEN, and KDM5C underwent multiple distinct and spatially separated inactivating mutations within a single tumor, suggesting convergent phenotypic evolution. Gene-expression signatures of good and poor prognosis were detected in different regions of the same tumor. Allelic composition and ploidy profiling analysis revealed extensive intratumor heterogeneity, with 26 of 30 tumor samples from four tumors harboring divergent allelic-imbalance profiles and with ploidy heterogeneity in two of four tumors.

CONCLUSIONS

Intratumor heterogeneity can lead to underestimation of the tumor genomics landscape portrayed from single tumor-biopsy samples and may present major challenges to personalized-medicine and biomarker development. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation and therapeutic failure through Darwinian selection. (Funded by the Medical Research Council and others.).

[Possibilities and limitations of stratified medicine based on biomarkers and targeted therapies in oncology]

Research over the past two decades has untangled the molecular heterogeneity of cancer at the cellular level. The molecular techniques that have been developed in the past 5 to 10 years are dramatically improving our understanding of the genomic aberrations that underlie the malignant transformation of normal cells. At the same time, however, advances in our understanding of the genetic basis of solid tumours and hematologic malignancies have revealed how complex cancer is, and consequently how much more challenging it is in many of the more common cancers to identify the right drug for the right patient in the adequate dose at the right time. Given the slow pace of translation from genome science to individualised medicine in oncology, this expert review, mainly taking into account recently published perspective articles and reviews, describes the molecular heterogeneity of cancer, the difficulties in developing novel molecularly targeted agents, and the need for developing biomarkers to optimise drug development and clinical use. Distinct types of biomarkers, breakthroughs as well as disappointments in the clinical implementation of biomarkers and targeted therapeutics into clinical practice are discussed by focusing on four targeted anti-cancer drugs. Finally, as clinical biomarker tests that predict response to particular therapies will play an important role in achieving stratified medicine in the near future, this article will conclude by giving some recommendations for effective biomarker evaluation and clinical trial designs for predictive biomarker validation.

Nordihydroguaiaretic acid and aspirin increase lifespan of genetically heterogeneous male mice

The National Institute on Aging's Interventions Testing Program was established to evaluate agents that are purported to increase lifespan and delay the appearance of age-related disease in genetically heterogeneous mice. Up to five compounds are added to the study each year and each compound is tested at three test sites (The Jackson Laboratory, University of Michigan, and University of Texas Health Science Center at San Antonio). Mice in the first cohort were exposed to one of four agents: aspirin, nitroflurbiprofen, 4-OH-alpha-phenyl-N-tert-butyl nitrone, or nordihydroguaiaretic acid (NDGA). Sample size was sufficient to detect a 10% difference in lifespan in either sex,with 80% power, using data from two of the three sites. Pooling data from all three sites, a log-rank test showed that both NDGA (p=0.0006) and aspirin (p=0.01) led to increased lifespan of male mice. Comparison of the proportion of live mice at the age of 90% mortality was used as a surrogate for measurement of maximum lifespan;neither NDGA (p=0.12) nor aspirin (p=0.16) had a significant effect in this test. Measures of blood levels of NDGA or aspirin and its salicylic acid metabolite suggest that the observed lack of effects of NDGA or aspirin on life span in females could be related to gender differences in drug disposition or metabolism. Further studies are warranted to find whether NDGA or aspirin, over a range of doses,might prove to postpone death and various age-related outcomes reproducibly in mice.

Functional heterogeneity of colony-stimulating factor-induced human monocyte-derived macrophages

Macrophages have various functions and play a critical role in host defense and the maintenance of homeostasis. However, macrophages are heterogeneous and exhibit a wide range of phenotypes with regard to their morphology, cell surface antigen expression, and function. When blood monocytes are cultured in medium alone in vitro, monocytes die, and colony-stimulating factors (CSFs) such as macrophage (M)-CSF or granulocyte-macrophage (GM)-CSF are necessary for their survival and differentiation into macrophages. However, M-CSF-induced monocyte-derived macrophages (M-Mphi) and GM-CSF-induced monocyte-derived macrophages (GM-Mphi) are distinct in their morphology, cell surface antigen expression, and functions, including Fcgamma receptor mediated-phagocytosis, H2O2 production, H2O2 sensitivity, catalase activity, susceptibility to human immunodeficiency virus type 1 and Mycobacterium tuberculosis, and suppressor activity. The characteristics of GM-Mphi resemble those of human alveolar macrophages.

Prevalence and genetic heterogeneity of the reverse transcriptase T69S-S-X insertion in pretreated HIV-infected patients

The emergence of resistance to antiretroviral drugs represents one of the main reasons for treatment failure in HIV-infected persons. Resistance to multiple nucleoside analogues may result from rearrangements in the HIV pol gene, in particular one insertion of two amino acids at position 69. Herein, we examined the prevalence of this resistant genotype and its genetic heterogeneity in a group of 475 healthy pretreated HIV-positive subjects in Spain. Only 4 (0.8%) carried the codon 69 insertion. It was always found coupled to the T69S mutation. The extra amino acids were S-S in 2 subjects and S-G in the other 2. The presence of the insert was seen only in subjects previously exposed to AZT monotherapy for at least 6 months.

Antimicrobial susceptibility test: from bacterial population analysis to therapy

The statistical methods and parameters commonly used to define bacterial susceptibility to antibiotics in vitro such as MIC(50), linear regression or others, usually lead to a considerable loss of information: they do not take into account the heterogeneity of the bacterial population. In contrast, multivariate data analyses are more adapted to the description of biological systems. In this way, a population of a given bacterial species can be separated into homogenous classes corresponding to the different sensitivity and resistance phenotypes. The applications of this mathematical approach include: (i) a new model for more relevant interpretation of antimicrobial susceptibility test results; (ii) numerical estimation of breakpoints having a known risk; (iii) calibration of a technique relative to a reference technique; (iv) detection of strains with new phenotypes; (v) in vitro evaluation of the activity of new compounds.

The multifactorial nature of hypertension: the greatest challenge for its treatment?

Essential hypertension is a polygenic disease involving a major contribution of various environmental factors. It is therefore not surprising that antihypertensive medications, whatever their mechanism(s) of action, only normalize the blood pressure for a fraction of hypertensive patients when administered as monotherapies. It is unfortunately not possible to predict with any degree of certainty which type of blood pressure-lowering agent is the most appropriate for a given patient. Although very attractive, genetic mapping is not really helpful in selecting a treatment for any individual patient. In most patients the association of two medications having different impacts on the cardiovascular system is necessary to normalize blood pressure. Fixed-low-dose combinations are becoming increasingly popular as first line treatment as they increase the probability of bringing the patient's blood pressure under control while minimizing the incidence of dose-dependent adverse effects.

Therapy-related chromosomal changes and cytogenetic heterogeneity in human gliomas

The karyotypes of 18 primary 'untreated' gliomas, 6 recurrent gliomas treated with radiotherapy and/or chemotherapy and 2 gliomas before and after treatment are described, based on observations using standard cytogenetic techniques. In comparison to the untreated gliomas there were relatively consistent chromosome differences in the treated gliomas, including (1) deletions of the long arm of chromosome 7 with breakpoint at q22, possibly induced by alkylating agents, and (2) numerous single cell abnormalities or unrelated clones of structural abnormalities, presumably induced by radiotherapy.