Label-free Imaging and Characterization of Cancer Cell Responses to Polymethoxyflavones Using Raman Microscopy

2016 ◽  
Vol 64 (51) ◽  
pp. 9708-9713 ◽  
Author(s):  
Hua Zhang ◽  
Jinkai Zheng ◽  
Anna Liu ◽  
Hang Xiao ◽  
Lili He
2013 ◽  
Author(s):  
A. C. De Luca ◽  
S. Manago ◽  
M. A. Ferrara ◽  
L. Sirleto ◽  
R. Puglisi ◽  
...  

2014 ◽  
Author(s):  
A. C. De Luca ◽  
S. Managò ◽  
M. A. Ferrara ◽  
L. Sirleto ◽  
R. Puglisi ◽  
...  

2021 ◽  
pp. 339359
Author(s):  
Sabrina Romanò ◽  
Flavio Di Giacinto ◽  
Aniello Primiano ◽  
Jacopo Gervasoni ◽  
Alberto Mazzini ◽  
...  

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5525
Author(s):  
Satheeshkumar Elumalai ◽  
Stefano Managó ◽  
Anna Chiara De Luca

In the last decade, Raman Spectroscopy (RS) was demonstrated to be a label-free, non-invasive and non-destructive optical spectroscopy allowing the improvement in diagnostic accuracy in cancer and analytical assessment for cell sensing. This review discusses how Raman spectra can lead to a deeper molecular understanding of the biochemical changes in cancer cells in comparison to non-cancer cells, analyzing two key examples, leukemia and breast cancer. The reported Raman results provide information on cancer progression and allow the identification, classification, and follow-up after chemotherapy treatments of the cancer cells from the liquid biopsy. The key obstacles for RS applications in cancer cell diagnosis, including quality, objectivity, number of cells and velocity of the analysis, are considered. The use of multivariant analysis, such as principal component analysis (PCA) and linear discriminate analysis (LDA), for an automatic and objective assessment without any specialized knowledge of spectroscopy is presented. Raman imaging for cancer cell mapping is shown and its advantages for routine clinical pathology practice and live cell imaging, compared to single-point spectral analysis, are debated. Additionally, the combination of RS with microfluidic devices and high-throughput screening for improving the velocity and the number of cells analyzed are also discussed. Finally, the combination of the Raman microscopy (RM) with other imaging modalities, for complete visualization and characterization of the cells, is described.


2021 ◽  
Vol 54 (18) ◽  
pp. 185401
Author(s):  
Long Zhang ◽  
Fukun Shi ◽  
Jinsong Guo ◽  
Qun Wang ◽  
Juergen F Kolb ◽  
...  

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A574-A574
Author(s):  
Ellen Duong ◽  
Timothy Fessenden ◽  
Arjun Bhutkar ◽  
Stefani Spranger

BackgroundCytotoxic (CD8+) T-cells are required for tumor eradication and durable anti-tumor immunity.1 The induction of tumor-reactive CD8+ T-cells is predominately attributed to a subset of dendritic cells (DC) called Batf3-driven DC1, given their robust ability to cross-present antigens for T-cell priming and their role in effector T-cell recruitment.2–4 Presence of the DC1 signature in tumors correlates with improved survival and response to immunotherapies.5–7 Yet, most tumors with a DC1 infiltrate still progress, suggesting that while DC1 can initiate tumor-reactive CD8+ T-cell responses, they are unable to sustain them. Therefore, there is a critical need to identify and engage additional stimulatory DC subsets to strengthen anti-tumor immunity and boost immunotherapy responses.MethodsTo identify DC subsets that drive poly-functional CD8+ T-cell responses, we compared the DC infiltrate of a spontaneously regressing tumor with a progressing tumor. Multicolor flow immunophenotyping and single-cell RNA-sequencing were used to profile the DC compartment of both tumors. IFNγ-ELISpot was performed on splenocytes to assess for systemic tumor-reactive T-cell responses. Sorted DC subsets from tumors were co-cultured with TCR-transgenic T-cells ex vivo to evaluate their stimulatory capacity. Cross-dressing (in vivo/ex vivo) was assayed by staining for transfer of tumor-derived H-2b MHC complexes to Balb/c DC, which express the H-2d haplotype. Protective systemic immunity was assayed via contralateral flank tumor outgrowth experiments.ResultsRegressor tumors were infiltrated with more cross-presenting DC1 than progressor tumors. However, tumor-reactive CD8+ T-cell responses and tumor control were preserved in Batf3-/- mice lacking DC1, indicating that anti-tumor immune responses could be induced independent of DC1. Through functional assays, we established that anti-tumor immunity against regressor tumors required CD11c+ DC and cGAS/STING-independent type-I-interferon-sensing. Single-cell RNA-sequencing of the immune infiltrate of regressor tumors revealed a novel CD11b+ DC subset expressing an interferon-stimulated gene signature (ISG+ DC). Flow studies demonstrated that ISG+ DC were more enriched in regressor tumors than progressor tumors. We showed that ISG+ DC could activate CD8+ T-cells by cross-dressing with tumor-derived peptide-MHC complexes, thereby bypassing the requirement for cross-presentation to initiate CD8+ T-cell-driven immunity. ISG+ DC highly expressed cytosolic dsRNA sensors (RIG-I/MDA5) and could be therapeutically harnessed by exogenous addition of a dsRNA analog to drive protective CD8+ T-cell responses in DC1-deficient mice.ConclusionsThe DC infiltrate in tumors can dictate the strength of anti-tumor immunity. Harnessing multiple stimulatory DC subsets, such as cross-presenting DC1 and cross-dressing ISG+ DC, provides a therapeutic opportunity to enhance anti-tumor immunity and increase immunotherapy responses.ReferencesFridman WH, et al. The immune contexture in human tumours: impact on clinical outcome. Nature Reviews Cancer 2012;12(4): p. 298–306.Hildner K, et al. Batf3 deficiency reveals a critical role for CD8alpha+ dendritic cells in cytotoxic T cell immunity. Science 2008;322(5904):p. 1097–100.Spranger S, et al. Tumor-Residing Batf3 dendritic cells are required for effector T cell trafficking and adoptive T cell therapy. Cancer Cell 2017;31(5):p. 711–723.e4.Roberts, EW, et al., Critical role for CD103(+)/CD141(+) dendritic cells bearing CCR7 for tumor antigen trafficking and priming of T cell immunity in melanoma. Cancer Cell 2016;30(2): p. 324–336.Broz ML, et al. Dissecting the tumor myeloid compartment reveals rare activating antigen-presenting cells critical for T cell immunity. Cancer Cell 2014;26(5): p. 638–52.Salmon H., et al., Expansion and activation of CD103(+) dendritic cell progenitors at the tumor site enhances tumor responses to therapeutic PD-L1 and BRAF inhibition. Immunity, 2016. 44(4): p. 924–38.Sánchez-Paulete AR, et al., Cancer immunotherapy with immunomodulatory anti-CD137 and Anti-PD-1 monoclonal antibodies requires BATF3-dependent dendritic cells. Cancer Discov, 2016;6(1):p. 71–9.


Pharmaceutics ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 590
Author(s):  
Jennifer Cauzzo ◽  
Nikhil Jayakumar ◽  
Balpreet Singh Ahluwalia ◽  
Azeem Ahmad ◽  
Nataša Škalko-Basnet

The rapid development of nanomedicine and drug delivery systems calls for new and effective characterization techniques that can accurately characterize both the properties and the behavior of nanosystems. Standard methods such as dynamic light scattering (DLS) and fluorescent-based assays present challenges in terms of system’s instability, machine sensitivity, and loss of tracking ability, among others. In this study, we explore some of the downsides of batch-mode analyses and fluorescent labeling, while introducing quantitative phase microscopy (QPM) as a label-free complimentary characterization technique. Liposomes were used as a model nanocarrier for their therapeutic relevance and structural versatility. A successful immobilization of liposomes in a non-dried setup allowed for static imaging conditions in an off-axis phase microscope. Image reconstruction was then performed with a phase-shifting algorithm providing high spatial resolution. Our results show the potential of QPM to localize subdiffraction-limited liposomes, estimate their size, and track their integrity over time. Moreover, QPM full-field-of-view images enable the estimation of a single-particle-based size distribution, providing an alternative to the batch mode approach. QPM thus overcomes some of the drawbacks of the conventional methods, serving as a relevant complimentary technique in the characterization of nanosystems.


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