Treatment with tumor-treating fields (TTFields) suppresses intercellular tunneling nanotube formation in vitro and upregulates immuno-oncologic biomarkers in vivo in malignant mesothelioma

Disruption of intercellular communication within tumors is emerging as a novel potential strategy for cancer-directed therapy. Tumor-Treating Fields (TTFields) therapy is a treatment modality that has itself emerged over the past decade in active clinical use for patients with glioblastoma and malignant mesothelioma, based on the principle of using low-intensity alternating electric fields to disrupt microtubules in cancer cells undergoing mitosis. There is a need to identify other cellular and molecular effects of this treatment approach that could explain reported increased overall survival when TTFields are added to standard systemic agents. Tunneling nanotube (TNTs) are cell-contact-dependent filamentous-actin-based cellular protrusions that can connect two or more cells at long-range. They are upregulated in cancer, facilitating cell growth, differentiation, and in the case of invasive cancer phenotypes, a more chemoresistant phenotype. To determine whether TNTs present a potential therapeutic target for TTFields, we applied TTFields to malignant pleural mesothelioma (MPM) cells forming TNTs in vitro. TTFields at 1.0 V/cm significantly suppressed TNT formation in biphasic subtype MPM, but not sarcomatoid MPM, independent of effects on cell number. TTFields did not significantly affect function of TNTs assessed by measuring intercellular transport of mitochondrial cargo via intact TNTs. We further leveraged a spatial transcriptomic approach to characterize TTFields-induced changes to molecular profiles in vivo using an animal model of MPM. We discovered TTFields induced upregulation of immuno-oncologic biomarkers with simultaneous downregulation of pathways associated with cell hyperproliferation, invasion, and other critical regulators of oncogenic growth. Several molecular classes and pathways coincide with markers that we and others have found to be differentially expressed in cancer cell TNTs, including MPM specifically. We visualized short TNTs in the dense stromatous tumor material selected as regions of interest for spatial genomic assessment. Superimposing these regions of interest from spatial genomics over the plane of TNT clusters imaged in intact tissue is a new method that we designate Spatial Profiling of Tunneling nanoTubes (SPOTT). In sum, these results position TNTs as potential therapeutic targets for TTFields-directed cancer treatment strategies. We also identified the ability of TTFields to remodel the tumor microenvironment landscape at the molecular level, thereby presenting a potential novel strategy for converting tumors at the cellular level from 'cold' to 'hot' for potential response to immunotherapeutic drugs.

BIOM-42. A DEEP LEARNING MODEL FOR AUTOMATED DETECTION AND COUNTING OF TUNNELING NANOTUBES AND CANCER CELLS IN MICROSCOPY IMAGES

BACKGROUND

Tunneling nanotubes (TNTs) are cellular structures connecting cell membranes and mediating intercellular communication. TNTs are manually identified and counted by a trained investigator; however, this process is time-intensive. We therefore sought to develop an automated approach for quantitative analysis of TNTs.

METHODS

We used the convolutional neural network (U-Net) deep learning model to segment phase contrast microscopy images of both cancer and non-cancer cells. Our method was composed of preprocessing and model development. We developed a new preprocessing method to label TNTs on a pixel-wise basis. Two sequential models were employed to detect TNTs. First, we identified the regions of images with TNTs by implementing a classification algorithm. Second, we fed parts of the image classified as TNT-containing into a modified U-Net model to estimate TNTs on a pixel-wise basis.

RESULTS

The U-Net model detected 73.3% of human expert-identified TNTs, counted TNTs and cells, and calculated the TNT-to-cell ratio (TCR). We obtained a precision of 0.88, recall of 0.67, and f-1 score of 0.76 on a test data set. The predicted and true TCRs were not significantly different between the training and test data sets.

CONCLUSIONS

In summary, we report application of an automated model generated by deep learning and trained to accurately label and detect TNTs and cells imaged in culture. Continued application and refinement of this process will provide a new approach to the analysis of TNTs, which form to connect cancer and other cells. This approach has the potential to enhance the drug screens intended to assess therapeutic efficacy of experimental agents, and to reproducibly assess TNTs as a potential biomarker of response to therapy in cancer.

Abstract 2037: Spatial omic changes of malignant pleural mesothelioma following treatment using tumor-treating fields

Background: Application of alternating-electric fields as cancer-directed therapy known as Tumor-Treating Fields (TTFields) has been shown to be effective by exerting dipole alignment forces on polar microtubule subunits and dielectrophoretic forces in the cytokinetic furrow. This effect results in disruption of mitosis at the cellular level, and at the clinical level with significantly prolonged overall survival of patients with glioblastoma and malignant pleural mesothelioma (MPM). The molecular alterations that occur at the genomic and transcriptomic levels following TTFields treatment are unknown. We applied a spatial omics approach to elucidate spatial intratumoral effects of TTFields at the molecular level in regions of interest (ROI) in a mouse model of MPM.

Methods: Eight Balb/C mice were injected with AB1 MPM cells until sizable tumors were observed (2-3 weeks). TTFields were applied, with heat sham used as a negative control. After 14 days (6 days of treatment, 2 days of rest, then 6 more days of treatment) tumors were resected, fixed and paraffin embedded. Following the Nanostring GeoMx protocol, thin sections of all eight tumors were placed on a slide, and incubated with both Ki-67 antibodies, and a GeoMx Mouse Cancer Transcriptome Atlas RNA probe set. Using Ki-67 staining as a guide, 12 ROIs were selected across each tumor to capture intratumoral heterogeneity, including the core and periphery of each tumor The DSP barcoded RNA probes were cleaved, sequenced and analyzed. We compared differential expression of subset gene classes of TTFields vs heat sham treated tumors; results were further stratified into Ki-67 high and low subsets for each sample. Results were assessed by Gene Set Enrichment.

Results: Sham-treated tumors grew to over 300 mm3; TTFields-treated tumors averaged 100 mm3, confirming anti-tumor effect. Gene Set Enrichment Analysis uncovered upregulation of genes associated with interferon-alpha and -gamma responses in TTFields-treated tumors, which also displayed downregulation of pathway components associated with glycolysis, mTOR signaling, oxidative phosphorylation, cell invasion, hypoxia, and TNF-alpha signaling. Spatial analysis detected a heterogeneous response and differential expression between different portions of tumors.

Conclusions: TTFields application induces clear patterns of differential expression in the transcriptome of treated tumors, including an increasingly immune-stimulated tumor microenvironment that also affects molecular pathways critical to cellular proliferation and invasion. These findings point the way toward improved understanding of timing and sequences of TTFields in relation to systemic cytotoxic, targeted, and immune modulation forms of therapeutic strategies. Our finding of upregulated immune response implicates TTFields as a potential synergistic tactic when coupled with immunotherapeutic approaches.

Citation Format: Emil Lou, Katherine Ladner, Kerem Wainer-Katsir, Karina Deniz, Yaara Porat, Boris Brant, Shiri Davidi, Yuki Padmanabhan, Phillip Wong, Amrinder Nain, Clifford J. Steer, Moshe Giladi. Spatial omic changes of malignant pleural mesothelioma following treatment using tumor-treating fields [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2037.

Quantitative Biophysical Metrics for Rapid Evaluation of Ovarian Cancer Metastatic Potential

Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous sub-mesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here, we fabricated extracellular-matrix mimicking suspended fiber networks: crosshatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying inter-fiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease, while force-disease biphasic relationship exhibited f-actin stress-fiber network dependence. However, unique to suspended fibers, coiling occurring at tips of protrusions and not the length or breadth of protrusions displayed strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on time scale of hours. [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text] [Media: see text].

Molecular alterations associated with improved outcome in patients with glioblastoma treated with Tumor-Treating Fields

Background

The genomic and overall biologic landscape of glioblastoma (GB) has become clearer over the past 2 decades, as predictive and prognostic biomarkers of both de novo and transformed forms of GB have been identified. The oral chemotherapeutic agent temozolomide (TMZ) has been integral to standard-of-care treatment for nearly 2 decades. More recently, the use of non-pharmacologic interventions, such as application of alternating electric fields, called Tumor-Treating Fields (TTFields), has emerged as a complementary treatment option that increases overall survival (OS) in patients with newly diagnosed GB. The genomic factors associated with improved or lack of response to TTFields are unknown.

Methods

We performed comprehensive genomic analysis of GB tumors resected from 55 patients who went on to receive treatment using TTFields, and compared results to 57 patients who received standard treatment without TTFields.

Results

We found that molecular driver alterations in NF1, and wild-type PIK3CA and epidermal growth factor receptor (EGFR), were associated with increased benefit from TTFields as measured by progression-free survival (PFS) and OS. There were no differences when stratified by TP53 status. When NF1, PIK3CA, and EGFR status were combined as a Molecular Survival Score, the combination of the 3 factors significantly correlated with improved OS and PFS in TTFields-treated patients compared to patients not treated with TTFields.

Conclusions

These results shed light on potential driver and passenger mutations in GB that can be validated as predictive biomarkers of response to TTFields treatment, and provide an objective and testable genomic-based approach to assessing response.

Abstract 2011: Tumor treating fields induce cellular and morphologic changes including disruption of intercellular communication networks in malignant pleural mesothelioma

Tumor Treating Fields (TTFields) is a novel therapeutic strategy that uses alternating electric fields to disrupt mitosis in actively dividing cells through exertion of dielectrophoretic force and dipole alignment on microtubule subunits. However, the additional effects of TTFields on cellular morphology and communication remain unclear. Tunneling nanotubes (TNTs) are ultrafine F-actin-based protrusions that facilitate intercellular communication through cell-cell contact, including efficient transport of molecular cargo that accelerate invasive potential and chemoresistance. We hypothesized that by creating dielectrophoretic force on polar actin subunits, treatment with TTFields would lead to sustained disruption or prevention of formation of MPM TNTs.

TTFields (200 kHz) were applied at 0.5 or 1.0 V/cm to VAMT and MSTO MPM cell lines using the Inovitro system (Novocure). TNT index (average # of TNTs/cell) was determined at 0, 24, 48, and 72 hours of TTFields application. At the 72 hour period, TTFields were discontinued and assessment for recovery of TNT formation was performed after an additional 24 hours. Cell viability was determined by staining with NucGreen 488 dye. We also used time-lapse microscopy with concurrent application of TTFields and the chemotherapeutic agents cisplatin and pemetrexed to analyze effects on TNTs and functional cargo transfer.

Application of continuous TTFields at 1.0 V/cm, but not at 0.5 V/cm, suppressed TNT formation by 48.9% in MSTO (p=0.005). This suppression was achieved at the 48-hour time point and was independent of cell proliferation. No significant differences in TNT index were noted for VAMT. Cell viability was consistently above 95% at all time points for both cell lines at the stated frequency and intensities. Cargo transfer rates were lower in experimental groups treated with TTFields and either cisplatin, pemetrexed, or both.

Here, we show that treatment with TTFields suppresses formation of TNTs between MSTO cells, but not VAMT, suggesting additional factors that may determine susceptibility to TTFields treatment. Additionally, TTFields treatment of MSTO decreased the function of TNTs in these cells, as demonstrated by lower cargo transfer rates. In sum, these data identify effects of TTFields on TNTs as a novel mechanism for this therapeutic modality.

Citation Format: Akshat Sarkari, Sophie Korenfeld, Katherine Ladner, Phillip Wong, Antonia Martinez, Eyal Dor-On, Moshe Giladi, Amrinder Nain, Emil Lou. Tumor treating fields induce cellular and morphologic changes including disruption of intercellular communication networks in malignant pleural mesothelioma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2011.

Serine/Threonine Kinase MLK4 Determines Mesenchymal Identity in Glioma Stem Cells in an NF-κB-dependent Manner

Activation of nuclear factor κB (NF-κB) induces mesenchymal (MES) transdifferentiation and radioresistance in glioma stem cells (GSCs), but molecular mechanisms for NF-κB activation in GSCs are currently unknown. Here, we report that mixed lineage kinase 4 (MLK4) is overexpressed in MES but not proneural (PN) GSCs. Silencing MLK4 suppresses self-renewal, motility, tumorigenesis, and radioresistance of MES GSCs via a loss of the MES signature. MLK4 binds and phosphorylates the NF-κB regulator IKKα, leading to activation of NF-κB signaling in GSCs. MLK4 expression is inversely correlated with patient prognosis in MES, but not PN high-grade gliomas. Collectively, our results uncover MLK4 as an upstream regulator of NF-κB signaling and a potential molecular target for the MES subtype of glioblastomas.

NF-κB-mediated Pax7 dysregulation in the muscle microenvironment promotes cancer cachexia

Cachexia is a debilitating condition characterized by extreme skeletal muscle wasting that contributes significantly to morbidity and mortality. Efforts to elucidate the underlying mechanisms of muscle loss have predominantly focused on events intrinsic to the myofiber. In contrast, less regard has been given to potential contributory factors outside the fiber within the muscle microenvironment. In tumor-bearing mice and patients with pancreatic cancer, we found that cachexia was associated with a type of muscle damage resulting in activation of both satellite and nonsatellite muscle progenitor cells. These muscle progenitors committed to a myogenic program, but were inhibited from completing differentiation by an event linked with persistent expression of the self-renewing factor Pax7. Overexpression of Pax7 was sufficient to induce atrophy in normal muscle, while under tumor conditions, the reduction of Pax7 or exogenous addition of its downstream target, MyoD, reversed wasting by restoring cell differentiation and fusion with injured fibers. Furthermore, Pax7 was induced by serum factors from cachectic mice and patients, in an NF-κB-dependent manner, both in vitro and in vivo. Together, these results suggest that Pax7 responds to NF-κB by impairing the regenerative capacity of myogenic cells in the muscle microenvironment to drive muscle wasting in cancer.

IKKα and alternative NF-κB regulate PGC-1β to promote oxidative muscle metabolism

Alternative NF-κB signaling modulates the activity of PGC-1β to promote oxidative metabolism in skeletal muscle.

Although the physiological basis of canonical or classical IκB kinase β (IKKβ)–nuclear factor κB (NF-κB) signaling pathway is well established, how alternative NF-κB signaling functions beyond its role in lymphoid development remains unclear. In particular, alternative NF-κB signaling has been linked with cellular metabolism, but this relationship is poorly understood. In this study, we show that mice deleted for the alternative NF-κB components IKKα or RelB have reduced mitochondrial content and function. Conversely, expressing alternative, but not classical, NF-κB pathway components in skeletal muscle stimulates mitochondrial biogenesis and specifies slow twitch fibers, suggesting that oxidative metabolism in muscle is selectively controlled by the alternative pathway. The alternative NF-κB pathway mediates this specificity by direct transcriptional activation of the mitochondrial regulator PPAR-γ coactivator 1β (PGC-1β) but not PGC-1α. Regulation of PGC-1β by IKKα/RelB also is mammalian target of rapamycin (mTOR) dependent, highlighting a cross talk between mTOR and NF-κB in muscle metabolism. Together, these data provide insight on PGC-1β regulation during skeletal myogenesis and reveal a unique function of alternative NF-κB signaling in promoting an oxidative metabolic phenotype.

Asc-dependent and independent mechanisms contribute to restriction of legionella pneumophila infection in murine macrophages

The apoptosis-associated speck-like protein containing a caspase recruitment domain (Asc) is an adaptor molecule that mediates inflammatory and apoptotic signals. Legionella pneumophila is an intracellular bacterium and the causative agent of Legionnaire's pneumonia. L. pneumophila is able to cause pneumonia in immuno-compromised humans but not in most inbred mice. Murine macrophages that lack the ability to activate caspase-1, such as caspase(-1-/-) and Nlrc4(-/-) allow L. pneumophila infection. This permissiveness is attributed mainly to the lack of active caspase-1 and the absence of its down stream substrates such as caspase-7. However, the role of Asc in control of L. pneumophila infection in mice is unclear. Here we show that caspase-1 is moderately activated in Asc(-/-) macrophages and that this limited activation is required and sufficient to restrict L. pneumophila growth. Moreover, Asc-independent activation of caspase-1 requires bacterial flagellin and is mainly detected in cellular extracts but not in culture supernatants. We also demonstrate that the depletion of Asc from permissive macrophages enhances bacterial growth by promoting L. pneumophila-mediated activation of the NF-κB pathway and decreasing caspase-3 activation. Taken together, our data demonstrate that L. pneumophila infection in murine macrophages is controlled by several mechanisms: Asc-independent activation of caspase-1 and Asc-dependent regulation of NF-κB and caspase-3 activation.