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A subset of drug-resistant EGFR -mutant MET -amplified lung cancer switches oncogenic dependence to MET and is treatable with MET inhibitor monotherapy.

Introduction Osimertinib is approved for advanced EGFR-mutated NSCLC, and identification of on-target mechanisms of resistance (i.e., EGFR C797S) to this third-generation EGFR inhibitor are evolving. Whether durable control of subsequently osimertinib-resistant NSCLC with the EGFR-sensitizing mutation (SM)/C797S is possible with first-generation EGFR inhibitors (such as gefitinib or erlotinib) remains underreported, as does the resultant acquired resistance profile. Methods We used N-ethyl-N-nitrosourea mutagenesis to determine the profile of EGFR SM/C797S preclinical models exposed to reversible EGFR inhibitors. In addition, we retrospectively probed a case of EGFR SM lung adenocarcinoma treated with first-line osimertinib, followed by second-line erlotinib in the setting of EGFR SM/C797S. Results Use of N-ethyl-N-nitrosourea mutagenesis against the background of EGFR L858R/C797S in conjunction with administration of gefitinib revealed preferential outgrowth of cells with EGFR L858R/T790M/C797S. A patient with EGFR delE746_T751insV NSCLC was treated with osimertinib with sustained response for 10 months before acquiring EGFR C797S. The patient was subsequently treated with erlotinib, with response for a period of 4 months, but disease progression ensued. Liquid biopsy disclosed EGFR delE746_T751insV with T790M and C797S present in cis. Conclusion EGFR SM NSCLC can acquire resistance to osimertinib through development of the EGFR C797S mutation. In this clinical scenario, the tumor may respond transiently to reversible first-generation EGFR inhibitors (gefitinib or erlotinib), but evolving mechanisms of on-target resistance—in clinical specimens and preclinical systems—indicate that EGFR C797S along with EGFR T790M can evolve. This report adds to the growing understanding of tumor evolution or adaptability to sequential EGFR inhibition and augments support for exploring combination therapies to delay or prevent on-target resistance.

Background Noninvasive genotyping using plasma cell-free DNA (cfDNA) has the potential to obviate the need for some invasive biopsies in cancer patients while also elucidating disease heterogeneity. We sought to develop an ultra-deep plasma next-generation sequencing (NGS) assay for patients with non-small-cell lung cancers (NSCLC) that could detect targetable oncogenic drivers and resistance mutations in patients where tissue biopsy failed to identify an actionable alteration. Patients and methods Plasma was prospectively collected from patients with advanced, progressive NSCLC. We carried out ultra-deep NGS using cfDNA extracted from plasma and matched white blood cells using a hybrid capture panel covering 37 lung cancer-related genes sequenced to 50 000× raw target coverage filtering somatic mutations attributable to clonal hematopoiesis. Clinical sensitivity and specificity for plasma detection of known oncogenic drivers were calculated and compared with tissue genotyping results. Orthogonal ddPCR validation was carried out in a subset of cases. Results In 127 assessable patients, plasma NGS detected driver mutations with variant allele fractions ranging from 0.14% to 52%. Plasma ddPCR for EGFR or KRAS mutations revealed findings nearly identical to those of plasma NGS in 21 of 22 patients, with high concordance of variant allele fraction (r = 0.98). Blinded to tissue genotype, plasma NGS sensitivity for de novo plasma detection of known oncogenic drivers was 75% (68/91). Specificity of plasma NGS in those who were driver-negative by tissue NGS was 100% (19/19). In 17 patients with tumor tissue deemed insufficient for genotyping, plasma NGS identified four KRAS mutations. In 23 EGFR mutant cases with acquired resistance to targeted therapy, plasma NGS detected potential resistance mechanisms, including EGFR T790M and C797S mutations and ERBB2 amplification. Conclusions Ultra-deep plasma NGS with clonal hematopoiesis filtering resulted in de novo detection of targetable oncogenic drivers and resistance mechanisms in patients with NSCLC, including when tissue biopsy was inadequate for genotyping.

BACKGROUND Although interest in droplet-digital PCR technology (ddPCR) for cell-free circulating DNA (cfDNA) analysis is burgeoning, the technology is compromised by subsampling errors and the few clinical targets that can be analyzed from limited input DNA. The paucity of starting material acts as a “glass ceiling” in liquid biopsies because, irrespective how analytically sensitive ddPCR techniques are, detection limits cannot be improved past DNA input limitations. METHODS We applied denaturation-enhanced ddPCR (dddPCR) using fragmented genomic DNA (gDNA) with defined mutations. We then tested dddPCR on cfDNA from volunteers and patients with cancer for commonly-used mutations. gDNA and cfDNA were tested with and without end repair before denaturation and digital PCR. RESULTS By applying complete denaturation of double-stranded DNA before ddPCR droplet formation the number of positive droplets increased. dddPCR using gDNA resulted in a 1.9–2.0-fold increase in data-positive droplets, whereas dddPCR applied on highly-fragmented cfDNA resulted in a 1.6–1.7-fold increase. End repair of cfDNA before denaturation enabled cfDNA to display a 1.9–2.0-fold increase in data-positive signals, similar to gDNA. Doubling of data-positive droplets doubled the number of potential ddPCR assays that could be conducted from a given DNA input and improved ddPCR precision for cfDNA mutation detection. CONCLUSIONS dddPCR is a simple and useful modification in ddPCR that enables extraction of more information from low-input clinical samples with minor change in protocols. It should be applicable to all ddPCR platforms for mutation detection and, potentially, for gene copy-number analysis in cancer and prenatal screening.

Background Tumor genotyping is transforming lung cancer care but requires adequate tumor tissue. Advances in minimally invasive biopsy techniques have increased access to difficult-to-access lesions, but often result in smaller samples. With the advent of highly sensitive DNA genotyping methods used for plasma analysis, we hypothesized that these same methods might allow genotyping of free DNA derived from fine needle aspiration supernatant (FNA-S). Methods We studied patients with known or suspected lung cancer undergoing fine needle aspirate (FNA). After spinning the sample for cellblock, the FNA-S (usually discarded) was saved for genotyping. Supernatant cell-free DNA (SN-cfDNA) was extracted and tested by both droplet digital PCR (EGFR, BRAF, KRAS mutations) and highly sensitive amplicon-based next-generation sequencing (NGS). Results 17 samples were studied, including 11 FNAs from patients with suspected lung cancer and 6 FNAs from patients with lung cancer and acquired drug resistance. Of 6 newly diagnosed adenocarcinomas, 4 had a driver mutations (1 EGFR, 2 KRAS, 1 HER2) found on tissue; all of these could be detected in SN-cfDNA. The EGFR driver mutation was detected in all 5 adenocarcinomas with acquired EGFR resistance and the EGFR T790 M in three cases, in agreement with cellblock. Conclusions FNA-S is a rich source of fresh tumor DNA, potentially increasing the diagnostic yield from small FNAs. Through use of emerging techniques for highly sensitive genotyping, this widely available biospecimen has potential for facilitating rapid cancer genotyping at diagnosis and after drug resistance.

Background Genomic analysis of plasma cell-free DNA is transforming lung cancer care; however, available assays are limited by cost, turnaround time, and imperfect accuracy. Here, we study amplicon-based plasma next-generation sequencing (NGS), rather than hybrid-capture-based plasma NGS, hypothesizing this would allow sensitive detection and monitoring of driver and resistance mutations in advanced non-small cell lung cancer (NSCLC). Patients and methods Plasma samples from patients with NSCLC and a known targetable genotype (EGFR, ALK/ROS1, and other rare genotypes) were collected while on therapy and analyzed blinded to tumor genotype. Plasma NGS was carried out using enhanced tagged amplicon sequencing of hotspots and coding regions from 36 genes, as well as intronic coverage for detection of ALK/ROS1 fusions. Diagnostic accuracy was compared with plasma droplet digital PCR (ddPCR) and tumor genotype. Results A total of 168 specimens from 46 patients were studied. Matched plasma NGS and ddPCR across 120 variants from 80 samples revealed high concordance of allelic fraction (R2 = 0.95). Pretreatment, sensitivity of plasma NGS for the detection of EGFR driver mutations was 100% (30/30), compared with 87% for ddPCR (26/30). A full spectrum of rare driver oncogenic mutations could be detected including sensitive detection of ALK/ROS1 fusions (8/9 detected, 89%). Studying 25 patients positive for EGFR T790M that developed resistance to osimertinib, 15 resistance mechanisms could be detected including tertiary EGFR mutations (C797S, Q791P) and mutations or amplifications of non-EGFR genes, some of which could be detected pretreatment or months before progression. Conclusions This blinded analysis demonstrates the ability of amplicon-based plasma NGS to detect a full range of targetable genotypes in NSCLC, including fusion genes, with high accuracy. The ability of plasma NGS to detect a range of preexisting and acquired resistance mechanisms highlights its potential value as an alternative to single mutation digital PCR-based plasma assays for personalizing treatment of TKI resistance in lung cancer.

In the past several years, interest in the clinical utility of cell-free DNA as a noninvasive cancer biomarker has grown rapidly. Success in the development of plasma genotyping assays and other liquid biopsy assays has widened the scope of cell-free DNA use in research and the clinic. Already approved by the US Food and Drug Administration in the narrow context of epidermal growth factor receptor-mutated non-small cell lung cancer, plasma genotyping assays are currently being investigated in a wide array of clinical settings and modalities. These include plasma genotyping as a tool for early diagnosis, the detection of minimal residual disease, and the evaluation of treatment response/progression. In this review, we assess the clinical landscape of plasma genotyping assays and propose strategies for their further expansion into routine clinical care.

Non–small cell lung cancers (NSCLC) that have developed resistance to EGF receptor (EGFR) tyrosine kinase inhibitor (TKI), including gefitinib and erlotinib, are clinically linked to an epithelial-to-mesenchymal transition (EMT) phenotype. Here, we examined whether modulating EMT maintains the responsiveness of EGFR-mutated NSCLCs to EGFR TKI therapy. Using human NSCLC cell lines harboring mutated EGFR and a transgenic mouse model of lung cancer driven by mutant EGFR (EGFR-Del19-T790M), we demonstrate that EGFR inhibition induces TGFβ secretion followed by SMAD pathway activation, an event that promotes EMT. Chronic exposure of EGFR-mutated NSCLC cells to TGFβ was sufficient to induce EMT and resistance to EGFR TKI treatment. Furthermore, NSCLC HCC4006 cells with acquired resistance to gefitinib were characterized by a mesenchymal phenotype and displayed a higher prevalence of the EGFR T790M mutated allele. Notably, combined inhibition of EGFR and the TGFβ receptor in HCC4006 cells prevented EMT but was not sufficient to prevent acquired gefitinib resistance because of an increased emergence of the EGFR T790M allele compared with cells treated with gefitinib alone. Conversely, another independent NSCLC cell line, PC9, reproducibly developed EGFR T790M mutations as the primary mechanism underlying EGFR TKI resistance, even though the prevalence of the mutant allele was lower than that in HCC4006 cells. Thus, our findings underscore heterogeneity within NSCLC cells lines harboring EGFR kinase domain mutations that give rise to divergent resistance mechanisms in response to treatment and anticipate the complexity of EMT suppression as a therapeutic strategy. Cancer Res; 75(20); 4372–83. ©2015 AACR.

Patients with EGFR-mutant non-small-cell lung cancer generally have a progression-free survival of 9-13 months while being treated with the EGFR tyrosine-kinase inhibitors gefitinib or erlotinib. However, resistance inevitably develops, and more effective EGFR inhibitors are needed. Dacomitinib is a covalent pan-HER inhibitor that has shown clinical activity in patients previously treated with gefitinib or erlotinib. We did a trial of dacomitinib as initial systemic therapy in clinically and molecularly selected patients with advanced non-small-cell lung cancer.In this open-label, multicentre, phase 2 trial, we enrolled treatment-naive patients with advanced lung cancer who had clinical (never-smokers [100 cigarettes per lifetime] or former light smokers [10 pack-years per lifetime] and ≥15 years since last cigarette) or molecular (EGFR mutation, regardless of smoking status) characteristics associated with response to EGFR inhibitors. We gave dacomitinib orally once daily (45 mg or 30 mg) until progressive disease, unacceptable toxicity, or patient withdrawal. We used Response Evaluation Criteria in Solid Tumors criteria (version 1.0) to investigate the activity of dacomitinib in all patients with a baseline scan and at least one post-treatment scan, with investigator assessment of response and progression. The primary endpoint was progression-free survival at 4 months in the as-enrolled population, with a null hypothesis of progression-free survival at 4 months of 50% or less. The study is registered with ClinicalTrials.gov, number NCT00818441, and is no longer accruing patients.Between March 11, 2009, and April 1, 2011, we enrolled 89 patients from 25 centres, including 45 (51%) with EGFR-activating mutations in exon 19 (n=25) or exon 21 (n=20). Progression-free survival at 4 months was 76·8% (95% CI 66·4-84·4) in the as-enrolled population, and was 95·5% (95% CI 83·2-98·9) in the EGFR-mutant population. The most common all-grade treatment-related adverse events were diarrhoea in 83 (93%) patients, dermatitis acneiform in 69 (78%) patients, dry skin in 39 (44%) patients, and stomatitis in 36 (40%) patients. Two patients (2%) had grade 4 treatment-related events (one with hypokalaemia and one with dyspnoea). No grade 5 toxicities were recorded.Dacomitinib had encouraging clinical activity as initial systemic treatment in clinically or molecularly selected patients with advanced non-small-cell lung cancer.Pfizer.

The rapid identification of protein biomarkers in biofluids is important to drug discovery and development. Here, we describe a general proteomic approach for the discovery and identification of proteins that exhibit a statistically significant difference in abundance in cerebrospinal fluid (CSF) before and after pharmacological intervention. This approach, differential mass spectrometry (dMS), is based on the analysis of full scan mass spectrometry data. The dMS workflow does not require complex mixing and pooling strategies, or isotope labeling techniques. Accordingly, clinical samples can be analyzed individually, allowing the use of longitudinal designs and within-subject data analysis in which each subject acts as its own control. As a proof of concept, we performed multifactorial dMS analyses on CSF samples drawn at 6 time points from n = 6 cisterna magna ported (CMP) rhesus monkeys treated with 2 potent gamma secretase inhibitors (GSI) or comparable vehicle in a 3-way crossover study that included a total of 108 individual CSF samples. Using analysis of variance and statistical filtering on the aligned and normalized LC-MS data sets, we detected 26 features that were significantly altered in CSF by drug treatment. Of those 26 features, which belong to 10 distinct isotopic distributions, 20 were identified by MS/MS as 7 peptides from CD99, a cell surface protein. Six features from the remaining 3 isotopic distributions were not identified. A subsequent analysis showed that the relative abundance of these 26 features showed the same temporal profile as the ELISA measured levels of CSF A beta 42 peptide, a known pharmacodynamic marker for gamma-secretase inhibition. These data demonstrate that dMS is a promising approach for the discovery, quantification, and identification of candidate target engagement biomarkers in CSF.

Constitutive activation of one or more kinase signaling pathways is a hallmark of many cancers. Here we extend the previously described mass spectrometry-based KAYAK approach by monitoring kinase activities from multiple signaling pathways simultaneously. This improved single-reaction strategy, which quantifies the phosphorylation of 90 synthetic peptides in a single mass spectrometry run, is compatible with nanogram to microgram amounts of cell lysate. Furthermore, the approach enhances kinase monospecificity through substrate competition effects, faithfully reporting the signatures of many signaling pathways after mitogen stimulation or of basal pathway activation differences across a panel of well-studied cancer cell lines. Hierarchical clustering of activities from related experiments groups peptides phosphorylated by similar kinases together and, when combined with pathway alteration using pharmacological inhibitors, distinguishes underlying differences in potency, off-target effects and genetic backgrounds. Finally, we introduce a strategy to identify the kinase, and even associated protein complex members, responsible for phosphorylation events of interest.

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.

Label-free LC-MS profiling is a powerful quantitative proteomic method to study relative peptide abundances between two or more biological samples. Here we demonstrate the use of a previously described comparative LC-MS method, differential mass spectrometry (dMS), to analyze high-resolution Fourier transform mass spectrometry (FTMS) data for detection and quantification of known peptide differences between two sets of complex mixtures. Six standard peptides were spiked into a processed plasma background at fixed ratios from 1.25:1 to 4:1 to make two sets of samples. The resulting mixtures were analyzed by microcapillary LC-FTMS and dMS. dMS successfully identified five out of the six peptides as statistically significant differences (por= 0.005). In this experiment, the smallest fold change reliably detected by our method was 1.5:1, and the errors of estimated ratios of concentrations were less than 20% for peptides spiked at 1.5:1 to 4:1. We conclude that LC-FTMS coupled with dMS is a useful label-free quantitative MS method that can be used to detect subtle yet statistically significant peptide differences in complex protein mixtures, including plasma samples.

Antibody microarrays are a new proteomic technology, which we have developed as a platform for identifying a cystic fibrosis (CF)-specific serum proteomic signature. Serum samples from CF patients have been pooled and compared with equivalent pools of control sera in order to identify patterns of protein expression unique to CF. We find that the set of significantly differentially expressed proteins is enriched in protein mediators of inflammation from the NFkappaB signaling pathway, and in proteins that may be selectively expressed in CF-affected tissues such as lung and intestine. In several instances, we validate the data from the antibody microarrays by quantitative analysis with Reverse Capture Protein Microarrays. We conclude that antibody microarray technology is sensitive, quantitative, and robust, and can be useful as a proteomic platform to discriminate between sera from CF and control patients.

Reverse phase protein arrays represent a new proteomics microarray technology with which to study the fluctuating state of the proteome in minute quantities of cells. The activation status of cell signaling pathways controls cellular fate and deregulation of these pathways underpins carcinogenesis. Changes in pathway activation that occur between early stage prostatic epithelial lesions, prostatic stroma and the extracellular matrix can be analyzed by obtaining pure populations of cell types by laser capture microdissection (LCM) and analyzing the relative states of several key phosphorylation points within the cellular circuitry. We have applied reverse phase protein array technology to analyze the status of key points in cell signaling involved in pro-survival, mitogenic, apoptotic and growth regulation pathways in the progression from normal prostate epithelium to invasive prostate cancer. Using multiplexed reverse phase protein arrays coupled with LCM, the states of signaling changes during disease progression from prostate cancer study sets were analyzed. Focused analysis of phospho-specific endpoints revealed changes in cellular signaling events through disease progression and between patients. We have used a new protein array technology to study specific molecular pathways believed to be important in cell survival and progression from normal epithelium to invasive carcinoma directly from human tissue specimens. With the advent of molecular targeted therapeutics, the identification, characterization and monitoring of the signaling events within actual human biopsies will be critical for patient-tailored therapy.

Laser capture microdissection was combined with reverse phase protein lysate arrays to quantitatively analyze the ratios of mitochondrial encoded cytochrome c oxidase subunits to nuclear encoded cytochrome c oxidase subunits, and to correlate the ratios with malignant progression in human prostate tissue specimens. Cytochrome c oxidase subunits I-III comprise the catalytic core of the enzyme and are all synthesized from mitochondrial DNA. The remaining subunits (IV-VIII) are synthesized from cellular nuclear DNA. A significant (P < 0.001, 30/30 prostate cases) shift in the relative concentrations of nuclear encoded cytochrome c oxidase subunits IV, Vb, and VIc compared to mitochondrial encoded cytochrome c oxidase subunits I and II was noted during the progression of prostate cancer from normal epithelium through premalignant lesions to invasive carcinoma. Significantly, this shift was discovered to begin even in the premalignant stage. Reverse phase protein lysate array-based observations were corroborated with immunohistochemistry, and extended to a few human carcinomas in addition to prostate. This analysis points to a role for nuclear DNA encoded mitochondrial proteins in carcinogenesis; underscoring their potential as targets for therapy while highlighting the need for full characterization of the mitochondrial proteome.

Protein microarrays offer a new means by which to conduct quantitative profiling of disease-associated proteins. The knowledge gained may provide novel strategies for early detection, diagnosis and therapeutic intervention. A variety of sophisticated approaches, including gene arrays, sequencing consortiums and large-scale two-dimensional gel electrophoresis, continue to generate lists of proteins potentially linked to disease aetiology and progression. The challenge is to evaluate quantitatively promising lead protein candidates using matched normal and diseased cell populations. In contrast to the antibody array, the reverse phase protein microarrays (RPPA) do not require labelling of cellular protein lysates, and constitute a sensitive high throughput platform for marker screening, pathophysiology investigation and therapeutic monitoring. In this paper, examples will be provided using RPPAs in the study of the apoptotic signalling cascade and in the evaluation of the expression of organ-specific protein makers using microdissected human organ cell lysates configured as 'human body arrays'.

Proteomic based approaches are beginning to be utilized to study the natural history and treatment of breast cancer. A variety of proteomics approaches are under study, and are summarized herein. Two-dimensional gel electrophoresis (2D-PAGE) is still the foundation of most proteomics studies. We present an analysis of 2D-PAGE studies reported to date in breast cancer, including those examining normal/tumor differences and selected populations of breast cells. Newer technologies such as laser capture microdissection and highly sensitive mass spectrometry methods are currently being used together to identify greater numbers of lower abundance proteins that are differentially expressed between defined cell populations. Novel technologies still in developmental phases will enable identification of validated targets in small biopsy specimens, including high density protein arrays, antibody arrays and lysate arrays. Surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) analysis enables the high throughput characterization of lysates from very few tumor cells and may be best suited for clinical biomarker studies. We present SELDI-TOF data herein to show the accuracy of the method in a small cohort of breast tumors, as well as its potential discriminatory capability. Such technologies are expected to supplement our armamentarium of mRNA-based assays, and provide critical information on protein levels and post-translational modifications.

Protein arrays are described for screening of molecular markers and pathway targets in patient matched human tissue during disease progression. In contrast to previous protein arrays that immobilize the probe, our reverse phase protein array immobilizes the whole repertoire of patient proteins that represent the state of individual tissue cell populations undergoing disease transitions. A high degree of sensitivity, precision and linearity was achieved, making it possible to quantify the phosphorylated status of signal proteins in human tissue cell subpopulations. Using this novel protein microarray we have longitudinally analysed the state of pro-survival checkpoint proteins at the microscopic transition stage from patient matched histologically normal prostate epithelium to prostate intraepithelial neoplasia (PIN) and then to invasive prostate cancer. Cancer progression was associated with increased phosphorylation of Akt (P

A strategy for proteomic analysis of microdissected cells derived from human tumor specimens is described and demonstrated by using esophageal cancer as an example. Normal squamous epithelium and corresponding tumor cells from two patients were procured by laser-capture microdissection and studied by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE). Fifty thousand cells resolved approximately 675 distinct proteins (or isoforms) with molecular weights ranging between 10 and 200 kDa and isoelectric points of pH 3–10. Comparison of the microdissected protein profiles showed a high degree of similarity between the matched normal-tumor samples (98% identical). However, 17 proteins showed tumor-specific alterations, including 10 that were uniquely present in the tumors and seven that were observed only in the normal epithelium. Two of the altered proteins were characterized by mass spectrometry and immunoblot analysis and were identified as cytokeratin 1 and annexin I. Acquisition of 2D-PAGE protein profiles, visualization of disregulated proteins, and subsequent determination of the identity of selected proteins through high-sensitivity MS-MS microsequencing are possible from microdissected cell populations. These separation and analytical techniques are uniquely capable of detecting tumor-specific alterations. Continued refinement of techniques and methodologies to determine the abundance and status of proteins in vivo holds great promise for future study of normal cells and associated neoplasms. Mol. Carcinog. 27:158–165, 2000. Published by Wiley-Liss Inc.

The complicated, changing pattern of protein expression should contain important infor- mation about the pathologic process taking place in the cells of actual tissue. Utilization of this information for the selection of druggable targets could be possible if a means existed to rapidly analyze and display changes in protein expression in defined microscopic cellular subpopulations. As a demonstration of feasi- bility, we show the generation of sensitive, rapid, and reproducible molecular weight protein profiles of patient-matched normal, premalignant, malignant, and metastatic microdissected cell populations from stained human esophageal, prostate, breast, ovary, colon, and hepatic tissue sections through the applica- tion of an affinity-based biochip. Reproducible, discriminatory protein biomarker profiles can be obtained from as few as 25 cells in less than 5 min from dissection to the generation of the protein fingerprint. Furthermore, these protein pattern profiles reveal reproducible changes in expression as cells undergo malignant transformation, and are discriminatory for different tumor types. Consistent protein changes were identified in the microdissected cells from patient-matched tumor and normal epithelium from eight out of eight different malignant esophageal tissue sets and three out of three malignant prostate tissue sets. A means to rapidly generate a display of expressed proteins from microscopic cellular populations sampled from tissue could be an important enabling technology for pharmacoproteomics, molecular pathology, drug intervention strategies, therapeutic assessment of drug entities, disease diagnosis, toxicity, and gene

Detection of minor, genetically distinct subpopulations within tumors is a key challenge in cancer genomics. Here we report STAR-FISH (specific-to-allele PCR-FISH), a novel method for the combined detection of single-nucleotide and copy number alterations in single cells in intact archived tissues. Using this method, we assessed the clinical impact of changes in the frequency and topology of PIK3CA mutation and HER2 (ERBB2) amplification within HER2-positive breast cancer during neoadjuvant therapy. We found that these two genetic events are not always present in the same cells. Chemotherapy selects for PIK3CA-mutant cells, a minor subpopulation in nearly all treatment-naive samples, and modulates genetic diversity within tumors. Treatment-associated changes in the spatial distribution of cellular genetic diversity correlated with poor long-term outcome following adjuvant therapy with trastuzumab. Our findings support the use of in situ single cell-based methods in cancer genomics and imply that chemotherapy before HER2-targeted therapy may promote treatment resistance.

SummaryBackground MET expression and activation appear to be important for initiation and progression of triple-negative breast cancer. Tivantinib (ARQ 197) is an orally administered agent that targets MET, although recent preclinical data suggests the agent may have mechanisms of action that are independent of MET signaling. We conducted a phase 2 study of tivantinib monotherapy in patients with metastatic triple-negative breast cancer. Methods Patients with metastatic triple-negative breast cancer who had received 1 to 3 prior lines of chemotherapy in the metastatic setting were enrolled into this two-stage, single arm phase 2 study. Treatment consisted of twice daily oral dosing of tivantinib (360 mg po bid) during a 21-day cycle. Patients underwent restaging scans at 6 weeks, and then every 9 weeks. Tumor biomarkers that might predict response to tivantinib were explored. Results 22 patients were enrolled. The overall response rate was 5 % (95 % CI 0–25 %) and the 6-month progression-free survival (PFS) was 5 % (95 % CI 0–25 %), with one patient achieving a partial response (PR). Toxicity was minimal with only 5 grade ≥3 adverse events (one grade 3 anemia, one grade 3 fatigue, and 3 patients with grade 3/4 neutropenia). Conclusion This study represents the first evaluation of tivantinib for the treatment of metastatic triple-negative breast cancer. These results suggest that single agent tivantinib is well tolerated, but did not meet prespecified statistical targets for efficacy.