Bilateral breast keloids in an elderly woman associated with bilateral breast cancers and high concentration of serum tumor growth factor‐β

Sakaguchi, Masanobu; Fukumoto, Takeshi; Fujishima, Fumiyoshi; Fukuda, Kentarou; Kozaru, Takeshi; Ban, Masashi; Oka, Masahiro

doi:10.1111/1346-8138.13910

Cited by 3 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… 7 , 8 Notably, sporadic case reports show that keloids may be a paraneoplastic phenomenon. 9 – 13 Keloid scar could develop within years after initial injury, and some of them may persist for a lifetime without treatment. The etiology of keloid scar formation is not completely understood, and the recurrence rate of this disease is relatively high.…”

Section: Introductionmentioning

confidence: 99%

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning

et al. 2023

View full text Add to dashboard Cite

Significance: Rapid diagnosis and analysis of human keloid scar tissues in an automated manner are essential for understanding pathogenesis and formulating treatment solutions.Aim: Our aim is to resolve the features of the extracellular matrix in human keloid scar tissues automatically for accurate diagnosis with the aid of machine learning.Approach: Multiphoton microscopy was utilized to acquire images of collagen and elastin fibers. Morphological features, histogram, and gray-level co-occurrence matrix-based texture features were obtained to produce a total of 28 features. The minimum redundancy maximum relevancy feature selection approach was implemented to rank these features and establish feature subsets, each of which was employed to build a machine learning model through the tree-based pipeline optimization tool (TPOT).Results: The feature importance ranking was obtained, and 28 feature subsets were acquired by incremental feature selection. The subset with the top 23 features was identified as the most accurate. Then stochastic gradient descent classifier optimized by the TPOT was generated with an accuracy of 96.15% in classifying normal, scar, and adjacent tissues. The area under curve of the classification results (scar versus normal and adjacent, normal versus scar and adjacent, and adjacent versus normal and scar) was 1.0, 1.0, and 0.99, respectively. Conclusions:The proposed approach has great potential for future dermatological clinical diagnosis and analysis and holds promise for the development of computer-aided systems to assist dermatologists in diagnosis and treatment.

show abstract

Section: Introductionmentioning

confidence: 99%

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning

et al. 2023

View full text Add to dashboard Cite

show abstract

“…Since keloids are a prototypic fibrous proliferative and sclerotic disease of the skin, this study investigated whether patients with keloids have a higher than normal tendency to develop cancers, including skin and internal cancers. Notably, sporadic case reports show that keloids may be a paraneoplastic phenomenon [7][8][9] . Coppa et al reported a 66-year-old woman…”

mentioning

confidence: 99%

“…Sakaguchi et al described the development of bilateral breast cancer in a 72-year-old woman with extensive keloids on the limbs, presternal area, and bilateral breasts. Notably, her serum level of transforming growth factor-β1 (TGF-β1) was abnormally high 8 .…”

mentioning

confidence: 99%

Risk of cancer development in patients with keloids

Lü

et al. 2021

Sci Rep

View full text Add to dashboard Cite

Keloid is a skin disease characterized by exaggerated scar formation, excessive fibroblast proliferation, and excessive collagen deposition. Cancers commonly arise from a fibrotic microenvironment; e.g., hepatoma arises from liver cirrhosis, and oral cancers arise from submucosal fibrosis. As keloids are a prototypic fibroproliferative disease, this study investigated whether patients with keloids have an increased cancer risk. In a matched, population-based study, first 17,401 patients treated for keloids during 1998–2010 with 69,604 controls without keloids at a ratio of 1:4 were evaluated. The association between keloids and risk of cancer was estimated by logistic regression or Cox proportional hazard regression models after adjustment of covariates. In total, 893 first-time cases of cancer were identified in the 17,401 patients with keloids. The overall cancer risk was 1.49-fold higher in the keloids group compared to controls. Regarding specific cancers, the keloids group, had a significantly higher risk of skin cancer compared to controls (Relative risk = 1.73). The relative risk for skin cancer was even higher for males with keloids (Relative risk = 2.16). Further stratified analyses also revealed a significantly higher risk of developing pancreatic cancer in female patients with keloids compared to controls (Relative risk = 2.19) after adjustment for known pancreatic cancer risk factors. This study indicates that patients with keloids have a higher than normal risk for several cancer types, especially skin cancers (both genders) and pancreatic cancer (females). Therefore, patients with keloids should undergo regular skin examinations, and females with keloids should regularly undergo abdominal ultrasonography.

show abstract

Chronic Sclerosing Sialadenitis of the Submandibular Gland and its Histopathological Spectrum in the IgG4-Related Disease: a Series of 17 Cases

Muniz,

Altemani,

Freitas

et al. 2024

Head and Neck Pathol

View full text Add to dashboard Cite

Bilateral breast keloids in an elderly woman associated with bilateral breast cancers and high concentration of serum tumor growth factor‐β

Cited by 3 publications

References 14 publications

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning

Risk of cancer development in patients with keloids

Chronic Sclerosing Sialadenitis of the Submandibular Gland and its Histopathological Spectrum in the IgG4-Related Disease: a Series of 17 Cases

Contact Info

Product

Resources

About