Non-Destructive Tumor Aggregate Morphology and Viability Quantification at Cellular Resolution, During Development and in Response to Drug

DMT1-dependent endosome-mitochondria interactions regulate mitochondrial iron translocation and metastatic outgrowth

Transient early endosome (EE)-mitochondria interactions can mediate mitochondrial iron translocation, but the associated mechanisms are still elusive. We showed that Divalent Metal Transporter 1 (DMT1) sustains mitochondrial iron translocation via EE-mitochondria interactions in triple-negative MDA-MB-231, but not in luminal A T47D breast cancer cells. DMT1 silencing increases labile iron pool (LIP) levels and activates PINK1/Parkin-dependent mitophagy in MDA-MB-231 cells. Mitochondrial bioenergetics and the iron-associated protein profile were altered by DMT1 silencing and rescued by DMT1 re-expression. Transcriptomic profiles upon DMT1 silencing are strikingly different between 2D and 3D culture conditions, suggesting that the environment context is crucial for the DMT1 knockout phenotype observed in MDA-MB-231 cells. Lastly, in vivo lung metastasis assay revealed that DMT1 silencing promoted the outgrowth of lung metastatic nodules in both human and murine models of triple-negative breast cancer cells. These findings reveal a DMT1-dependent pathway connecting EE-mitochondria interactions to mitochondrial iron translocation and metastatic fitness of breast cancer cells.

Organoid assessment technologies

Despite enormous advances in the generation of organoids, robust and stable protocols of organoids are still a major challenge to researchers. Research for assessing structures of organoids and the evaluations of their functions on in vitro or in vivo is often limited by precision strategies. A growing interest in assessing organoids has arisen, aimed at standardizing the process of obtaining organoids to accurately resemble human-derived tissue. The complex microenvironment of organoids, intricate cellular crosstalk, organ-specific architectures and further complicate functions urgently quest for high-through schemes. By utilizing multi-omics analysis and single-cell analysis, cell-cell interaction mechanisms can be deciphered, and their structures can be investigated in a detailed view by histological analysis. In this review, we will conclude the novel approaches to study the molecular mechanism and cell heterogeneity of organoids and discuss the histological and morphological similarity of organoids in comparison to the human body. Future perspectives on functional analysis will be developed and the organoids will become mature models.

Protein ligand and nanotopography separately drive the phenotype of mouse embryonic stem cells

Biochemical and biomechanical signals regulate stem cell function in the niche environments in vivo. Current in vitro culture of mouse embryonic stem cells (mESC) uses laminin (LN-511) to provide mimetic biochemical signaling (LN-521 for human systems) to maintain stemness. Alternative approaches propose topographical cues to provide biomechanical cues, however combined biochemical and topographic cues may better mimic the in vivo environment, but are largely unexplored for in vitro stem cell expansion. In this study, we directly compare in vitro signals from LN-511 and/or topographic cues to maintain stemness, using systematically-varied submicron pillar patterns or flat surfaces with or without preadsorbed LN-511. The adhesion of cells, colony formation, expression of the pluripotency marker,octamer-binding transcription factor 4 (Oct4), and transcriptome profiling were characterized. We observed that either biochemical or topographic signals could maintain stemness of mESCs in feeder-free conditions, indicated by high-level Oct4 and gene profiling by RNAseq. The combination of LN-511 with nanotopography reduced colony growth, while maintaining stemness markers, shifted the cellular phenotype indicating that the integration of biochemical and topographic signals is antagonistic. Overall, significantly faster (up to 2.5 times) colony growth was observed at nanotopographies without LN-511, suggesting for improved ESC expansion.

Three-dimensional, label-free cell viability measurements in tissue engineering scaffolds using optical coherence tomography

In the field of tissue engineering, 3D scaffolds and cells are often combined to yield constructs that are used as therapeutics to repair or restore tissue function in patients. Viable cells are often required to achieve the intended mechanism of action for the therapy, where the live cells may build new tissue or may release factors that induce tissue regeneration. Thus, there is a need to reliably measure cell viability in 3D scaffolds as a quality attribute of a tissue-engineered medical product. Here, we developed a noninvasive, label-free, 3D optical coherence tomography (OCT) method to rapidly (2.5 min) image large sample volumes (1 mm3 ) to assess cell viability and distribution within scaffolds. OCT imaging was assessed using a model scaffold-cell system consisting of a polysaccharide-based hydrogel seeded with human Jurkat cells. Four test systems were used: hydrogel seeded with live cells, hydrogel seeded with heat-shocked or fixed dead cells and hydrogel without any cells. Time series OCT images demonstrated changes in the time-dependent speckle patterns due to refractive index (RI) variations within live cells that were not observed for pure hydrogel samples or hydrogels with dead cells. The changes in speckle patterns were used to generate live-cell contrast by image subtraction. In this way, objects with large changes in RI were binned as live cells. Using this approach, on average, OCT imaging measurements counted 326 ± 52 live cells per 0.288 mm3 for hydrogels that were seeded with 288 live cells (as determined by the acridine orange-propidium iodide cell counting method prior to seeding cells in gels). Considering the substantial uncertainties in fabricating the scaffold-cell constructs, such as the error from pipetting and counting cells, a 13% difference in the live-cell count is reasonable. Additionally, the 3D distribution of live cells was mapped within a hydrogel scaffold to assess the uniformity of their distribution across the volume. Our results demonstrate a real-time, noninvasive method to rapidly assess the spatial distribution of live cells within a 3D scaffold that could be useful for assessing tissue-engineered medical products.

Nondestructive 3D pathology with analysis of nuclear features for prostate cancer risk assessment

Prostate cancer treatment decisions rely heavily on subjective visual interpretation [assigning Gleason patterns or International Society of Urological Pathology (ISUP) grade groups] of limited numbers of two-dimensional (2D) histology sections. Under this paradigm, interobserver variance is high, with ISUP grades not correlating well with outcome for individual patients, and this contributes to the over- and undertreatment of patients. Recent studies have demonstrated improved prognostication of prostate cancer outcomes based on computational analyses of glands and nuclei within 2D whole slide images. Our group has also shown that the computational analysis of three-dimensional (3D) glandular features, extracted from 3D pathology datasets of whole intact biopsies, can allow for improved recurrence prediction compared to corresponding 2D features. Here we seek to expand on these prior studies by exploring the prognostic value of 3D shape-based nuclear features in prostate cancer (e.g. nuclear size, sphericity). 3D pathology datasets were generated using open-top light-sheet (OTLS) microscopy of 102 cancer-containing biopsies extracted ex vivo from the prostatectomy specimens of 46 patients. A deep learning-based workflow was developed for 3D nuclear segmentation within the glandular epithelium versus stromal regions of the biopsies. 3D shape-based nuclear features were extracted, and a nested cross-validation scheme was used to train a supervised machine classifier based on 5-year biochemical recurrence (BCR) outcomes. Nuclear features of the glandular epithelium were found to be more prognostic than stromal cell nuclear features (area under the ROC curve [AUC] = 0.72 versus 0.63). 3D shape-based nuclear features of the glandular epithelium were also more strongly associated with the risk of BCR than analogous 2D features (AUC = 0.72 versus 0.62). The results of this preliminary investigation suggest that 3D shape-based nuclear features are associated with prostate cancer aggressiveness and could be of value for the development of decision-support tools. © 2023 The Pathological Society of Great Britain and Ireland.

Spatial topology of organelle is a new breast cancer cell classifier

Genomics and proteomics have been central to identify tumor cell populations, but more accurate approaches to classify cell subtypes are still lacking. We propose a new methodology to accurately classify cancer cells based on their organelle spatial topology. Herein, we developed an organelle topology-based cell classification pipeline (OTCCP), which integrates artificial intelligence (AI) and imaging quantification to analyze organelle spatial distribution and inter-organelle topology. OTCCP was used to classify a panel of human breast cancer cells, grown as 2D monolayer or 3D tumor spheroids using early endosomes, mitochondria, and their inter-organelle contacts. Organelle topology allows for a highly precise differentiation between cell lines of different subtypes and aggressiveness. These findings lay the groundwork for using organelle topological profiling as a fast and efficient method for phenotyping breast cancer function as well as a discovery tool to advance our understanding of cancer cell biology at the subcellular level.

Sophorolipid Candidates Demonstrate Cytotoxic Efficacy against 2D and 3D Breast Cancer Models

Sophorolipids are biosurfactants derived from the nonpathogenic yeasts such as Starmerella bombicola with potential efficacy in anticancer applications. Simple and cost-effective synthesis of these drugs makes them a promising alternative to traditional chemotherapeutics, pending their success in preliminary drug-screening. Drug-screening typically utilizes 2D cell monolayers due to their simplicity and ease of high-throughput assessment. However, 2D assays fail to capture the complexity and 3D context of the tumor microenvironment and have consequently been implicated in the high percentage of drugs investigated in vitro that later fail in clinical trials. Herein, we screened two sophorolipid candidates and a clinically-used chemotherapeutic, doxorubicin, on in vitro breast cancer models ranging from 2D monolayers to 3D spheroids, employing optical coherence tomography to confirm these morphologies. We calculated corresponding IC50 values for these drugs and found one of the sophorolipids to have comparable toxicities to the chemotherapeutic control. Our findings show increased drug resistance associated with model dimensionality, such that all drugs tested showed that 3D spheroids exhibited higher IC50 values than their 2D counterparts. These findings demonstrate promising preliminary data to support the use of sophorolipids as a more affordable alternative to traditional clinical interventions and demonstrate the importance of 3D tumor models in assessing drug response.

Molecularly Engineered Surfactin Analogues Induce Nonapoptotic-Like Cell Death and Increased Selectivity in Multiple Breast Cancer Cell Types

Surfactin, a negatively charged amphiphilic lipopeptide biosurfactant, is synthesized by the bacterium Bacillus subtilis. It consists of a cyclic heptapeptide and an 11-15C β-hydroxy fatty acid. To probe how the modification of the molecular skeleton of surfactin influences its selectivity and activity against breast cancer, six synthetic surfactins were generated. Modifications were accomplished by conjugating amine-functionalized molecules to the Glu and Asp carboxyl moieties of the heptapeptide. The resulting synthetic surfactins provided a diverse series of molecules with differences in charge, size, and hydrophilicity. After purification and structural analysis, insights into biological activity and specificity were generated for each compound. Dose-dependent growth inhibition was determined for four tumorigenic breast cancer cell lines in monolayer and spheroid morphologies, as well as nontumorigenic fibroblasts and sheep erythrocytes, which were utilized to determine selectivity indices. Results indicated that two compounds, which have amplified anionic charge, had increased activity on breast cancer, with reduced activity on nontumorigenic fibroblasts and erythrocytes. Cationic derivative surf-ethylenediamine has increased activity on all cell lines tested. Novel correlations between dose-response activities and physicochemical properties of all compounds determined that there is a significant correlation between the critical micelle concentration and activity against multiple cell lines.

Cell monitoring with optical coherence tomography

BACKGROUND AIMS

We evaluated a commercially available instrument, OCTiCell (chromologic.com/octicell), for monitoring cell growth in suspended agitated bioreactors based on optical coherence tomography. OCTiCell is an in-line, completely non-invasive instrument that can operate on any suspended-cell bioreactor with a window or transparent wall. In traditional optical coherence tomography, the imaging beam is rastered over the sample to form a three-dimensional image. OCTiCell, instead uses a fixed imaging beam and takes advantage of the motion of the media to move the cells across the interrogating optical beam.

RESULTS

We found strong correlations between the non-invasive, non-contact, reagent-free OCTiCell measurements of cell concentration and viability and those obtained from the automated cell counter, and the XTT viability assay, which is a colorimetric assay for quantifying metabolic activity.

CONCLUSIONS

This novel cell monitoring method can adapt to different bioreactor form factors and could reduce the labor cost and contamination risks associated with cell growth monitoring.

Non-Destructive Evaluation of Regional Cell Density Within Tumor Aggregates Following Drug Treatment

Multicellular tumor spheroid (MCTSs) models have demonstrated increasing utility for in vitro study of cancer progression and drug discovery. These relatively simple avascular constructs mimic key aspects of in vivo tumors, such as 3D structure and pathophysiological gradients. MCTSs models can provide insights into cancer cell behavior during spheroid development and in response to drugs; however, their requisite size drastically limits the tools used for non-destructive assessment. Optical Coherence Tomography structural imaging and Imaris 3D analysis software are explored for rapid, non-destructive, and label-free measurement of regional cell density within MCTSs. This approach is utilized to assess MCTSs over a 4-day maturation period and throughout an extended 5-day treatment with Trastuzumab, a clinically relevant anti-HER2 drug. Briefly, AU565 HER2+ breast cancer MCTSs were created via liquid overlay with or without the addition of Matrigel (a basement membrane matrix) to explore aggregates of different morphologies (thicker, disk-like 2.5D aggregates or flat 2D aggregates, respectively). Cell density within the outer region, transitional region, and inner core was characterized in matured MCTSs, revealing a cell-density gradient with higher cell densities in core regions compared to outer layers. The matrix addition redistributed cell density and enhanced this gradient, decreasing outer zone density and increasing cell compaction in the cores. Cell density was quantified following drug treatment (0 h, 24 h, 5 days) within progressively deeper 100 µm zones to assess potential regional differences in drug response. By the final timepoint, nearly all cell death appeared to be constrained to the outer 200 µm of each aggregate, while cells deeper in the aggregate appeared largely unaffected, illustrating regional differences in the drug response, possibly due to limitations in drug penetration. The current protocol provides a unique technique to non-destructively quantify regional cell density within dense cellular tissues and measure it longitudinally.

Volumetric growth tracking of patient-derived cancer organoids using optical coherence tomography

Patient-derived cancer organoids (PCOs) are in vitro organotypic models that reflect in vivo drug response, thus PCOs are an accessible model for cancer drug screening in a clinically relevant timeframe. However, current methods to assess the response of PCOs are limited. Here, a custom swept-source optical coherence tomography (OCT) system was used to rapidly evaluate volumetric growth and drug response in PCOs. This system was optimized for an inverted imaging geometry to enable high-throughput imaging of PCOs. An automated image analysis framework was developed to perform 3D single-organoid tracking of PCOs across multiple time points over 48 hours. Metabolic inhibitors and cancer therapies decreased PCOs volumetric growth rate compared to control PCOs. Single-organoid tracking improved sensitivity to drug treatment compared to a pooled analysis of changes in organoid volume. OCT provided a more accurate assessment of organoid volume compared to a volume estimation method based on 2D projections. Single-organoid tracking with OCT also identified heterogeneity in drug response between solid and hollow PCOs. This work demonstrates that OCT and 3D single-organoid tracking are attractive tools to monitor volumetric growth and drug response in PCOs, providing rapid, non-destructive methods to quantify heterogeneity in PCOs.