Evaluation of Diagnostic Algorithm Based on Collagen Organization Parameters for Breast Tumors

Lukianova, N Yu; Zadvornyi, Taras; Mushii, Oleksandr; Pyatchanina, T.V.; Чехун, В Ф

doi:10.32471/exp-oncology.2312-8852.vol-44-no-4.19137

Cited by 5 publications

(4 citation statements)

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“…The formation of an aggressive basal molecular BCa subtype is accompanied by an increase in TSR indices. The obtained data on the relationship of the above parameters of collagen fibers with the main clinical and pathological indices of BCa testify to the effectiveness of using the developed microphoto analysis algorithm to assess the spatial organization of the collagen fibrillar framework as part of the stromal microenvironment and coincide with the results of our previous studies [12]. Further study of the features of the spatial organization of collagen will allow us to identify the dynamical changes in its indices during cancer progression and to develop approaches to the personification of cancer therapy.…”

Section: Discussionsupporting

confidence: 75%

Development of an algorithm for biomedical image analysis of the spatial organization of collagen in breast cancer tissue of patients with different clinical status

Lukianova,

Mushii,

Zadvornyi

et al. 2024

FEBS Open Bio

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Collagen, the main component of the tumor microenvironment, plays a key role in the development of breast cancer (BCa); however, the specific changes in its spatial organization during tumor progression have not been definitively elucidated. The existing and available methods for assessing the morphometric parameters of the stroma's fibrous component are insufficient for a detailed description of the state of collagen fibers and for assessing its changes to evaluate the aggressiveness of the BCa course. The aim of the work was to develop an algorithm for microphoto analysis to assess the spatial organization of collagen in BCa tissue of patients with different clinical statuses. The study was conducted on 60 tissue samples of stage I‐II BCa. The processed images were analyzed using the software packages CurveAlign v4.0 and imagej. We established that the increase in BCa stage and the decrease in tumor differentiation grade are associated with decreased length, width, and straightness of collagen fibers, as well as their increased density. The formation of an aggressive basal molecular BCa subtype was accompanied by an increase in tumor‐stroma ratio. The obtained results indicate the possibility of practical application of the developed algorithm for evaluating the spatial organization of collagen in BCa tissue to predict the aggressiveness of the disease course.

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Section: Discussionsupporting

confidence: 75%

Development of an algorithm for biomedical image analysis of the spatial organization of collagen in breast cancer tissue of patients with different clinical status

Lukianova,

Mushii,

Zadvornyi

et al. 2024

FEBS Open Bio

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“…The main fibrillar component of the stroma is collagen, which makes up to 30% of the total protein mass in the human body. The changes in the ratio and spatial structure of collagen are currently considered a key diagnostic and prognostic factor associated with the occurrence and progression of many malignant neoplasms, including BCa, which is confirmed by the data of our previous study [7].…”

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confidence: 83%

Features of Col1a1 Expression in Breast Cancer Tissue of Young Patients

Chekhun,

Mushii,

Zadvornyi

et al. 2023

Exp. oncol.

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Background. In the last decades, the incidence of breast cancer (BCa) in young women has been increasing steadily. The quantitative indicators of expression of collagen, which play important role in stromal microenvironment, and their association with the age and survival rates of BCa patients have not been yet definitively clarified. Aim. To investigate the relationship between the COL1A1 gene expression at the mRNA and protein levels in BCa tissue and the clinicopatological features and survival rates of BCa patients of different age groups. Materials and Methods. The study was conducted on the clinical material of 50 patients with stage I—III BCa. COL1A1 gene expression at the mRNA and protein levels in BCa tissue were studied using the real-time PCR and immunohistochemical methods, as well as the bioinformatic analysis (UALCAN and Kaplan — Meier Plotter databases). Results. The bioinformatic analysis showed that BCa tissue is characterized by 6.0 times (p < 0.05) higher level of COL1A1 mRNA compared to normal breast tissue. The correlation of COL1A1 expression at the mRNA and protein levels with the molecular subtype of neoplasms was demonstrated. According to Kaplan — Meier Plotter database, a low level of expression of COL1A1 protein level in BCa tissue is associated with lower rates of relapse-free survival of patients. The ex vivo study of the clinical material revealed a decrease in COL1A1 protein expression in tumor tissue of young patients with BCa of T3 category (p < 0.0374), low differentiation grade (p < 0.0163) and basal molecular subtype (p < 0.0001). A correlation between the expression of COL1A1 at the mRNA and protein levels and the expression status of estrogen receptors (p < 0.0001) and progesterone receptors (p < 0.0040) was established. The relapse-free 3-year survival rate of young BCa patients is significantly lower in the presence of a low COL1A1 optical density index in the tumor tissue. Conclusions. The identified relationship between COL1A1 expression and such indicators of BCa malignancy as tumor size, differentiation grade, molecular subtype, receptor status, and the recurrencefree survival of patients indicates the prospects of its use to predict the aggressiveness of the BCa course in young patients.

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“…Therefore, the role of the stromal components of the microenviron-components compared to the aged components. Despite the proven role of the stro mal microenvironment in the development and progression of BCa [53,54], the molecular biological parameters of the disorganization and collagen expression indicators associated with the age of patients have not been definitively elucidated and require further research.…”

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confidence: 99%

Features of Breast Cancer in Patients of Young Age: Search for Diagnosis Optimization and Personalized Treatment

CHEKHUN,

MARTYNYUK,

LUKIANOVA

et al. 2023

Exp. oncol.

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The statistical data of the recent decades demonstrate a rapid growth of breast cancer (BCa) incidence and a tendency toward its increase especially in young women. In the structure of morbidity of women in the age group of 18—29 years, BCa ranks first and in the age range of 15—39 years, BCa is one of the leading causes of mortality. According to the data of the epidemiological and clinical studies, the young age is an independent unfavorable prognostic factor of BCa that is associated with an unfavorable prognosis and low survival rates and is considered an important predictor of the disease aggressiveness, a high risk of metastasis and recurrence. The variability of clinicopathological and molecular-biological features of BCa in patients of different age groups as well as the varying course of the disease and different responses to the therapy are mediated by many factors. The analysis of the literature data on the factors and mechanisms of BCa initiation in patients of different age groups demonstrates that the pathogen- esis of BCa depends not only on the molecular-genetic alterations but also on the metabolic disorders caused by the current social and household rhythm of life and nutrition peculiarities. All these factors affect both the general con- dition of the body and the formation of an aggressive microenvironment of the tumor lesion. The identified features of transcriptome and the differential gene expression give evidence of different regulations of the immune response and the metabolic processes in BCa patients of different age groups. Association between the high expression of the components of the stromal microenvironment and the inflammatory immune infiltrate as well as the increased vascu- larization of the tumor lesion has been found in BCa tissue of young patients. Proving the nature of the formation of the landscape comprising molecular-genetic, cytokine, and immune factors of the tumor microenvironment will undoubtedly contribute to our understanding of the mechanisms of tumor growth allowing for the development of algorithms for delineating the groups at high risk of tumor progression, which requires more careful monitoring and personalized treatment approach. Th s will be helpful in the development of innovative technologies for complex BCa treatment.

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Evaluation of Diagnostic Algorithm Based on Collagen Organization Parameters for Breast Tumors

Cited by 5 publications

References 0 publications

Development of an algorithm for biomedical image analysis of the spatial organization of collagen in breast cancer tissue of patients with different clinical status

Development of an algorithm for biomedical image analysis of the spatial organization of collagen in breast cancer tissue of patients with different clinical status

Features of Col1a1 Expression in Breast Cancer Tissue of Young Patients

Features of Breast Cancer in Patients of Young Age: Search for Diagnosis Optimization and Personalized Treatment

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