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PAPER View Article OnlineView Journal | View Issue

964 | Lab Chip, 2014, 14, 964–971 This journal is © The R

a Biomedical Engineering Department, Cornell University, Ithaca, NY 14853, USAb Sibley School of Mechanical and Aerospace Engineering, Cornell University,

240 Upson Hall, Ithaca, NY 14853, USA. E-mail: de54@cornell.edu;

Fax: +1 (607) 255 1222; Tel: +1 (607) 255 4861

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c3lc51173a

Cite this: Lab Chip, 2014, 14, 964

Received 15th October 2013,Accepted 13th December 2013

DOI: 10.1039/c3lc51173a

www.rsc.org/loc

Mechanical decision trees for investigating andmodulating single-cell cancer invasion dynamics†

Michael Maka and David Erickson*b

Physical cues exist across all biological scales, from the geometries of molecules to the shapes of

complex organisms. While their roles have been identified across a range of scales, i.e. the arrangements

of biomolecules and the form and function of tissues, less is known in some intermediate lengths.

Particularly, at the cell scale, there is emerging evidence demonstrating the impact of mechanical signals,

such as substrate stiffness and confinement, on many critical biological processes and malignancies,

especially cancer dissemination. In the context of cell invasion, it is currently unclear how cells select

from accessible mechanical paths that result in migratory patterns observed in physiological

environments. Here, we devise microchannel decision trees to explore how fundamental and ubiquitous

mechanical factors, specifically dimensionality and directionality, affect migratory cell decision making.

We then implement strategies based purely on mechanical asymmetries to induce repetitive, non-disseminating

motions, in a phenomenon we call iteratio ad nauseam.

Introduction

Cell invasion is a critical component of cancer metastasis, aprocess associated with many mechanical transport stepsthrough physically complex environments, including cell nav-igation through the heterogeneous porous medium of thetumor stromal extracellular matrix (ECM), permeation acrossendothelial barriers, and circulation and trafficking in micro-vessels.1–3 The physical interactions of cancer cells with themechanical components of these environments are not wellunderstood. To break down this complex process into anaddressable form, here we consider quantized cell decisionmaking events during invasion. We assume the scenario of acell in 3D space with n available tangential paths; this is anal-ogous to a cell in ECM surrounded by n pores of various char-acteristics. If these paths are all accessible then there is afinite probability Pi, where i = 1, 2,…n, in which the ith pathwould be chosen. The average displacement of the cell at eachdecisional step can be represented by the vector <x>, where

x xi

n

iP1

i (1a)

Pi = F[environmental signals] (1b)

and xi is the unit step in the direction of the ith path. Ingeneral, Pi is a multi-parameter function F of the propertiesof the ith path, including canonical chemical signals such aschemotactic gradients and physical signals such as substratestiffness, stress and strain fields, and flow. The ultimate goalis to comprehensively elucidate all of the modulators of Pi inorder to be able to predict exact cell trajectories duringinvasion. While many chemical factors have been identifiedand associated with cancer, such as the overexpression orderegulation of epidermal growth factor receptors (EGFRs)and G-protein coupled receptors (GPCRs),4 by contrast muchless is known about mechanical factors. Therefore, here wefocus exclusively on mechanical factors. Previous work hasdemonstrated the role of substrate stiffness in malignanttransformation5 and stiffness gradients in guiding migratorydirections via durotaxis.6 More recent work has shown thatfibrillar alignment and interstitial flow in 3D ECMs can alsodirect paths via topography7 and autologous chemotacticgradients,8,9 respectively. However, it is still unclear fromthese studies how cells select paths at each decisional step.Current state-of-the-art models for cell invasion, which islargely based on cells embedded in 3D ECMs, exhibit an envi-ronment that consists of a characteristically heterogeneousfibrillar network of pores with large dispersion in size andlocal alignment. These features occlude our understanding ofthe contribution of basic characteristics in the mechanicalenvironment, such as dimensional and directional signals,toward cell invasion. Microchannel-based systems with well-defined

oyal Society of Chemistry 2014

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features can enable this analysis. Cell-scaled mechanical pathshave been shown to promote highly persistent migratory andinvasive behavior, and subnucleus gaps and pores rate-limitinvasion.10–13 Novel experimental and computational modelsare emerging that explore the impact of confinement oncell migration.10,14,15 Biochemical gradients generated insidemicrochannels can be used to investigate chemotaxis andimmune cell chemotactic response. For instance, bifurcatingmicrochannels with different chemoattractant profiles, whichare generated by controlling the channel lengths betweenthe chemical source (outlet) and sink (inlet), have beenused to investigate neutrophil chemotactic response to fMLP(Formyl-methionyl-leucyl-phenylalaine).16 Microgeometries in2D studies also have been shown to impact cell behavior, fromdirected migration to stem cell differentiation.17,18 Despitethese recent advances, cell migratory decision making, andthus the basic mechanism in the formation of complex inva-sion patterns, in 3D as a function of mechanical modulators isstill unsolved. The goal in our current work is to focus specifi-cally on fundamental mechanical modulators in the microenvi-ronment, so we aim to eliminate externally applied chemicalgradients. To do this, in our microchannel devices, we connectthe inlet and outlet to a single unifying reservoir. This elimi-nates chemical and pressure gradients across the channels, asfurther described in the methods section, and enables ourwork to emphasize on engineered local mechanical featuresin the cell invasion path. The physiological local environment(e.g. the ECM) around individual cancer cells contains numerouspossible paths that are mechanically disperse (varying poresizes and fiber orientation),3,19 and currently we cannot predictthe path selection behavior based on local mechanical signals.This is critical because mechanical signals are omnipresent,so if they do indeed have an impact on migratory decisionaloutput, identifying their roles could provide fundamentalinsights toward the very phenomenon of cell invasion, enablingus to better predict and model this process.

Results and discussionsMechanical decision trees

Our work here aims to develop a system that can elicitmigratory decisional processes with well-defined mechanicalfeatures that span the cell and subnucleus-scales, which aretwo scales that induce unique responses in cells,10,11,13 andincorporate directional cues that consider migratory persis-tence.20 Thus, our approach, through precise microchanneldefinitions, uniquely integrates a priori ubiquitous differen-tial mechanical modulators of cell behavior and specificallytargets their contributions toward cell decision makingduring invasion. We focused on two mechanical factors –

dimensionality and directionality. Their existence is funda-mental and ubiquitous in all physical and physiological envi-ronments, but their role in cell invasion is not well understood.For instance, during cancer invasion, matrix remodelingcould lead to the generation of directionally-guided persistenttracks via proteolytic degradation and aligned ECM fibers

This journal is © The Royal Society of Chemistry 2014

via cell tension.19,21,22 These physical cues have been shownto promote cancer cell dissemination and lead to highly per-sistent migratory states both in native-like matrix models andmicropatterned environments.10,23 However, the statistics anddynamics of how cells make migratory decisions in responseto these physical properties in their microenvironment havenot been systematically studied in a quantitative manner.To address this, we aimed to establish a platform thatspecifically modulates the local dimensional and directionalmechanical signals around individual cells.

We created a microchannel system with binary decisiontrees implemented for single invading cells. Just as chemo-taxis and durotaxis studies probe cell affinities toward achemotactic or substrate stiffness gradient, the decision treemicrochannels here is an enabling and quantitative means tostudy subtle cell behavior and preferences in response tocommon mechanical signals in the local environment. In thisenvironment, eqn (1a) simplifies to:

⟨x⟩ = P1x1 + P2x2 (2a)

Pi = F[dimension, direction] (2b)

As shown in Fig. 1, cells are loaded into the microchannelinlet reservoir. They spontaneously migrate unidirectionallyin the cell-scaled channels and encounter the decision tree.Decision trees of the same design are serially patterned ineach separate channel, and two different designs are incorpo-rated in parallel. The first design is a circular pattern withtwo path branches that split at the same angle which is per-pendicular to the initial cell path; the larger path at the tophas a width of 10 μm and the smaller path at the bottom hasa subnucleus width of 3.3 μm. The second design is a semi-circular pattern; the features are identical to the first designexcept the bottom smaller path is collinear with the originalpath leading to the decision tree. x1 and x2 in eqn (2a) referto the top and bottom paths, respectively. The decisionalprobabilities Pi can then be represented as:

P1 = F[cell scale, ⊥] (2c)

P2 = F[subnucleus scale, ⊥] (2d)

for the circular design and

P1 = F[cell scale, ⊥] (2e)

P2 = F[subnucleus scale, ∥] (2f)

for the semicircular design. The goal of this work is to experi-mentally elucidate P1 and P2 of the different binary trees inorder to identify the intrinsic mechanical affinities of inva-sive cells. For our studies we used the MDA-MB-231 breastadenocarcinoma cell line, which models highly metastaticcancer cells and thus could provide insights toward aggres-sively invasive behavior.

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Fig. 1 Schematics and images illustrating the decision treemicrochannel device concept and operations. a) Cells are loadedinto the device via pipetting into the reservoir. They will thenspontaneously invade into the microchannels. There are two patternsincorporated into our device design. The first design is a circularpattern with a larger arched top path (cell-scaled, 10 μm) and a smallerarched bottom path that is highly confining (subnucleus-scaled,3.3 μm), and the second design is a semicircular pattern with the samedesign features as the circular pattern except that the smaller bottompath is straight and collinear to the original cell path. The height of thechannels is 10 μm. b) Conceptual illustration of a cell migrating along aparticular direction and encountering an interface with split paths. Thegoal is to analyze some under-explored but ubiquitous factors thatbias the decision making process in route choosing. c) Typical imagesof cells in the split path device. This matrix of images shows thepossible cell–path interactions at the path junction. In both patterns,cells can exhibit a single extension interaction, in which the cellmigrates along one leading edge, or a split extension interaction inwhich two leading edges, with one in each path, compete for the cell'sultimate decision. Leading edges are marked by arrows.

Fig. 2 Cell invasion dynamics in decision tree microchannels. a) A cell enexhibits split extensions. Eventually, one side collapses and the cell is polarsemicircular pattern and split extensions are formed. The extensions elongin the cell being polarized along the remaining leading edge. c, d) Blebbistalong and thin extensions that drag the cell body along in a motile mode tthe top path of the circular pattern in (c) and along the bottom path ofrounded with less noticeable extensions and have decreased migratory peminutes. For scale reference, the width of the top path is 10 μm.

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As shown in Fig. 1c, as an individual cell encounters thedecision tree, two scenarios can occur. The cell exhibitseither a single extension path choice, in which the cell entersthe selected path with no contest, or a split extension pathchoice, in which the cell splits into two competing edges. Inthe latter case, as demonstrated in Fig. 2a and b and ESI†videos 1 and 2, the two competing edges both extend and thecell appears to exhibit a highly tensional state. Eventually,one of the edges collapses and the cell is polarized along theremaining edge. This competing edge phenomenon andthe subsequent dynamics elicited in the decision treemicrochannels are difficult to recreate and analyze in othercell invasion models, such as with cells embedded in 3DECMs, where the heterogeneous fibrillar meshwork masksthe subtle dynamics in mechanical cell decision making.

Next we treated the cells with blebbistatin (Bleb) and pac-litaxel (Taxol). Both molecules have been demonstrated previ-ously to have an impact on cell invasiveness. Blebbistatin isan inhibitor of non-muscle myosin IIa, which is implicatedin cell contractility and tensional force generation.5,7,24–26

Myosin IIa plays an important role in matrix reorganizationin 3D, leading to local matrix alignment and enabling cellinvasion.7,25 In general, myosin contracts actin filaments inthe cytoskeleton, enabling cells to squeeze across constrictionpoints and navigate through dense porous matrices in3D without necessarily requiring protease activity.27 Theamoeboid motile mode is also regulated by actomyosincontractility and can be induced when matrix proteolysisis inhibited.28 Previous studies have demonstrated that blebbistatincan inhibit invasion in 3D gels and can alter tractionforces.5,7,25 In particular, cancer cells treated with blebbistatinhave decreased capacity in invasion into 3D Matrigel when

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counters the decision tree of the circular pattern. Upon entry, the cellized along the other edge. b) A cell encounters the decision tree of theate in competing directions until asymmetric collapse occurs, resultingtin-treated cells typically exhibit an altered cell morphology. They havehat resembles a tethered ball. Here, the extension drags the cell alongthe semicircular pattern in (d). e) Taxol treated cells tend to be morersistence. Arrows point to cell extensions. All time coordinates are in

Fig. 3 Cell decision making statistics. a) Untreated, 50 μMblebbistatin-treated, and 10 μM taxol-treated cells have a probability ofmaking a decision within 5 hours of encountering the decision tree of0.90 (n = 97), 0.86 (n = 70), and 0.23 (n = 22), respectively, where n isthe number of cells. b) The probability of a cell choosing the larger(top) path for untreated cells in the circular pattern, untreated cells inthe semicircular pattern, blebbistatin-treated cells in the circular pat-tern, and blebbistatin-treated cells in the semicircular pattern are 0.91(n = 66), 0.68 (n = 63), 0.90 (n = 59), 0.33 (n = 104), respectively,where n is the number of decisions observed. ** indicates p < 0.01and n.s. indicates not statistically different based on the chi-squaretest. Error bars are standard error of the mean (s.e.m.) calculated fromthe Bernoulli distribution.

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seeded on the surface and have reduced uropod formation andcell speeds when embedded inside the gel.25 More recent studieshave shown that in 3D collagen matrices, actomyosin contrac-tility and proteolytic activity can cooperate or compensate foreach other to promote cell invasion and nucleus deformationand translocation across constrictions by modulating forcegeneration and matrix pore size.29 Here we demonstrate that inconfined spaces, blebbistatin alters the migratory mode ofcells and changes invasion patterns. Blebbistatin-treated cellsexhibit morphologies with long and thin extensions and typi-cally have more rounded cell bodies. This phenotype gives sem-blance of a tethered ball motile mode, as in a thin stringpulling on a tethered ball, as shown in Fig. 2c and d and ESI†video 3.

Taxol stabilizes microtubules and is a common chemo-therapeutic traditionally used for anti-mitotic effects.30 Micro-tubule disruption has also been shown to inhibit a cell'sability to permeate through subnucleus-scaled constrictionsand impair cell polarity.13,20,31 Taxol-treated cells tend to losemigratory persistence and exhibit a more rounded morphology,as shown in Fig. 2e and ESI† video 4.

Our results show that as the invading cells encounter thedecision tree, >85% of untreated and blebbistatin-treatedcells are able to make a path decision within 5 hours, butmost taxol-treated cells (>77%) fail to make a decision, asshown in Fig. 3a. This shows that taxol (at 10 μM) is a deci-sion suppressor. Next, we analyzed the decisions of theuntreated and blebbistatin-treated cells. In Fig. 3b, ourresults from the circular pattern show that untreated invad-ing cells have an overwhelmingly high affinity towards largerchannels of ≈90%. However, when the directionality of thesmaller channel is altered to be collinear with the originalcell path as in the semicircular pattern, the affinity for thelarger path decreases to 68%, demonstrating that migratorypolarization effects can bias cell invasion preferences. Whenthe cells are treated with blebbistatin, the affinity for the col-linear route of the smaller path in the semicircular pattern isfurther increased to 67%, but the affinities are unchangedin the circular pattern. These results suggest inhibition ofmyosin IIa increases the invading cells' sensitivity to direc-tionality, while maintaining the path size affinity when direc-tional biases are not present. Here, we have shown thatdimensional and directional factors, which are present alongcritical steps during cancer metastasis and other phenomenaassociated with cell motility, can bias cell decision makingin a tunable manner, and molecular inhibitors can furthermodulate those decisions.

Cell ring traps and iteratio ad nauseam

In understanding some of the mechanical and molecularmodulators of cell invasive behavior, we can begin to designstrategies to manipulate the patterns of invasion. We haveshown that cells have an affinity towards cell-scaled pathsover subnucleus-scaled paths that can be altered via direc-tional cues and actomyosin activity inhibition. Here, we

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designed a new mechanical microenvironment that intro-duces an invasion path, with directional and dimensionalasymmetries, that is aimed to bias and prolong cell residencetimes in localized regions. We call this a ring trap.

As shown in Fig. 4a, the trap consists of a cell-scaled ringregion with subnucleus-scaled entrance/exit paths that areperpendicular to the ring. Two designs are incorporated inparallel – the long trap and the short trap, with long andshort exit constrictions, respectively. Since longer trapsrequire permeating cells to undergo larger deformations (andthus require more energy), we hypothesized that this maymodulate the trapping stiffness of the rings. The concept isto utilize geometric asymmetry to induce invasive cells topreferentially remain inside the ring and invade in circles.

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Fig. 4 Cell invasion dynamics in ring traps. a) Two different trap designs are incorporated in parallel, the short trap and the long trap with 10 μmlong exits and with 60 μm long exits, respectively. The outer ring has a radius of 50 μm. b) As a cell enters the ring trap, it is focused by thesubnucleus-scaled constriction. Then it emerges into the trap and expands in a symmetric manner. Next, spontaneous symmetry breaking inducespolarized cell migration. Arrows point in the direction of cell extension and migration. c) Cells that enter the trap often exhibit the phenomenoniteratio ad nauseam, during which the cells invade in circular patterns in a confined space rather than disseminate. Arrows point in the direction ofcell migration. d) The trap lifetime of untreated cells is over 18 hours, and this is extended by blebbistatin treatment (n = 46, 42, 38, 18 for cells inthe short trap untreated, long trap untreated, short trap blebbistatin-treated, and long trap blebbistatin-treated, respectively, where n is thenumber of trapping events). The horizontal line denotes the 10 hour mark. Note that this data includes censored data points, i.e. the cells areeither already in the trap at the beginning of the experiments or are still in the trap at the end of the experiments, so these measurements areunder-estimates. e) The probability that a cell spends more than 10 hours in the ring trap is shown for the long and short traps for untreated andblebbistatin treated cells. This enables an assessment of the statistical difference between untreated and blebbistatin-treated cells when includingcensored data. The probabilities are 0.54, 0.57, 0.95, 0.89 for cells in the short trap untreated, long trap untreated, short trap blebbistatin-treated,and long trap blebbistatin-treated, respectively, for the same data as in (d). Error bars are standard error of the mean (s.e.m.) calculated from theBernoulli distribution. We note that censored data points under 10 hours (7 out of 151 data points from the raw data) were discarded in order toeliminate arbitrarily short trap lifetimes. f) Cell division promotes escape from the ring traps. Immediately after cell division, the first cell thatescapes exhibits a trap lifetime of only around 4.5 hours (n = 21), in comparison to 18+ hours (n = 46) for the overall average in the short trap. Weagain did not include censored data under 10 hours to eliminate arbitrary short trap lifetimes. We note however that for this data set, only 1 out of68 data points fell in this category, and including that data point did not alter the statistical significance of our results. Also there were no censored datapoints for the cell escape after division data. * indicates p < 0.05 and ** indicates p < 0.01. All time stamps on time lapse image stacks are in minutes.

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Our experiments show that cell–trap interactions exhibitseveral phenomena. As cells invade through the subnucleus-scaled entrance of the ring trap, typically they enter the ringin a symmetric manner, with split edges extending in opposingdirections, as shown in Fig. 4b and ESI† video 5. After severalminutes, the cells undergo spontaneous symmetry breaking,inducing the onset of polarized cell migration. Thus, we have

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shown here a novel way of inducing spontaneous symmetrybreaking in single-cells by first focusing the cell with asubnucleus barrier, followed by a mechanical barrier upon exitto induce an initial symmetric response. This is essentially a“cell scattering” experiment, analogous to photon scatteringexperiments in the Rayleigh (subphoton-scaled) and Mie(photon-scaled) regimes that helped uncover the nature of

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light–matter interactions. Spontaneous symmetry breaking canthen be observed and analyzed at the single-cell level, andsince symmetry breaking is a fundamental feature that governsthe formation and function of all of life,32–34 enabling experi-mental apparatuses are important for more in depth studies.In particular, symmetry breaking in single-cell migration, espe-cially in 3D, is not well understood. Thus, we have created away of systematically inducing single-cell scattering experi-ments and eliciting the dynamics of cell-mechanical environ-ment interactions.

Next, the well-designed asymmetries in dimensionalityand directionality suppress cell dissemination by localizinginvasion zones. As shown in Fig. 4c and ESI† video 6, cellstypically remain in the ring trap for an extended period oftime and invade in circular and repetitive patterns, which wecall iteratio ad nauseam. We characterized the trap lifetimeand demonstrate in Fig. 4d that cells spend over 18 hours inthe ring traps. The trap lifetime can be extended byinhibiting myosin IIa with blebbistatin, which increases theproportion of cells that spend greater than 10 hours in thetrap from 55% to 90%, as shown in Fig. 4d and e. The traplifetime also does not appear to be strongly impacted by thelength of the exit constriction. We note here that in our previ-ous studies, we have shown that these aggressive breastcancer cells are highly persistent, maintain speeds on theorder of micrometers per minute, and are readily able to per-meate through the subnucleus-scaled barriers when no deci-sion trees are presented.13 The strategically designed ringtrap architectures here are able to confine cells within aregion of 50 μm radius for an extended period of time simplyby catering to natural migratory affinities. Finally, weexplored the escape mechanisms of cells in the ring traps.We demonstrate in Fig. 4f and ESI† video 7 that cell divisionwithin or immediately before entering the ring trapspromotes cell escape. The trap lifetime after division isreduced to around 4.5 hours, which is significantly less thanthe 18+ hours of the general population. This is an interestingresult that opens a new perspective for future studies, asexisting paradigms typically do not consider any couplingbetween cell migration and proliferation. Here we have shownthat there is causality between the cell cycle and cell invasive-ness, suggesting that invasiveness is a dynamic rather thanstatic property that evolves with the natural temporal changesof each cell.

Conclusion

Cell behavior during invasion is a highly complex processthat is not well understood. We created microfluidic devicesthat elicit the decision making process of cells when encoun-tering mechanical asymmetries on the cell and subnucleusscale. By using well-defined geometries and features, weprobed the path affinities of invasive cells and exploredmechanical and molecular means of modulating these affini-ties. We demonstrated that dimensional and directional cuescan bias cell invasion patterns, actomyosin inhibition can

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alter migratory decision making, and properly designedmechanical asymmetries can promote the phenomenoniteratio ad nauseam. The devices and experiments shown herecan help reveal more complex factors in the dynamics ofinvasion at the single-cell level. In future studies and nextgeneration modules of our device, the incorporation of angu-lar modulation, additional path choices, alternate geometriesof channel entries and exits, and a systematic combinatorialanalysis of the effects of mechanical signals can help gener-ate empirical measurements of eqn (1a) for different celltypes and elucidate cell behaviors in a well-defined environ-ment that starts to possess the mechanical complexities ofphysiological 3D matrices. In particular, micro- and nano-topographies at channel entry and exit points could poten-tially modulate cell force generation and traction, leading toaltered cell behavior.17

Additionally, we emphasize from our results that purelymechanical factors in a 3D environment can induce complexcell behavior. This suggests that mechanically modulatingtumor microenvironments may be a potential method inaltering cancer invasion patterns, and we have shown a par-ticular type of pattern that could trap invasive cells. Futurework in developing tissue engineering methods that can stra-tegically alter the architecture of the fibrillar meshworkof the tumor stroma, particularly based on preconceivedmodules such as the ring trap presented here, may be a newavenue in cancer therapy aimed at suppressing cancerdissemination. Additionally, the trap micropatterns, with itssmall footprint, may be converted into a micro-pill or particleformat that could be injected into local tumor environmentsand serve as traps for invasive cells. In particular, previouslywe have shown that non-metastatic breast epithelial cells areless likely to permeate through subnucleus-scaled barriersthan highly metastatic cells,12 so these patterns may be ableto selectively trap the most aggressive cells. The devices anddesigns presented here illustrate a means to rapidly prototypemechanical modules that could impact cell migratory behav-ior and generate complex and tunable patterns of motility.

MethodsCell culture

MDA-MB-231 cells were obtained from the National CancerInstitute Physical-Sciences in Oncology Centers (NCI PS-OC),originally from the American Tissue Culture Collection (ATCC).They were cultured at 37 °C without CO2 supplement inLeibovitz L-15 media (Life Technologies) with 10% fetal bovineserum (Atlanta Biologicals) and 1% Penicillin-Streptavidin(Life Technologies).

Device fabrication

Devices were fabricated at the Cornell Nanoscale Scienceand Technology Facility (CNF). Standard photolithographyfollowed by soft lithography was used to fabricate polydi-methylsiloxane (PDMS) microfluidic devices. Briefly, SU8resist was spun onto a wafer and exposed in a UV stepper

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aligner under a photomask with the designed patterns tocreate the mold master. PDMS was cast onto the master,cross-linked, and bonded to glass slides to create the finalmicrofluidic devices.

Cell loading into devices

The devices were made hydrophilic via oxygen plasma treat-ment for 40 seconds. Complete cell growth media (L-15 plus10% FBS and 1% Penicillin-Streptavidin) was added into thereservoirs and allowed to coat the channels with serumproteins prior to cell loading. Cells in complete media wereloaded into the channels by applying a gravity driven pressuregradient between the inlet and outlet reservoirs. After cellswere injected into the device, the inlet and outlet reservoirswere filled and connected to the same larger unifying reser-voir again filled with complete media. By connecting the inletand outlet of the channels to the same reservoir, chemicaland pressure gradients across the channels were eliminated.A schematic illustrating the integration of the unifying reser-voir is shown in ESI† Fig. 1, where the larger reservoir isplaced at the top of the device and equilibrates the inlet andoutlet to the same pressure. We also traced diffusing celldebris in the channels and show in ESI† Fig. 2 and video8 that significant flow, with flow rates comparable to those ininterstitial flow experiments i.e. around 1 μm s−1,9,35 is notobserved across these channels. Complete cell media withserum was used in our experiments in order to maintain thefully functional cell states observed under normal culture con-ditions. Full deprivation of serum may artificially impair cellinvasive capacity.36 We note that through the course of theexperiments, autologous gradients may be generated locallyinside the channels via serum and nutrient consumption byinvading cells. Future experiments with actively perfusedmedia that replenishes the channels continuously and/or theuse of serum-free media could help in the investigation ofautologous chemical gradients and their impact on cell deci-sion making in response to mechanical cues. By imposingdifferent media constraints, we can gain insights toward therange of possible physiological conditions.

Experiments and analysis

Time lapse video microscopy was used to record cell invasiondynamics in the microfluidic channels, which were kept at37 °C via a heating plate. Videos were recorded at 3.4minutes per frame. Image analysis was performed manuallyon ImageJ. Data processing was performed using customMATLAB code. For statistical analysis, chi-square and studentt-tests were used. Statistical significance is indicated by * and** for p < 0.05 and p < 0.01, respectively. For pharmacologictreatments, we added the complete growth media with eithertaxol (Cytoskeleton, Inc.) at 10 μM for 7 hours or blebbistatin(Sigma-Aldrich) at 50 μM for 1 hour in the device reservoirbefore experimental tracking of cells. Cells were tracked whileunder continuous drug treatment. Concentrations of thedrugs and the time of drug incubation before experiment

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were chosen based on levels and response times that induceclear and observable phenotypic changes in cell morphologyand behavior according to previous studies.10,26 Cell affinitywas deduced by observing cells as they invaded towards themechanical decision trees. Once the body of a cell enters oneof the paths, the cell decision is scored for that path. We notethat conventional biology studies usually do not considermultiple measurements per cell, and newer single-cell studiestypically measure the behavior of each cell once. However,because the cell is dynamic and plastic with the capability ofaltering morphological states, size, and motile modes, it isimportant to sample each cell multiple times in order to fullyappreciate the capability of each individual cell. Our devicedesign, with decision trees patterned serially along eachchannel, enables each cell to be probed multiple times. Inour experiments, each cell is typically sampled two to fourtimes. Future studies that explore even larger sampling foreach individual cell can enable us to address a deeper under-standing of the fundamental behaviors and dynamics ofsingle-cells and provide insights toward heterogeneity, plas-ticity, and ergodicity in cell populations.

It is also noteworthy here that in the confined channelsused in our experiments, cells exhibit a 3D environment, astheir protrusions are seen to extend both along the center ofthe channels as well as along the channel side walls (ESI†videos 1–7). Both glass and PDMS are conducive to celladhesion and migration, especially when the surfaces arehydrophilized (e.g. via oxygen plasma treatment) and coatedwith serum.37 MDA-MB-231 cells are also capable of invad-ing persistently in confined channels without any substratecoating beyond serum proteins in the media.12,13 In confinedmicrochannel spaces, it has also been previously demonstratedthat adhesion sites can form along all three dimensions.38

Acknowledgements

The work described was supported by the Cornell Center onthe Microenvironment and Metastasis through Award NumberU54CA143876 from the National Cancer Institute. This workwas performed in part at the Cornell NanoScale Science andTechnology Facility, a member of the National NanotechnologyNetwork, which is supported by the National Science Foundation(grant ECS-0335765). Michael Mak is a National Science Foun-dation Graduate Research Fellow.

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