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Supplementary Table 1 PDF file 55K, Cut-points for protein markers used in different analyses. Cut-points selected for pair-wise comparisons were chosen to reduce the total number of comparisons that would be done. Cut-points for the discovery/confirmation analyses (see Supplementary Methods) were optimized based on enrichment of responders versus non-responders and reasonable population size

Supplementary Figure 1 PDF file 77K, Biomarker sample collection from the LYM-3001 intent-to-treat population

Supplementary Table 4 PDF file 69K, OS, ORR, CR rate, and TTNT in all patients in the cross-validation model (see Supplementary Methods) who were positive or negative for the biomarker pair PSMB1 P11A (G allele) and low CD68 expression (≤50 CD68-positive cells). Among all biomarker-positive patients there was a significantly longer OS with bortezomib-rituximab versus rituximab, a significantly higher ORR, a higher CR rate, and a significantly longer TTNT. No significant differences were seen for biomarker-negative patients

Supplementary Table 3 PDF file 70K, Median PFS for patients in the discovery and confirmation sets, and in all patients, in the cross-validation model (see Supplementary Materials) who were positive or negative for the biomarker pair PSMB1 P11A (G allele) and low CD68 expression (≤50 CD68-positive cells). Presence of the biomarker pair was associated with a significant PFS benefit in patients treated with bortezomib-rituximab versus rituximab in the discovery set, a positive trend in the smaller confirmation sets, and a significant benefit among all patients. No significant differences were seen for biomarker-negative patients

Purpose: Identify subgroups of patients with relapsed/refractory follicular lymphoma deriving substantial progression-free survival (PFS) benefit with bortezomib–rituximab versus rituximab in the phase III LYM-3001 study.Experimental Design: A total of 676 patients were randomized to five 5-week cycles of bortezomib–rituximab or rituximab. The primary end point was PFS; this prespecified analysis of candidate protein biomarkers and genes was an exploratory objective. Archived tumor tissue and whole blood samples were collected at baseline. Immunohistochemistry and genetic analyses were completed for 4 proteins and 8 genes.Results: In initial pairwise analyses, using individual single-nucleotide polymorphism genotypes, one biomarker pair (PSMB1 P11A C/G heterozygote, low CD68 expression) was associated with a significant PFS benefit with bortezomib–rituximab versus rituximab, controlling for multiple comparison corrections. The pair was analyzed under dominant, recessive, and additive genetic models, with significant association with PFS seen under the dominant model (G/G+C/G). In patients carrying this biomarker pair [PSMB1 P11A G allele, low CD68 expression (≤50 CD68-positive cells), population frequency: 43.6%], median PFS was 14.2 months with bortezomib–rituximab versus 9.1 months with rituximab (HR 0.47, P < 0.0001), and there was a significant overall survival benefit (HR 0.49, P = 0.0461). Response rates were higher and time to next antilymphoma therapy was longer in the bortezomib–rituximab group. In biomarker-negative patients, no significant efficacy differences were seen between treatment groups. Similar proportions of patients had high-risk features in the biomarker-positive and biomarker-negative subsets.Conclusions: Patients with PSMB1 P11A (G allele) and low CD68 expression seemed to have significantly longer PFS and greater clinical benefit with bortezomib–rituximab versus rituximab. Clin Cancer Res; 19(9); 2551–61. ©2013 AACR.

Supplementary Figure 2 PDF file 135K, Forest plot for single marker (A) protein and (B) germ-line DNA biomarker analyses

Supplementary Methods PDF file 64K, TaqMan SNP Genoytping Assays and Ligation-based Multiplexed Genotyping Assays

Supplementary Table 2 PDF file 78K, Evaluation of PFS and OS under the G-dominant genetic model for PSMB1 P11A among all patients evaluable for the biomarker pair of PSMB1 P11A genotype and CD68 expression who had low (≤50 CD68-positive cells) CD68 expression

Supplementary Figure 3 PDF file 78K, Kaplan-Meier distributions of A) PFS and B) OS under the G-dominant genetic model for PSMB1 P11A among all patients evaluable for the biomarker pair of PSMB1 P11A genotype and CD68 expression who had low (≤50 CD68-positive cells) CD68 expression

In this exploratory analysis, patients with recurrent ovarian cancer carrying BRCA1mut gene had improved outcomes with trabectedin + PLD treatment compared with PLD alone. Prospective evaluation of BRCA status is likely an important evaluation for DNA-damaging agents and may significantly impact interpretation of clinical studies. XPG may be a biomarker of poor outcome in these patients. Background We investigated the association of BRCA1 and XPG mutations with response rate (RR), progression-free survival (PFS) and overall survival (OS) in a subset of patients from a phase 3 clinical trial comparing the efficacy and safety of trabectedin + pegylated liposomal doxorubicin (PLD) versus PLD alone in patients with recurrent ovarian cancer. Patients and methods A candidate array was designed based on the Breast Cancer Information Core database for BRCA mutation analyses. An exploratory analysis of BRCA1/XPG mutation status was conducted using a two-sided log-rank test and 0.05 significance in germline DNA samples from 264 women with failed first-line platinum-based chemotherapy, randomized (1 : 1) to trabectedin + PLD or PLD alone. Results Overall, 41 (16%) of the 264 women had BRCA1mut (trabectedin + PLD: n = 24/135, 18%; PLD: n = 17/129; 13%) and 17 (6%) had XPGmut (trabectedin + PLD: n = 8/135, 6%; PLD: n = 9/129, 7%). A higher RR was observed in BRCA1mut patients (20/41; 49%) versus BRCA1wt patients (62/223; 28%). Within the BRCA1mut group, trabectedin + PLD-treated patients had longer PFS and longer OS than PLD-treated patients (median PFS 13.5 versus 5.5 months, P = 0.0002; median OS 23.8 versus 12.5 months, P = 0.0086), whereas in BRCA1wt patients, OS was not significantly different (median OS: 19.1 versus 19.3 months; P = 0.9377). There were no differences in OS or PFS of patients with XPGmut between the two treatment arms. However, trabectedin + PLD-treated patients with XPGmut had a trend toward shorter PFS (median PFS: 1.9 versus 7.5 months; P = 0.1666) and OS (median OS: 14.5 versus 20.7 months; P = 0.1774) than those with XPGwt. Conclusions In this exploratory analysis, patients with recurrent ovarian cancer carrying the BRCA1mut had improved outcomes with trabectedin + PLD treatment compared with PLD alone. Prospective evaluation of BRCA status is likely an important evaluation for DNA-damaging agents and may significantly impact interpretation of clinical studies. XPG may be a biomarker of poor outcome in these patients.

Purpose: Identify subgroups of patients with relapsed/refractory follicular lymphoma deriving substantial progression-free survival (PFS) benefit with bortezomib–rituximab versus rituximab in the phase III LYM-3001 study. Experimental Design: A total of 676 patients were randomized to five 5-week cycles of bortezomib–rituximab or rituximab. The primary end point was PFS; this prespecified analysis of candidate protein biomarkers and genes was an exploratory objective. Archived tumor tissue and whole blood samples were collected at baseline. Immunohistochemistry and genetic analyses were completed for 4 proteins and 8 genes. Results: In initial pairwise analyses, using individual single-nucleotide polymorphism genotypes, one biomarker pair (PSMB1 P11A C/G heterozygote, low CD68 expression) was associated with a significant PFS benefit with bortezomib–rituximab versus rituximab, controlling for multiple comparison corrections. The pair was analyzed under dominant, recessive, and additive genetic models, with significant association with PFS seen under the dominant model (G/G+C/G). In patients carrying this biomarker pair [PSMB1 P11A G allele, low CD68 expression (≤50 CD68-positive cells), population frequency: 43.6%], median PFS was 14.2 months with bortezomib–rituximab versus 9.1 months with rituximab (HR 0.47, P < 0.0001), and there was a significant overall survival benefit (HR 0.49, P = 0.0461). Response rates were higher and time to next antilymphoma therapy was longer in the bortezomib–rituximab group. In biomarker-negative patients, no significant efficacy differences were seen between treatment groups. Similar proportions of patients had high-risk features in the biomarker-positive and biomarker-negative subsets. Conclusions: Patients with PSMB1 P11A (G allele) and low CD68 expression seemed to have significantly longer PFS and greater clinical benefit with bortezomib–rituximab versus rituximab. Clin Cancer Res; 19(9); 2551–61. ©2013 AACR.

Supplemental Digital Content is available in the text., Objectives: Previous studies have established the role of SCN9A in various pain conditions, including idiopathic small fiber neuropathy. In the present study, we interrogate the relationship between common and rare variants in SCN9A gene and chronic neuropathic pain associated with diabetic peripheral neuropathy. Design: Using a cohort of 938 patients of European ancestry with chronic neuropathic pain associated with diabetic peripheral neuropathy enrolled in 6 clinical studies and 2 controls (POPRES, n=2624 and Coriell, n=1029), we examined the relationship between SCN9A variants and neuropathic pain in a case-control study using a 2-stage design. The exonic regions of SCN9A were sequenced in a subset of 244 patients with neuropathic pain, and the variants discovered were compared with POPRES control (stage 1). The top associated variants were followed up by genotyping in the entire case collection and Coriell controls restricting the analysis to the matching patients from the United States and Canada only (stage 2). Results: Seven variants were found to be associated with neuropathic pain at the sequencing stage. Four variants (Asp1908Gly, Val991Leu/Met932Leu, and an intronic variant rs74449889) were confirmed by genotyping to occur at a higher frequency in cases than controls (odds ratios ∼2.1 to 2.6, P=0.05 to 0.009). Val991Leu/Met932Leu was also associated with the severity of pain as measured by pain score Numeric Rating Scale (NRS-11, P=0.047). Val991Leu/Met932Leu variants were in complete linkage disequilibrium and previously shown to cause hyperexcitability in dorsal root ganglia neurons. Conclusions: The association of SCN9A variants with neuropathic pain and pain severity suggests a role of SCN9A in the disease etiology of neuropathic pain.

Background: BRCA1 is a tumour suppressor with pleiotropic actions. Germline mutations in BRCA1 are responsible for a large proportion of breast–ovarian cancer families. Several missense variants have been identified throughout the gene but because of lack of information about their impact on the function of BRCA1 , predictive testing is not always informative. Classification of missense variants into deleterious/high risk or neutral/low clinical significance is essential to identify individuals at risk. Objective: To investigate a panel of missense variants. Methods and results: The panel was investigated in a comprehensive framework that included (1) a functional assay based on transcription activation; (2) segregation analysis and a method of using incomplete pedigree data to calculate the odds of causality; (3) a method based on interspecific sequence variation. It was shown that the transcriptional activation assay could be used as a test to characterise mutations in the carboxy-terminus region of BRCA1 encompassing residues 1396–1863. Thirteen missense variants (H1402Y, L1407P, H1421Y, S1512I, M1628T, M1628V, T1685I, G1706A, T1720A, A1752P, G1788V, V1809F, and W1837R) were specifically investigated. Conclusions: While individual classification schemes for BRCA1 alleles still present limitations, a combination of several methods provides a more powerful way of identifying variants that are causally linked to a high risk of breast and ovarian cancer. The framework presented here brings these variants nearer to clinical applicability.

Purpose: Molecular profiling of alterations associated with lung cancer holds the promise to define clinical parameters such as response to treatment or survival. Because Experimental Design: p53 mutation status was assessed from the DNA and RNA of biopsies collected prospectively from 83 patients with lung cancer. Biopsies were obtained either by conventional bronchoscopy or computed tomography-guided percutaneous biopsy. Matched surgical specimens were available for 22 patients. Three assays were used: direct sequencing; a functional assay in yeast; and a newly developed PCR/ligase detection reaction/Universal DNA array assay. Results: Using the functional assay, p53 mutation was found in 62% of biopsies and 64% of surgical specimens with a concordance of 80%. The sensitivity of the functional assay was determined to be 5%. Direct sequencing confirmed mutations in 92% of surgical specimens but in only 78% of biopsies. The DNA array confirmed 100% of mutations in both biopsies and surgical specimens. Using this newly developed DNA array, we demonstrate the feasibility of directly identifying p53 mutations in clinical samples containing Conclusions: The versatility and sensitivity of this new array assay should allow additional development of mutation profiling arrays that could be applied to biological samples with a low tumor cell content such as bronchial aspirates, bronchoalveolar lavage fluid, or serum.

Successful investigation of common diseases requires advances in our understanding of the organization of the genome. Linkage disequilibrium provides a theoretical basis for performing candidate gene or whole-genome association studies to analyze complex disease. However, to constructively interrogate SNPs for these studies, technologies with sufficient throughput and sensitivity are required. A plethora of suitable and reliable methods have been developed, each of which has its own unique advantage. The characteristics of the most promising genotyping and polymorphism scanning technologies are presented. These technologies are examined both in the context of complex disease investigation and in their capacity to face the unique physical and molecular challenges (allele amplification, loss of heterozygosity and stromal contamination) of solid tumor research.

Single nucleotide polymorphisms (SNPs) in the multiple drug resistance protein 1 (MRP1) and P-glycoprotein 1 (MDR1) genes modulate their ability to mediate drug resistance. We therefore sought to retrospectively evaluate their influence on outcomes in relapsed and/or refractory myeloma patients treated with bortezomib or bortezomib with pegylated liposomal doxorubicin (PLD). The MRP1/R723Q polymorphism was found in five subjects among the 279 patient study population, all of whom received PLD + bortezomib. Its presence was associated with a longer time to progression (TTP; median 330 vs. 129 days; p = 0.0008), progression-free survival (PFS; median 338 vs. 129 days; p = 0.0006), and overall survival (p = 0.0045). MDR1/3435(C > T), which was in Hardy–Weinberg equilibrium, showed a trend of association with PFS (p = 0.0578), response rate (p = 0.0782) and TTP (p = 0.0923) in PLD + bortezomib patients, though no correlation was found in the bortezomib arm. In a recessive genetic model, MDR1/3435 T was significantly associated with a better TTP (p = 0.0405) and PFS (p = 0.0186) in PLD + bortezomib patients. These findings suggest a potential role for MRP1 and MDR1 SNPs in modulating the long-term outcome of relapsed and/or refractory myeloma patients treated with PLD + bortezomib. Moreover, they support prospective studies to determine if such data could be used to tailor therapy to the genetic makeup of individual patients.

Molecular profiling of alterations associated with lung cancer holds the promise to define clinical parameters such as response to treatment or survival. Because5% of small cell lung cancers and30% of non-small cell lung cancers are surgically resectable, molecular analysis will perforce rely on routinely available clinical samples such as biopsies. Identifying tumor mutations in such samples will require a sensitive and robust technology to overcome signal from excess amounts of normal DNA.p53 mutation status was assessed from the DNA and RNA of biopsies collected prospectively from 83 patients with lung cancer. Biopsies were obtained either by conventional bronchoscopy or computed tomography-guided percutaneous biopsy. Matched surgical specimens were available for 22 patients. Three assays were used: direct sequencing; a functional assay in yeast; and a newly developed PCR/ligase detection reaction/Universal DNA array assay.Using the functional assay, p53 mutation was found in 62% of biopsies and 64% of surgical specimens with a concordance of 80%. The sensitivity of the functional assay was determined to be 5%. Direct sequencing confirmed mutations in 92% of surgical specimens but in only 78% of biopsies. The DNA array confirmed 100% of mutations in both biopsies and surgical specimens. Using this newly developed DNA array, we demonstrate the feasibility of directly identifying p53 mutations in clinical samples containing5% of tumor cells.The versatility and sensitivity of this new array assay should allow additional development of mutation profiling arrays that could be applied to biological samples with a low tumor cell content such as bronchial aspirates, bronchoalveolar lavage fluid, or serum.

The p53 gene is a critical tumor suppressor that is inactivated in a majority of cancers. The central role of p53 in response to stresses such as DNA damage, hypoxia, and oncogene activation underlies this high frequency of negative selection during tumorigenic transformation. Mutations in p53 disrupt checkpoint responses to DNA damage and result in the potential for destabilization of the genome. Consistent with this, p53 mutant cells have been shown to accumulate genomic alterations in cell culture, mouse models, and some human tumors. The relationship between p53 mutation and genomic instability in human osteosarcoma is addressed in this report. Similar to some other primary human tumors, the mutation of p53 correlates significantly with the presence of high levels of genomic instability in osteosarcomas. Surprisingly, osteosarcomas harboring an amplification of the HDM2 oncogene, which inhibits the tumor-suppressive properties of p53 , do not display high levels of genomic instability. These results demonstrate that the inactivation of p53 in osteosarcomas directly by mutation versus indirectly by HDM2 amplification may have different cellular consequences with respect to the stability of the genome.

Array-based mutation detection methodology typically relies on direct hybridization of the fluorescently labeled query sequence to surface-bound oligonucleotide probes. These probes contain either small sequence variations or perfect-match sequence. The intensity of fluorescence bound to each oligonucleotide probe is intended to reveal which sequence is perfectly complementary to the query sequence. However, these approaches have not always been successful, especially for detection of small frameshift mutations. Here we describe a multiplex assay to detect small insertions and deletions by using a modified PCR to evenly amplify each amplicon (PCR/PCR), followed by ligase detection reaction (LDR). Mutations were identified by screening reaction products with a universal DNA microarray, which uncouples mutation detection from array hybridization and provides for high sensitivity. Using the three BRCA1 and BRCA2 founder mutations in the Ashkenazi Jewish population (BRCA1 185delAG; BRCA1 5382insC; BRCA2 6174delT) as a model system, the assay readily detected these mutations in multiplexed reactions. Our results demonstrate that universal microarray analysis of PCR/PCR/LDR products permits rapid identification of small insertion and deletion mutations in the context of both clinical diagnosis and population studies.

Abstract 265 Background: Treatment goals in patients with relapsed FL are to prolong PFS and improve overall survival (OS). To optimize treatment for individual patients, identification of subgroups most likely to benefit from a specific therapy is important. The international, randomized, phase 3 LYM3001 study in patients with relapsed or refractory FL demonstrated improved PFS with bortezomib-rituximab vs rituximab alone (median 12.8 vs 11.0 months, HR 0.822, p=0.039), plus increased overall response rate (ORR; 63% vs 49%, p=0.0004), complete response rate (CR/CRu; 25% vs 18%, p=0.035), and durable (≥6 months) response rate (50% vs 38%, p=0.002) in an unselected patient population. Here we present exploratory biomarker analyses aimed at identifying patient subgroups deriving a longer PFS benefit with bortezomib-rituximab and showing a trend for better OS. Methods: Patients received five 5-week cycles of bortezomib-rituximab (N=336) or rituximab (N=340). Response was assessed using modified International Working Group response criteria. Archived tumor tissue was collected at baseline from 502 (74%) patients; whole blood samples for germ-line DNA were collected on day 1 of cycle 1 from 619 (92%) patients. Protocol-specified candidate biomarkers were based on associations with bortezomib (NF-κB p65, PSMA5, p27, PSMB1/5/8/9) or rituximab (CD68, FCGR2A/3A) activity. Immunohistochemistry assays were used for protein analysis. Taqman SNP assays and PCR/LDR were used for genotyping. Statistical analyses included single-marker analyses, pair-wise combination analyses (n=1140 comparisons), and multiple comparison analyses of all evaluable patients in LYM3001. Clinical covariates included in the analysis were baseline FLIPI score, prior rituximab, time since last anti-lymphoma therapy, region, age, gender, race, Ann Arbor stage, high tumor burden, and number of prior lines of therapy. Results: Single markers and biomarker pairs (n=102) highlighted patient subsets that had significantly improved outcomes with bortezomib-rituximab vs rituximab. For 14 of the pairs, the PFS benefit was ≥6 months. Using false discovery rate (FDR) to control for multiple comparison corrections, one biomarker pair was significant. This pair (presence of the PSMB1 P11A C/G heterozygote, and low CD68 expression [0–50 CD68-positive macrophages in the follicular space]) was associated with significantly improved PFS in patients receiving bortezomib-rituximab vs rituximab (median 16.6 vs 9.1 months, HR 0.407, p2 prior lines of therapy). There was also a trend towards an OS benefit (medians not reached, HR 0.426, p=0.0550), as well as a significantly higher ORR (73.7% vs 47.5%, p=0.0077), a higher CR rate (33.3% vs 23%, p=0.3044), and a significantly longer time to next therapy (median 33.1 vs 14.8 months, p=0.0013). In patients lacking this biomarker pair (N=238) no significant efficacy differences were seen. No other similar studies were available to confirm the reproducibility of these analyses. Therefore, we split the LYM3001 dataset into discovery and confirmation cohorts (7:3 ratio of biomarker-evaluable patients) to enable evaluation and confirmation in independent cohorts of patients The significant biomarker pair of PSMB1 P11A C/G heterozygote and low CD68 was identified in the discovery cohort (N=198) with a PFS advantage with bortezomib-rituximab vs rituximab of 5.7 months (median 14.2 vs 8.4 months, p=0.0003) and an indication of longer OS (HR 0.47, p=0.1291). This biomarker pair also showed a clear PFS advantage in the confirmation cohort (N=108, 8.7-month PFS benefit; median 18.2 vs 9.5 months, HR 0.44, p=0.0817). Other significant biomarker combinations, including combinations of molecular and clinical variables (e.g. high tumor burden) were identified and will be presented. Conclusions: Analyses of the phase 3 LYM3001 trial identified biomarker combinations present in a third of patients offering a significant PFS benefit with bortezomib-rituximab vs rituximab. Use of such biomarker assays in patients with relapsed or refractory FL may aid identification of subgroups deriving maximal benefit from the addition of bortezomib to rituximab therapy. Disclosures: Coiffier: Janssen-Cilag: Consultancy; Roche: Consultancy; Amgen: Consultancy; Sanofi: Consultancy; Pfizer: Consultancy; Millennium Pharmaceuticals, Inc.: Consultancy; Celgene: Consultancy; Pharmacyclics: Consultancy; MedImmune: Consultancy; CTI: Consultancy. Off Label Use: Bortezomib used in combination with rituximab in patients with relapsed/refractory follicular lymphoma. Li:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Henitz:Janssen Research & Development: Employment. Karkera:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Favis:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Gaffney:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Shapiro:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Theocharous:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Elsayed:Janssen Research & Development: Employment; Johson & Johnson: Equity Ownership. de Velde:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Rule:Johnson & Johnson: Advisory Board, Institutional grant, meeting attendance expenses, Honoraria. Walewski:Janssen-Cilag: Institutional/personal grants, advisory board; Hoffman La Roche: Honoraria, Institutional/personal grants, travel/accommodation expenses; Mundipharma: Honoraria; Celgene: Honoraria. de Vos:Millennium Pharmaceuticals, Inc: Consultancy. Crump:Janssen/Ortho-Biotech: Consultancy. Shpilberg:Janssen-Cilag: Consultancy, Honoraria. Cakana:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership. Esseltine:Millennium Pharmaceuticals, Inc: Employment; Johnson & Johnson: Equity Ownership. Mulligan:Millennium Pharmaceuticals, Inc.: Employment. Ricci:Janssen Research & Development: Employment; Johnson & Johnson: Equity Ownership.

Abstract 109 Background: Single nucleotide polymorphisms (SNPs) in the gene encoding multiple drug resistance protein 1 (ATP-binding cassette, sub-family C member 1 (ABCC1) influence its ability to act as a mediator of anthracycline resistance. The same is true for SNPs in P-glycoprotein 1 (ATP-binding cassette, sub-family B member 1 (ABCB1)), and the latter have been associated with outcome in newly diagnosed patients with multiple myeloma treated with anthracycline-based therapy. We therefore sought to evaluate the role of SNPs in ABCC1 and ABCB1 in the outcome of patients with relapsed and/or refractory multiple myeloma. Methods: The DOXIL-MMY-3001 study was an international, randomized, phase III trial comparing the efficacy of single-agent bortezomib to that of bortezomib with pegylated liposomal doxorubicin (PLD) in patients with relapsed and/or refractory multiple myeloma. Patients treated with bortezomib received this proteasome inhibitor at 1.3 mg/m2 as an intravenous push on days 1, 4, 8, and 11 of every 21-day cycle, while patients on the combination arm received this dose and schedule of bortezomib along with PLD as an infusion at 30 mg/m2 on day 4. Genomic DNA samples were obtained from all subjects in the intention-to-treat cohort who consented to DNA testing under Part 1 of the pharmacogenomic component of the clinical trial protocol. Samples that produced at least one useable genotype were included in this pharmacogenomic analysis. SNPs in ABCC1 (R723Q) and ABCB1 (1236 C>T, 2677 G>W (W = T or A), and 3435 C>T) were correlated with the overall response rate (complete + partial), time to progression, progression-free survival, and overall survival. Results: Genetic transmission patterns differ among racial groups, and since usable genotype and clinical data were available for 301 subjects, 279 of whom were Caucasians, this analysis focused on that group. The ABCC1 gene polymorphism R723Q was not represented in the bortezomib arm, and found in 5 subjects (3.5%) who received bortezomib + PLD. Its presence was significantly associated with a longer time to progression (median of 330 days vs. 129 days; p = 0.0008), a longer progression-free survival (median of 338 days vs. 129 days p = 0.0006), and a superior overall survival (p = 0.0045) in these patients. The ABCB1 gene polymorphism at 3435 (C>T) was associated with progression-free survival (p = 0.0578), response rate (p = 0.0782) and time to progression (p = 0.0923) in patients receiving bortezomib + PLD, though not at the level of statistical significance, and no correlation was found in the bortezomib alone arm. However, in a recessive genetic model, the ABCB1 gene polymorphism at 3435 T allele was significantly associated with a better clinical outcome, specifically time to progression (p = 0.0405), and progression-free survival (p = 0.0186) in patients receiving bortezomib + PLD. Haplotype analysis indicated that the three most frequent haplotypes for ABCB1 may have been associated with response rate in subjects with relapsed multiple myeloma who received bortezomib + PLD treatment (p = 0.0775), though not at the level of statistical significance. Diplotypes that contained 3435T may have been associated with a superior time to progression (p = 0.0819) and progression-free survival (p = 0.0891) in subjects with relapsed multiple myeloma who received bortezomib + PLD when compared to the most frequent diplotype containing 3435C, though not at the level of statistical significance. Conclusions: These findings indicate a potential role for SNPs in both ABCC1 and ABCB1 in modulating the long-term outcome of patients with relapsed and/or refractory multiple myeloma treated with the combination of bortezomib + PLD. Moreover, they support additional prospective studies to determine if such data could be incorporated into an algorithm by which therapy in the relapsed and/or refractory setting could be tailored to each individual patient's own genetic make-up. Disclosures: Ricci: Centocor Ortho Biotech Inc.: Employment. Cohen:Johnson & Johnson Pharmaceutical Research and Development: Employment. Favis:Johnson & Johnson Pharmaceutical Research and Development: Employment. Huang:Centocor Ortho Biotech Inc.: Employment. Rackoff:Centocor Ortho Biotech Inc.: Employment. Zhuang:Centocor Ortho Biotech Inc.: Employment. Sonneveld:Centocor Ortho Biotech Inc.: Membership on an entity's Board of Directors or advisory committees.

Introduction: This phase 2 study was conducted to determine the efficacy and safety of erlotinib alone and with bortezomib in patients with non-small cell lung cancer (NSCLC). Methods: Patients with histologically or cytologically confirmed relapsed or refractory stage IIIb/IV NSCLC were randomized (1:1; stratified by baseline histology, smoking history, sex) to receive erlotinib 150 mg/d alone (arm A; n = 25) or in combination with bortezomib 1.6 mg/m 2 , days 1 and 8 (arm B; n = 25) in 21-day cycles. Responses were assessed using Response Evaluation Criteria in Solid Tumors. Tumor samples were evaluated for mutations predicting response. Six additional patients received the combination in a prior dose deescalation stage and were included in safety analyses. Results: Response rates were 16% in arm A and 9% in arm B; disease control rates were 52 and 45%, respectively. The study was halted at the planned interim analysis due to insufficient clinical activity in arm B. Median progression-free survival and overall survival were 2.7 and 7.3 months in arm A, and 1.3 and 8.5 months in arm B. Six-month survival rates were 56.0% in both arms; 12-month rates were 40 and 30% in arms A and B, respectively. Response rate to erlotinib±bortezomib was significantly higher in patients with epidermal growth factor receptor mutations (50 versus 9% for wild type). The most common treatment-related grade ≥3 adverse event was skin rash (three patients in each treatment group). Conclusion: Insufficient activity was seen with erlotinib plus bortezomib in patients with relapsed/refractory advanced NSCLC to warrant a phase 3 study of the combination.

Background The monogenic disease osteogenesis imperfecta (OI) is due to single mutations in either of the collagen genes ColA1 or ColA2, but within the same family a given mutation is accompanied by a wide range of disease severity. Although this phenotypic variability implies the existence of modifier gene variants, genome wide scanning of DNA from OI patients has not been reported. Promising genome wide marker-independent physical methods for identifying disease-related loci have lacked robustness for widespread applicability. Therefore we sought to improve these methods and demonstrate their performance to identify known and novel loci relevant to OI. Results We have improved methods for enriching regions of identity-by-descent (IBD) shared between related, afflicted individuals. The extent of enrichment exceeds 10- to 50-fold for some loci. The efficiency of the new process is shown by confirmation of the identification of the Col1A2 locus in osteogenesis imperfecta patients from Amish families. Moreover the analysis revealed additional candidate linkage loci that may harbour modifier genes for OI; a locus on chromosome 1q includes COX-2, a gene implicated in osteogenesis. Conclusion Technology for physical enrichment of IBD loci is now robust and applicable for finding genes for monogenic diseases and genes for complex diseases. The data support the further investigation of genetic loci other than collagen gene loci to identify genes affecting the clinical expression of osteogenesis imperfecta. The discrimination of IBD mapping will be enhanced when the IBD enrichment procedure is coupled with deep resequencing.