Identification of dirty necrosis in colorectal carcinoma based on multiphoton microscopy

Li, Lianhuang; Jiang, Weizhong; Yang, Yinghong; Chen, Zhifen; Feng, Changyin; Li, Hongsheng; Guan, Guoxian; Chen, Jianxin

doi:10.1117/1.jbo.19.6.066008

Cited by 13 publications

(11 citation statements)

References 41 publications

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“…The nonlinear optical imaging system used in this study has been previously described in detail [ 34 , 35 ]. In short, an inverted microscope (LSM 510 META; Zeiss, Oberkochen, Germany) equipped with a mode-locked femtosecond Ti:sapphire laser (Mira 900-F; Coherent, Inc., Santa Clara, CA) was used to obtain high-resolution images.…”

Section: Methodsmentioning

confidence: 99%

Monitoring neoadjuvant therapy responses in rectal cancer using multimodal nonlinear optical microscopy

Chen

Wang

et al. 2017

Oncotarget

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Most patients with rectal cancer have a better prognosis after receiving neoadjuvant therapy because of its remarkable curative effect. However, no device delivers real-time histopathologic information on treatment response to help clinicians tailor individual therapeutic strategies. We assessed the potential of multimodal nonlinear optical microscopy to monitor therapeutic responses, including tumoral and stromal responses. We found that two-photon excited fluorescence imaging can, without labeling, identify colloid response, inflammatory cell infiltration, vascular proliferation, and tumor regression. It can also directly detect rare residual tumor cells, which may be helpful for distinguishing tumor shrinkage from tumor fragmentation. In addition, second harmonic generation imaging shows the ability to monitor three types of fibrotic responses: mature, intermediate, and immature. We also determined nonlinear spectra, collagen density, and collagen orientation indexes to quantitatively analyze the histopathologic changes induced by neoadjuvant therapy in rectal cancer. Our work demonstrates that nonlinear optical microscopy has the potential to become a label-free, real-time, in vivo medical imaging technique and provides the groundwork for further exploration into the application of nonlinear optical microscopy in a clinical setting.

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Section: Methodsmentioning

confidence: 99%

Monitoring neoadjuvant therapy responses in rectal cancer using multimodal nonlinear optical microscopy

Chen

Wang

et al. 2017

Oncotarget

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“…In addition to being dispersed throughout the stroma, CD66b-positive neutrophils preferentially accumulate in CRC pseudolumina. The luminal contents likely result from shedding of dying tumour cells and consequential inflammatory cell infiltration and are thus designated by pathologists as ‘dirty necrosis’ [ 19 ]. This term, however, describes the morphology of the dead cell content irrespective of underlying cell death pathway [ 20 ].…”

Section: Resultsmentioning

confidence: 99%

Tumour cell apoptosis modulates the colorectal cancer immune microenvironment via interleukin-8-dependent neutrophil recruitment

et al. 2022

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Sporadic apoptosis of tumour cells is a commonly observed feature of colorectal cancer (CRC) and strongly correlates with adverse patient prognosis. The uptake of apoptotic cell debris by neutrophils induces a non-inflammatory, pro-regenerative, and hence potentially pro-tumorigenic phenotype. In this study, we therefore sought to investigate the impact of apoptotic CRC cells on neutrophils and its consequence on other immune cells of the tumour microenvironment. Apoptosis induced by combined TNFα-treatment and UV-C irradiation, as well as various chemotherapeutic agents, led to a substantial release of neutrophil-attracting chemokines, most importantly interleukin-8 (IL-8), in both primary patient-derived and established CRC cells. Accordingly, conditioned media of apoptotic tumour cells selectively stimulated chemotaxis of neutrophils, but not T cells or monocytes. Notably, caspase-inhibition partially reduced IL-8 secretion, suggesting that caspase activity might be required for apoptosis-induced IL-8 release. Moreover, apoptotic tumour cell-conditioned media considerably prolonged neutrophil lifespan and induced an activated CD66bhighCD11bhighCD62Llow phenotype, comparable to that of tumour-associated neutrophils in CRC patients, as assessed by flow cytometry of dissociated CRC tissues. Immunohistochemical analyses of 35 CRC patients further revealed a preferential accumulation of neutrophils at sites of apoptotic tumour cells defined by the expression of epithelial cell-specific caspase-cleaved cytokeratin-18. The same areas were also highly infiltrated by macrophages, while T cells were virtually absent. Notably, neutrophils induced an M2-like CD86lowCD163+CD206+ phenotype in co-cultured monocyte-derived macrophages and suppressed LPS-induced pro-inflammatory cytokine release. In an in vitro transwell model, IL-8 blockade efficiently prevented neutrophil-induced anti-inflammatory macrophage polarisation by inhibiting neutrophil migration towards IL-8 gradients generated by apoptotic CRC cells. To conclude, our data suggest that apoptotic cancer cells release chemotactic factors that attract neutrophils into the tumour, where their interaction with neighbouring macrophages might promote an immunologically unfavourable tumour microenvironment. This effect may contribute to tumour recurrence after chemotherapy-induced apoptosis.

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“…Therefore, it is necessary to perform prospective studies to verify the effectiveness of NTR in routine clinical. Secondly, this study did not distinguish between different subtypes of necrosis (such as dirty necrosis or none‐dirty necrosis) [38, 39]. Thus, we will focus on refining the necrosis classification in the model in the future.…”

Section: Discussionmentioning

confidence: 99%

Automated assessment of necrosis tumor ratio in colorectal cancer using an artificial intelligence‐based digital pathology analysis

Wang

et al. 2023

Medicine Advances

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Background With the advance in digital pathology and artificial intelligence (AI)‐powered approaches, necrosis is proposed as a marker of poor prognosis in colorectal cancer (CRC). However, most previous studies quantified necrosis merely as a tissue type and patch‐level segmentation. Thus, it was worth exploring and validating the prognostic and predictive value of necrosis proportion with a pixel‐level segmentation in large multicenter cohorts. Methods A semantic segmentation model was trained with 12 tissue types labeled by pathologists. Segmentation was performed using the U‐net model with a subsequently derived necrosis tumor ratio (NTR). We proposed the NTR score (NTR‐low or NTR‐high) to evaluate the prognostic and predictive value of necrosis for disease‐free survival (DFS) and overall survival (OS) in the development (N = 443) and validation cohorts (N = 333) using 75% as a threshold. Results The 2‐category NTR was an independent prognostic factor and NTR‐low was associated with significant prolonged DFS (unadjusted HR for high vs. low 1.72 [95% CI 1.19–2.49] and 1.98 [1.22–3.23] in the development and validation cohorts). Similar trends were observed for OS. The prognostic value of NTR was maintained in the multivariate analysis for both cohorts. Furthermore, a stratified analysis showed that NTR‐high was a high risk with adjuvant chemotherapy for OS in stage II CRC (p = 0.047). Conclusion AI‐based pixel‐level quantified NTR has a stable prognostic value in CRC associated with unfavorable survival. Additionally, adjuvant chemotherapy provided survival benefits for patients with a high NTR score in stage II CRC.

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Identification of dirty necrosis in colorectal carcinoma based on multiphoton microscopy

Cited by 13 publications

References 41 publications

Monitoring neoadjuvant therapy responses in rectal cancer using multimodal nonlinear optical microscopy

Monitoring neoadjuvant therapy responses in rectal cancer using multimodal nonlinear optical microscopy

Tumour cell apoptosis modulates the colorectal cancer immune microenvironment via interleukin-8-dependent neutrophil recruitment

Automated assessment of necrosis tumor ratio in colorectal cancer using an artificial intelligence‐based digital pathology analysis

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