Association of subcutaneous and visceral adipose tissue with overall survival in Taiwanese patients with bone metastases – results from a retrospective analysis of consecutively collected data

Chuang, Wen Ching; Tsang, Ngan Ming; Chuang, Chi Cheng; Chang, Kai Ping; Pai, Ping‐Ching; Chen, Kuan Hung; Chou, Wen Chi; Tai, Shiao Fwu; Liu, Shu Chen; Lei, Kin Fong

doi:10.1371/journal.pone.0228360

Cited by 7 publications

(3 citation statements)

References 32 publications

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“…Furthermore, a recent study substantiated that lower SFI independently predicted poor overall survival in hepatocellular carcinoma [ 50 ]. Another study proposed that patients with bone metastases exhibiting elevated SFI and VFI demonstrated superior overall survival [ 51 ]. However, Bradshaw et al observed that, among women with non-metastatic breast cancer, increased SAT was associated with shorter survival [ 16 ].…”

Section: Discussionmentioning

confidence: 99%

Subcutaneous fat predicts bone metastasis in breast cancer: A novel multimodality-based deep learning model

Miao,

Jia,

Huang

et al. 2024

CBM

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OBJECTIVES: This study explores a deep learning (DL) approach to predicting bone metastases in breast cancer (BC) patients using clinical information, such as the fat index, and features like Computed Tomography (CT) images. METHODS: CT imaging data and clinical information were collected from 431 BC patients who underwent radical surgical resection at Harbin Medical University Cancer Hospital. The area of muscle and adipose tissue was obtained from CT images at the level of the eleventh thoracic vertebra. The corresponding histograms of oriented gradients (HOG) and local binary pattern (LBP) features were extracted from the CT images, and the network features were derived from the LBP and HOG features as well as the CT images through deep learning (DL). The combination of network features with clinical information was utilized to predict bone metastases in BC patients using the Gradient Boosting Decision Tree (GBDT) algorithm. Regularized Cox regression models were employed to identify independent prognostic factors for bone metastasis. RESULTS: The combination of clinical information and network features extracted from LBP features, HOG features, and CT images using a convolutional neural network (CNN) yielded the best performance, achieving an AUC of 0.922 (95% confidence interval [CI]: 0.843–0.964, P< 0.01). Regularized Cox regression results indicated that the subcutaneous fat index was an independent prognostic factor for bone metastasis in breast cancer (BC). CONCLUSION: Subcutaneous fat index could predict bone metastasis in BC patients. Deep learning multimodal algorithm demonstrates superior performance in assessing bone metastases in BC patients.

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Section: Discussionmentioning

confidence: 99%

Subcutaneous fat predicts bone metastasis in breast cancer: A novel multimodality-based deep learning model

Miao,

Jia,

Huang

et al. 2024

CBM

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“…Prior studies investigating the prognostic relevance of subcutaneous adiposity in cancer patients have yielded inconsistent results, which appear to differ by tumor type and stage, possibly consistent with adiposity being a risk factor for some cancers (e.g., breast cancer). In patients diagnosed with hepatocellular carcinoma [27] or bone metastases [28], high SAT was associated with better survival. In a large retrospective Canadian study, including n = 1,473 stage I-IV gastrointestinal and lung cancer patients, and n = 273 patients diagnosed with metastatic renal cell carcinoma, high SAT was an independent prognostic factor, predicting reduction in mortality [29].…”

Section: Introductionmentioning

confidence: 91%

Metabolomics profiling of visceral and abdominal subcutaneous adipose tissue in colorectal cancer patients: results from the ColoCare study

Ose

Holowatyj

Nattenmüller

et al. 2020

Cancer Causes Control

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People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:

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“…While some studies showed an association between obesity and a poor survival rate (Meyerhardt et al, 2003;Kasenda et al, 2014), others have reported obesity to be associated with lower mortality rates (Martin et al, 2013;Schlesinger et al, 2014;Ebadi et al, 2017). Estimating the VAT index (VATI) and the SAT index (SATI) as adiposity markers, SAT appears to correlate with a reduction in mortality risk for gastrointestinal, respiratory cancer, and renal carcinoma patients (Ebadi et al, 2017) and an increased survival rate among patients with bone metastases, thus demonstrating the prognostic value of AT distribution (Chuang et al, 2020). In colorectal tumor patients, low SATI and VATI are associated with an increased risk of dying, as did high SAT and VAT density, where high VAT density was the main predictor of a poor survival rate in metastatic colorectal tumor patients (Charette et al, 2019).…”

Section: Adiposity Parameters In Tumor Patientsmentioning

confidence: 99%

Adipogenesis in Different Body Depots and Tumor Development

Trivanović¹,

Petrinović

Djordjević

et al. 2020

Front. Cell Dev. Biol.

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Adipose tissue (AT) forms depots at different anatomical locations throughout the body, being in subcutaneous and visceral regions, as well as the bone marrow. These ATs differ in the adipocyte functional profile, their insulin sensitivity, adipokines' production, lipolysis, and response to pathologic conditions. Despite the recent advances in lineage tracing, which have demonstrated that individual adipose depots are composed of adipocytes derived from distinct progenitor populations, the cellular and molecular dissection of the adipose clonogenic stem cell niche is still a great challenge. Additional complexity in AT regulation is associated with tumor-induced changes that affect adipocyte phenotype. As an integrative unit of cell differentiation, AT microenvironment regulates various phenotype outcomes of differentiating adipogenic lineages, which consequently may contribute to the neoplastic phenotype manifestations. Particularly interesting is the capacity of AT to impose and support the aberrant potency of stem cells that accompanies tumor development. In this review, we summarize the current findings on the communication between adipocytes and their progenitors with tumor cells, pointing out to the coexistence of healthy and neoplastic stem cell niches developed during tumor evolution. We also discuss tumor-induced adaptations in mature adipocytes and the involvement of alternative differentiation programs.

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Association of subcutaneous and visceral adipose tissue with overall survival in Taiwanese patients with bone metastases – results from a retrospective analysis of consecutively collected data

Cited by 7 publications

References 32 publications

Subcutaneous fat predicts bone metastasis in breast cancer: A novel multimodality-based deep learning model

Subcutaneous fat predicts bone metastasis in breast cancer: A novel multimodality-based deep learning model

Metabolomics profiling of visceral and abdominal subcutaneous adipose tissue in colorectal cancer patients: results from the ColoCare study

Adipogenesis in Different Body Depots and Tumor Development

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