Abstract P2-11-07: Association of PIK3CA mutations with efficacy in HER2-positive first-line metastatic breast cancer: a meta-analysis

BACKGROUND: PIK3CA mutations have been shown to be associated with poor prognosis in HER2-positive breast cancer (BC). We combined data from three completed Phase III Roche-sponsored randomized trials of HER2-targeted therapy for the first-line treatment of HER2-positive metastatic BC (MBC); this allowed for exploration of the prognostic impact of PIK3CA mutations observed in the three individual trials across subgroups of interest.

METHODS: Data from CLEOPATRA (pertuzumab + trastuzumab + docetaxel [PHD] vs. placebo [Pla] + HD; NCT00567190; N = 808), MARIANNE (HD vs. ado-trastuzumab emtansine [K] + Pla vs. K + P; NCT01120184; N = 1095), and PUFFIN (PHD vs. Pla + HD; NCT02896855; N = 243) were included. An individual patient data (IPD) meta-analysis was performed to test the association between PIK3CA mutation status in tumor tissue (mutated vs. wild type [WT]) and efficacy (progression-free and overall survival [PFS/OS]) in different biomarker and clinical subgroups. Confounder adjustment was conducted for age, Eastern Cooperative Oncology Group Performance Status, body mass index, treatment, disease type, and number of metastases (all at baseline). “Study” was included as a random effect in the IPD meta-analysis model to account for variability between studies.

A landmark analysis was conducted on fast and non-fast progressors (cutoff of >137 days [i.e., after six chemotherapy cycles]) from CLEOPATRA and PUFFIN only, since they include the current standard-of-care regimens (PHD), by using Day 137 as the landmark time with separate Cox proportional hazards models.

RESULTS: PIK3CA mutation data were available for 1905/2146 patients (89%; ~80% from primary tissue); mutation prevalence was 27% (n = 521). PIK3CA-mutated vs. WT in association with PFS in pooled treatment arms is shown in the table. OS data were consistent.

CONCLUSIONS: PIK3CA mutations were associated with a worse prognosis across subgroups of interest, including in fast and non-fast progressors, in the two PHD-containing studies as compared with the overall ITT population.

Table: PIK3CA-mutated vs. WT in association with PFS in pooled treatment arms

Citation Format: Sandra Swain, Javier Cortés, Binghe Xu, Chiara Lambertini, Laurent Essioux, Adam Knott, Eleonora Restuccia, Katrin Madjar, Sanne Lysbet De Haas. Association of PIK3CA mutations with efficacy in HER2-positive first-line metastatic breast cancer: a meta-analysis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-11-07.

Baseline risk factors associated with immune related adverse events and atezolizumab

Background

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of cancer patients in the last decade, but immune-related adverse events (irAEs) pose significant clinical challenges. Despite advances in the management of these unique toxicities, there remains an unmet need to further characterize the patient-level drivers of irAEs in order to optimize the benefit/risk balance in patients receiving cancer immunotherapy.

Methods

An individual-patient data post-hoc meta-analysis was performed using data from 10,344 patients across 15 Roche sponsored clinical trials with atezolizumab in five different solid tumor types to assess the association between baseline risk factors and the time to onset of irAE. In this study, the overall analysis was conducted by treatment arm, indication, toxicity grade and irAE type, and the study design considered confounder adjustment to assess potential differences in risk factor profiles.

Results

This analysis demonstrates that the safety profile of atezolizumab is generally consistent across indications in the 15 studies evaluated. In addition, our findings corroborate with prior reviews which suggest that reported rates of irAEs with PD-(L)1 inhibitors are nominally lower than CTLA-4 inhibitors. In our analysis, there were no remarkable differences in the distribution of toxicity grades between indications, but some indication-specific differences regarding the type of irAE were seen across treatment arms, where pneumonitis mainly occurred in lung cancer, and hypothyroidism and rash had a higher prevalence in advanced renal cell carcinoma compared to all other indications. Results showed consistency of risk factors across indications and by toxicity grade. The strongest and most consistent risk factors were mostly organ-specific such as elevated liver enzymes for hepatitis and thyroid stimulating hormone (TSH) for thyroid toxicities. Another strong but non-organ-specific risk factor was ethnicity, which was associated with rash, hepatitis and pneumonitis. Further understanding the impact of ethnicity on ICI associated irAEs is considered as an area for future research.

Conclusions

Overall, this analysis demonstrated that atezolizumab safety profile is consistent across indications, is clinically distinguishable from comparator regimens without checkpoint inhibition, and in line with literature, seems to suggest a nominally lower reported rates of irAEs vs CTLA-4 inhibitors. This analysis demonstrates several risk factors for irAEs by indication, severity and location of irAE, and by patient ethnicity. Additionally, several potential irAE risk factors that have been published to date, such as demographic factors, liver enzymes, TSH and blood cell counts, are assessed in this large-scale meta-analysis, providing a more consistent picture of their relevance. However, given the small effects size, changes to clinical management of irAEs associated with the use of Anti-PDL1 therapy are not warranted.

Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on ∼150,000 individuals give a higher accuracy than LDSC estimates based on ∼400,000 individuals (from combined meta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.

Large-Scale Identification of Common Trait and Disease Variants Affecting Gene Expression

Genome-wide association studies (GWASs) have identified a multitude of genetic loci involved with traits and diseases. However, it is often unclear which genes are affected in such loci and whether the associated genetic variants lead to increased or decreased gene function. To mitigate this, we integrated associations of common genetic variants in 57 GWASs with 24 studies of expression quantitative trait loci (eQTLs) from a broad range of tissues by using a Mendelian randomization approach. We discovered a total of 3,484 instances of gene-trait-associated changes in expression at a false-discovery rate < 0.05. These genes were often not closest to the genetic variant and were primarily identified in eQTLs derived from pathophysiologically relevant tissues. For instance, genes with expression changes associated with lipid traits were mostly identified in the liver, and those associated with cardiovascular disease were identified in arterial tissue. The affected genes additionally point to biological processes implicated in the interrogated traits, such as the interleukin-27 pathway in rheumatoid arthritis. Further, comparing trait-associated gene expression changes across traits suggests that pleiotropy is a widespread phenomenon and points to specific instances of both agonistic and antagonistic pleiotropy. For instance, expression of SNX19 and ABCB9 is positively correlated with both the risk of schizophrenia and educational attainment. To facilitate interpretation, we provide this lexicon of how common trait-associated genetic variants alter gene expression in various tissues as the online database GWAS2Genes.

Current Status of Companion and Complementary Diagnostics: Strategic Considerations for Development and Launch

US Food and Drug Administration (FDA)‐approved diagnostic assays play an increasingly common role in managing patients to prolong lifespan while also enhancing quality of life. Diagnostic assays can be essential for the safe and effective use of therapeutics (companion diagnostic), or may inform on improving the benefit/risk ratio without restricting drug access (complementary diagnostic). This tutorial reviews strategic considerations for drug and assay development resulting in FDA‐approved companion or complementary diagnostic status.

Growth Differentiation Factor-15 and Risk of CKD Progression

Growth differentiation factor-15 (GDF-15) is a member of the TGF-β cytokine superfamily that is widely expressed and may be induced in response to tissue injury. Elevations in GDF-15 may identify a novel pathway involved in loss of kidney function among patients with CKD. Among participants in the Clinical Phenotyping and Resource Biobank (C-PROBE) study and the Seattle Kidney Study (SKS), we tested whether kidney tissue expression of GDF15 mRNA correlates with circulating levels of GDF-15 and whether elevations in circulating GDF-15 are associated with decline in kidney function. In matching samples of 24 patients with CKD from the C-PROBE study, circulating GDF-15 levels significantly correlated with intrarenal GDF15 transcript levels (r=0.54, P=0.01). Among the 224 C-PROBE and 297 SKS participants, 72 (32.1%) and 94 (32.0%) patients, respectively, reached a composite end point of 30% decline in eGFR or progression to ESRD over a median of 1.8 and 2.0 years of follow up, respectively. In multivariable models, after adjusting for potential confounders, every doubling of GDF-15 level associated with a 72% higher (95% confidence interval, 1.21 to 4.45; P=0.003) and 65% higher (95% confidence interval, 1.08 to 2.50; P=0.02) risk of progression of kidney disease in C-PROBE and SKS participants, respectively. These results show that circulating GDF-15 levels strongly correlated with intrarenal expression of GDF15 and significantly associated with increased risk of CKD progression in two independent cohorts. Circulating GDF-15 may be a marker for intrarenal GDF15-related signaling pathways associated with CKD and CKD progression.

Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker

Chronic kidney disease (CKD) affects 8 to 16% people worldwide, with an increasing incidence and prevalence of end-stage kidney disease (ESKD). The effective management of CKD is confounded by the inability to identify patients at high risk of progression while in early stages of CKD. To address this challenge, a renal biopsy transcriptome-driven approach was applied to develop noninvasive prognostic biomarkers for CKD progression. Expression of intrarenal transcripts was correlated with the baseline estimated glomerular filtration rate (eGFR) in 261 patients. Proteins encoded by eGFR-associated transcripts were tested in urine for association with renal tissue injury and baseline eGFR. The ability to predict CKD progression, defined as the composite of ESKD or 40% reduction of baseline eGFR, was then determined in three independent CKD cohorts. A panel of intrarenal transcripts, including epidermal growth factor (EGF), a tubule-specific protein critical for cell differentiation and regeneration, predicted eGFR. The amount of EGF protein in urine (uEGF) showed significant correlation (P < 0.001) with intrarenal EGF mRNA, interstitial fibrosis/tubular atrophy, eGFR, and rate of eGFR loss. Prediction of the composite renal end point by age, gender, eGFR, and albuminuria was significantly (P < 0.001) improved by addition of uEGF, with an increase of the C-statistic from 0.75 to 0.87. Outcome predictions were replicated in two independent CKD cohorts. Our approach identified uEGF as an independent risk predictor of CKD progression. Addition of uEGF to standard clinical parameters improved the prediction of disease events in diverse CKD populations with a wide spectrum of causes and stages.

Abstract 3944: Combining tumor glypican-3 expression and CD16 Expression on NK cells from peripheral blood to identify patients responding to codrituzumab/GC33/RO5137382

Background & Aims: Codrituzumab (GC33 or RO5137382), a monoclonal antibody targeting an oncofetal protein glypican-3 (GPC3) expressed on the cell surface of hepatocellular carcinoma (HCC), induces antibody-dependent cellular cytotoxicity (ADCC) and inhibits tumor growth in preclinical studies. Based on this mechanism of codrituzumab, two biomarkers GPC3 and CD16 of the NK cells, which are the effector cells of ADCC, were investigated to correlate with clinical efficacy of codrituzumab in patients with advanced HCC.

Methods: Data from a phase II clinical trial of codrituzumab were used for this analysis. GPC3 expression was determined by immunohistochemistry (IHC) analysis of tumor biopsies, and CD16 expression on NK cells were quantified by a flow cytometry analysis of peripheral blood mononuclear cells. Overall survival of patients with high exposure of codrituzumab or placebo (n = 113) was used to compare different patient subgroups stratified by high or low expression of GPC3 and CD16.

Results: In individual-biomarker analyses, longer survival after codrituzumab treatment correlates with either high expression level of GPC3 in tumors (n = 97, HR = 0.39, 95%CI = 0.21 - 0.70, p = 0.00081) or a relatively high level of CD16 expressed on NK cells (n = 80, HR = 0.44, 95%CI = 0.23 - 0.83, p = 0.0056) at baseline. Furthermore, joint analyses of the two biomarkers reveal that both high levels of GPC3 and CD16 are required for patients to benefit from codrituzumab treatment (n = 67, HR = 0.29, 95%CI = 0.13 - 0.62, p = 0.00074), and lack of either one of them leads to a loss of codrituzumab therapeutic effect.

Conclusions: The retrospective analysis supports the mechanism of ADCC, in which the combination of high GPC3 expression in tumors and high CD16 expression in NK cells from peripheral blood is associated with prolonged overall survival given treatment of codrituzumab. This result supports the usage of both GPC3 and CD16 as potential biomarkers to select HCC patients for codrituzumab treatment.

Citation Format: Gong Chen, Ya-Chi Chen, Bernhard Reis, Anton Belousov, Lori Jukofsky, Christine Rossin, Axel Muehlig, Chao Xu, Laurent Essioux, Toshihiko Ohtomo, Laura Di Laurenzio, Oscar Puig, Ray Lee. Combining tumor glypican-3 expression and CD16 Expression on NK cells from peripheral blood to identify patients responding to codrituzumab/GC33/RO5137382. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3944.

Drug Target Identification and Validation: Global Pharmaceutical Industry Experts on Challenges, Best Strategies, Innovative Precompetitive Collaboration Concepts, and Future Areas of Industry Precompetitive Research and Development

Focused interviews were conducted with global pharmaceutical company representatives in order to derive a consistent view on drug target identification/validation challenges, collaborative strategies, and future developments in a precompetitive space. Analysis revealed translation into clinical utility as a major hurdle of novel drug target validation, originating from lack of biological understanding, irreproducibility of published results, and lack of valid animal models. Direct and close collaborations with academia are the preferred model to tackle basic research on novel drug targets in high-risk projects. Efforts to conduct target identification in large precompetitive consortia are acknowledged with some doubts about the pace of progress and data-sharing policies, while concept to extend the precompetitive space to target validation in phase II trials was curtailed to niche indications together with a revision of current intellectual property (IP) practice. Public-private partnerships in established areas are forecasted to increase. Novel emerging themes are toxicology data sharing, joint genetic patient data analysis, and reimbursement concepts.

Combined Plasma and Cerebrospinal Fluid Signature for the Prediction of Midterm Progression From Mild Cognitive Impairment to Alzheimer Disease

Importance

A reliable method of detecting Alzheimer disease (AD) in its prodromal state is needed for patient stratification in clinical trials or for personalizing existing or potential upcoming therapies. Current cerebrospinal fluid (CSF)- or imaging-based single biomarkers for AD offer reliable identification of patients with underlying AD but insufficient prediction of the rate of AD progression.

Objective

To optimize prediction of progression from mild cognitive impairment (MCI) to AD dementia by combining information from diverse patient variables.

Design, Setting, and Participants

This cohort study from the Alzheimer Disease Neuroimaging Initiative (ADNI) enrolled 928 patients with MCI at baseline and 249 selected variables available in the ADNI data set. Variables included clinical and demographic data, cognitive scores, magnetic resonance imaging-based brain volumetric data, the apolipoprotein E (APOE) and translocase of outer mitochondrial membrane 40 homolog (TOMM40) genotypes, and analyte levels measured in the CSF and plasma. Data were collected in July 2012 and analyzed from July 1, 2012, to June 1, 2015.

Main Outcomes and Measures

Progression from MCI to AD within 1 to 6 years. To determine whether combinations of markers could predict progression from MCI to AD within 1 to 6 years, the elastic net algorithm was used in an iterative resampling of a training- and test-based variable selection and modeling approach.

Results

Among the 928 patients with MCI in the ADNI database, 94 had 224 of the required variables available for the modeling. The results showed the contributions of age, Clinical Dementia Rating Sum of Boxes composite test score, hippocampal volume, and multiple plasma and CSF factors in modeling progression to AD. A combination of apolipoprotein A-II and cortisol levels in plasma and fibroblast growth factor 4, heart-type fatty acid binding protein, calcitonin, and tumor necrosis factor-related apoptosis-inducing ligand receptor 3 (TRAIL-R3) in CSF allowed for reliable prediction of disease status 3 years from the time of sample collection (80% classification accuracy, 88% sensitivity, and 70% specificity).

Conclusions and Relevance

These study findings suggest that a combination of markers measured in plasma and CSF, distinct from β-amyloid and tau, could prove useful in predicting midterm progression from MCI to AD dementia. Such a large-scale, multivariable-based analytical approach could be applied to other similar large data sets involving AD and beyond.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Abstract 2835: MDM2 antagonist-based therapeutic response is discriminated by a 4-gene signature in acute myeloid leukemia patients

The activity of p53, a key tumor suppressor is tightly controlled by MDM2-mediated ubiquination and degradation. Nutlins, a class of small-molecule MDM2 antagonists, have been characterized as drivers of p53 re-activation. Acute myeloid leukemia (AML) is uniquely sensitive to p53 re-activation as ∼90% of cases have wild-type TP53 and frequent MDM2 overexpression to overcome mechanisms of oncogene addiction. Personalized theranostic strategies may distinguish patients likely to clinically benefit from MDM2-antagonist therapy.

Association between MDM2 antagonist (RG7112) growth inhibition (IC50s) in 287 human cancer cell lines (Cell Lines for Oncology/Chugai Accumulative Tumor Encyclopedia), and pretreatment RNAseq profiling established a classifier comprising MDM2, XPC, BBC3, and CDKN2A. This signature significantly associated with cell-line efficacy to MDM2 antagonist (odds ratio = 2.53; P&lt;0.001) and discriminated MDM2 antagonist-sensitive (IC50 10 uM) better than MDM2 mRNA or TP53 mutation status alone (AUC = 0.92). Multivariate logistic regression indicated signature scores were significant (odds ratio = 1.84; P&lt;0.001) when adjusted for TP53 mutation status.

RG7112 treatment was assessed in a phase 1 dose escalation trial in relapsed/refractory AML patients (NO21279). Signature scores of AML patient blood specimens at baseline significantly associated with clinical response (PD&lt;HI&lt;MLFS&lt;CR; Spearman correlation coefficient 0.58; P&lt;0.001); and with pharmacodynamic biomarker response, defined as change in MDM2 mRNA expression in blood (Spearman correlation coefficient 0.41; P = 0.02). Patient response was discriminated by the signature with 100% sensitivity/71% specificity (Wilcoxon p = .0007, AUC = 0.72). Monitoring of signature with clinical response in a second AML Phase 1/1b clinical trial NP28679 with a next generation nutlin-class MDM2 Antagonist RG7388 validated this panel as significantly discriminating MDM2 antagonist therapeutic responders and non-responders in AML patients (Wilcoxon Rank Sum Test P = 0.008; AUC = .75).

In summary, we demonstrate that a biological classifier discriminates response broadly to MDM2-antagonist therapy. The level of evidence attained by cell line efficacy modeling and response assessments in trial NO21279 (with MDM2 antagonist RG7112) and now in trial NP28679 (with MDM2 antagonist RG7388) adds substantial weight to the validity of this panel.

Citation Format: Hua Zhong, Gong Chen, Lori Jukofsky, David Geho, Sung Won Han, Fabian Birzele, Sabine Bader, Lucia Himmelein, James Cai, Zayed Albertyn, Mark Rothe, Laurent Essioux, Helmut Burtscher, Steven A. Middleton, Lin-Chi Chen, Markus Dangl, William E. Pierceall, Gwen Nichols. MDM2 antagonist-based therapeutic response is discriminated by a 4-gene signature in acute myeloid leukemia patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2835. doi:10.1158/1538-7445.AM2015-2835

Multiple protein analysis of formalin-fixed and paraffin-embedded tissue samples with reverse phase protein arrays

Reverse-phase protein arrays (RPPAs) have become an important tool for the sensitive and high-throughput detection of proteins from minute amounts of lysates from cell lines and cryopreserved tissue. The current standard method for tissue preservation in almost all hospitals worldwide is formalin fixation and paraffin embedding, and it would be highly desirable if RPPA could also be applied to formalin-fixed and paraffin embedded (FFPE) tissue. We investigated whether the analysis of FFPE tissue lysates with RPPA would result in biologically meaningful data in two independent studies. In the first study on breast cancer samples, we assessed whether a human epidermal growth factor receptor (HER) 2 score based on immunohistochemistry (IHC) could be reproduced with RPPA. The results showed very good concordance between the IHC and RPPA classifications of HER2 expression. In the second study, we profiled FFPE tumor specimens from patients with adenocarcinoma and squamous cell carcinoma in order to find new markers for differentiating these two subtypes of non-small cell lung cancer. p21-activated kinase 2 could be identified as a new differentiation marker for squamous cell carcinoma. Overall, the results demonstrate the technical feasibility and the merits of RPPA for protein expression profiling in FFPE tissue lysates.

Improving basic and translational science by accounting for litter-to-litter variation in animal models

Background

Animals from the same litter are often more alike compared with animals from different litters. This litter-to-litter variation, or “litter effects”, can influence the results in addition to the experimental factors of interest. Furthermore, sometimes an experimental treatment can only be applied to whole litters rather than to individual offspring. An example is the valproic acid (VPA) model of autism, where VPA is administered to pregnant females thereby inducing the disease phenotype in the offspring. With this type of experiment the sample size is the number of litters and not the total number of offspring. If such experiments are not appropriately designed and analysed, the results can be severely biased as well as extremely underpowered.

Results

A review of the VPA literature showed that only 9% (3/34) of studies correctly determined that the experimental unit (n) was the litter and therefore made valid statistical inferences. In addition, litter effects accounted for up to 61% (p <0.001) of the variation in behavioural outcomes, which was larger than the treatment effects. In addition, few studies reported using randomisation (12%) or blinding (18%), and none indicated that a sample size calculation or power analysis had been conducted.

Conclusions

Litter effects are common, large, and ignoring them can make replication of findings difficult and can contribute to the low rate of translating preclinical in vivo studies into successful therapies. Only a minority of studies reported using rigorous experimental methods, which is consistent with much of the preclinical in vivo literature.

The frequency of anti-infliximab antibodies in patients with rheumatoid arthritis treated in routine care and the associations with adverse drug reactions and treatment failure

OBJECTIVES

To investigate the frequency of anti-infliximab antibodies in patients with RA and the associations with adverse drug reactions and treatment failure.

METHODS

Based on the DANBIO registry, patients with RA who initiated treatment with infliximab at Hvidovre Hospital between 2000 and 2008 and had available serum samples were identified. The patients were followed for 52 weeks. Anti-infliximab antibodies were determined prior to infusion at baseline and during follow-up (weeks 2, 6, 14 and 52 or at withdrawal) using the IMPACT indirect assay (Roche Diagnostics) and merged with clinical data prospectively registered in the DANBIO registry.

RESULTS

A total of 218 patients with RA were included (80% females, median age 56 years, disease duration 10 years, 65% RF positive, median DAS28 = 5.0). During the 52-week follow-up, 28 patients (13%) withdrew due to adverse events and 50 (23%) due to treatment failure. Antibodies were detected in 118 patients (54%) during follow-up. Patients with detectable anti-infliximab antibodies after 6 weeks had an increased risk of adverse drug reactions [hazard ratio (HR) = 5.06, 95% CI 2.36, 10.84; P < 0.0001] compared with patients without anti-infliximab antibodies. Similar results were observed in patients with anti-infliximab antibodies after 14 weeks (HR = 3.30, 95% CI 1.56, 6.99; P = 0.0009). Patients with detectable anti-infliximab antibodies during the 52-week follow-up were less likely to achieve sustained minimal disease activity and remission.

CONCLUSION

Early anti-infliximab antibody formation increased the risk of adverse drug reactions, including infusion reactions. Anti-infliximab antibody formation during the 52-week follow-up decreased the likelihood of minimal disease activity and remission in patients with RA treated in routine care.

Quantitative chemical proteomics profiling differentiates erlotinib from gefitinib in EGFR wild-type non-small cell lung carcinoma cell lines

Although both erlotinib and gefitinib target the EGF receptor (EGFR), erlotinib is effective in patients with EGFR wild-type or mutated tumors, whereas gefitinib is only beneficial for patients with activating mutations. To determine whether these differences in clinical outcomes can be attributed to their respective protein interaction profiles, a label-free, quantitative chemical proteomics study was conducted. Using this method, 24 proteins were highlighted in the binding profiles of erlotinib and gefitinib. Unlike gefinitib, erlotinib displaced the ternary complex formed by integrin-linked kinase (ILK), α-parvin, and PINCH (IPP). The docking of erlotinib in the three-dimensional structure of ILK showed that erlotinib has the ability to bind to the ATP-binding site, whereas gefitinib is unlikely to bind with high affinity. As the IPP complex has been shown to be involved in epithelial-to-mesenchymal transition (EMT) and erlotinib sensitivity has been correlated with EMT status, we used a cellular model of inducible transition and observed that erlotinib prevented EMT in a more efficient way than gefitinib by acting on E-cadherin expression as well as on IPP levels. A retrospective analysis of the MERIT trial indicated that, besides a high level of E-cadherin, a low level of ILK could be linked to clinical benefit with erlotinib. In conclusion, we propose that, in an EGFR wild-type context, erlotinib may have a complementary mode of action by inhibiting IPP complex activities, resulting in the slowing down of the metastatic process of epithelial tumors.

ViralZone: recent updates to the virus knowledge resource

ViralZone (http://viralzone.expasy.org) is a knowledge repository that allows users to learn about viruses including their virion structure, replication cycle and host-virus interactions. The information is divided into viral fact sheets that describe virion shape, molecular biology and epidemiology for each viral genus, with links to the corresponding annotated proteomes of UniProtKB. Each viral genus page contains detailed illustrations, text and PubMed references. This new update provides a linked view of viral molecular biology through 133 new viral ontology pages that describe common steps of viral replication cycles shared by several viral genera. This viral cell-cycle ontology is also represented in UniProtKB in the form of annotated keywords. In this way, users can navigate from the description of a replication-cycle event, to the viral genus concerned, and the associated UniProtKB protein records.

CD6 and syntaxin binding protein 6 variants and response to tumor necrosis factor alpha inhibitors in Danish patients with rheumatoid arthritis

BACKGROUND

TNFα inhibitor therapy has greatly improved the treatment of patients with rheumatoid arthritis, however at least 30% do not respond. We aimed to investigate insertions and deletions (INDELS) associated with response to TNFα inhibitors in patients with rheumatoid arthritis (RA).

METHODOLOGY AND PRINCIPAL FINDINGS

In the DANBIO Registry we identified 237 TNFα inhibitor naïve patients with RA (81% women; median age 56 years; disease duration 6 years) who initiated treatment with infliximab (n=160), adalimumab (n=56) or etanercept (n=21) between 1999 and 2008 according to national treatment guidelines. Clinical response was assessed at week 26 using EULAR response criteria. Based on literature, we selected 213 INDELS potentially related to RA and treatment response using the GeneVa® (Compugen) in silico database of 350,000 genetic variations in the human genome. Genomic segments were amplified by polymerase chain reaction (PCR), and genotyped by Sanger sequencing or fragment analysis. We tested the association between genotypes and EULAR good response versus no response, and EULAR good response versus moderate/no response using Fisher's exact test. At baseline the median DAS28 was 5.1. At week 26, 68 (29%) patients were EULAR good responders, while 81 (34%) and 88 (37%) patients were moderate and non-responders, respectively. A 19 base pair insertion within the CD6 gene was associated with EULAR good response vs. no response (OR=4.43, 95% CI: 1.99-10.09, p=7.211×10(-5)) and with EULAR good response vs. moderate/no response (OR=4.54, 95% CI: 2.29-8.99, p=3.336×10(-6)). A microsatellite within the syntaxin binding protein 6 (STXBP6) was associated with EULAR good response vs. no response (OR=4.01, 95% CI: 1.92-8.49, p=5.067×10(-5)).

CONCLUSION

Genetic variations within CD6 and STXBP6 may influence response to TNFα inhibitors in patients with RA.

A multicentre phase II gene expression profiling study of putative relationships between tumour biomarkers and clinical response with erlotinib in non-small-cell lung cancer

Background: Identification of appropriate markers for predicting clinical benefit with erlotinib in non-small-cell lung cancer (NSCLC) may be able to guide patient selection for treatment. This open-label, multicentre, phase II trial aimed to identify genes with potential use as biomarkers for clinical benefit from erlotinib therapy.

Methods: Adults with stage IIIb/IV NSCLC in whom one or more chemotherapy regimen had failed were treated with erlotinib (150 mg/day). Tumour biopsies were analysed using gene expression profiling with Affymetrix GeneChip® microarrays. Differentially expressed genes were verified using quantitative RT–PCR (qRT–PCR).

Results: A total of 264 patients were enrolled in the study. Gene expression profiles found no statistically significant differentially expressed genes between patients with and without clinical benefit. In an exploratory analysis in responding versus nonresponding patients, three genes on chromosome 7 were expressed at higher levels in the responding group [epidermal growth factor receptor (EGFR), phosphoserine phosphatase (PSPH) and Rap guanine nucleotide exchange factor 5 (RAPGEF5)]. Independent quantification using qRT–PCR validated the association between EGFR and PSPH overexpression, but not RAPGEF5 overexpression, and clinical outcome.

Conclusions: This study supports the use of erlotinib as an alternative to chemotherapy for patients with relapsed advanced NSCLC. Genetic amplification of the EGFR region of chromosome 7 may be associated with response to erlotinib therapy.

Association of four DNA polymorphisms with acute rejection after kidney transplantation

Renal transplant outcomes exhibit large inter-individual variability, possibly on account of genetic variation in immune-response mediators and genes influencing the pharmacodynamics/pharmacokinetics of immunosuppressants. We examined 21 polymorphisms from 10 genes in 237 de novo renal transplant recipients participating in an open-label, multicenter study [Cyclosporine Avoidance Eliminates Serious Adverse Renal-toxicity (CAESAR)] investigating renal function and biopsy-proven acute rejection (BPAR) with different cyclosporine A regimens and mycophenolate mofetil. Genes were selected for their immune response and pharmacodynamic/pharmacokinetic relevance and were tested for association with BPAR. Four polymorphisms were significantly associated with BPAR. The ABCB1 2677T allele tripled the odds of developing BPAR (OR: 3.16, 95% CI [1.50-6.67]; P=0.003), as did the presence of at least one IMPDH2 3757C allele (OR: 3.39, 95% CI [1.42-8.09]; P=0.006). BPAR was almost fivefold more likely in patients homozygous for IL-10 -592A (OR: 4.71, 95% CI [1.52-14.55]; P=0.007) and twice as likely in patients with at least one A allele of TNF-alpha G-308A (OR: 2.18, 95% CI [1.08-4.41]; P=0.029). There were no statistically significant interactions between polymorphisms, or the different treatment regimens. Variation in genes of immune response and pharmacodynamic/pharmacokinetic relevance may be important in understanding acute rejection after renal transplant.

Synergistic Inhibition of Protease-Inhibitor-Resistant HIV type 1 by Saquinavir in Combination with Atazanavir or Lopinavir

Background

Double-boosted protease inhibitors (PIs) are under investigation for the treatment of patients who are unable to take nucleoside reverse transcriptase inhibitors because of cross-resistance and/or intolerance. Evidence of synergistic inhibition of wild-type HIV has been reported for saquinavir with atazanavir or lopinavir.

Methods

We investigated the activity of these two combinations against a panel of six site-directed mutant HIV-1 strains and 14 clinically derived recombinant HIV-1 strains presenting a range of PI-resistance profiles.

Results

No evidence of synergy was observed against wild-type virus for either combination. The combination of saquinavir and lopinavir showed evidence of synergy against four viruses displaying high-level resistance to lopinavir and low-level resistance to saquinavir. Similarly, evidence of synergy between saquinavir and atazanavir was only observed in two viruses which were more susceptible to saquinavir than to atazanavir.

Conclusions

We hypothesize that differences between the PIs in intracellular protein-binding behaviour or inhibition of drug transporters (P glycoprotein, MDR1 and MDR2) could result in intracellular levels of saquinavir being increased by co-administration with lopinavir or atazanavir. The effect of this increase would be masked in cases involving viruses that were susceptible to atazanavir or lopinavir. In virus resistant to lopinavir or atazanavir but susceptible to saquinavir, the majority of the antiviral effect is due to saquinavir; thus even small increases in intracellular concentration could significantly increase virus inhibition. These results confirm that in vitro synergy can be observed between PIs and suggest that the degree of synergy observed might depend on the resistance profile of the virus.

Synergistic inhibition of protease-inhibitor-resistant HIV type 1 by saquinavir in combination with atazanavir or lopinavir

BACKGROUND

Double-boosted protease inhibitors (PIs) are under investigation for the treatment of patients who are unable to take nucleoside reverse transcriptase inhibitors because of cross-resistance and/or intolerance. Evidence of synergistic inhibition of wild-type HIV has been reported for saquinavir with atazanavir or lopinavir.

METHODS

We investigated the activity of these two combinations against a panel of six site-directed mutant HIV-1 strains and 14 clinically derived recombinant HIV-1 strains presenting a range of PI-resistance profiles.

RESULTS

No evidence of synergy was observed against wild-type virus for either combination. The combination of saquinavir and lopinavir showed evidence of synergy against four viruses displaying high-level resistance to lopinavir and low-level resistance to saquinavir. Similarly, evidence of synergy between saquinavir and atazanavir was only observed in two viruses which were more susceptible to saquinavir than to atazanavir.

CONCLUSIONS

We hypothesize that differences between the PIs in intracellular protein-binding behaviour or inhibition of drug transporters (P glycoprotein, MDR1 and MDR2) could result in intracellular levels of saquinavir being increased by co-administration with lopinavir or atazanavir. The effect of this increase would be masked in cases involving viruses that were susceptible to atazanavir or lopinavir. In virus resistant to lopinavir or atazanavir but susceptible to saquinavir, the majority of the antiviral effect is due to saquinavir; thus even small increases in intracellular concentration could significantly increase virus inhibition. These results confirm that in vitro synergy can be observed between PIs and suggest that the degree of synergy observed might depend on the resistance profile of the virus.

A common polymorphism of the growth hormone receptor is associated with increased responsiveness to growth hormone

Growth hormone is used to increase height in short children who are not deficient in growth hormone, but its efficacy varies largely across individuals. The genetic factors responsible for this variation are entirely unknown. In two cohorts of short children treated with growth hormone, we found that an isoform of the growth hormone receptor gene that lacks exon 3 (d3-GHR) was associated with 1.7 to 2 times more growth acceleration induced by growth hormone than the full-length isoform (P < 0.0001). In transfection experiments, the transduction of growth hormone signaling through d3-GHR homo- or heterodimers was approximately 30% higher than through full-length GHR homodimers (P < 0.0001). One-half of Europeans are hetero- or homozygous with respect to the allele encoding the d3-GHR isoform, which is dominant over the full-length isoform. These observations suggest that the polymorphism in exon 3 of GHR is important in growth hormone pharmacogenetics.

Association in Multifactorial Traits: How to Deal with Rare Observations?

To detect the role of a candidate gene for a trait in a sample of individuals, we may test SNP haplotype or diplotype effects. For a limited sample size, many haplotype or diplotype categories may contain few individuals. This involves a power decrease when testing the association between the trait and the haplotypes or diplotypes as these categories provide little additional information while increasing the degrees of freedom. The present paper proposes a new strategy to group rare categories based on a measure of similarity between haplotypes or diplotypes and compares it to two other possible strategies to deal with rare categories: a SNP selection strategy based on haplotype diversity, and a grouping strategy that pools all rare categories into a single baseline group. This comparison is performed by means of simulation under four scenarios. We show that this new strategy shows the largest increase in power irrespective of the model underlying the candidate gene in the studied trait. This strategy therefore provides a powerful alternative to currently used methods to reduce the number of rare categories.

Improved use of SNP information to detect the role of genes

A topical question in genetic association studies is the optimal use of the information provided by genotyped single-nucleotide polymorphisms (SNPs) in order to detect the role of a candidate gene in a multifactorial disease. We propose a strategy called "combination test" that tests the association between a quantitative trait and all possible phased combinations of various numbers of SNPs. We compare this strategy to two alternative strategies: the association test that considers each SNP separately, and a multilocus genotype-based test that considers the phased combination of all SNPs together. To compare these three tests, a quantitative trait was simulated under different models of correspondence between phenotype and genotype, including the extreme case when two SNPs interact with no marginal effects of each SNP. The genotypes were taken from a sample of 290 independent individuals genotyped for three genes with various number of SNPs (from 5-8 SNPs). The results show that the "combination test" is the only one able to detect the association when the two SNPs involved in disease susceptibility interact with no marginal effects. Interestingly, even in the case of a single etiological SNP, the "combination test" performed well. We apply the three tests to Genetic Analysis Workshop 12 (Almasy et al. [2001] Genet. Epidemiol. 21:332-338) simulated data, and show that although there was no interactions between the etiological SNPs, the "combination test" was preferable to the two other compared methods to detect the role of the candidate gene.

GENECOUNTING: haplotype analysis with missing genotypes

A general algorithm is described for haplotype analysis of unrelated individuals with missing genotypes. It can handle problems involving multiple polymorphic markers with missing data.

Genetic and physiological data implicating the new human gene G72 and the gene for D-amino acid oxidase in schizophrenia

A map of 191 single-nucleotide polymorphism (SNPs) was built across a 5-Mb segment from chromosome 13q34 that has been genetically linked to schizophrenia. DNA from 213 schizophrenic patients and 241 normal individuals from Canada were genotyped with this marker set. Two 1,400- and 65-kb regions contained markers associated with the disease. Two markers from the 65-kb region were also found to be associated to schizophrenia in a Russian sample. Two overlapping genes G72 and G30 transcribed in brain were experimentally annotated in this 65-kb region. Transfection experiments point to the existence of a 153-aa protein coded by the G72 gene. This protein is rapidly evolving in primates, is localized to endoplasmic reticulum/Golgi in transfected cells, is able to form multimers and specifically binds to carbohydrates. Yeast two-hybrid experiments with the G72 protein identified the enzyme d-amino acid oxidase (DAAO) as an interacting partner. DAAO is expressed in human brain where it oxidizes d-serine, a potent activator of N-methyl-D-aspartate type glutamate receptor. The interaction between G72 and DAAO was confirmed in vitro and resulted in activation of DAAO. Four SNP markers from DAAO were found to be associated with schizophrenia in the Canadian samples. Logistic regression revealed genetic interaction between associated SNPs in vicinity of two genes. The association of both DAAO and a new gene G72 from 13q34 with schizophrenia together with activation of DAAO activity by a G72 protein product points to the involvement of this N-methyl-d-aspartate receptor regulation pathway in schizophrenia.

Common haplotypes in five genes influence genetic variance of LDL and HDL cholesterol in the general population

We studied the association between common haplotypes in six relevant lipid metabolism genes with plasma lipid levels. We selected single-nucleotide polymorphisms (SNPs) in the cholesterol ester transfer protein (CETP), lipoprotein lipase (LPL), hepatic triglyceride lipase (HL), low-density lipoprotein cholesterol receptor (LDLR), apolipoprotein E (ApoE) and lecithin-cholesterol acyltransferase (LCAT) genes, and studied 732 individuals from 184 German families. Total cholesterol (TC), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) were similar to those reported in other European and American populations. Haplotypes derived from SNP combinations resulted in more significance and of a higher degree than did single SNPs in the genotype-phenotype association analysis. Reduction of the polygenic variance attributable to haplotypes was estimated using variance components analysis. Under the biometrical genetic model, allelic association of haplotypes was highly significant for HDL, LDL and the LDL/HDL ratio. The residual kinship correlation was reduced accordingly. The ApoE gene had a strong effect on trait variation; however, the other genes also contributed substantially. An epistatic interaction could not be demonstrated in this sample. The data are consistent with the notion that common genetic variants influence common traits.

Genetic analysis of case/control data using estimated haplotype frequencies: application to APOE locus variation and Alzheimer's disease

There is growing debate over the utility of multiple locus association analyses in the identification of genomic regions harboring sequence variants that influence common complex traits such as hypertension and diabetes. Much of this debate concerns the manner in which one can use the genotypic information from individuals gathered in simple sampling frameworks, such as the case/control designs, to actually assess the association between alleles in a particular genomic region and a trait. In this paper we describe methods for testing associations between estimated haplotype frequencies derived from multilocus genotype data and disease endpoints assuming a simple case/control sampling design. These proposed methods overcome the lack of phase information usually associated with samples of unrelated individuals and provide a comprehensive way of assessing the relationship between sequence or multiple-site variation and traits and diseases within populations. We applied the proposed methods in a study of the relationship between polymorphisms within the APOE gene region and Alzheimer's disease. Cases and controls for this study were collected from the United States and France. Our results confirm the known association between the APOE locus and Alzheimer's disease, even when the epsilon 4 polymorphism is not contained in the tested haplotypes. This suggests that, in certain situations, haplotype information and linkage disequilibrium-induced associations between polymorphic loci that neighbor loci harboring functional sequence variants can be exploited to identify disease-predisposing alleles in large, freely mixing populations via estimated haplotype frequency methods.

Marker segregation information in breast/ovarian cancer genetic counseling: is it still useful? Groupe Génétique et Cancer de la Fédération Nationale des Centres de Lutte Contre le Cancer

The use of mutation screening of BRCA1 and BRCA2 genes as a genetic test is still to a certain extent limited and the oncogeneticist may want to use complementary approaches to identify at-risk individuals. In a series of 23 families with at least three breast or ovarian cancer cases, screened for mutations at BRCA1 and BRCA2 and typed for markers at both loci, we investigated the usefulness of marker segregation information at two levels: 1) to what extent can the indirect approach identify the mutation carrier status of screened cases and their first-degree relatives, and 2) in what way does it help to identify the gene implicated in a family in which neither BRCA1 nor BRCA2 mutation has been detected? Using the indirect approach, the carrier status of the screened case could be determined with quasi certainty in three families and with a high probability in eight families. This status could be inferred in unaffected first-degree relatives as almost certain in one family and as highly probable in six families. Fourteen mutations were found concurrently in our series. Among the nine mutation-negative families, we were able to conclude that a BRCA1 mutation most probably segregated in one and that a mutation other than BRCA1 and BRCA2 was probably involved in two families. Our results show that, in small families, little help is to be expected from linkage data and mutation screening is the only way of identifying the origin of a genetic predisposition in a family. Marker segregation information may be useful in some large breast/ovarian cancer families in which no BRCA1 or BRCA2 mutation has been detected.

BRCA1 sequence variations in 160 individuals referred to a breast/ovarian family cancer clinic. Institut Curie Breast Cancer Group

An account of familial aggregation in breast/ovarian cancer has become possible with the identification of BRCA1 germ-line mutations. We evaluated, for 249 individuals registered with the Institut Curie in Paris, the prior probability that an individual carried a mutation that predisposes to these diseases. We chose 160 women for BRCA1 analysis: 103 with a family history of breast cancer and 57 with a family history of breast-ovarian cancer. To detect small mutations, we generated and analyzed 35 overlapping genomic PCR products that cover the coding portion of the gene, by using denaturing gradient gel electrophoresis. Thirty-eight truncating mutations (32 frameshifts, 4 nonsense mutations, and 2 splice variants) were observed in 15% of women with a family history of breast cancer only and in 40% of those with a history of breast-ovarian cancer. Twelve of 25 distinct truncating mutations identified were novel and unique. Most BRCA1 mutations that had been reported more than five times in the Breast Cancer Information Core were present in our series. One mutation (5149del4) observed in two apparently unrelated families most likely originates from a common ancestor. The position of truncating mutations did not significantly affect the ratio of the risk of breast cancer to that of ovarian cancer. In addition, 15 DNA variants (14 missense mutations and 1 neutral mutation) were identified, 9 of which were novel. Indirect evidence suggests that seven of these mutations are deleterious.

Integrated map of the chromosome 8p12-p21 region, a region involved in human cancers and Werner syndrome

Detailed physical maps of the human genome are important resources for the identification and isolation of disease genes and for studying the structure and function of the genome. To improve the definition of the 8p12-p21 chromosomal region, an integrated physical and genetic map was constructed extending from the genes. NEFL to FGFR1. The map comprises a series of contigs (the larger of these being around 9 Mb) of yeast artificial chromosomes (YACs) spanning the proximal region of deletion involved in a broad range of human cancers, including breast carcinomas, and in the Werner syndrome. In addition, losses of heterozygosity at 8p markers and linkage analysis of breast cancer families were also detailed. Finally, several genes potentially involved in 8p-associated diseases, namely GTF2E2, PPP2CB, and HGL, were precisely mapped within the YAC contigs. The reported map and contigs of YACs should facilitate the search for putative genes involved in sporadic and familial breast cancer as well as in the Werner syndrome.

Genetic epidemiology of breast cancer: interest of survival analysis methods

In an attempt to explain the controversy resulting from the analysis of the breast cancer data collected by Jacobsen, a segregation analysis was performed using successively the unified mixed model (UM) and the logistic hazard function model (LHM) (Abel & Bonney, 1990). Under the UM, age of onset of the disease cannot be taken into account, each individual being assigned to a liability class according to his age at examination, whereas, in the LHM, variable age of onset is modelled using survival analysis methods. Under the UM, we confirmed the results of Demenais et al. (1986b), i.e. the transmission probabilities are significantly different from Mendelian expectations. The same results were obtained when taking into account the specific mortality for the computation of the morbid risk observed in a given liability class. Under the LHM, the analysis provides evidence for a monogenic autosomal model with a rare dominant allele responsible for the disease, and transmission probabilities compatible with Mendelian expectations. This study shows that the rejection of the Mendelian transmission under the UM can be due to a violation of a constraint of this model (i.e. the probability of being and not being affected in a given liability class should sum to 1) when a specific mortality is induced by the disease as in breast cancer. Survival analysis methods avoid these problems by taking into account the onset of the disease as the failure time event and are more suitable when studying a complex trait such as breast cancer.

Loss of heterozygosity and linkage analysis in breast carcinoma: indication for a putative third susceptibility gene on the short arm of chromosome 8

We have analysed losses of heterozygosity (LOH) at eight markers from the p12-p22 region of human chromosome 8 in a panel of 113 breast tumors. LOH were detected in almost half of the tumors. The most frequently deleted region included microsatellite (CA)n repeats markers D8S258, D8S133 and D8S259, located at 8p12-p22, while markers NEFL and LPL appeared less frequently altered. In parallel, linkage analysis was performed using the same informative markers, to test for the involvement of chromosome 8p loci in familial breast cancer. Positive cumulative multipoint lod score of 2.51 at theta = 0.0 was obtained with markers NEFL and D8S259. These results suggest that region 8p12-p22 carries at least one tumor suppressor gene involved in sporadic and perhaps also in familial breast cancer.

Linkage analyses of 3 French families to Loci on chromosome-2p and chromosome-3p predisposing to hereditary nonpolyposis colon-cancer

Hereditary, non-polyposis colon cancer (HNPCC) is caused by mutations in different loci. One gene causing HNPCC was mapped to chromosome 2p and recently a tight linkage between a polymorphic marker on the chromosome 3p and the disease locus has been demonstrated and these families also manifest signs of a general DNA replicator disorder. We report detailed genetic studies of three French HNPCC families with D2S123 and D3S1029. In one of the families (F 230), the segregation pattern for markers on chromosomes 2 and 3 suggests absence of linkage. The two other families are not informative enough to conclude on linkage status with chromosomes 2 and 3. If confirmed, this result would mean that the inherited colon cancer in this family is linked to another HNPCC gene. Implication for genetic counselling is discussed. Even with cloned genes, linkage analysis with flanking microsatellite markers for informative families may help to avoid tedious work of seeking point mutations in HNPCC genes.

Analyses of linkage to 17q11-q23 in 3 French hereditary nonpolyposis colon-cancer families

Hereditary non-polyposis colorectal cancer (HNPCC) is an autosomal dominant disease, accounting for approximately 6% of colorectal cancers. We performed linkage analyses with the aim of proving or excluding the existence of a susceptibility locus on 17q. Three HNPCC families (102 collected members, 25 colorectal cancers, 9 other cancers and 6 colorectal adenomas) were studied with 7 polymorphic DNA markers Mfd15, THRA 1, D17S800, D17S855, Mfd 188, 42D6, 46E6 localized in the 17q11-q23 region. After in vitro enzymatic amplification, the different alleles were separated by classic vertical poly-acrylamide gel electrophoresis or analyzed with the automatic sequencing machine 373A (Applied Biosystems). Results showed that none of the 7 studied markers of the chromosome 17q were linked to the HNPCC disease.

The effect of population structure on the relationship between heterosis and heterozygosity at marker loci

The relationship between heterozygosity at neutral marker loci and heterosis of F1 hybrids is investigated using a theoretical model. Results emphasize that linkage disequilibrium between the markers and the loci implicated in heterosis [quantitative trait loci (QTLs) that exhibit dominance effects] is a necessary condition to finding a correlation (ϱ mh ) between heterozygosity at marker loci and the heterosis. The effect of population structure, in which the parental inbred lines of the hybrids belong to different heterotic groups, is considered. ϱ mh is investigated for: (1) hybrids between lines that belong to the same heterotic group (within-group hybrids); (2) hybrids between lines that belong to different groups (between-group hybrids); and (3) all hybrids, both within and between-groups. Within a group, significant values of (ϱ mh ) may arise because of linkage disequilibrium generated by drift. At the between-group level, no correlation is expected since link-age disequilibrium should differ randomly from one group to the other, which is consistent with recent experimental results. Possible ways to achieve prediction of the heterosis in this situation are discussed. When all hybrids are considered simultaneously, divergence of allelic frequencies among groups for the markers and the QTLs produces a correlation between heterosis and heterozygosity at marker loci. This correlation increases with the number of markers that are considered.