Enhanced Dendritic Actin Network Formation in Extended Lamellipodia Drives Proliferation in Growth-Challenged Rac1P29S Melanoma Cells

Morphological control of merlin-Rac antagonism in proliferation-promoting signaling

The extension of lamellipodia, which are thin, fanlike projections at the cell periphery, requires the assembly of branched actin networks under the control of the small GTPase Rac1. In melanoma, a hyperactive P29S Rac1 mutant is associated with resistance to inhibitors that target the kinases BRAF and MAPK and with more aggressive disease because it sequesters and inactivates the tumor suppressor merlin (encoded by NF2) inside abnormally large lamellipodia. Here, we investigated how these merlin-inactivating lamellipodia are maintained using quantitative, live cell imaging of cell morphology and signaling dynamics. We showed that Rac1 and merlin activity were regulated in spatially confined regions or microdomains within the lamellipodium. The role of merlin as a proliferation-limiting tumor suppressor required its ability to inhibit lamellipodial extension and to locally inhibit Rac1 signaling. Conversely, local inactivation of merlin in lamellipodia released these restraints on morphology and signaling, leading to enhanced proliferation. Merlin and Rac1 are thus in a morphologically and dynamically regulated double-negative feedback loop, a signaling motif that can amplify and stabilize modest stimuli of lamellipodia extensions that enable melanoma to sustain mitogenic signaling under growth challenge. This represents an example of how acute oncogenicity is promoted by collaborations between cell morphological programs and biochemical signaling.

Spatial proteomics of ER tubules reveals CLMN, an ER-actin tether at focal adhesions that promotes cell migration

The endoplasmic reticulum (ER) is structurally and functionally diverse, yet how its functions are organized within morphological subdomains is incompletely understood. Utilizing TurboID-based proximity labeling and CRISPR knockin technologies, we map the proteomic landscape of the human ER network. Sub-organelle proteomics reveals enrichments of proteins into ER tubules, sheets, and the nuclear envelope. We uncover an ER-enriched actin-binding protein, calmin/CLMN, and define it as an ER-actin tether that localizes to focal adhesions adjacent to ER tubules. Mechanistically, we find that CLMN depletion perturbs adhesion disassembly, actin dynamics, and cell movement. CLMN-depleted cells display decreased polarization of ER-plasma membrane contacts and calcium signaling factor STIM1 and altered calcium signaling near ER-actin interfaces, suggesting that CLMN influences calcium signaling to facilitate F-actin/adhesion dynamics. Collectively, we map the sub-organelle proteome landscape of the ER, identify CLMN as an ER-actin tether, and describe a non-canonical mechanism by which ER tubules engage actin to regulate cell migration.

Autonomous learning of pathologists' cancer grading rules

Deep learning (DL) algorithms have demonstrated remarkable proficiency in histopathology classification tasks, presenting an opportunity to discover disease-related features escaping visual inspection. However, the "black box" nature of DL obfuscates the basis of the classification. Here, we develop an algorithm for interpretable Deep Learning (IDL) that sheds light on the links between tissue morphology and cancer biology. We make use of a generative model trained to represent images via a combination of a semantic latent space and a noise vector to capture low level image details. We traversed the latent space so as to induce prototypical image changes associated with the disease state, which we identified via a second DL model. Applied to a dataset of clear cell renal cell carcinoma (ccRCC) tissue images the AI system pinpoints nuclear size and nucleolus density in tumor cells (but not other cell types) as the decisive features of tumor progression from grade 1 to grade 4 - mirroring the rules that have been used for decades in the clinic and are taught in textbooks. Moreover, the AI system posits a decrease in vasculature with increasing grade. While the association has been illustrated by some previous reports, the correlation is not part of currently implemented grading systems. These results indicate the potential of IDL to autonomously formalize the connection between the histopathological presentation of a disease and the underlying tissue architectural drivers.

Vimentin filament transport and organization revealed by single-particle tracking and 3D FIB-SEM

Vimentin intermediate filaments (VIFs) form complex, tightly packed networks; due to this density, traditional imaging approaches cannot discern single-filament behavior. To address this, we developed and validated a sparse vimentin-SunTag labeling strategy, enabling single-particle tracking of individual VIFs and providing a sensitive, unbiased, and quantitative method for measuring global VIF motility. Using this approach, we define the steady-state VIF motility rate, showing a constant ∼8% of VIFs undergo directed microtubule-based motion irrespective of subcellular location or local filament density. Significantly, our single-particle tracking approach revealed uncorrelated motion of individual VIFs within bundles, an observation seemingly at odds with conventional models of tightly cross-linked bundles. To address this, we acquired high-resolution focused ion beam scanning electron microscopy volumes of vitreously frozen cells and reconstructed three-dimensional VIF bundles, finding that they form only loosely organized, semi-coherent structures from which single VIFs frequently emerge to locally engage neighboring microtubules. Overall, this work demonstrates single VIF dynamics and organization in the cellular milieu for the first time.

Universal consensus 3D segmentation of cells from 2D segmented stacks

Cell segmentation is the foundation of a wide range of microscopy-based biological studies. Deep learning has revolutionized 2D cell segmentation, enabling generalized solutions across cell types and imaging modalities. This has been driven by the ease of scaling up image acquisition, annotation, and computation. However, 3D cell segmentation, requiring dense annotation of 2D slices still poses significant challenges. Manual labeling of 3D cells to train broadly applicable segmentation models is prohibitive. Even in high-contrast images annotation is ambiguous and time-consuming. Here we develop a theory and toolbox, u-Segment3D, for 2D-to-3D segmentation, compatible with any 2D method generating pixel-based instance cell masks. u-Segment3D translates and enhances 2D instance segmentations to a 3D consensus instance segmentation without training data, as demonstrated on 11 real-life datasets, >70,000 cells, spanning single cells, cell aggregates, and tissue. Moreover, u-Segment3D is competitive with native 3D segmentation, even exceeding when cells are crowded and have complex morphologies.

Identification of LIMK1 as a biomarker in clear cell renal cell carcinoma: from data mining to validation

PURPOSE

Clear cell renal cell carcinoma (ccRCC) is one of the most common types of renal cancer. LIM kinase 1 (LIMK1) reportedly plays an important role in tumorigenesis. However, the involvement of LIMK1 in the progression of ccRCC remains ambiguous.

METHODS

Based on the TCGA and CPTAC databases, the expression of LIMK1 in ccRCC was evaluated. In the TCGA-ccRCC cohort, the relationships between LIMK1 and immune cell infiltration as well as immune checkpoints were assessed. The high expression of LIMK1 in ccRCC was verified by qRT-PCR in four RCC cell lines. Immunohistochemistry was used to evaluate the expression of LIMK1 in clinical samples. The association between LIMK1 expression and survival prognosis was explored via Kaplan-Meier survival curve in the TCGA-ccRCC and local cohorts. The effects of LIMK1 knockdown on the proliferation, migration, and invasion abilities of RCC cells were evaluated via colony, CCK-8, wound healing, and Transwell assays.

RESULTS

Elevated expression level of LIMK1 was found in the TCGA-ccRCC cohort and was confirmed in RCC cell lines and clinical samples. Up-regulation of LIMK1 was found to be correlated with poor prognosis in TCGA-ccRCC and external cohorts. In addition, high-LIMK1 was associated with clinicopathological stage, immune cell infiltration and immune checkpoint in ccRCC. Importantly, knockdown of LIMK1 diminished the capability of proliferation, migration, and invasion in RCC cells.

CONCLUSION

LIMK1 may serve as a promising diagnostic and prognostic biomarker of ccRCC.

Role of Hypoxia and Rac1 Inhibition in the Metastatic Cascade

The hypoxic condition has a pivotal role in solid tumors and was shown to correlate with the poor outcome of anticancer treatments. Hypoxia contributes to tumor progression and leads to therapy resistance. Two forms of a hypoxic environment might have relevance in tumor mass formation: chronic and cyclic hypoxia. The main regulators of hypoxia are hypoxia-inducible factors, which regulate the cell survival, proliferation, motility, metabolism, pH, extracellular matrix function, inflammatory cells recruitment and angiogenesis. The metastatic process consists of different steps in which hypoxia-inducible factors can play an important role. Rac1, belonging to small G-proteins, is involved in the metastasis process as one of the key molecules of migration, especially in a hypoxic environment. The effect of hypoxia on the tumor phenotype and the signaling pathways which may interfere with tumor progression are already quite well known. Although the role of Rac1, one of the small G-proteins, in hypoxia remains unclear, predominantly, in vitro studies performed so far confirm that Rac1 inhibition may represent a viable direction for tumor therapy.

Anchorage-independent cell proliferation promoted by fascin's F-actin bundling

The actin filament (F-actin) bundling protein fascin-1 is highly enriched in many metastatic cancers. Fascin's contribution to metastasis have been ascribed to its enhancement of cell migration and invasion. However, mouse genetic studies clearly point to functions also in tumorigenesis, yet without mechanistic underpinnings. Here, we show that fascin expression promotes the formation of a non-canonical signaling complex that enables anchorage-independent proliferation. This complex shares similarities to focal adhesions and we refer to them as pseudo-adhesion signaling scaffolds (PASS). PASS are enriched with tyrosine phosphorylated proteins and require fascin's F-actin-bundling activity for its assembly. PASS serve as hubs for the Rac1/PAK/JNK proliferation signaling axis, driven by PASS-associated Rac-specific GEFs. Experimental disruption of either fascin or RacGEF function abrogates sustained proliferation of aggressive cancers in vitro and in vivo . These results add a new molecular element to the growing arsenal of metabolic and oncogenic signaling programs regulated by the cytoskeleton architecture.

Unique vulnerability of RAC1-mutant melanoma to combined inhibition of CDK9 and immune checkpoints

RAC1P29S is the third most prevalent hotspot mutation in sun-exposed melanoma. RAC1 alterations in cancer are correlated with poor prognosis, resistance to standard chemotherapy, and insensitivity to targeted inhibitors. Although RAC1P29S mutations in melanoma and RAC1 alterations in several other cancers are increasingly evident, the RAC1-driven biological mechanisms contributing to tumorigenesis remain unclear. Lack of rigorous signaling analysis has prevented identification of alternative therapeutic targets for RAC1P29S-harboring melanomas. To investigate the RAC1P29S-driven effect on downstream molecular signaling pathways, we generated an inducible RAC1P29S expression melanocytic cell line and performed RNA-sequencing (RNA-seq) coupled with multiplexed kinase inhibitor beads and mass spectrometry (MIBs/MS) to establish enriched pathways from the genomic to proteomic level. Our proteogenomic analysis identified CDK9 as a potential new and specific target in RAC1P29S-mutant melanoma cells. In vitro, CDK9 inhibition impeded the proliferation of in RAC1P29S-mutant melanoma cells and increased surface expression of PD-L1 and MHC Class I proteins. In vivo, combining CDK9 inhibition with anti-PD-1 immune checkpoint blockade significantly inhibited tumor growth only in melanomas that expressed the RAC1P29S mutation. Collectively, these results establish CDK9 as a novel target in RAC1-driven melanoma that can further sensitize the tumor to anti-PD-1 immunotherapy.

Rac1 promotes kidney collecting duct repair by mechanically coupling cell morphology to mitotic entry

Prolonged obstruction of the ureter, which leads to injury of the kidney collecting ducts, results in permanent structural damage, while early reversal allows for repair. Cell structure is defined by the actin cytoskeleton, which is dynamically organized by small Rho guanosine triphosphatases (GTPases). In this study, we identified the Rho GTPase, Rac1, as a driver of postobstructive kidney collecting duct repair. After the relief of ureteric obstruction, Rac1 promoted actin cytoskeletal reconstitution, which was required to maintain normal mitotic morphology allowing for successful cell division. Mechanistically, Rac1 restricted excessive actomyosin activity that stabilized the negative mitotic entry kinase Wee1. This mechanism ensured mechanical G2-M checkpoint stability and prevented premature mitotic entry. The repair defects following injury could be rescued by direct myosin inhibition. Thus, Rac1-dependent control of the actin cytoskeleton integrates with the cell cycle to mediate kidney tubular repair by preventing dysmorphic cells from entering cell division.

RhoA activation promotes glucose uptake to elevate proliferation in MAPK inhibitor resistant melanoma cells

Cutaneous melanomas harboring a B-RafV600E mutation are treated with immune check point inhibitors or kinase inhibitor combination therapies relying on MAPK inhibitors (MAPKi) Dabrafenib and Trametinib (Curti and Faries, 2021). However, cells become resistant to treatments over the timespan of a few months. Resistance to MAPKi has been associated with adoption of an aggressive amoeboid phenotype characterized by elevated RhoA signaling, enhanced contractility and thick cortical filamentous actin (F-actin) structures (Kim et al., 2016; Misek et al., 2020). Targeting active RhoA through Rho-kinase (ROCK) inhibitors, either alone or in combination with immunotherapies, reverts MAPKi-resistance (Misek et al., 2020; Orgaz et al., 2020). Yet, the mechanisms for this behavior remain largely unknown. Given our recent findings of cytoskeleton's role in cancer cell proliferation (Mohan et al., 2019), survival (Weems et al., 2023), and metabolism (Park et al., 2020), we explored possibilities by which RhoA-driven changes in cytoskeleton structure may confer resistance. We confirmed elevated activation of RhoA in a panel of MAPKi-resistant melanoma cell lines, leading to a marked increase in the presence of contractile F-actin bundles. Moreover, these cells had increased glucose uptake and glycolysis, a phenotype disrupted by pharmacological perturbation of ROCK. However, glycolysis was unaffected by disruption of F-actin bundles, indicating that glycolytic stimulation in MAPKi-resistant melanoma is independent of F-actin organization. Instead, our findings highlight a mechanism in which elevated RhoA signaling activates ROCK, leading to the activation of insulin receptor substrate 1 (IRS1) and P85 of the PI3K pathway, which promotes cell surface expression of GLUT1 and elevated glucose uptake. Application of ROCK inhibitor GSK269962A results in reduced glucose uptake and glycolysis, thus impeding cell proliferation. Our study adds a mechanism to the proposed use of ROCK inhibitors for long-term treatments on MAPKi-resistant melanomas.

Understanding cancer drug resistance with Sleeping Beauty functional genomic screens: Application to MAPK inhibition in cutaneous melanoma

Combined BRAF and MEK inhibition is an effective treatment for BRAF-mutant cutaneous melanoma. However, most patients progress on this treatment due to drug resistance. Here, we applied the Sleeping Beauty transposon system to understand how melanoma evades MAPK inhibition. We found that the specific drug resistance mechanisms differed across melanomas in our genetic screens of five cutaneous melanoma cell lines. While drivers that reactivated MAPK were highly conserved, many others were cell-line specific. One such driver, VAV1, activated a de-differentiated transcriptional program like that of hyperactive RAC1, RAC1P29S. To target this mechanism, we showed that an inhibitor of SRC, saracatinib, blunts the VAV1-induced transcriptional reprogramming. Overall, we highlighted the importance of accounting for melanoma heterogeneity in treating cutaneous melanoma with MAPK inhibitors. Moreover, we demonstrated the utility of the Sleeping Beauty transposon system in understanding cancer drug resistance.

Key role for Rac in the early transcriptional response to extracellular matrix stiffness and stiffness-dependent repression of ATF3

The Rho family GTPases Rac and Rho play critical roles in transmitting mechanical information contained within the extracellular matrix (ECM) to the cell. Rac and Rho have well-described roles in regulating stiffness-dependent actin remodeling, proliferation and motility. However, much less is known about the relative roles of these GTPases in stiffness-dependent transcription, particularly at the genome-wide level. Here, we selectively inhibited Rac and Rho in mouse embryonic fibroblasts cultured on deformable substrata and used RNA sequencing to elucidate and compare the contribution of these GTPases to the early transcriptional response to ECM stiffness. Surprisingly, we found that the stiffness-dependent activation of Rac was dominant over Rho in the initial transcriptional response to ECM stiffness. We also identified activating transcription factor 3 (ATF3) as a major target of stiffness- and Rac-mediated signaling and show that ATF3 repression by ECM stiffness helps to explain how the stiffness-dependent activation of Rac results in the induction of cyclin D1.

Unique vulnerability of RAC1-mutant melanoma to combined inhibition of CDK9 and immune checkpoints

RAC1P29S is the third most prevalent hotspot mutation in sun-exposed melanoma. RAC1 alterations in cancer are correlated with poor prognosis, resistance to standard chemotherapy, and insensitivity to targeted inhibitors. Although RAC1P29S mutations in melanoma and RAC1 alterations in several other cancers are increasingly evident, the RAC1-driven biological mechanisms contributing to tumorigenesis remain unclear. Lack of rigorous signaling analysis has prevented identification of alternative therapeutic targets for RAC1P29S-harboring melanomas. To investigate the RAC1P29S-driven effect on downstream molecular signaling pathways, we generated an inducible RAC1P29S expression melanocytic cell line and performed RNA-sequencing (RNA-seq) coupled with multiplexed kinase inhibitor beads and mass spectrometry (MIBs/MS) to establish enriched pathways from the genomic to proteomic level. Our proteogenomic analysis identified CDK9 as a potential new and specific target in RAC1P29S-mutant melanoma cells. In vitro, CDK9 inhibition impeded the proliferation of in RAC1P29S-mutant melanoma cells and increased surface expression of PD-L1 and MHC Class I proteins. In vivo, combining CDK9 inhibition with anti-PD-1 immune checkpoint blockade significantly inhibited tumor growth only in melanomas that expressed the RAC1P29S mutation. Collectively, these results establish CDK9 as a novel target in RAC1-driven melanoma that can further sensitize the tumor to anti-PD-1 immunotherapy.

Guanine nucleotide exchange factors for Rho GTPases (RhoGEFs) as oncogenic effectors and strategic therapeutic targets in metastatic cancer

Metastatic cancer cells dynamically adjust their shape to adhere, invade, migrate, and expand to generate secondary tumors. Inherent to these processes is the constant assembly and disassembly of cytoskeletal supramolecular structures. The subcellular places where cytoskeletal polymers are built and reorganized are defined by the activation of Rho GTPases. These molecular switches directly respond to signaling cascades integrated by Rho guanine nucleotide exchange factors (RhoGEFs), which are sophisticated multidomain proteins that control morphological behavior of cancer and stromal cells in response to cell-cell interactions, tumor-secreted factors and actions of oncogenic proteins within the tumor microenvironment. Stromal cells, including fibroblasts, immune and endothelial cells, and even projections of neuronal cells, adjust their shapes and move into growing tumoral masses, building tumor-induced structures that eventually serve as metastatic routes. Here we review the role of RhoGEFs in metastatic cancer. They are highly diverse proteins with common catalytic modules that select among a variety of homologous Rho GTPases enabling them to load GTP, acquiring an active conformation that stimulates effectors controlling actin cytoskeleton remodeling. Therefore, due to their strategic position in oncogenic signaling cascades, and their structural diversity flanking common catalytic modules, RhoGEFs possess unique characteristics that make them conceptual targets of antimetastatic precision therapies. Preclinical proof of concept, demonstrating the antimetastatic effect of inhibiting either expression or activity of βPix (ARHGEF7), P-Rex1, Vav1, ARHGEF17, and Dock1, among others, is emerging.

Blebs promote cell survival by assembling oncogenic signalling hubs

Most human cells require anchorage for survival. Cell-substrate adhesion activates diverse signalling pathways, without which cells undergo anoikis-a form of programmed cell death1. Acquisition of anoikis resistance is a pivotal step in cancer disease progression, as metastasizing cells often lose firm attachment to surrounding tissue2,3. In these poorly attached states, cells adopt rounded morphologies and form small hemispherical plasma membrane protrusions called blebs4-11. Bleb function has been thoroughly investigated in the context of amoeboid migration, but it has been examined far less in other scenarios12. Here we show by three-dimensional imaging and manipulation of cell morphological states that blebbing triggers the formation of plasma membrane-proximal signalling hubs that confer anoikis resistance. Specifically, in melanoma cells, blebbing generates plasma membrane contours that recruit curvature-sensing septin proteins as scaffolds for constitutively active mutant NRAS and effectors. These signalling hubs activate ERK and PI3K-well-established promoters of pro-survival pathways. Inhibition of blebs or septins has little effect on the survival of well-adhered cells, but in detached cells it causes NRAS mislocalization, reduced MAPK and PI3K activity, and ultimately, death. This unveils a morphological requirement for mutant NRAS to operate as an effective oncoprotein. Furthermore, whereas some BRAF-mutated melanoma cells do not rely on this survival pathway in a basal state, inhibition of BRAF and MEK strongly sensitizes them to both bleb and septin inhibition. Moreover, fibroblasts engineered to sustain blebbing acquire the same anoikis resistance as cancer cells even without harbouring oncogenic mutations. Thus, blebs are potent signalling organelles capable of integrating myriad cellular information flows into concerted cellular responses, in this case granting robust anoikis resistance.

Fine-grained, nonlinear registration of live cell movies reveals spatiotemporal organization of diffuse molecular processes

We present an application of nonlinear image registration to align in microscopy time lapse sequences for every frame the cell outline and interior with the outline and interior of the same cell in a reference frame. The registration relies on a subcellular fiducial marker, a cell motion mask, and a topological regularization that enforces diffeomorphism on the registration without significant loss of granularity. This allows spatiotemporal analysis of extremely noisy and diffuse molecular processes across the entire cell. We validate the registration method for different fiducial markers by measuring the intensity differences between predicted and original time lapse sequences of Actin cytoskeleton images and by uncovering zones of spatially organized GEF- and GTPase signaling dynamics visualized by FRET-based activity biosensors in MDA-MB-231 cells. We then demonstrate applications of the registration method in conjunction with stochastic time-series analysis. We describe distinct zones of locally coherent dynamics of the cytoplasmic protein Profilin in U2OS cells. Further analysis of the Profilin dynamics revealed strong relationships with Actin cytoskeleton reorganization during cell symmetry-breaking and polarization. This study thus provides a framework for extracting information to explore functional interactions between cell morphodynamics, protein distributions, and signaling in cells undergoing continuous shape changes. Matlab code implementing the proposed registration method is available at https://github.com/DanuserLab/Mask-Regularized-Diffeomorphic-Cell-Registration.

Quantitative cell imaging approaches to metastatic state profiling

Genetic heterogeneity of metastatic dissemination has proven challenging to identify exploitable markers of metastasis; this bottom-up approach has caused a stalemate between advances in metastasis and the late stage of the disease. Advancements in quantitative cellular imaging have allowed the detection of morphological phenotype changes specific to metastasis, the morphological changes connected to the underlying complex signaling pathways, and a robust readout of metastatic cell state. This review focuses on the recent machine and deep learning developments to gain detailed information about the metastatic cell state using light microscopy. We describe the latest studies using quantitative cell imaging approaches to identify cell appearance-based metastatic patterns. We discuss how quantitative cancer biologists can use these frameworks to work backward toward exploitable hidden drivers in the metastatic cascade and pioneering new Frontier drug discoveries specific for metastasis.

SRC-RAC1 signaling drives drug resistance to BRAF inhibition in de-differentiated cutaneous melanomas

Rare gain-of-function mutations in RAC1 drive drug resistance to targeted BRAF inhibition in cutaneous melanoma. Here, we show that wildtype RAC1 is a critical driver of growth and drug resistance, but only in a subset of melanomas with elevated markers of de-differentiation. Similarly, SRC inhibition also selectively sensitized de-differentiated melanomas to BRAF inhibition. One possible mechanism may be the suppression of the de-differentiated state, as SRC and RAC1 maintained markers of de-differentiation in human melanoma cells. The functional differences between melanoma subtypes suggest that the clinical management of cutaneous melanoma can be enhanced by the knowledge of differentiation status. To simplify the task of classification, we developed a binary classification strategy based on a small set of ten genes. Using this gene set, we reliably determined the differentiation status previously defined by hundreds of genes. Overall, our study informs strategies that enhance the precision of BRAFi by discovering unique vulnerabilities of the de-differentiated cutaneous melanoma subtype and creating a practical method to resolve differentiation status.

Isotropic imaging across spatial scales with axially swept light-sheet microscopy

Light-sheet fluorescence microscopy is a rapidly growing technique that has gained tremendous popularity in the life sciences owing to its high-spatiotemporal resolution and gentle, non-phototoxic illumination. In this protocol, we provide detailed directions for the assembly and operation of a versatile light-sheet fluorescence microscopy variant, referred to as axially swept light-sheet microscopy (ASLM), that delivers an unparalleled combination of field of view, optical resolution and optical sectioning. To democratize ASLM, we provide an overview of its working principle and applications to biological imaging, as well as pragmatic tips for the assembly, alignment and control of its optical systems. Furthermore, we provide detailed part lists and schematics for several variants of ASLM that together can resolve molecular detail in chemically expanded samples, subcellular organization in living cells or the anatomical composition of chemically cleared intact organisms. We also provide software for instrument control and discuss how users can tune imaging parameters to accommodate diverse sample types. Thus, this protocol will serve not only as a guide for both introductory and advanced users adopting ASLM, but as a useful resource for any individual interested in deploying custom imaging technology. We expect that building an ASLM will take ~1-2 months, depending on the experience of the instrument builder and the version of the instrument.

Intratumoral Resolution of Driver Gene Mutation Heterogeneity in Renal Cancer Using Deep Learning

Intratumoral heterogeneity arising from tumor evolution poses significant challenges biologically and clinically. Dissecting this complexity may benefit from deep learning (DL) algorithms, which can infer molecular features from ubiquitous hematoxylin and eosin (H&E)-stained tissue sections. Although DL algorithms have been developed to predict some driver mutations from H&E images, the ability of these DL algorithms to resolve intratumoral mutation heterogeneity at subclonal spatial resolution is unexplored. Here, we apply DL to a paradigm of intratumoral heterogeneity, clear cell renal cell carcinoma (ccRCC), the most common type of kidney cancer. Matched IHC and H&E images were leveraged to develop DL models for predicting intratumoral genetic heterogeneity of the three most frequently mutated ccRCC genes, BAP1, PBRM1, and SETD2. DL models were generated on a large cohort (N = 1,282) and tested on several independent cohorts, including a TCGA cohort (N = 363 patients) and two tissue microarray (TMA) cohorts (N = 118 and 365 patients). These models were also expanded to a patient-derived xenograft (PDX) TMA, affording analysis of homotopic and heterotopic interactions of tumor and stroma. The status of all three genes could be inferred by DL, with BAP1 showing the highest sensitivity and performance within and across tissue samples (AUC = 0.87-0.89 on holdout). BAP1 results were validated on independent human (AUC = 0.77-0.84) and PDX (AUC = 0.80) cohorts. Finally, BAP1 predictions correlated with clinical outputs such as disease-specific survival. Overall, these data show that DL models can resolve intratumoral heterogeneity in cancer with potential diagnostic, prognostic, and biological implications.

SIGNIFICANCE

This work demonstrates the potential for deep learning analysis of histopathologic images to serve as a fast, low-cost method to assess genetic intratumoral heterogeneity. See related commentary by Song et al., p. 2672.

Machine learning approach informs biology of cancer drug response

Background

The mechanism of action for most cancer drugs is not clear. Large-scale pharmacogenomic cancer cell line datasets offer a rich resource to obtain this knowledge. Here, we present an analysis strategy for revealing biological pathways that contribute to drug response using publicly available pharmacogenomic cancer cell line datasets.

Methods

We present a custom machine-learning based approach for identifying biological pathways involved in cancer drug response. We test the utility of our approach with a pan-cancer analysis of ML210, an inhibitor of GPX4, and a melanoma-focused analysis of inhibitors of BRAF^V600. We apply our approach to reveal determinants of drug resistance to microtubule inhibitors.

Results

Our method implicated lipid metabolism and Rac1/cytoskeleton signaling in the context of ML210 and BRAF inhibitor response, respectively. These findings are consistent with current knowledge of how these drugs work. For microtubule inhibitors, our approach implicated Notch and Akt signaling as pathways that associated with response.

Conclusions

Our results demonstrate the utility of combining informed feature selection and machine learning algorithms in understanding cancer drug response.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04720-z.

The Role of Fast-Cycling Atypical RHO GTPases in Cancer

Simple Summary

For many years, cancer-associated mutations in RHO GTPases were not identified and observations suggesting roles for RHO GTPases in cancer were sparse. Instead, RHO GTPases were considered primarily to regulate cell morphology and cell migration, processes that rely on the dynamic behavior of the cytoskeleton. This notion is in contrast to the RAS proteins, which are famous oncogenes and found to be mutated at high incidence in human cancers. Recent advancements in the tools for large-scale genome analysis have resulted in a paradigm shift and RHO GTPases are today found altered in many cancer types. This review article deals with the recent views on the roles of RHO GTPases in cancer, with a focus on the so-called fast-cycling RHO GTPases.

Abstract

The RHO GTPases comprise a subfamily within the RAS superfamily of small GTP-hydrolyzing enzymes and have primarily been ascribed roles in regulation of cytoskeletal dynamics in eukaryotic cells. An oncogenic role for the RHO GTPases has been disregarded, as no activating point mutations were found for genes encoding RHO GTPases. Instead, dysregulated expression of RHO GTPases and their regulators have been identified in cancer, often in the context of increased tumor cell migration and invasion. In the new landscape of cancer genomics, activating point mutations in members of the RHO GTPases have been identified, in particular in RAC1, RHOA, and CDC42, which has suggested that RHO GTPases can indeed serve as oncogenes in certain cancer types. This review describes the current knowledge of these cancer-associated mutant RHO GTPases, with a focus on how their altered kinetics can contribute to cancer progression.

Cytoskeletal Remodelling as an Achilles’ Heel for Therapy Resistance in Melanoma

Melanoma is an aggressive skin cancer with a poor prognosis when diagnosed late. MAPK-targeted therapies and immune checkpoint blockers benefit a subset of melanoma patients; however, acquired therapy resistance inevitably arises within a year. In addition, some patients display intrinsic (primary) resistance and never respond to therapy. There is mounting evidence that resistant cells adapt to therapy through the rewiring of cytoskeleton regulators, leading to a profound remodelling of the actomyosin cytoskeleton. Importantly, this renders therapy-resistant cells highly dependent on cytoskeletal signalling pathways for sustaining their survival under drug pressure, which becomes a vulnerability that can be exploited therapeutically. Here, we discuss the current knowledge on cytoskeletal pathways involved in mainly targeted therapy resistance and future avenues, as well as potential clinical interventions.

RAC1 Activation as a Potential Therapeutic Option in Metastatic Cutaneous Melanoma

Metastasis is a complex process by which cancer cells escape from the primary tumor to colonize distant organs. RAC1 is a member of the RHO family of small guanosine triphosphatases that plays an important role in cancer migration, invasion, angiogenesis and metastasis. RAC1 activation has been related to most cancers, such as cutaneous melanoma, breast, lung, and pancreatic cancer. RAC1P29S driver mutation appears in a significant number of cutaneous melanoma cases. Likewise, RAC1 is overexpressed or hyperactivated via signaling through oncogenic cell surface receptors. Thus, targeting RAC1 represents a promising strategy for cutaneous melanoma therapy, as well as for inhibition of other signaling activation that promotes resistance to targeted therapies. In this review, we focus on the role of RAC1 in metastatic cutaneous melanoma emphasizing the anti-metastatic potential of RAC1- targeting drugs.

RhoGTPase Signalling in Cancer Progression and Dissemination

Rho GTPases are a family of small G proteins that regulate a wide array of cellular processes related to their key roles controlling the cytoskeleton. On the other hand, cancer is a multi-step disease caused by the accumulation of genetic mutations and epigenetic alterations, from the initial stages of cancer development when cells in normal tissues undergo transformation, to the acquisition of invasive and metastatic traits, responsible for a large number of cancer related deaths. In this review, we discuss the role of Rho GTPase signalling in cancer in every step of disease progression. Rho GTPases contribute to tumour initiation and progression, by regulating proliferation and apoptosis, but also metabolism, senescence and cell stemness. Rho GTPases play a major role in cell migration, and in the metastatic process. They are also involved in interactions with the tumour microenvironment and regulate inflammation, contributing to cancer progression. After years of intensive research, we highlight the importance of relevant models in the Rho GTPase field, and we reflect on the therapeutic opportunities arising for cancer patients.

Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma

Deep learning has emerged as the technique of choice for identifying hidden patterns in cell imaging data but is often criticized as "black box." Here, we employ a generative neural network in combination with supervised machine learning to classify patient-derived melanoma xenografts as "efficient" or "inefficient" metastatic, validate predictions regarding melanoma cell lines with unknown metastatic efficiency in mouse xenografts, and use the network to generate in silico cell images that amplify the critical predictive cell properties. These exaggerated images unveiled pseudopodial extensions and increased light scattering as hallmark properties of metastatic cells. We validated this interpretation using live cells spontaneously transitioning between states indicative of low and high metastatic efficiency. This study illustrates how the application of artificial intelligence can support the identification of cellular properties that are predictive of complex phenotypes and integrated cell functions but are too subtle to be identified in the raw imagery by a human expert. A record of this paper's transparent peer review process is included in the supplemental information. VIDEO ABSTRACT.

Emerging machine learning approaches to phenotyping cellular motility and morphodynamics

Cells respond heterogeneously to molecular and environmental perturbations. Phenotypic heterogeneity, wherein multiple phenotypes coexist in the same conditions, presents challenges when interpreting the observed heterogeneity. Advances in live cell microscopy allow researchers to acquire an unprecedented amount of live cell image data at high spatiotemporal resolutions. Phenotyping cellular dynamics, however, is a nontrivial task and requires machine learning (ML) approaches to discern phenotypic heterogeneity from live cell images. In recent years, ML has proven instrumental in biomedical research, allowing scientists to implement sophisticated computation in which computers learn and effectively perform specific analyses with minimal human instruction or intervention. In this review, we discuss how ML has been recently employed in the study of cell motility and morphodynamics to identify phenotypes from computer vision analysis. We focus on new approaches to extract and learn meaningful spatiotemporal features from complex live cell images for cellular and subcellular phenotyping.

Rac1, A Potential Target for Tumor Therapy

RAS-related C3 botulinum toxin substrate 1 (Rac.1) is one of the important members of Rho GTPases. It is well known that Rac1 is a cytoskeleton regulation protein that regulates cell adhesion, morphology, and movement. Rac1 is highly expressed in different types of tumors, which is related to poor prognosis. Studies have shown that Rac1 not only participates in the tumor cell cycle, apoptosis, proliferation, invasion, migration and angiogenesis, but also participates in the regulation of tumor stem cell, thus promoting the occurrence of tumors. Rac1 also plays a key role in anti-tumor therapy and participates in immune escape mediated by the tumor microenvironment. In addition, the good prospects of Rac1 inhibitors in cancer prevention and treatment are exciting. Therefore, Rac1 is considered as a potential target for the prevention and treatment of cancer. The necessity and importance of Rac1 are obvious, but it still needs further study.

Development of an Immune-Related Gene Signature for Prognosis in Melanoma

Melanoma remains a potentially deadly malignant tumor. The incidence of melanoma continues to rise. Immunotherapy has become a new treatment method and is widely used in a variety of tumors. Original melanoma data were downloaded from TCGA. ssGSEA was performed to classify them. GSVA software and the "hclust" package were used to analyze the data. The ESTIMATE algorithm screened DEGs. The edgeR package and Venn diagram identified valid immune-related genes. Univariate, LASSO and multivariate analyses were used to explore the hub genes. The "rms" package established the nomogram and calibrated the curve. Immune infiltration data were obtained from the TIMER database. Compared with that of samples in the high immune cell infiltration cluster, we found that the tumor purity of samples in the low immune cell infiltration cluster was higher. The immune score, ESTIMATE score and stromal score in the low immune cell infiltration cluster were lower. In the high immune cell infiltration cluster, the immune components were more abundant, while the tumor purity was lower. The expression levels of TIGIT, PDCD1, LAG3, HAVCR2, CTLA4 and the HLA family were also higher in the high immune cell infiltration cluster. Survival analysis showed that patients in the high immune cell infiltration cluster had shorter OS than patients in the low immune cell infiltration cluster. IGHV1-18, CXCL11, LTF, and HLA-DQB1 were identified as immune cell infiltration-related DEGs. The prognosis of melanoma was significantly negatively correlated with the infiltration of CD4+ T cells, CD8+ T cells, dendritic cells, neutrophils and macrophages. In this study, we identified immune-related melanoma core genes and relevant immune cell subtypes, which may be used in targeted therapy and immunotherapy of melanoma.

Evaluating Melanoma Viability and Proliferation in 3D Microenvironments

Researchers often aim to incorporate microenvironmental variables such as the dimensionality and composition of the extracellular matrix into their cell-based assays. A technical challenge created by introduction of these variables is quantification of single-cell measurements and control of environmental reproducibility. Here, we detail a methodology to quantify viability and proliferation of melanoma cells in 3D collagen-based culture platforms by automated microscopy and 3D image analysis to yield robust, high-throughput results of single-cell responses to drug treatment.

A versatile oblique plane microscope for large-scale and high-resolution imaging of subcellular dynamics

We present an oblique plane microscope (OPM) that uses a bespoke glass-tipped tertiary objective to improve the resolution, field of view, and usability over previous variants. Owing to its high numerical aperture optics, this microscope achieves lateral and axial resolutions that are comparable to the square illumination mode of lattice light-sheet microscopy, but in a user friendly and versatile format. Given this performance, we demonstrate high-resolution imaging of clathrin-mediated endocytosis, vimentin, the endoplasmic reticulum, membrane dynamics, and Natural Killer-mediated cytotoxicity. Furthermore, we image biological phenomena that would be otherwise challenging or impossible to perform in a traditional light-sheet microscope geometry, including cell migration through confined spaces within a microfluidic device, subcellular photoactivation of Rac1, diffusion of cytoplasmic rheological tracers at a volumetric rate of 14 Hz, and large field of view imaging of neurons, developing embryos, and centimeter-scale tissue sections.

Subversion of Ras Small GTPases in Cutaneous Melanoma Aggressiveness

The rising incidence and mortality rate associated with the metastatic ability of cutaneous melanoma represent a major public health concern. Cutaneous melanoma is one of the most invasive human cancers, but the molecular mechanisms are poorly understood. Moreover, currently available therapies are not efficient in avoiding melanoma lethality. In this context, new biomarkers of prognosis, metastasis, and response to therapy are necessary to better predict the disease outcome. Additionally, the knowledge about the molecular alterations and dysregulated pathways involved in melanoma metastasis may provide new therapeutic targets. Members of the Ras superfamily of small GTPases regulate various essential cellular activities, from signaling to membrane traffic and cytoskeleton dynamics. Therefore, it is not surprising that they are differentially expressed, and their functions subverted in several types of cancer, including melanoma. Indeed, Ras small GTPases were found to regulate melanoma progression and invasion. Hence, a better understanding of the mechanisms regulated by Ras small GTPases that are involved in melanoma tumorigenesis and progression may provide new therapeutic strategies to block these processes. Here, we review the current knowledge on the role of Ras small GTPases in melanoma aggressiveness and the molecular mechanisms involved. Furthermore, we summarize the known involvement of these proteins in melanoma metastasis and how these players influence the response to therapy.

The cytoskeletal regulator HEM1 governs B cell development and prevents autoimmunity

The WAVE regulatory complex (WRC) is crucial for assembly of the peripheral branched actin network constituting one of the main drivers of eukaryotic cell migration. Here, we uncover an essential role of the hematopoietic-specific WRC component HEM1 for immune cell development. Germline-encoded HEM1 deficiency underlies an inborn error of immunity with systemic autoimmunity, at cellular level marked by WRC destabilization, reduced filamentous actin, and failure to assemble lamellipodia. Hem1^-/- mice display systemic autoimmunity, phenocopying the human disease. In the absence of Hem1, B cells become deprived of extracellular stimuli necessary to maintain the strength of B cell receptor signaling at a level permissive for survival of non-autoreactive B cells. This shifts the balance of B cell fate choices toward autoreactive B cells and thus autoimmunity.

A functionally neutral single chain antibody to measure beta-1 integrin uptake and recycling

Integrin‐mediated cell adhesion and signaling are critical for many physiological processes. The dynamic turnover of integrins and their associated adhesion complexes through endocytic and recycling pathways has emerged as an important mechanism for controlling cell migration and invasion in cancer. Thus, the regulation of integrin trafficking and how this may be altered by disease‐specific molecular mechanisms has generated considerable interest. However, current tools available to study integrin trafficking may cause artifacts and/or do not provide adequate kinetic information. Here, we report the generation of a functionally neutral and monovalent single chain antibody to quantitatively and qualitatively measure β1 integrin trafficking in cells. Our novel probe can be used in a variety of assays and allows for the biochemical characterization of rapid recycling of endogenous integrins. We also demonstrate its potential utility in live cell imaging, providing proof of principle to guide future integrin probe design.

The dynamic turnover of integrins through endocytic trafficking pathways has emerged as a key mechanism for cell migration and invasion. Lakoduk et al. report the generation of a functionally neutral and monovalent antibody‐based probe to track and measure endogenous beta‐1 integrin uptake and fast recycling in multiple cell types. Their tool, scFv^K20, serves as proof of principle inspiration for future integrin probe design.

The stressful tumour environment drives plasticity of cell migration programmes, contributing to metastasis

Tumours evolve to cope with environmental stresses or challenges such as nutrient starvation, depletion of survival factors, and unbalanced mechanical forces. The uncontrolled growth and aberrant deregulation of core cell homeostatic pathways induced by genetic mutations create an environment of stress. Here, we explore how the adaptations of tumours to the changing environment can drive changes in the motility machinery of cells, affecting migration, invasion, and metastasis. Tumour cells can invade individually or collectively, or they can be extruded out of the surrounding epithelium. These mechanisms are thought to be modifications of normal processes occurring during development or tissue repair. Therefore, tumours may activate these pathways in response to environmental stresses, enabling them to survive in hostile environments and spread to distant sites. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

RAC1 as a Therapeutic Target in Malignant Melanoma

Small GTPases of the RAS and RHO families are related signaling proteins that, when activated by growth factors or by mutation, drive oncogenic processes. While activating mutations in KRAS, NRAS, and HRAS genes have long been recognized and occur in many types of cancer, similar mutations in RHO family genes, such as RAC1 and RHOA, have only recently been detected as the result of extensive cancer genome-sequencing efforts and are linked to a restricted set of malignancies. In this review, we focus on the role of RAC1 signaling in malignant melanoma, emphasizing recent advances that describe how this oncoprotein alters melanocyte proliferation and motility and how these findings might lead to new therapeutics in RAC1-mutant tumors.