Response to trastuzumab, erlotinib, and bevacizumab, alone and in combination, is correlated with the level of human epidermal growth factor receptor-2 expression in human breast cancer cell lines.

Human epidermal growth factor receptor-2 (HER2) and epidermal growth factor receptor (EGFR) heterodimerize to activate mitogenic signaling pathways. We have shown previously, using MCF7 subcloned cell lines with graded levels of HER2 expression, that responsiveness to trastuzumab and AG1478 (an anti-EGFR agent), varied directly with levels of HER2 expression. HER2 and EGFR up-regulate vascular endothelial growth factor (VEGF), a growth factor that promotes angiogenesis and participates in autocrine growth-stimulatory pathways that might be active in vitro. Here, we show that trastuzumab, erlotinib, and bevacizumab, individually and in combination, inhibit cell proliferation in a panel of unrelated human breast cancer cell lines, in proportion to their levels of HER2 expression. The combination of all three drugs provided a greater suppression of growth than any single drug or two-drug combination in the high HER2-expressing cell lines (P < 0.001). Combination index analysis suggested that the effects of these drugs in combination were additive. The pretreatment net level of VEGF production in each cell line was correlated with the level of HER2 expression (r = 0.883, P = 0.016). Trastuzumab and erlotinib each reduced total net VEGF production in all cell lines. Multiparameter flow cytometry studies indicated that erlotinib alone and the triple drug combination produced a prolonged but reversible blockade of cells in G1, but did not increase apoptosis substantially. These studies suggest that the effects of two and three-drug combinations of trastuzumab, erlotinib, and bevacizumab might offer potential therapeutic advantages in HER2-overexpressing breast cancers, although these effects are of low magnitude, and are likely to be transient.

Reconstructing tumor phylogenies from heterogeneous single-cell data.

Studies of gene expression in cancerous tumors have revealed that tumors presenting indistinguishable symptoms in the clinic can be substantially different entities at the molecular level. The ability to distinguish between these genetically distinct cancers will make possible more accurate prognoses and more finely targeted therapeutics, provided we can characterize commonly occurring cancer sub-types and the specific molecular abnormalities that produce them. We develop a new method for identifying these common tumor progression pathways by applying phylogeny inference algorithms to single-cell assays, taking advantage of information on tumor heterogeneity lost to prior microarray-based approaches. We combine this approach with expectation maximization to infer unknown parameters used in the phylogeny construction. We further develop new algorithms to merge inferred trees across different assays. We validate the expectation maximization method on simulated data and demonstrate the combined approach on a set of fluorescent in situ hybridization (FISH) data measuring cell-by-cell gene and chromosome copy numbers in a large sample of breast cancers. The results further validate the proposed computational methods by showing consistency with several previous findings on these cancers and provide novel insights into the mechanisms of tumor progression in these patients.

A simple correction for cell autofluorescence for multiparameter cell-based analysis of human solid tumors.

BACKGROUND: Corrections that have been proposed to minimize the unwanted contribution of cell autofluorescence to the total fluorescence signal often require either specialized instrumentation or the sacrifice of a data channel so as to perform a measurement that can be used to correct for autofluorescence in individual cells. Here we propose a simple cell by cell correction for autofluorescence that is suitable for multiparameter laser scanning cytometry (LSC) studies in human solid tumors that relies on the ratio of mean autofluorescence to mean total cell fluorescence (mean Flauto/mean Fltotal). This approach assumes a correlation between the autofluorescence component and the total signal in individual cells. This correction does not require specialized instrumentation, and does not sacrifice a data channel in multiparameter studies. A potential disadvantage is that errors may be introduced by the assumption of a correlation between the two components of the total fluorescence signal in individual cells in samples in which no such correlation exists. METHODS: Distributions of cell autofluorescence and total Her-2/neu cell fluorescence were obtained separately by LSC in three human breast cancer cell lines and in three samples of primary human lung cancer. In the breast cancer cell lines, autofluorescence measurements and Her-2/neu measurements were also obtained on the same cells. RESULTS: We show that there is a partial correlation between autofluorescence and total Her-2/neu/FITC fluorescence in individual cells in the three breast cancer cell lines. We also show that the results of a ratio-based autofluorescence correction agree with those based on a true cell by cell correction. Computer simulation studies suggest that in samples with no correlation between the autofluorescence component and the true probe/dye fluorescence component, the ratio correction produces robust estimates of the mean true fluorescence signal, with relatively small but systematic underestimates of the coefficient of variation of such measurements under conditions commonly encountered in the measurement of human solid tumors. CONCLUSIONS: A simple cell by cell correction for autofluorescence based on the ratio of mean Flauto to mean Fltotal can be applied in cell samples in which there is a correlation between cell autofluorescence and true probe/dye fluorescence in individual cells. In cell samples that lack this correlation, or in which it is not known whether such a correlation exists, this correction can be used with the reservation that there is a systematic but relatively small underestimation of the degree of variability of the measurements.

Evidence that L1AD3, an apoptosis-inducing cyclic peptide, binds a leukemic T-cell membrane protein receptor.

Human leukemic T-lymphocytes undergo extensive and rapid apoptosis in the presence of L1AD3, a small cyclic peptide derivative of cobra cardiotoxin. The first step in this process involves its binding to membranes of susceptible cells. By the use of a biotin "handle" synthetically incorporated at the N-terminus of L1AD3, we show that binding is saturable and selective: normal human peripheral blood lymphocytes do not bind this peptide. Fluorescence resonance energy transfer experiments indicate that the binding sites are separated by at least 55 A. Loss of binding occurs if membrane proteins are enzymatically degraded, suggesting that L1AD3's target is a cell-membrane surface protein receptor. Finally, crosslinking of cyclic BTNL1AD3 peptide to a leukemic T-cell membrane surface receptor, as examined using a biotin-avidin blot, indicated a molecular weight of approximately 34,400.

A cyclic peptide, L1AD3, induces early signs of apoptosis in human leukemic T-cell lines.

L1AD3 is a small cyclic synthetic peptide designed to resemble the first loop of a cobra venom cytotoxin. Instead of inducing membrane disruption similar to that caused by the parent toxin, L1AD3 promotes extensive and unusually rapid apoptosis in leukemic T-cells without making the plasma membrane permeable to small fluorescent dyes. Within 4 h, micromolar concentrations of L1AD3 almost totally inhibit thymidine incorporation, and ATP levels decrease significantly. By contrast, normal human white blood cells are not affected by L1AD3, nor is heart cell function affected by it. If L1AD3 kills by interacting with targets that are different from those of currently applied agents, this peptide, or a derivative of it, could become a useful adjunct for cancer chemotherapy.

Intracellular patterns of Her-2/neu, ras, and ploidy abnormalities in primary human breast cancers predict postoperative clinical disease-free survival.

PURPOSE: In an earlier study, the presence of aneuploidy, Her-2/neu overexpression, and ras overexpression in the same cells (triple-positive cells) was of prognostic significance (P < 0.015) in 91 patients with localized breast cancer (median follow up, 32 months). Here, we present results involving a larger group of patients with longer follow-up. EXPERIMENTAL DESIGN: Fixed cell suspensions prepared from primary tumors of 189 patients with early breast cancer were studied prospectively by multiparameter flow cytometry. Correlated intracellular fluorescence-based measurements of cell DNA content and Her-2/neu and ras protein were obtained on each of >2000 cells in each tumor. Intracellular combinations of abnormalities in these measurements were correlated with subsequent patient disease-free survival (DFS). Median time on study was 54 months (range, 7-128 months). RESULTS: DFS of patients with > or = 5% triple-positive tumor cells was shorter than those who did not meet this criterion (P = 0.004). The difference remained statistically significant after accounting for nodal status, tumor size, and each of the component abnormalities (P = 0.006). Node-negative patients whose tumors had fewer than 2 abnormalities/cell had an especially favorable clinical course, with a 5-year DFS of 96% (lower confidence bound, 86%). CONCLUSIONS: Patterns of accumulated intracellular molecular abnormalities in cells of primary human breast cancers are predictive for subsequent DFS independently of the abnormalities themselves taken individually.

A suitable method for identifying cell aggregates in laser scanning cytometry listmode data for analyzing disaggregated cell suspensions obtained from human cancers.

BACKGROUND: The presence of cell aggregates in cell suspensions obtained from human solid tumors can interfere with the measurement of cell DNA content of cell singlets, and can confound multiparameter analysis of other measurements on the same cells. Flow cytometric corrections for cell aggregates based on signal pulse shape have not proven to be reliable. Mathematical models have been developed to correct for cell aggregates in binned DNA histogram data, but they are not suitable for the correction of correlated non-DNA measurements obtained on the same cells. METHODS: A total of 21 samples representing a variety of normal and malignant human cell types, including normal lymphocytes, normal sputum, human breast cancer cell lines, and mechanically disaggregated cell suspensions from primary breast cancers and nonsmall cell lung cancers, were studied by laser scanning cytometry (LSC) using the CompuCyte laser scanning cytometer (Cambridge, MA). Nuclear area, nuclear perimeter, and an LSC-based cell texture parameter were measured on approximately 400 cells in each sample, using an air-cooled, violet laser emitting at a wavelength of 405 nm for DAPI excitation, and each cell was classified as a singlet or aggregate by its appearance under direct observation. A "saddle function" provided by CompuCyte was used, together with an algorithm based on the measurements of nuclear area, perimeter, and cell texture (the APT algorithm), to identify cell aggregates and exclude them from the listmode data file. RESULTS: Proportions of cell aggregates in the uncorrected samples ranging from 6 to 56% (mean, 20%) were reduced to proportions ranging from 0 to 7% (mean, 2.4%) after correction. The discriminant function was "tuned" to maintain both average cell singlet purity and average cell singlet yield at >70% over a broad range of cell DNA contents. CONCLUSIONS: A combined approach to cell aggregate detection, which utilizes both the saddle function and the APT algorithm, produces list mode data files that exclude >80% of cell aggregates from samples of disaggregated cell suspensions of human tumors and other sources of clinical material. Such data files are suitable for multiparameter analysis.