ing primary cells obtained from pleural efusions and atomic force microscopy (3). Two years later, this fnding was confrmed with optical stretching by using oral squamous cell carcinomas obtained from fve patients (4). However, further activity toward clinical application has so far been hampered by one main factor: Cell sampling rates have been too low to screen relevant population sizes and many patient samples, to obtain reliable statistics, or to identify common outcome profles. In this issue of Science Translational Medicine, Tse et al. (5) fnally deliver on the promise of using cell mechanical analysis in a diagnostic clinical setting, largely powered by an enormous jump in cell sampling
CANCER
Mechanics Meets Medicine Jochen Guck1,2* and Edwin R. Chilvers3
1
Biotechnology Center, Technische Universität Dresden, Tatzberg 47/49, 01307 Dresden, Germany. 2Cavendish Laboratory, Department of Physics, University of Cambridge, J. J. Thomson Avenue., Cambridge CB3 0HE, UK. 3Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke’s and Papworth Hospitals, Hills Road, Cambridge CB2 0QQ, UK. *Corresponding author. E-mail: jochen.guck@ tu-dresden.de
cancer cells are more deformable than their healthy counterparts. But these studies were conducted with cell lines. Only a handful of studies have so far attempted to move in an explicit way toward clinical application. In 2007, Cross et al. were frst to confrm the general trend of cancer cell sofening by us-
A
Streamlines
B
Cell exit
Number of publications
d
a b
Cell input
1975 1980 1985 1990 1995 2000 2005 2010
C
Initial diameter, d Deformability, D=a/b
Measurement rate vs. information content 104
Optimal performance
DC
10-1
10-2
10-3
MTC
AM MA
OS AFM
Mechanical information content
D Total cells measured vs. information content
Total cells per experiment
CELL MECHANICS: A DIAGNOSTIC MARKER A feature of cancer cells that is invariably altered during malignant transformation is the cytoskeleton. Tat this change is diagnostic and important has ofen been pointed out— for example, in a special issue of Science 15 years ago (1). But then, how does one assess the properties of the cytoskeleton in a simple and quantifable way so that this insight becomes useful for diagnostic purposes? A likely answer is the measurement of the cells’ overall mechanical properties. Tese are largely determined by the cytoskeleton (even though the nucleus also plays a role, especially at large deformations), which in turn is strongly regulated and intricately involved in many important cell functions, such as mitosis and migration. Any disturbance of these functions, such as in cancer, necessarily afects the cytoskeleton, which can be monitored conveniently by measuring the stifness of the cells. Tis link between function and cell mechanical assessment holds great promise for a better understanding of cell function but also as a diagnostic or even prognostic marker. But how does one measure this property reliably and efciently? Te study of the mechanical properties of cells has a very long tradition (2). It has seen a remarkable renaissance over the past two decades with an exponential increase in publications (Fig. 1A), largely driven by the development of new technologies that can exert forces on the small length scale of cells and measure the resulting deformations. Most publications fall safely into the realm of basic research, unrelated to cancer, but a subfraction have cancer cell lines as their object of interest. Remarkably, almost all of them demonstrate a clear trend: Somatic
Measured cells per second
CREDIT: V. ALTOUNIAN/SCIENCE TRANSLATIONAL MEDICINE
A new high-throughput measurement technique moves mechanical phenotyping of cells in malignant pleural efusions closer to the clinic (Tse et al., this issue).
1000
Optimal performance
DC
OS
100
10
MTC
MA
AM
AFM
Mechanical information content
Fig. 1. Measuring cell mechanics. (A) An apparently exponential increase in cell mechanics publications over the past two decades, sorted by measurement technique. DC falls under the category of hydrodynamic deformation, or HD. These data were obtained from PubMed (www.ncbi.nlm.nih.gov/ pubmed) by searching for combinations of “cell deformation“ OR “cell deformability“ OR “mechanical properties” OR “cell mechanics” OR “mechanical phenotyping “ OR “cellular mechanobiology” AND the relevant technique names listed here. Raw data for this analysis are in supplementary materials, file “Data Fig1A.xlsx.” (B) Illustration of the HD technique applied by Tse et al. (5). In DC, the cells are flowed toward the four-way intersection from either side. When they encounter the opposing flow, the cells are deformed and exit the channels. This deformability is quantified by relating the major to minor axis of the resulting spheroid. (C and D) Schematic illustration of the trade-off between cellsampling rate (C) or cells measured (D) and information content of the different techniques. www.ScienceTranslationalMedicine.org 20 November 2013 Vol 5 Issue 212 212fs41
1
Downloaded from stm.sciencemag.org on December 10, 2013
FOCUS
rate. Last year, the authors introduced a new microfuidic technique, termed deformability cytometry (DC) (6). A cell suspension is fowed with speed from opposing sides toward a four-way crossing before exiting through either intersecting channel (Fig. 1B). Te inertial forces at the stagnation point are sufcient to deform the cells. Tis deformation is recorded with a high-speed camera and allows cell-sampling rates of over 1000 cells per second. Te deformability is defned as the ratio of major to minor axis of the cell’s spheroidal shape. A sof cell has a high deformability; a stif one, low deformability. Te deformability can be plotted in a scatter plot—for example, against cell size—very much like scattering or fuorescence intensities in a conventional fow cytometer, and analyzed in a similar fashion. Here, the massive improvement in cell sampling rate using DC (several orders of magnitude as compared with all other single-cell measurement techniques) (Fig. 1C) led to an actual, extended clinical study. Tse et al. applied DC to analyze the deformability of cells present in malignant pleural efusions (MPE) of 119 patient samples. Substantial volumes of fuid only accumulate around the lung in the setting of disease, but sorting out the exact underlying pathology— which can vary from infection (including tuberculosis) to heart or kidney failure to a variety of primary or secondary cancers—is a common challenge to the clinician. In order to extract characteristic features of the cells in each sample, the authors developed an algorithmic scoring system of the deformability-size scatter plots obtained. In parallel, the samples were assessed in the usual way by cytopathologists. Te scoring system accurately classifed 63% of the samples into two high-confdence regimes, with 100% positive and negative predictive values (PPV and NPV, respectively). Even 8 out of 16 samples that were labeled “atypical” by conventional assessment could be accurately classifed. Importantly, 10 of 17 samples considered negative by classical cytology were correctly identifed as positive when compared with the clinical outcome. It appears that DC in conjunction with the scoring system does provide an attractive and promising, quantitative and objective adjunct technology to aid the decisions of pathologists when assessing pleural efusions for cancer cells. PASSING THE MECHANICAL CHECKUP Tis study (5) marks a watershed in the application of cell mechanics for clinical di-
agnostic purposes. No other technique has ever come this far. However, there is still a lot of room for improvement. One area relates to mechanical analysis in the context of existing research, the other relates to concerns in light of existing clinical practice. Te main advantage of DC over other cell mechanics measurement techniques is the improvement in cell-sampling rate (Fig. 1C). At frst sight, the advantages of a high cell-sampling rate seem obvious: solid statistical power, short measurement times, and many samples included. However, cellsampling rate should not be confused with actual throughput. Cells are only measured for a few seconds, so the throughput is still rather limited (only about 3000 cells are being reported for a single experimental run with one patient sample) (Fig. 1D). Tere are other current studies with diferent techniques, including optical stretching and other hydrodynamic deformation approaches that get close to reaching similar total cell numbers. A more serious fipside of the high cell-sampling rate is that there is little time available for assessing the mechanical properties of each cell. Very fast could be too fast. If there is more time, additional relevant mechanical information could be gleaned from each cell, such as in the case of atomic force microscopy (AFM), in which throughput is low (0.001 cells per second) but the information content is high (Fig. 1, C and D). In contrast to “deformability” as defned in this publication, which depends on other factors such as fow speed and channel geometry, there are many parameters measured with the other techniques that characterize the actual mechanical material properties of cells and that convey important and complementary information; these include viscosity, compressibility, elastic modulus, or powerlaw exponent, obtained in compression, shear, or tension and sometimes even spatially resolved within the cell. Furthermore, mechanical properties are generally time-dependent, which is especially true for cells. In fact, the time scale at which cell mechanics is assessed matters quite a bit. For example, circulating blood cells need to be deformable on a subsecond time scale in order to efectively pass constrictions in the microvasculature; however, they require entirely diferent mechanical properties—namely, low steady-state viscosity—in order to fow through the narrow gaps in the tissue on the time scale of minutes and hours (7). In contrast, DC measures cell mechanics on a submillisec-
ond time scale, which does not seem to be important in many physiological processes (if any). What if the most important diferences in cell mechanics can only be assessed when deforming cells on long time scales? What if the relevant property is an active response of the cell? Tere have been reports that the decisive property of metastatic cancer cells is their ability to contract under external loading (8). Tese parameters are not accessible when deforming cells so quickly. And then, which physiological information does DC actually provide? Te enormous deceleration the cells experience causes deformation by huge forces (>1 μN). Most likely [even though not addressed here (5)], the cells’ integrity and viability will be severely compromised. Of course, in DC the cells are not needed aferward, so, at the moment, cell viability is irrelevant. Future insights into cancer and the “mechanical phenotype” of malignant cells may beneft from connecting mechanical properties to physiology, thus requiring the intact cell to be recovered from the device for further analysis. Tus, although DC is an important and impressive step forward in our ability to assess mechanical characteristics of cells and diagnose certain diseases, there are still many technical details to be addressed in order to glean meaningful information about cancer progression. INTO THE CLINIC So, how does this study stack up from a clinical perspective? Tere is literature describing the value of readily available clinical and radiological features (such as the size of the efusion and presence or absence of chest wall pain), the macroscopic appearance of the pleural fuid (especially if blood-stained), and several simple biochemical parameters to defne a pretest probability for MPE. Tese factors alone ofer area-under-the-curve values >0.87 (9). Hence, it could be argued that mechanical phenotyping by DC might struggle to beat what already exists. Before being deployed in the clinic, the diagnostic utility of DC will also need to be properly “stress-tested” by using a discrete and independent validation cohort [rather than the fvefold cross-validation approach used here (5)] and a complete set of sensitivity, specifcity, pre- and posttest probability, and positive and negative predictive values presented (10). On a similar theme, the authors did not provide information on the protein content of the samples analyzed (which can be valuable because a low pro-
www.ScienceTranslationalMedicine.org 20 November 2013 Vol 5 Issue 212 212fs41
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Downloaded from stm.sciencemag.org on December 10, 2013
FOCUS
FOCUS there is a high probability of an MPE, and the desire for fast, one-stop, biopsy-based diagnostics, may further reduce the interest in developing cytological methods. Te biggest challenge for DC, however, and one that Tse et al. noted, is to address how DC will pinpoint the precise cancerof-origin in MPE, as most cancer-related pleural efusions are due to metastatic disease from a distant primary tumor. Tis is a vital part of the cytopathologist’s current work and immunohistochemistry. Although time-consuming, tracking down the origin of a MPE allows diferentiation of, for example, primary lung [NSCLC or smallcell lung cancer (SCLC)], pleural (mesothelioma), hematological (lymphoma), and metastatic epithelial tumors (such as breast, upper gastrointestinal, renal, and colonic). As yet, this is out of the reach of DC-based cell mechanical phenotyping but is a major goal of the technology. MECHANICS IN MEDICINE Although there are lingering questions and translational barriers to mechanics-based diagnostics, this study marks a quantum leap in the clinical application of mechanical phenotyping (5). Future success requires getting this technique into the hands of many more people—from engineers to clinicians—so that more experience can be gained, applicability refned, data independently confrmed, and current concerns addressed. Choosing MPEs was a clever frst-choice demonstration because the suspended state of the cells eases sample preparation. But there are other possible clinical applications for DC. Apart from using cells obtained directly from solid tumors via biopsies, there are many pathologies with an infammatory etiology, including autoimmune disorders, in which aberrant migration, activation, phagocytosis, or cell division is implicated—processes that involve
the cytoskeleton or the nucleus and that can potentially be studied by using this technique. Tse and colleagues have opened a door to merging mechanics with medicine; now, it is well worth stepping through to explore what lies behind. REFERENCES AND NOTES 1. S. M. Hurtley, Cell biology of the cytoskeleton. Science 279, 459 (1998). 2. A. E. Pelling, M. A. Horton, An historical perspective on cell mechanics. Pfugers Arch. (2007). 3. S. E. Cross, Y.-S. Jin, J. Rao, J. K. Gimzewski, Nanomechanical analysis of cells from cancer patients. Nat. Nanotechnol. 2, 780–783 (2007). 4. T. W. Remmerbach, F. Wottawah, J. Dietrich, B. Lincoln, C. Wittekind, J. Guck, Oral cancer diagnosis by mechanical phenotyping. Cancer Res. 69, 1728–1732 (2009). 5. H. T. K. Tse, D. R. Gossett, Y. S. Moon, M. Masaeli, M. Sohsman, Y. Ying, K. Mislick, R. P. Adams, J. Rao, D. Di Carlo, Quantitative diagnosis of malignant pleural effusions by single-cell mechanophenotyping. Sci. Transl. Med. 5, 212ra163 (2013). 6. D. R. Gossett, H. T. Tse, S. A. Lee, Y. Ying, A. G. Lindgren, O. O. Yang, J. Rao, A. T. Clark, D. Di Carlo, Hydrodynamic stretching of single cells for large population mechanical phenotyping. Proc. Natl. Acad. Sci. U.S.A. 109, 7630–7635 (2012). 7. A. E. Ekpenyong, G. Whyte, K. Chalut, S. Pagliara, F. Lautenschläger, C. Fiddler, S. Paschke, U. F. Keyser, E. R. Chilvers, J. Guck, Viscoelastic properties of differentiating blood cells are fate- and function-dependent. PLOS ONE 7, e45237 (2012). 8. A. Fritsch, M. Höckel, T. Kiessling, K. D. Nnetu, F. Wetzel, M. Zink, J. A. Käs, Are biomechanical changes necessary for tumour progression? Nat. Phys. 6, 730–732 (2010). 9. L. Valdés, E. San-José, L. Ferreiro, F.-J. González-Barcala, A. Golpe, J. M. Alvarez-Dobaño, M. E. Toubes, N. RodríguezNúñez, C. Rábade, A. Lama, F. Gude, Combining clinical and analytical parameters improves prediction of malignant pleural effusion. Lung, published online 2 October 2013 (10.1007/s00408-013-9512-2). 10. M. A. Martínez-García, E. Cases-Viedma, P. J. CorderoRodríguez, M. Hidalgo-Ramírez, M. Perpiñá-Tordera, F. Sanchis-Moret, J. L. Sanchis-Aldás, Diagnostic utility of eosinophils in the pleural fluid. Eur. Respir. J. 15, 166–169 (2000). Competing interests: J.G. holds a patent on the optical stretcher technology. 10.1126/scitranslmed.3007731 Citation: J. Guck, E. R. Chilvers, Mechanics meets medicine. Sci. Transl. Med. 5, 212fs41 (2013).
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tein “transudate” strongly predicts a nonmalignant etiology). Moreover, the authors did not test many MPE samples from patients with non–small cell lung cancer (NSCLC), which is one of the most common causes of MPE. Additional testing with more and varied patient samples will give a refned view of the clinical capabilities of DC. Perhaps the most promising clinical application of DC relates to the value of obtaining unbiased mechanical phenotyping information in patients with “atypical” or “reactive” cytology or in patients with nonmalignant cytology on initial sampling but a high pretest probability of pleural malignancy according to clinical, imaging, and biochemical analyses; these are both common situations. Hence, this technique may ofer most in the realm of improving diagnostic accuracy or suspicion. Despite improvement in diagnostics, the poor outlook for most patients with MPE dictates that DC profling—or diagnostics in general—may not afect actual prognosis. Claims that this technology when optimized might reduce health care costs are also probably overstated. Hence, the authors’ predictions about reduction in workload are based on excluding all cytopathological analysis of samples with high NPV (scores of 6 or less) or high PPV (scores >8), which does not refect the clinical scenario. Likewise, although it has been argued that mechanical phenotyping will reduce the need for cytopathologists’, input in resourcepoor settings, establishing this technology is likely—at least initially—to be expensive and potentially more complex than the basic para%n-embedded sample preparation used currently for microscopy. Using fresh rather than fxed samples also mandates category 2 laboratory handling, which may contribute to a higher cost. In contrast, in advanced health care systems, the move to early thoracoscopy in patients in which
CANCER
Mechanics Meets Medicine Jochen Guck1,2* and Edwin R. Chilvers3
1
Biotechnology Center, Technische Universität Dresden, Tatzberg 47/49, 01307 Dresden, Germany. 2Cavendish Laboratory, Department of Physics, University of Cambridge, J. J. Thomson Avenue., Cambridge CB3 0HE, UK. 3Department of Medicine, University of Cambridge School of Clinical Medicine, Addenbrooke’s and Papworth Hospitals, Hills Road, Cambridge CB2 0QQ, UK. *Corresponding author. E-mail: jochen.guck@ tu-dresden.de
cancer cells are more deformable than their healthy counterparts. But these studies were conducted with cell lines. Only a handful of studies have so far attempted to move in an explicit way toward clinical application. In 2007, Cross et al. were frst to confrm the general trend of cancer cell sofening by us-
A
Streamlines
B
Cell exit
Number of publications
d
a b
Cell input
1975 1980 1985 1990 1995 2000 2005 2010
C
Initial diameter, d Deformability, D=a/b
Measurement rate vs. information content 104
Optimal performance
DC
10-1
10-2
10-3
MTC
AM MA
OS AFM
Mechanical information content
D Total cells measured vs. information content
Total cells per experiment
CELL MECHANICS: A DIAGNOSTIC MARKER A feature of cancer cells that is invariably altered during malignant transformation is the cytoskeleton. Tat this change is diagnostic and important has ofen been pointed out— for example, in a special issue of Science 15 years ago (1). But then, how does one assess the properties of the cytoskeleton in a simple and quantifable way so that this insight becomes useful for diagnostic purposes? A likely answer is the measurement of the cells’ overall mechanical properties. Tese are largely determined by the cytoskeleton (even though the nucleus also plays a role, especially at large deformations), which in turn is strongly regulated and intricately involved in many important cell functions, such as mitosis and migration. Any disturbance of these functions, such as in cancer, necessarily afects the cytoskeleton, which can be monitored conveniently by measuring the stifness of the cells. Tis link between function and cell mechanical assessment holds great promise for a better understanding of cell function but also as a diagnostic or even prognostic marker. But how does one measure this property reliably and efciently? Te study of the mechanical properties of cells has a very long tradition (2). It has seen a remarkable renaissance over the past two decades with an exponential increase in publications (Fig. 1A), largely driven by the development of new technologies that can exert forces on the small length scale of cells and measure the resulting deformations. Most publications fall safely into the realm of basic research, unrelated to cancer, but a subfraction have cancer cell lines as their object of interest. Remarkably, almost all of them demonstrate a clear trend: Somatic
Measured cells per second
CREDIT: V. ALTOUNIAN/SCIENCE TRANSLATIONAL MEDICINE
A new high-throughput measurement technique moves mechanical phenotyping of cells in malignant pleural efusions closer to the clinic (Tse et al., this issue).
1000
Optimal performance
DC
OS
100
10
MTC
MA
AM
AFM
Mechanical information content
Fig. 1. Measuring cell mechanics. (A) An apparently exponential increase in cell mechanics publications over the past two decades, sorted by measurement technique. DC falls under the category of hydrodynamic deformation, or HD. These data were obtained from PubMed (www.ncbi.nlm.nih.gov/ pubmed) by searching for combinations of “cell deformation“ OR “cell deformability“ OR “mechanical properties” OR “cell mechanics” OR “mechanical phenotyping “ OR “cellular mechanobiology” AND the relevant technique names listed here. Raw data for this analysis are in supplementary materials, file “Data Fig1A.xlsx.” (B) Illustration of the HD technique applied by Tse et al. (5). In DC, the cells are flowed toward the four-way intersection from either side. When they encounter the opposing flow, the cells are deformed and exit the channels. This deformability is quantified by relating the major to minor axis of the resulting spheroid. (C and D) Schematic illustration of the trade-off between cellsampling rate (C) or cells measured (D) and information content of the different techniques. www.ScienceTranslationalMedicine.org 20 November 2013 Vol 5 Issue 212 212fs41
1
Downloaded from stm.sciencemag.org on December 10, 2013
FOCUS
rate. Last year, the authors introduced a new microfuidic technique, termed deformability cytometry (DC) (6). A cell suspension is fowed with speed from opposing sides toward a four-way crossing before exiting through either intersecting channel (Fig. 1B). Te inertial forces at the stagnation point are sufcient to deform the cells. Tis deformation is recorded with a high-speed camera and allows cell-sampling rates of over 1000 cells per second. Te deformability is defned as the ratio of major to minor axis of the cell’s spheroidal shape. A sof cell has a high deformability; a stif one, low deformability. Te deformability can be plotted in a scatter plot—for example, against cell size—very much like scattering or fuorescence intensities in a conventional fow cytometer, and analyzed in a similar fashion. Here, the massive improvement in cell sampling rate using DC (several orders of magnitude as compared with all other single-cell measurement techniques) (Fig. 1C) led to an actual, extended clinical study. Tse et al. applied DC to analyze the deformability of cells present in malignant pleural efusions (MPE) of 119 patient samples. Substantial volumes of fuid only accumulate around the lung in the setting of disease, but sorting out the exact underlying pathology— which can vary from infection (including tuberculosis) to heart or kidney failure to a variety of primary or secondary cancers—is a common challenge to the clinician. In order to extract characteristic features of the cells in each sample, the authors developed an algorithmic scoring system of the deformability-size scatter plots obtained. In parallel, the samples were assessed in the usual way by cytopathologists. Te scoring system accurately classifed 63% of the samples into two high-confdence regimes, with 100% positive and negative predictive values (PPV and NPV, respectively). Even 8 out of 16 samples that were labeled “atypical” by conventional assessment could be accurately classifed. Importantly, 10 of 17 samples considered negative by classical cytology were correctly identifed as positive when compared with the clinical outcome. It appears that DC in conjunction with the scoring system does provide an attractive and promising, quantitative and objective adjunct technology to aid the decisions of pathologists when assessing pleural efusions for cancer cells. PASSING THE MECHANICAL CHECKUP Tis study (5) marks a watershed in the application of cell mechanics for clinical di-
agnostic purposes. No other technique has ever come this far. However, there is still a lot of room for improvement. One area relates to mechanical analysis in the context of existing research, the other relates to concerns in light of existing clinical practice. Te main advantage of DC over other cell mechanics measurement techniques is the improvement in cell-sampling rate (Fig. 1C). At frst sight, the advantages of a high cell-sampling rate seem obvious: solid statistical power, short measurement times, and many samples included. However, cellsampling rate should not be confused with actual throughput. Cells are only measured for a few seconds, so the throughput is still rather limited (only about 3000 cells are being reported for a single experimental run with one patient sample) (Fig. 1D). Tere are other current studies with diferent techniques, including optical stretching and other hydrodynamic deformation approaches that get close to reaching similar total cell numbers. A more serious fipside of the high cell-sampling rate is that there is little time available for assessing the mechanical properties of each cell. Very fast could be too fast. If there is more time, additional relevant mechanical information could be gleaned from each cell, such as in the case of atomic force microscopy (AFM), in which throughput is low (0.001 cells per second) but the information content is high (Fig. 1, C and D). In contrast to “deformability” as defned in this publication, which depends on other factors such as fow speed and channel geometry, there are many parameters measured with the other techniques that characterize the actual mechanical material properties of cells and that convey important and complementary information; these include viscosity, compressibility, elastic modulus, or powerlaw exponent, obtained in compression, shear, or tension and sometimes even spatially resolved within the cell. Furthermore, mechanical properties are generally time-dependent, which is especially true for cells. In fact, the time scale at which cell mechanics is assessed matters quite a bit. For example, circulating blood cells need to be deformable on a subsecond time scale in order to efectively pass constrictions in the microvasculature; however, they require entirely diferent mechanical properties—namely, low steady-state viscosity—in order to fow through the narrow gaps in the tissue on the time scale of minutes and hours (7). In contrast, DC measures cell mechanics on a submillisec-
ond time scale, which does not seem to be important in many physiological processes (if any). What if the most important diferences in cell mechanics can only be assessed when deforming cells on long time scales? What if the relevant property is an active response of the cell? Tere have been reports that the decisive property of metastatic cancer cells is their ability to contract under external loading (8). Tese parameters are not accessible when deforming cells so quickly. And then, which physiological information does DC actually provide? Te enormous deceleration the cells experience causes deformation by huge forces (>1 μN). Most likely [even though not addressed here (5)], the cells’ integrity and viability will be severely compromised. Of course, in DC the cells are not needed aferward, so, at the moment, cell viability is irrelevant. Future insights into cancer and the “mechanical phenotype” of malignant cells may beneft from connecting mechanical properties to physiology, thus requiring the intact cell to be recovered from the device for further analysis. Tus, although DC is an important and impressive step forward in our ability to assess mechanical characteristics of cells and diagnose certain diseases, there are still many technical details to be addressed in order to glean meaningful information about cancer progression. INTO THE CLINIC So, how does this study stack up from a clinical perspective? Tere is literature describing the value of readily available clinical and radiological features (such as the size of the efusion and presence or absence of chest wall pain), the macroscopic appearance of the pleural fuid (especially if blood-stained), and several simple biochemical parameters to defne a pretest probability for MPE. Tese factors alone ofer area-under-the-curve values >0.87 (9). Hence, it could be argued that mechanical phenotyping by DC might struggle to beat what already exists. Before being deployed in the clinic, the diagnostic utility of DC will also need to be properly “stress-tested” by using a discrete and independent validation cohort [rather than the fvefold cross-validation approach used here (5)] and a complete set of sensitivity, specifcity, pre- and posttest probability, and positive and negative predictive values presented (10). On a similar theme, the authors did not provide information on the protein content of the samples analyzed (which can be valuable because a low pro-
www.ScienceTranslationalMedicine.org 20 November 2013 Vol 5 Issue 212 212fs41
2
Downloaded from stm.sciencemag.org on December 10, 2013
FOCUS
FOCUS there is a high probability of an MPE, and the desire for fast, one-stop, biopsy-based diagnostics, may further reduce the interest in developing cytological methods. Te biggest challenge for DC, however, and one that Tse et al. noted, is to address how DC will pinpoint the precise cancerof-origin in MPE, as most cancer-related pleural efusions are due to metastatic disease from a distant primary tumor. Tis is a vital part of the cytopathologist’s current work and immunohistochemistry. Although time-consuming, tracking down the origin of a MPE allows diferentiation of, for example, primary lung [NSCLC or smallcell lung cancer (SCLC)], pleural (mesothelioma), hematological (lymphoma), and metastatic epithelial tumors (such as breast, upper gastrointestinal, renal, and colonic). As yet, this is out of the reach of DC-based cell mechanical phenotyping but is a major goal of the technology. MECHANICS IN MEDICINE Although there are lingering questions and translational barriers to mechanics-based diagnostics, this study marks a quantum leap in the clinical application of mechanical phenotyping (5). Future success requires getting this technique into the hands of many more people—from engineers to clinicians—so that more experience can be gained, applicability refned, data independently confrmed, and current concerns addressed. Choosing MPEs was a clever frst-choice demonstration because the suspended state of the cells eases sample preparation. But there are other possible clinical applications for DC. Apart from using cells obtained directly from solid tumors via biopsies, there are many pathologies with an infammatory etiology, including autoimmune disorders, in which aberrant migration, activation, phagocytosis, or cell division is implicated—processes that involve
the cytoskeleton or the nucleus and that can potentially be studied by using this technique. Tse and colleagues have opened a door to merging mechanics with medicine; now, it is well worth stepping through to explore what lies behind. REFERENCES AND NOTES 1. S. M. Hurtley, Cell biology of the cytoskeleton. Science 279, 459 (1998). 2. A. E. Pelling, M. A. Horton, An historical perspective on cell mechanics. Pfugers Arch. (2007). 3. S. E. Cross, Y.-S. Jin, J. Rao, J. K. Gimzewski, Nanomechanical analysis of cells from cancer patients. Nat. Nanotechnol. 2, 780–783 (2007). 4. T. W. Remmerbach, F. Wottawah, J. Dietrich, B. Lincoln, C. Wittekind, J. Guck, Oral cancer diagnosis by mechanical phenotyping. Cancer Res. 69, 1728–1732 (2009). 5. H. T. K. Tse, D. R. Gossett, Y. S. Moon, M. Masaeli, M. Sohsman, Y. Ying, K. Mislick, R. P. Adams, J. Rao, D. Di Carlo, Quantitative diagnosis of malignant pleural effusions by single-cell mechanophenotyping. Sci. Transl. Med. 5, 212ra163 (2013). 6. D. R. Gossett, H. T. Tse, S. A. Lee, Y. Ying, A. G. Lindgren, O. O. Yang, J. Rao, A. T. Clark, D. Di Carlo, Hydrodynamic stretching of single cells for large population mechanical phenotyping. Proc. Natl. Acad. Sci. U.S.A. 109, 7630–7635 (2012). 7. A. E. Ekpenyong, G. Whyte, K. Chalut, S. Pagliara, F. Lautenschläger, C. Fiddler, S. Paschke, U. F. Keyser, E. R. Chilvers, J. Guck, Viscoelastic properties of differentiating blood cells are fate- and function-dependent. PLOS ONE 7, e45237 (2012). 8. A. Fritsch, M. Höckel, T. Kiessling, K. D. Nnetu, F. Wetzel, M. Zink, J. A. Käs, Are biomechanical changes necessary for tumour progression? Nat. Phys. 6, 730–732 (2010). 9. L. Valdés, E. San-José, L. Ferreiro, F.-J. González-Barcala, A. Golpe, J. M. Alvarez-Dobaño, M. E. Toubes, N. RodríguezNúñez, C. Rábade, A. Lama, F. Gude, Combining clinical and analytical parameters improves prediction of malignant pleural effusion. Lung, published online 2 October 2013 (10.1007/s00408-013-9512-2). 10. M. A. Martínez-García, E. Cases-Viedma, P. J. CorderoRodríguez, M. Hidalgo-Ramírez, M. Perpiñá-Tordera, F. Sanchis-Moret, J. L. Sanchis-Aldás, Diagnostic utility of eosinophils in the pleural fluid. Eur. Respir. J. 15, 166–169 (2000). Competing interests: J.G. holds a patent on the optical stretcher technology. 10.1126/scitranslmed.3007731 Citation: J. Guck, E. R. Chilvers, Mechanics meets medicine. Sci. Transl. Med. 5, 212fs41 (2013).
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tein “transudate” strongly predicts a nonmalignant etiology). Moreover, the authors did not test many MPE samples from patients with non–small cell lung cancer (NSCLC), which is one of the most common causes of MPE. Additional testing with more and varied patient samples will give a refned view of the clinical capabilities of DC. Perhaps the most promising clinical application of DC relates to the value of obtaining unbiased mechanical phenotyping information in patients with “atypical” or “reactive” cytology or in patients with nonmalignant cytology on initial sampling but a high pretest probability of pleural malignancy according to clinical, imaging, and biochemical analyses; these are both common situations. Hence, this technique may ofer most in the realm of improving diagnostic accuracy or suspicion. Despite improvement in diagnostics, the poor outlook for most patients with MPE dictates that DC profling—or diagnostics in general—may not afect actual prognosis. Claims that this technology when optimized might reduce health care costs are also probably overstated. Hence, the authors’ predictions about reduction in workload are based on excluding all cytopathological analysis of samples with high NPV (scores of 6 or less) or high PPV (scores >8), which does not refect the clinical scenario. Likewise, although it has been argued that mechanical phenotyping will reduce the need for cytopathologists’, input in resourcepoor settings, establishing this technology is likely—at least initially—to be expensive and potentially more complex than the basic para%n-embedded sample preparation used currently for microscopy. Using fresh rather than fxed samples also mandates category 2 laboratory handling, which may contribute to a higher cost. In contrast, in advanced health care systems, the move to early thoracoscopy in patients in which
