Improved Tumor Purity Metrics in Next-generation Sequencing for Clinical Practice: The Integrated Interpretation of Neoplastic Cellularity and Sequencing Results (IINCaSe) Approach.

Neoplastic cellularity contributes to the analytic sensitivity of most present technologies for mutation detection, such that they underperform when stroma and inflammatory cells dilute a cancer specimen's variant fraction. Thus, tumor purity assessment by light microscopy is used to determine sample adequacy before sequencing and to interpret the significance of negative results and mutant allele fraction afterwards. However, pathologist estimates of tumor purity are imprecise and have limited reproducibility. With the advent of massively parallel sequencing, large amounts of molecular data can be analyzed by computational purity algorithms. We retrospectively compared tumor purity of 3 computational algorithms with neoplastic cellularity using hematoxylin and eosin light microscopy to determine which was best for clinical evaluation of molecular profiling. Data were analyzed from 881 cancer patients from a clinical trial cohort, LCCC1108 (UNCseq), whose tumors had targeted massively parallel sequencing. Concordance among algorithms was poor, and the specimens analyzed had high rates of algorithm failure partially due to variable tumor purity. Computational tumor purity estimates did not add value beyond the pathologist's estimate of neoplastic cellularity microscopy. To improve present methods, we propose a semiquantitative, clinically applicable strategy based on mutant allele fraction and copy number changes present within a given specimen, which when combined with the morphologic tumor purity estimate, guide the interpretation of next-generation sequencing results in cancer patients.

Diagnostic accuracy and prediction increment of markers of epithelial-mesenchymal transition to assess cancer cell detachment from primary tumors.

BACKGROUND: Metastases play a role in about 90% of cancer deaths. Markers of epithelial-mesenchymal transition (EMT) measured in primary tumor cancer cells might provide diagnostic information about the likelihood that cancer cells have detached from the primary tumor. Used together with established diagnostic tests of detachment-lymph node evaluation and radiologic imaging-EMT marker measurements might improve the ability of clinicians to assess the patient's risk of metastatic disease. Translation of EMT markers to clinical use has been hampered by a lack of valid analyses of clinically-informative parameters. Here, we demonstrate a rigorous approach to estimating the sensitivity, specificity, and prediction increment of an EMT marker to assess cancer cell detachment from primary tumors. METHODS: We illustrate the approach using immunohistochemical measurements of the EMT marker E-cadherin in a set of colorectal primary tumors from a population-based prospective cohort in North Carolina. Bayesian latent class analysis was used to estimate sensitivity and specificity in a setting of multiple imperfect diagnostic tests and no gold standard. Risk reclassification analysis was used to assess the extent to which addition of the marker to the panel of established diagnostic tests would improve mortality prediction. We explored how changing the latent class conditional dependence assumptions and definition of marker positivity would impact the results. RESULTS: All diagnostic accuracy and prediction increment statistics varied with the choice of cut point to define marker positivity. When comparing different definitions of marker positivity to each other, numerous trade-offs were observed in terms of sensitivity, specificity, predictive discrimination, and prediction model calibration. We then discussed several implementation considerations and the plausibility of analytic assumptions. CONCLUSIONS: The approaches presented here can be extended to any EMT marker, to most forms of cancer, and to different kinds of EMT marker measurements, such as RNA or gene methylation data. These methods provide valid, clinically-informative assessment of whether and how to use a given EMT marker to refine tumor staging and consequent treatment decisions.

Enhancing Next-Generation Sequencing-Guided Cancer Care Through Cognitive Computing.

BACKGROUND: Using next-generation sequencing (NGS) to guide cancer therapy has created challenges in analyzing and reporting large volumes of genomic data to patients and caregivers. Specifically, providing current, accurate information on newly approved therapies and open clinical trials requires considerable manual curation performed mainly by human "molecular tumor boards" (MTBs). The purpose of this study was to determine the utility of cognitive computing as performed by Watson for Genomics (WfG) compared with a human MTB. MATERIALS AND METHODS: One thousand eighteen patient cases that previously underwent targeted exon sequencing at the University of North Carolina (UNC) and subsequent analysis by the UNCseq informatics pipeline and the UNC MTB between November 7, 2011, and May 12, 2015, were analyzed with WfG, a cognitive computing technology for genomic analysis. RESULTS: Using a WfG-curated actionable gene list, we identified additional genomic events of potential significance (not discovered by traditional MTB curation) in 323 (32%) patients. The majority of these additional genomic events were considered actionable based upon their ability to qualify patients for biomarker-selected clinical trials. Indeed, the opening of a relevant clinical trial within 1 month prior to WfG analysis provided the rationale for identification of a new actionable event in nearly a quarter of the 323 patients. This automated analysis took <3 minutes per case. CONCLUSION: These results demonstrate that the interpretation and actionability of somatic NGS results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing could potentially improve patient care by providing a rapid, comprehensive approach for data analysis and consideration of up-to-date availability of clinical trials. IMPLICATIONS FOR PRACTICE: The results of this study demonstrate that the interpretation and actionability of somatic next-generation sequencing results are evolving too rapidly to rely solely on human curation. Molecular tumor boards empowered by cognitive computing can significantly improve patient care by providing a fast, cost-effective, and comprehensive approach for data analysis in the delivery of precision medicine. Patients and physicians who are considering enrollment in clinical trials may benefit from the support of such tools applied to genomic data.

A Phase 2/3 Multicenter, Randomized, Open-Label Study to Compare the Efficacy and Safety of Lenalidomide Versus Investigator's Choice in Patients with Relapsed or Refractory Diffuse Large B-Cell Lymphoma.

Purpose: Randomized, multicenter, open-label, phase 2/3 trial investigating lenalidomide versus investigator's choice (IC) in relapsed/refractory diffuse large B-cell lymphoma (DLBCL).Experimental Design: Patients with DLBCL who received ≥2 prior therapies were stratified by DLBCL subtype [germinal center B-cell (GCB) vs. non-GCB; determined by immunohistochemistry (IHC)] and then randomized 1:1 to lenalidomide (25 mg/day, 21 days of 28-day cycle) or IC (gemcitabine, rituximab, etoposide, or oxaliplatin). Crossover to lenalidomide was permitted for IC-treated patients with radiologically confirmed progressive disease. The primary endpoint was overall response rate (ORR). Progression-free survival (PFS), overall survival, and subtype analysis [GCB vs. activated B-cell (ABC)] using gene expression profiling (GEP) were exploratory endpoints.Results: Stage 1: 102 DLBCL patients (by IHC: non-GCB, n = 54; GCB, n = 48) received ≥1 dose of lenalidomide or IC. Hematologic treatment-emergent adverse events with lenalidomide versus IC included neutropenia (42.6%; 36.4%), anemia (33.3%; 47.3%), thrombocytopenia (24.1%; 43.6%), and leukopenia (5.6%; 12.7%), respectively. Overall, lenalidomide-treated patients had an ORR of 27.5% versus 11.8% in IC (ORRs were similar regardless of IHC-defined DLBCL subtype). Median PFS was increased in patients receiving lenalidomide (13.6 weeks) versus IC (7.9 weeks; P = 0.041), with greater improvements in non-GCB patients (15.1 vs. 7.1 weeks, respectively; P = 0.021) compared with GCB (10.1 vs. 9.0 weeks, respectively; P = 0.550).Conclusions: The clinical benefit of lenalidomide monotherapy in DLBCL patients was more evident in the non-GCB subtype. Exploratory analyses suggest that this preferential benefit was more pronounced in the GEP-defined ABC population, demonstrating a need for additional studies of lenalidomide in DLBCL using GEP subtyping. Clin Cancer Res; 23(15); 4127-37. ©2017 AACR.

The molecular basis of breast cancer pathological phenotypes.

The histopathological evaluation of morphological features in breast tumours provides prognostic information to guide therapy. Adjunct molecular analyses provide further diagnostic, prognostic and predictive information. However, there is limited knowledge of the molecular basis of morphological phenotypes in invasive breast cancer. This study integrated genomic, transcriptomic and protein data to provide a comprehensive molecular profiling of morphological features in breast cancer. Fifteen pathologists assessed 850 invasive breast cancer cases from The Cancer Genome Atlas (TCGA). Morphological features were significantly associated with genomic alteration, DNA methylation subtype, PAM50 and microRNA subtypes, proliferation scores, gene expression and/or reverse-phase protein assay subtype. Marked nuclear pleomorphism, necrosis, inflammation and a high mitotic count were associated with the basal-like subtype, and had a similar molecular basis. Omics-based signatures were constructed to predict morphological features. The association of morphology transcriptome signatures with overall survival in oestrogen receptor (ER)-positive and ER-negative breast cancer was first assessed by use of the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset; signatures that remained prognostic in the METABRIC multivariate analysis were further evaluated in five additional datasets. The transcriptomic signature of poorly differentiated epithelial tubules was prognostic in ER-positive breast cancer. No signature was prognostic in ER-negative breast cancer. This study provided new insights into the molecular basis of breast cancer morphological phenotypes. The integration of morphological with molecular data has the potential to refine breast cancer classification, predict response to therapy, enhance our understanding of breast cancer biology, and improve clinical management. This work is publicly accessible at www.dx.ai/tcga_breast. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Identification of Human Papillomavirus Infection in Cancer Tissue by Targeted Next-generation Sequencing.

Human papillomaviruses (HPV) are oncogenic DNA viruses implicated in squamous cell carcinomas of several anatomic sites, as well as endocervical adenocarcinomas. Identification of HPV is an actionable finding in some carcinomas, potentially influencing tumor classification, prognosis, and management. We incorporated capture probes for oncogenic HPV strains 16 and 18 into a broader next-generation sequencing (NGS) panel designed to identify actionable mutations in solid malignancies. A total of 21 head and neck, genitourinary, and gynecologic squamous cell carcinomas and endocervical adenocarcinomas were sequenced as part of the UNCSeq project. Using p16 immunohistochemical results as the gold standard, we set a cutoff for proportion of aligned HPV reads that maximized performance of our NGS assay (92% sensitive, 100% specific for HPV). These results suggest that sequencing of oncogenic pathogens can be incorporated into targeted NGS panels, extending the clinical utility of genomic assays.

Evaluating markers of epithelial-mesenchymal transition to identify cancer patients at risk for metastatic disease.

Most cancer deaths are due to metastases. Markers of epithelial-mesenchymal transition (EMT) measured in primary tumor cancer cells could be helpful to assess patient risk of metastatic disease, even among those otherwise diagnosed with local disease. Previous studies of EMT markers and patient outcomes used inconsistent methods and did not compare the clinical impact of different expression cut points for the same marker. Using digital image analysis, we measured the EMT markers Snail and E-cadherin in primary tumor specimens from 190 subjects in tissue microarrays from a population-based prospective cohort of colorectal cancer patients and estimated their associations with time-to-death. After measuring continuous marker expression data, we performed a systematic search for the cut point for each marker with the best model fit between dichotomous marker expression and time-to-death. We also assessed the potential clinical impact of different cut points for the same marker. After dichotomizing expression status at the statistically-optimal cut point, we found that Snail expression was not associated with time-to-death. When measured as a weighted average of tumor cores, low E-cadherin expression was associated with a greater risk of dying within 5 years of surgery than high expression (risk difference = 33 %, 95 % confidence interval 3-62 %). Identifying a clinically-optimal cut point for an EMT marker requires trade-offs between strength and precision of the association with patient outcomes, as well as consideration of the number of patients whose treatments might change based on using the marker at a given cut point.

Combined Targeted DNA Sequencing in Non-Small Cell Lung Cancer (NSCLC) Using UNCseq and NGScopy, and RNA Sequencing Using UNCqeR for the Detection of Genetic Aberrations in NSCLC.

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07-0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11-1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion.

Targeted next generation sequencing identifies clinically actionable mutations in patients with melanoma.

Somatic sequencing of cancers has produced new insight into tumorigenesis, tumor heterogeneity, and disease progression, but the vast majority of genetic events identified are of indeterminate clinical significance. Here, we describe a NextGen sequencing approach to fully analyzing 248 genes, including all those of known clinical significance in melanoma. This strategy features solution capture of DNA followed by multiplexed, high-throughput sequencing and was evaluated in 31 melanoma cell lines and 18 tumor tissues from patients with metastatic melanoma. Mutations in melanoma cell lines correlated with their sensitivity to corresponding small molecule inhibitors, confirming, for example, lapatinib sensitivity in ERBB4 mutant lines and identifying a novel activating mutation of BRAF. The latter event would not have been identified by clinical sequencing and was associated with responsiveness to a BRAF kinase inhibitor. This approach identified focal copy number changes of PTEN not found by standard methods, such as comparative genomic hybridization (CGH). Actionable mutations were found in 89% of the tumor tissues analyzed, 56% of which would not be identified by standard-of-care approaches. This work shows that targeted sequencing is an attractive approach for clinical use in melanoma.

Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration.

High-throughput 'omics' technologies that generate molecular profiles for biospecimens have been extensively used in preclinical studies to reveal molecular subtypes and elucidate the biological mechanisms of disease, and in retrospective studies on clinical specimens to develop mathematical models to predict clinical endpoints. Nevertheless, the translation of these technologies into clinical tests that are useful for guiding management decisions for patients has been relatively slow. It can be difficult to determine when the body of evidence for an omics-based test is sufficiently comprehensive and reliable to support claims that it is ready for clinical use, or even that it is ready for definitive evaluation in a clinical trial in which it may be used to direct patient therapy. Reasons for this difficulty include the exploratory and retrospective nature of many of these studies, the complexity of these assays and their application to clinical specimens, and the many potential pitfalls inherent in the development of mathematical predictor models from the very high-dimensional data generated by these omics technologies. Here we present a checklist of criteria to consider when evaluating the body of evidence supporting the clinical use of a predictor to guide patient therapy. Included are issues pertaining to specimen and assay requirements, the soundness of the process for developing predictor models, expectations regarding clinical study design and conduct, and attention to regulatory, ethical, and legal issues. The proposed checklist should serve as a useful guide to investigators preparing proposals for studies involving the use of omics-based tests. The US National Cancer Institute plans to refer to these guidelines for review of proposals for studies involving omics tests, and it is hoped that other sponsors will adopt the checklist as well.

Criteria for the use of omics-based predictors in clinical trials.

The US National Cancer Institute (NCI), in collaboration with scientists representing multiple areas of expertise relevant to 'omics'-based test development, has developed a checklist of criteria that can be used to determine the readiness of omics-based tests for guiding patient care in clinical trials. The checklist criteria cover issues relating to specimens, assays, mathematical modelling, clinical trial design, and ethical, legal and regulatory aspects. Funding bodies and journals are encouraged to consider the checklist, which they may find useful for assessing study quality and evidence strength. The checklist will be used to evaluate proposals for NCI-sponsored clinical trials in which omics tests will be used to guide therapy.

Tissue pattern recognition error rates and tumor heterogeneity in gastric cancer.

The anatomic pathology discipline is slowly moving toward a digital workflow, where pathologists will evaluate whole-slide images on a computer monitor rather than glass slides through a microscope. One of the driving factors in this workflow is computer-assisted scoring, which depends on appropriate selection of regions of interest. With advances in tissue pattern recognition techniques, a more precise region of the tissue can be evaluated, no longer bound by the pathologist's patience in manually outlining target tissue areas. Pathologists use entire tissues from which to determine a score in a region of interest when making manual immunohistochemistry assessments. Tissue pattern recognition theoretically offers this same advantage; however, error rates exist in any tissue pattern recognition program, and these error rates contribute to errors in the overall score. To provide a real-world example of tissue pattern recognition, 11 HER2-stained upper gastrointestinal malignancies with high heterogeneity were evaluated. HER2 scoring of gastric cancer was chosen due to its increasing importance in gastrointestinal disease. A method is introduced for quantifying the error rates of tissue pattern recognition. The trade-off between fully sampling tumor with a given tissue pattern recognition error rate versus randomly sampling a limited number of fields of view with higher target accuracy was modeled with a Monte-Carlo simulation. Under most scenarios, stereological methods of sampling-limited fields of view outperformed whole-slide tissue pattern recognition approaches for accurate immunohistochemistry analysis. The importance of educating pathologists in the use of statistical sampling is discussed, along with the emerging role of hybrid whole-tissue imaging and stereological approaches.

Evaluating tumor heterogeneity in immunohistochemistry-stained breast cancer tissue.

Quantitative clinical measurement of heterogeneity in immunohistochemistry staining would be useful in evaluating patient therapeutic response and in identifying underlying issues in histopathology laboratory quality control. A heterogeneity scoring approach (HetMap) was designed to visualize a individual patient's immunohistochemistry heterogeneity in the context of a patient population. HER2 semiquantitative analysis was combined with ecology diversity statistics to evaluate cell-level heterogeneity (consistency of protein expression within neighboring cells in a tumor nest) and tumor-level heterogeneity (differences of protein expression across a tumor as represented by a tissue section). This approach was evaluated on HER2 immunohistochemistry-stained breast cancer samples using 200 specimens across two different laboratories with three pathologists per laboratory, each outlining regions of tumor for scoring by automatic cell-based image analysis. HetMap was evaluated using three different scoring schemes: HER2 scoring according to American Society of Clinical Oncology and College of American Pathologists (ASCO/CAP) guidelines, H-score, and a new continuous HER2 score (HER2(cont)). Two definitions of heterogeneity, cell-level and tumor-level, provided useful independent measures of heterogeneity. Cases where pathologists had disagreement over reads in the area of clinical importance (+1 and +2) had statistically significantly higher levels of tumor-level heterogeneity. Cell-level heterogeneity, reported either as an average or the maximum area of heterogeneity across a slide, had low levels of dependency on the pathologist choice of region, while tumor-level heterogeneity measurements had more dependence on the pathologist choice of regions. HetMap is a measure of heterogeneity, by which pathologists, oncologists, and drug development organizations can view cell-level and tumor-level heterogeneity for a patient for a given marker in the context of an entire patient cohort. Heterogeneity analysis can be used to identify tumors with differing degrees of heterogeneity, or to highlight slides that should be rechecked for QC issues. Tumor heterogeneity plays a significant role in disconcordant reads between pathologists.

Diverse somatic mutation patterns and pathway alterations in human cancers.

The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics. Here we report the identification of 2,576 somatic mutations across approximately 1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. We found that mutation rates and the sets of mutated genes varied substantially across tumour types and subtypes. Statistical analysis identified 77 significantly mutated genes including protein kinases, G-protein-coupled receptors such as GRM8, BAI3, AGTRL1 (also called APLNR) and LPHN3, and other druggable targets. Integrated analysis of somatic mutations and copy number alterations identified another 35 significantly altered genes including GNAS, indicating an expanded role for galpha subunits in multiple cancer types. Furthermore, our experimental analyses demonstrate the functional roles of mutant GNAO1 (a Galpha subunit) and mutant MAP2K4 (a member of the JNK signalling pathway) in oncogenesis. Our study provides an overview of the mutational spectra across major human cancers and identifies several potential therapeutic targets.

A tumor sorting protocol that enables enrichment of pancreatic adenocarcinoma cells and facilitation of genetic analyses.

Molecular profiling of human cancer is complicated by both stromal contamination and cellular heterogeneity within samples from tumor biopsies. In this study, we developed a tissue-processing protocol using mechanical dissociation and flow cytometric sorting that resulted in the respective enrichment of stromal and tumor fractions from frozen pancreatic adenocarcinoma samples. Molecular profiling of DNA from the sorted populations using high-density single nucleotide polymorphism arrays revealed widespread chromosomal loss of heterozygosity in tumor fractions but not in either the stromal fraction or unsorted tissue specimens from the same sample. Similarly, a combination of KRAS mutations and chromosomal copy number changes at key pancreatic cancer loci, such as CDK2NA and TP53, was detected in a substantial proportion of the tumor fractions but not in matched stromal fractions from the same sample. This approach to tissue processing could greatly expand the amount of archived tissue that is available for molecular profiling of human cancer and enable a more accurate diagnosis of genetic alterations in patient samples.

Biomarkers of response to epidermal growth factor receptor inhibitors in Non-Small-Cell Lung Cancer Working Group: standardization for use in the clinical trial setting.

The body of literature on the correlations between molecular assessments and patient outcomes after treatment with epidermal growth factor receptor (EGFR) inhibitors continues to grow. It will be important in the future to determine how to most effectively integrate molecular assays that assess the likelihood of therapeutic benefit into clinical practice. Although EGFR-targeted therapies such as erlotinib have been approved for use without molecular testing, immunohistochemistry, fluorescence in situ hybridization, and mutational analyses of the EGFR gene have all been proposed as candidates to help predict response or survival benefit from EGFR-targeted therapy in patients with non-small-cell lung cancer (NSCLC). Further prospective validation from ongoing randomized studies will be needed to fully determine which assays are best to help predict patient outcome. In addition, it will be critical for these assays to undergo standardization before widespread clinical use. The Molecular Assays in NSCLC Working Group, under the sponsorship of Genentech Inc, Roche Pharmaceuticals, and OSI Pharmaceuticals, Inc, was convened to evaluate the available molecular assays for use in the clinical trial setting and provide recommendations for application and interpretation of these tests for future clinical trials. Recommendations of the Molecular Assays in NSCLC Working Group for the use of EGFR molecular assays are presented and include guidelines for tissue storage, handling, and processing. Recommendations for the standardization of molecular assays are also discussed.

Efficacy and safety of single-agent pertuzumab, a human epidermal receptor dimerization inhibitor, in patients with non small cell lung cancer.

PURPOSE: Pertuzumab, a first-in-class human epidermal receptor 2 (HER2) dimerization inhibitor, is a humanized monoclonal anti-HER2 antibody that binds HER2's dimerization domain and inhibits HER2 signaling. Based on supporting preclinical studies, we undertook a Phase II trial of pertuzumab in patients with recurrent non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: Patients with previously treated NSCLC accessible for core biopsy and naive to HER pathway inhibitors were treated with pertuzumab i.v. once every 3 weeks. Tumor assessments were done at 6 and 12 weeks and then every 3 months thereafter. The primary efficacy end point was overall response rate by Response Evaluation Criteria in Solid Tumors. Measurement of tumor glucose metabolism (SUVmax) by F-18-fluorodeoxyglucose positron emission tomography was used as an exploratory pharmacodynamic marker of drug activity. RESULTS: Of 43 patients treated with pertuzumab, no responses were seen; 18 of 43 (41.9%) and 9 of 43 (20.9%) patients had stable disease at 6 and 12 weeks, respectively. The median and 3-month progression-free survival rates (PFS) were 6.1 weeks (95% confidence interval, 5.3-11.3 weeks) and 28.4% (95% confidence interval, 14.4-44.2%), respectively. Of 22 patients who underwent F-18-fluorodeoxyglucose positron emission tomography, six (27.3%) had a metabolic response to pertuzumab as evidenced by decreased SUV max. These patients had prolonged PFS (HR = 0.11, log-rank P value = 0.018) compared with the 16 patients who had no metabolic response. Four patients (9.3%) experienced a grade 3/grade 4 adverse event judged related to pertuzumab; none exhibited grade 3/grade 4 cardiac toxicity. CONCLUSIONS: Pertuzumab is well tolerated as monotherapy. Pharmacodynamic activity correlated with prolonged PFS was detected in a moderate percentage of patients (27.3%). Further clinical development of pertuzumab should focus on rational combinations of pertuzumab with other drugs active in NSCLC.

Highly efficient somatic-mutation identification using Escherichia coli mismatch-repair detection.

The discovery of somatic mutations in cancer tissue is extremely laborious, time-consuming and costly. In an evaluation comparing mismatch repair detection (MRD) against Sanger sequencing for somatic-mutation detection, we found that MRD had a specificity of 96% and a sensitivity of 92%. Our results showed that MRD is a robust and cost-effective alternative to Sanger sequencing for identifying somatic mutations in human tumors.

Clinical activity of pertuzumab (rhuMAb 2C4), a HER dimerization inhibitor, in advanced ovarian cancer: potential predictive relationship with tumor HER2 activation status.

PURPOSE: Ovarian cancers (OCs) frequently have HER2 activation in the absence of HER2 overexpression. Pertuzumab, a humanized antibody that prevents HER2 dimerization and inhibits multiple HER-mediated pathways, was studied in a phase II, multicenter trial in advanced, refractory OC. PATIENTS AND METHODS: Sixty-one patients (cohort 1) with relapsed OC received a loading dose of 840 mg pertuzumab intravenously followed by 420 mg every 3 weeks; 62 patients (cohort 2) received 1,050 mg every 3 weeks. Response rate was the primary end point. Fresh tumor biopsies were obtained in cohort 1 to assay for phosphorylated HER2 (pHER2). RESULTS: Median age was 57 years and median number of prior chemotherapy regimens was five. Fifty-five patients in cohort 1 and 62 patients in cohort 2 were assessable for efficacy. There were five partial responses (response rate [RR] = 4.3%; 95% CI, 1.7% to 9.4%), eight patients (6.8%) with stable disease (SD) lasting at least 6 months, and 10 patients with CA-125 reduction of at least 50% (includes two partial responses and four patients with SD > or = 6 months; total clinical activity, 14.5%). Median progression-free survival (PFS) was 6.6 weeks. Eight of 28 tumor biopsies (28.6%) were pHER2+ by enzyme-linked immunosorbent assay (ELISA; without gene amplification). Median PFS for pHER2+ patients was 20.9 weeks (n = 8) versus 5.8 weeks for pHER2- (n = 20; P = .14) and 9.1 weeks for unknown pHER2 status (n = 27). Pertuzumab was well tolerated with diarrhea in 69.1% (11.4% grade 3, no grade 4). Five patients had asymptomatic left ventricular ejection fraction decreases to less than 50% (one confirmed by central facility). CONCLUSION: Pertuzumab is well tolerated with a RR of 4.3% in heavily-pretreated OC patients. Further studies on pHER2 as a diagnostic are warranted.